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BUSINESS VALUE OF INFORMATION TECHNOLOGY: A COMPLEX ADAPTIVE
SYSTEMS THEORY VIEW
Mohammad Fakhrul Alam Onik B.Sc. in Computer Science and Engineering
Principal Supervisor: Dr Erwin Fielt
Associate Supervisor: Professor Guy G. Gable and
Dr. Meng Zhang
Submitted in fulfilment of the requirements for the degree of
Doctor of Philosophy (IF49)
School of Information Systems
Science and Engineering Faculty
Queensland University of Technology
2019
Business Value of Information Technology: A Complex Adaptive Systems Theory View i
Keywords
Business value of IT
Complex Adaptive Systems
Coevolution
Emergence
IT-enabled Capability
Competitive Advantage
ii Business Value of Information Technology: A Complex Adaptive Systems Theory View
Abstract
There has been a long-running discourse in the Information Systems (IS)
literature examining the organisational performance impacts of information
technology; the business value of IT (BVIT). The use within and among organizations
of multi-scale digital technologies such as, cloud computing, big data, digital
platforms, and Internet-of-Things, is proliferating; altering the ways in which firms
acquire factor inputs, manage products and services, and share value with their
customers. The deployment of these digital technologies has given rise to a step-
change in the complexity, dynamism, and unpredictability of organisational
phenomena. Recent studies have begun to explore the implications of this step-change
for how value is created, with prominent IS scholars arguing the need for alternative
approaches to understanding BVIT in the contemporary economy and society.
In attention to this need, this research adopts a complexity theory lens; more
specifically a complex adaptive systems (CAS) theory view. Taking existing
theorising on BVIT as a starting point, the study develops a reconceptualisation via
CAS theory that helps to explain implicit dynamics in relation to BVIT. The CAS
theory offers a theoretical base to develop deeper understanding of the dynamic side
of BVIT phenomenon, herein focusing on two particular CAS theoretical concepts,
emergence and coevolution in the context of BVIT. This research employs a novel
theory development approach based on the ideas of Shepherd and Suddaby’s (2017)
review of methods and tools related to theory building.
First, a preliminary, high-level BVIT framework consisting of IT assets-
organisational resources, IT-enabled capabilities, and competitive advantage
constructs, is presented so as to interrelate main existing strategic perspectives on
BVIT in the literature. Subsequently, the research includes two major phases. In the
first phase, it adopts the CAS ‘emergence’ concept to explore how IT-enabled
capabilities emerge in contemporary organisations. A new interpretation of the
emergence concept as complex-emergence, containing four enabling conditions -
semi-structures, simple rules, self-organised management, and compatibility is
presented. The complex-emergence conceptual framework of IT-enabled capabilities,
Business Value of Information Technology: A Complex Adaptive Systems Theory View iii
demonstrates how IT-enabled capabilities emerge via bottom-up interactions between
the components of IT assets and organisational resources.
In the second phase, the CAS ‘coevolution’ concept is used to investigate how
these capabilities help organisations in obtaining competitive advantage. The
coevolution concept investigates the mutual evolution of IT-enabled capabilities, and
how they aid organisations to obtain competitive advantage. Two types of coevolution,
micro and macro-level coevolution, are discussed in the context of IT-enabled
capabilities, representing how capabilities improve over time within and between
organizations. Variation, selection and retention evolutionary mechanisms are
discussed to explain micro-coevolution of IT-enabled capabilities. In addition, three
distinct macro-coevolutionary dynamic phenomena; namely, Red Queen effect,
competitive exclusion, and niche separation, are discussed in relation to capabilities,
highlighting action-based competitive relationships among firms and how they vie for
advantage. Moreover, an operational NKC model is used in this phase to formalise
several strategies to manage coevolution in the IT-enabled capabilities.
The study concludes with a CAS theory based BVIT framework that
theoretically explains the dynamic path from IT assets towards creation of business
value as competitive advantage in contemporary organisations. It integrates the
emergence and coevolution lenses on IT-enabled capabilities, which together represent
action-based competitive advantage; a new BVIT framework.
iv Business Value of Information Technology: A Complex Adaptive Systems Theory View
Table of Contents
Keywords ................................................................................................................................... i
Abstract ..................................................................................................................................... ii
Table of Contents ..................................................................................................................... iv
List of Figures .......................................................................................................................... vi
List of Tables .......................................................................................................................... vii
List of Abbreviations ............................................................................................................. viii
Statement of Original Authorship ............................................................................................ ix
Acknowledgements ................................................................................................................... x
Dedication ................................................................................................................................ xi
Publications ............................................................................................................................. xii
Chapter 1: Introduction ....................................................................................... 11.1 Research background ...................................................................................................... 1
1.2 Research Motivation ....................................................................................................... 6
1.3 Research Problem and Questions ................................................................................... 7
1.4 Research Methodology ................................................................................................. 12
1.5 Research Design ........................................................................................................... 22
1.6 Chapter Summary ......................................................................................................... 25
Chapter 2: Background Literature ................................................................... 272.1 Historical Background .................................................................................................. 28
2.2 Business Value of Information Technology (BVIT) .................................................... 29
2.3 A High Level Conceptual Framework of BVIT ........................................................... 35
2.4 Complexity Theories .................................................................................................... 40
2.5 Chapter Summary ......................................................................................................... 45
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 473.1 Introduction .................................................................................................................. 48
3.2 Background Literature .................................................................................................. 51
3.3 Review Design .............................................................................................................. 55
3.4 The Status of CAS Theory in the IS Discipline ............................................................ 58
3.5 the Conceptual Perspective of CAS in is ...................................................................... 59
3.6 The Objectives of CAS Theory in the IS Research ...................................................... 63
3.7 The theoretical perspectives of CAS research in IS ..................................................... 69
3.8 The Methodological Approaches of CAS in IS Research ............................................ 71
3.9 Context of the CAS Theory in IS research ................................................................... 76
Business Value of Information Technology: A Complex Adaptive Systems Theory View v
3.10 Conclusion .................................................................................................................... 79
Chapter 4: An Emergence Perspective on IT-enabled Capabilities ............... 834.1 Introduction .................................................................................................................. 83
4.2 Overview of Emergence ............................................................................................... 89
4.3 Recap of Nevo and Wade (2010) Model ...................................................................... 97
4.4 A Complex Emergence Framework of IT-enabled Capabilities ................................ 107
4.5 Chapter Summary ....................................................................................................... 121
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities ............. 1245.1 Introduction ................................................................................................................ 124
5.2 Overview of Coevolution ........................................................................................... 131
5.3 A prelimnary coevolution framework for IT-enabled Capabilities ............................ 137
5.4 Micro coevolution of IT-enabled capabilities within the firm ................................... 141
5.5 Macro Coevolution of IT-enabled capabilities between the firms ............................. 147
5.6 A Coevolution based framework of IT-enabled Capabilities ..................................... 154
5.7 Chapter Summary ....................................................................................................... 161
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities ...... 1646.1 Introduction ................................................................................................................ 164
6.2 Applications of NKC Model in Research ................................................................... 165
6.3 Managing The Coevolution of the IT-enabled Capabilities ....................................... 174
6.4 Chapter Summary ....................................................................................................... 184
Chapter 7: Discussion and Conclusion ........................................................... 1857.1 A CAS-BVIT Framework .......................................................................................... 185
7.2 From a Static, Linear perspective to a Dynamic, Non-linear Perspective .................. 190
7.3 Key Insights Compared with Prominent, Traditional BVIT Models ......................... 192
7.4 Conclusion .................................................................................................................. 197
Appendices ............................................................................................................... 209Appendix A Abstract of the publications .............................................................................. 209
References ................................................................................................................ 213
vi Business Value of Information Technology: A Complex Adaptive Systems Theory View
List of Figures
Figure 1.1 A high level conceptual framework of Strategic-BVIT .................... 5
Figure 1.2 The position of the CAS concepts in the high-level conceptual framework of BVIT (The arrows are positioned under the concepts to represent their position in the thesis) .................................................. 11
Figure 1.3 Research Approach .......................................................................... 17
Figure 1.4 Approach to theory development in relation to BVIT ..................... 21Figure 1.5 An overview of Research Design .................................................... 23
Figure 3.1 Overview of sampling sources ........................................................ 55Figure 4.1 A Subset of the BVIT framework (Figure 1.2 in Chapter 1) ........... 84
Figure 4.2 A Subset of Research Method (see Figure 1.3 in Chapter 1) .......... 87Figure 4.3 (Nevo & Wade, 2010) ..................................................................... 97
Figure 4.4 A complex emergence framework of IT-enabled capabilities ...... 108Figure 5.1 A Subset of the BVIT framework ................................................. 126
Figure 5.2 A Subset of Research Method for Coevolution of IT-enabled Capabilities ....................................................................................... 129
Figure 5.3 A Preliminary Coevolution Framework of BVIT (With the focus on the coevolution of IT-enabled Capabilities) ..................................... 138
Figure 5.4 Micro coevolution of IT-enabled capabilities via variation, selection and retention (VSR) processes .......................................................... 145
Figure 5.5 A Coevolution Framework of IT-enabled Capabilities ................. 155Figure 7.1: A CAS-BVIT framework ............................................................. 188
Business Value of Information Technology: A Complex Adaptive Systems Theory View vii
List of Tables
Table 2.1 Typologies of IT assets and organisational resources (Adapted from (Kim, et al., 2011)) ............................................................................. 38
Table 2.2 Summary of the High Level BVIT Framework ................................ 40
Table 2.3 Basic building blocks of complex adaptive systems (CAS) theory .. 44Table 3.1 Journal/ conference and year wise distribution of CAS article ........ 59
Table 3.2 Classification of papers based on CAS concepts in IS literature ...... 61Table 3.3 CAS objectives in IS research .......................................................... 66
Table 3.4 Theoretical approaches in CAS research in IS ................................. 71Table 3.5 Overview of methodologies in CAS based IS research .................... 72
Table 3.6 Context of CAS theory in IS ............................................................. 77Table 4.1 Typologies of Emergence ................................................................. 92
Table 4.2 Simple vs Complex Emergence ........................................................ 96Table 4.3: Complex Emergence of IT-enabled Capabilities ........................... 122
Table 5.1 Application of Coevolution in Management .................................. 135Table 5.2 Application of Coevolution in BVIT related IS research ............... 137
Table 5.3 The complete coevolution Framework of IT-enabled capabilities and strategies ........................................................................................... 162
Table 6.1 NKC Applications in Management and IS Studies (Summarised from Vidgen and Bull (2011)) ................................................................... 171
Table 6.2 Translation of NKC model into the context of IT-enabled capabilities ........................................................................................ 177
Table 6.3 Strategies for managing Micro and Macro Coevolutionary Competition in Organisations ........................................................... 178
Table 7.1 Propositions related to the emergence and coevolution perspectives of the IT-enabled capabilities ........................................................... 189
viii Business Value of Information Technology: A Complex Adaptive Systems Theory View
List of Abbreviations
BVIT Business Value of IT
CAS Complex Adaptive Systems
DCT Dynamic Capabilities Theory
RBV Resource based View
CRM Customer Relationship Management
ERP Enterprise Resource Planning
IoT Internet of Things
IS Information Systems
IT Information Technology
PACIS Pacific Asia Conference on Information
Systems
ACIS Australasian Conference on Information
Systems
Business Value of Information Technology: A Complex Adaptive Systems Theory View ix
Statement of Original Authorship
The work contained in this thesis has not been previously submitted to meet
requirements for an award at this or any other higher education institution. To the best
of my knowledge and belief, the thesis contains no material previously published or
written by another person except where due reference is made.
Signature:
Date: ________20.08.2019_________________
QUT Verified Signature
x Business Value of Information Technology: A Complex Adaptive Systems Theory View
Acknowledgements
Pursuing a PhD has been an emotional roller coaster ride. Throughout this
process I have been fortunate to enjoy immense support from a large number of people.
I would like to acknowledge my indebtedness and render my warmest thanks to
my supervisory team, Dr. Erwin Fielt, Professor Guy Gable and Dr. Meng Zhang, who
made this work possible. Specially, Erwin’s friendly guidance and expert advice have
been invaluable throughout all stages of the work. Thank you, Erwin for your critical
thoughts and suggestions that kept me focused. Further, you have challenged me
intellectually, provided a broad theoretical base, and pointed me in fruitful directions
when perplexed. Maybe most importantly, you have reminded me of the importance
of enjoying research.
I would also wish to express my gratitude to Professor Guy Gable for extended
discussions and valuable suggestions which have contributed greatly to the
improvement of the thesis. Moreover, your comments and reviews were instrumental
during my stage 2, confirmation and final seminar milestones. Thank you Guy for
showing me the craftsmanship of research. I also gratefully acknowledge financial
support that I have received from your ARC grant and supervisory top-up scholarship,
which have been crucial during my PhD journey.
I gratefully acknowledge the scholarship- QUT Postgraduate Research Award
received towards my PhD from Queensland University of Technology. I am also
grateful to the funding received through the QUT Excellence Top Up Scholarship.
The thesis has also benefited from comments and suggestions made by Dr. Sue
Nielsen and Dr. Nev Schefe who have read through the manuscript. I take this
opportunity to thank them.
I was fortunate to be surrounded by lovely colleagues in the School of
Information Systems, who constantly inspired and supported me during some of the
toughest study periods of the PhD journey. I would like to specially thank Lucky for
inspiring me a lot with positive suggestions and motivations during my journey. I also
wish to thank you Y-7 friends and colleagues Fahame, Abdul, Yancong, Ignatius,
Syed, and Sharmistha for the enjoyable memories with you that I will keep forever.
Business Value of Information Technology: A Complex Adaptive Systems Theory View xi
Dedication
I dedicate this research to-
My grandfather (Late), grandmother and my maternal uncle, Md Moslehuddin
for supporting me from my childhood till now.
My father, Md Alauddin and my mother, Fakhrunnahar Begum, for giving me
the freedom to choose my decisions in my life.
Last but not least, my beautiful wife, Dr Fatimatuz Zannat, for always inspiring
me and keeping me cheerful during the most demanding times of our lives.
xii Business Value of Information Technology: A Complex Adaptive Systems Theory View
Publications1
Conference Publications
• Onik, M. F. A., Fielt, E., & Gable, G. G. (2017). Complex Adaptive Systems Theory in Information Systems Research-A Systematic Literature Review. In the Proceedings of 21st Pacific Asia Conference on Information Systems (PACIS), Langkawi, Malaysia.
• Onik, M. F. A., Fielt, E., & Gable, G. G. (2017). Towards Complex Adaptive Systems
Roadmap for Information Systems Research. In the Proceedings of 21st Pacific Asia Conference on Information Systems (PACIS), Langkawi, Malaysia.
• Onik, M. F. A. & Fielt, E. (2016). Understanding The Dynamics of BVIT Process: A
Complex Adaptive Systems Approach. In the Proceedings of 27th Australasian Conference on Information Systems (ACIS), Wollongong, Australia.
Doctoral Consortium
• Onik, M. F. A., Fielt, E. & Gable, G. G. (2017). Understanding The Dynamics of
BVIT Creation: A Complex Adaptive Systems Approach. ISS Doctoral Consortium, QUT Brisbane.
• Onik, M. F. A., Fielt, E. & Gable, G. G. (2016). What Are Information Systems-
Information Systems as Complex Adaptive Systems. ISS Doctoral Consortium, QUT Brisbane.
1 The abstracts of the publications are available in 1)a)Appendix A.
Chapter 1: Introduction 1
Chapter 1: Introduction
The business value of Information Technology (BVIT) has been one of the
foremost concerns among Information Systems (IS) practitioners and researchers for
decades. Over the years, researchers have conceived various approaches to understand
BVIT creation mechanisms. However, the contemporary business environment has
become complex and dynamic due to advances in technologies and their deployment,
which influence the way BVIT is generated in and across organisations. This
dissertation has adopted complex adaptive systems (CAS) theory as an overarching
theoretical lens to explore the dynamics related to BVIT.
This chapter first presents an overview of the research background and the
motivation behind this study. The subsequent sections introduce the research
problems, questions and a high level conceptual BVIT framework. Lastly, the study
research methodology and research design are presented.
1.1 RESEARCH BACKGROUND
The term BVIT is commonly used to refer to the “organisational performance
impacts of information technology (IT)…” (Melville, Kraemer, & Gurbaxani, 2004, p.
287). The research suggests various measures that are used to refer BVIT, such as,
productivity enhancement, cost reduction, competitive advantage and other measures
of performance (Kohli & Devaraj, 2003; Melville, et al., 2004). Broadly, an analysis
of the BVIT literature reveals a key distinction between performance-efficiency and
performance-effectiveness (Melville, et al., 2004). Efficiency refers to an
improvement from an organisational internal perspective, such as cost reduction and
improved operational processes (Soh & Markus, 1995). In contrast, effectiveness
denotes achievement of superior strategies that may manifest in increased competitive
advantage (Barney, 1991). In sum, BVIT refers to the organisational performance
impacts of information technology at both the operational process level and the
strategic level of organisations and comprises both efficiency and competitive impacts
(Melville, et al., 2004).
2 Chapter 1: Introduction
Researchers have adopted various approaches, such as process-centric,
variance-based or intangible measures, to analyse the mechanisms by which IT
impacts organisational performance and to gauge its magnitude. The studies that adopt
variance theories explore variations in the magnitude of particular outcomes i.e. BVIT
under certain and sufficient conditions (Markus & Robey, 1983); whereas process
theories provide causal explanations of ‘how’ BVIT occurs in an organisation - the
necessary conditions, particular events and sequences (Soh & Markus, 1995). Previous
research shows that IT has indeed contributed to the improvement of organisational
performance (e.g. Hitt & Brynjolfsson, 1996; Kohli & Devaraj, 2003; Oh, Teo, &
Sambamurthy, 2012; Radhakrishnan, Zu, & Grover, 2008). Moreover, researchers
have also considered different antecedents and contextual factors, such as
organisational structure and culture, management practices, competitive environment
etc. that influence BVIT creation mechanisms (e.g. Dewan & Kraemer, 2000; Melville,
et al., 2004; Schryen, 2012). This stream of research also suggests that firms may not
be able to capture and appropriate all the value possible from IT, as value can be
competed-away or captured by end-customers in the form of satisfaction, better
quality, or lower prices (Devaraj & Kohli, 2000; Limayem & Cheung, 2008). A
contrary view in the 1990s controversially identified a productivity paradox- low
productivity growth against high spending on IT (Avison, Cuthbertson, & Powell,
1999; Brynjolfsson, 1993).
Information systems (IS) scholars have conducted conceptual, theoretical,
analytical and empirical studies with regards to BVIT. The empirical studies include
qualitative studies - case studies and field studies (e.g. Weill, 1992) - and quantitative
studies that explicate BVIT at the individual, firm and country levels of analysis
(Dewan & Kraemer, 2000; Mooney, Gurbaxani, & Kraemer, 1995). The conceptual
and theoretical research adopts competing theories and grounded observation to
describe BVIT (Mata, Fuerst, & Barney, 1995; Porter, Michael, & Gibbs, 2001).
Finally, analytical studies of BVIT use a variety of techniques to model BVIT and
derive solutions to improve organisational performance, by changing operational or
management processes in the competitive business environment (Belleflamme, 2001).
In addition, researchers have employed many theoretical lenses including
microeconomics- growth accounting (e.g. Hitt & Brynjolfsson, 1996), Tobin’s q (e.g.
Bharadwaj, Bharadwaj, & Konsynski, 1999), industrial organisation theory- game
Chapter 1: Introduction 3
theory (e.g. Belleflamme, 2001), socio-political perspective (e.g. Hoogeveen &
Oppelland, 2002a) and the Resource-based View (RBV) theory (e.g. Aral & Weill,
2007; Bharadwaj, 2000) to analyse the value that IT creates for organisations.
Our knowledge of BVIT derives largely from an organisation-centric
perspective on BVIT, based in internal business processes, organisational capabilities
and organisational practices (e.g. Bharadwaj, 2000; Melville, et al., 2004;
Sambamurthy, Bharadwaj, & Grover, 2003; Schryen, 2012). This research on BVIT
can largely be classified into two categories- the operational perspective and the
strategic perspective. The operational perspective on BVIT emphasises the
enhancement of internal efficiency through improving business process performance,
measures of which may include improved customer service, better information sharing
or faster inventory turnover (Melville, et al., 2004). Alternatively, the strategic
perspective is concerned with how organisations can obtain superior competitive
advantage by employing IT resources accompanied by organisational resources, such
as, non-IT physical or non-IT human resources and organisational capital resources
(Melville, et al., 2004; Wade & Hulland, 2004). In the strategic perspective, BVIT is
widely represented as competitive advantage (Barney, 2000; Bharadwaj, Varadarajan,
& Fahy, 1993; Grant, 1991). A broad discussion of the strategic perspective on BVIT
is presented in section 2.2.3 in Chapter 2.
This dissertation focuses on the strategic perspective of BVIT research, which
involves deeply analysing main strategic-BVIT models to develop a theoretical base
for this study. An analysis of how IS researchers have formulated these core strategic-
BVIT models, shows that the majority of the models have three key parts. In the first
part, the model contains aggregated variables or interdependencies between IT and
other complementary organisational resources (e.g. Melville, et al., 2004; Nevo &
Wade, 2010; Wade & Hulland, 2004). The second part contains emergent capabilities
or synergies and competencies that may improve business processes (Kim, Shin, Kim,
& Lee, 2011; Melville, et al., 2004). The third part of the model contains outcomes;
the competitive advantage that organisations obtain by deploying IT resources (Mata,
et al., 1995). It is important to note that RBV theory is used in the majority of strategic-
BVIT studies to examine the competitive advantage implications of IT resources
(Bharadwaj, 2000; Wade & Hulland, 2004).
4 Chapter 1: Introduction
Based on the above discussion, I present a high-level conceptual framework of
BVIT (Figure 1.1). The proposed model represents the strategic perspective of the
BVIT models. The model includes three key parts, which are termed lenses in this
dissertation: 1) IT assets and organisational resources, 2) IT-enabled capabilities and
3) competitive advantage. A more detailed discussion on the conceptual framework is
presented in Chapter 2. The framework serves simply to interrelate the way in which
the strategic perspective of BVIT is understood in existing literature. This involves
relationships between IT assets and other organisational resources, which lead to IT-
enabled capabilities, which subsequently influence firm performance, in particular
competitive advantage. A broader discussion of the proposed framework is included
in section 2.3 of Chapter 2.
As mentioned above in this section, this study focuses on the strategic side of
BVIT. The high level BVIT conceptual framework proposed here is based on the
Resource-based view (RBV) of organisations (Barney, 1991; Barney, 2001) and
following the ideas of Nevo and Wade (2010) on the strategic role of IT assets in
shaping competitive advantage (discussed in section 2.2.3 in Chapter 2). The RBV
view of the organisation is widely applied in strategic management literature, and
assumes that firms compete with each other on the basis of valuable, rare, difficult to
imitate and non-substitutable resources to achieve competitive advantage (Barney,
1991; Barney, 2001) and this study aims to explore the dynamics related to the
competitive advantage. It is important to note that, the competitive environment in
which focal firm operates has two major components- industry characteristics and
trading partners following (Melville, et al., 2004). The industry characteristics include
competitiveness, digitally enabled processes and rapid technological innovation that
shape the way IT assets are deployed in the focal firm to generate business value (Kohli
& Devaraj, 2003; Melville, et al., 2004). Moreover, when IT systems span firm’s
boundary via software applications or electronic markets and blend with the business
processes of trading partners and IT and non-IT resources of trading partners also
impact business value of IT, in particular competitive advantage of focal firm
(Mukhopadhyay & Kekre, 2002).
Chapter 1: Introduction 5
Figure 1.1 A high level conceptual framework of Strategic-BVIT (Emphasises the strategic perspective; competitive advantage being the ultimate
outcome) (Broadly discussed in section 2.3, Chapter 2)
The lenses in the proposed strategic conceptual framework of BVIT are briefly
described below-
1. IT assets and organisational resources:
IT assets: Anything tangible or intangible related to IT that can be used in
organizational processes for creating, producing, and offering products and services
(Wade & Hulland, 2004). Tangible IT assets are hardware, network infrastructure, or
human resources and Intangible IT assets are software, information assets, employees’
IT skills in IT functions (Melville, et al., 2004).
Organisational resources: “tangible or intangible factors of production that
organizations own, control, or have access to on a semi-permanent basis” (Nevo &
Wade, 2010, p. 164).
2. IT-enabled capabilities:
The ability to effectively use IT assets to support the organisational resources for
the benefit of organisations (Pavlou & El Sawy, 2006).
3. Competitive advantage:
Ma (1999, p. 259) defines competitive advantage as- “the asymmetry or
differential in any firm attribute or factor that allows one firm to better serve the
customers than others and hence create better customer value and achieve
superior performance”.
IT-enabled Capabilities
• IT Assets
• OrganisationalResources
Competitive Advantage
6 Chapter 1: Introduction
1.2 RESEARCH MOTIVATION
This study concurs with recent thought, that the dynamic and turbulent
environment of modern business has changed the way IT influences the creation of
business value in contemporary organisations, and thus an alternative
conceptualisation of BVIT is required. Recent IS studies have already applied
alternative approaches to understanding BVIT, such as, Nevo and Wade (2010) who
base their arguments on a combination of system thinking and RBV to study strategic
advantage; while Tanriverdi, Rai, and Venkatraman (2010) use concepts from
complexity thinking to explore the dynamics related to strategic competitive
advantage. Although these emerging studies have begun to explore aspects of the
dynamics related to the BVIT ‘puzzle’ (Chen et al., 2014), our knowledge in this
direction remains underdeveloped and unsystematic (Schryen, 2012).
With the above context in mind, this research entails three key motivations-
First, IT has become pervasive, ubiquitous and fused with business in
contemporary organisations (El Sawy, 2003; El Sawy & Pavlou, 2008). The fusion of
IT and business in contemporary organisations has led to emerging IT-enabled
capabilities, which in turn have caused a step-change in the complexity, dynamism and
uncertainty in complex adaptive business organisations (El Sawy, Malhotra, Park, &
Pavlou, 2010; Tanriverdi, et al., 2010). The role of digital technologies is no longer
merely as functional resources, rather they play a significant role in driving strategic
change (Yoo, Henfridsson, & Lyytinen, 2010). The relationship between these
technologies and business has become reciprocal, which gives rise to emergent IT-
enabled capabilities across different levels in organisations (El Sawy & Pavlou, 2008).
Consequently, there is a need to better understand the mechanisms by which emergent
technologies, such as, artificial intelligence (AI), Internet of Things (IoT), digital twins
and Blockchain, empower organisations with IT-enabled capabilities. Thus,
understanding the emergent nature of IT-enabled capabilities and its implications for
BVIT is a key challenge for today’s organisations in the increasingly turbulent
environment.
Second, there is a growing recognition that firms’ IT enabled business processes
and capabilities are distinctive sources of value creation (El Sawy & Pavlou, 2008;
Nevo & Wade, 2010). The contemporary business environment, characterised by
unpredictability arising from non-deterministic changes in market demand, consumer
Chapter 1: Introduction 7
preferences, turbulent business conditions, and techonogical breakthroughs, can cause
rapid transformations in IT enabled business capabilities, which in turn influence
strategic advantage (El Sawy & Pavlou, 2008; Yoo, Boland Jr, Lyytinen, & Majchrzak,
2012). Recent discourse in IS and strategy literature has focused on the relationship
between a firm’s IT enabled business processes and capabilities, and its governance
choices such as interfirm alliances, sourcing to the market, or establishing new
collaborations using a coevolutionary perspective (Benbya & McKelvey, 2006b;
D'Aveni, Dagnino, & Smith, 2010; Tanriverdi, et al., 2010; Tiwana, Konsynski, &
Bush, 2010). These studies show that IT-enabled business capabilities influence
competitive advantage in contemporary organisations. However, the underlying
mechanisms of how these capabilities influence BVIT remain under-theorised.
Third, the-ubiquity of digital technologies, environmental turbulence, and fast-
paced organisational change, cause adaptive organisations to constantly evolve
dynamically (Morel & Ramanujam, 1999). Due to rapidly improving technologies and
intense market competition, the adaptive organisations are evolving at an accelerating
rate, and competitive advantage has become transient (Iansiti & Levien, 2004;
Tanriverdi, et al., 2010). Strategies have become perishable; the landscapes of
technologies, IT enabled processes and capabilities, products and services have
become rugged and are constantly changing (Levinthal, 1997). Subtle changes to one
of the variables, for instance reconfiguration of a digital platform or coevolution of one
of the operational processes, can stem from rapid and/or unexpected movements
between players in the business system (Burgelman & Grove, 2007). Preparing for
these ‘unknown unknowns’ requires new types of sensing frameworks or perspectives
to capture the unpredictable dynamics in the business landscape (Meyer, Gaba, &
Colwell, 2005) . Yet, few studies have focused on the dynamic perspectives and their
roles in shaping BVIT across the business landscape, and this requires further
attention. The next section presents the research problem and research questions of the
study.
1.3 RESEARCH PROBLEM AND QUESTIONS
The overarching research problem is that the competitive landscape resulting
from advances in digital technologies and their deployment in organisations is
becoming complex, characterised by increased dynamism, non-linearity and
unpredictability; and the dominant approaches for theorising BVIT in this dynamic
8 Chapter 1: Introduction
environment are inadequate; there is need for new holistic perspectives and non-linear
approaches to better understand this emerging context. In brief, the research problem
consists of combination of two issues- 1) complexity and dynamism in contemporary
organisations due to the deployment of the digital technologies and 2) inadequacy of
dynamic approaches to explore the dynamics. It is important to note that, the terms
dynamism, complexity, unpredictability, non-linearity have been widely used in
broader strategic management and organisational research and IS literature to explain
dynamic behaviors/ patterns of adaptive organisations (Anderson, Meyer, Eisenhardt,
Carley, & Pettigrew, 1999; McKelvey, 1997c, 2002; Merali, 2006; Merali,
Papadopoulos, & Nadkarni, 2012; Mitleton-Kelly, 2003b). In this thesis, I have used
these terms in a similar way to refer to the dynamic behaviors of complex adaptive
organisations.
The research aim is to understand BVIT in the contemporary dynamic business
environment and the research question is-
RQ 1: How is BVIT created in the dynamic business-IT environment?
Given that the contemporary conditions outlined above have caused a step-
change in the complexity, dynamism, non-linearity, and unpredictability of
relationships among various business elements; this study has particularly considered
the recommendation that to deal with these challenges, we must adopt alternative
approaches; these include holistic system thinking, complexity perspective, and
configuration theories (Nevo & Wade, 2010; Oh & Pinsonneault, 2007; Peppard &
Ward, 2004; Tanriverdi, et al., 2010; Wade & Hulland, 2004). Scholars have suggested
several alternatives, such as, chaos theory (Boisot, 2006; Burgelman & Grove, 2007),
coevolutionary theory (Altschuller, Gelb, & Henry, 2010; McKelvey, 2002),
ecodynamics (El Sawy, et al., 2010), ecosystem (Peltoniemi & Vuori, 2004),
networked view (Courtney, Merali, Paradice, & Wynn, 2008) and complex adaptive
systems (Allen, 2001; Nan, 2011; Schneider & Somers, 2006; Vidgen & Wang,
2006b).
To address this research question, this study adopts complex adaptive systems
(CAS) theory (Holland, 1995), a branch of complexity theories (Vidgen & Wang,
2009), to understand the dynamism related to BVIT. A number of researchers, Merali
(2006), Benbya and McKelvey (2006a) and McKelvey (1999) consider CAS as a
concept of complexity theory. The broader complexity literature has different views
Chapter 1: Introduction 9
on CAS. However, I have considered CAS as a theory following Stacey, Griffin, and
Shaw (2000) approach throughout the thesis. Few reasons to choose Stacey’s approach
and consider CAS as a theory. First, Stacey assumes that organisations can be
considered as CAS consisting of large number of agents, where each agent follows a
smaller number of simple local rules, which determine the patterns of behavior of the
organisation as whole. Second, she argues that internal dynamics of the agent
interactions are nonlinear and unpredictable, which lead to structural development of
the system. Moreover, the emergent properties of the system mutually change with
properties internal and external to the system as soon as they start emerging, which
means properties of the system mutually evolve with respect to each other over time
(Lewin, Long, & Carroll, 1999; Van Valen, 1983). It is important to mention that, CAS
theory in this study has been used as “transitional objects” (Mitleton-Kelly, 2003b, p.
4), which provides a way of thinking about dynamic creation of BVIT. The CAS theory
can also be used metaphorically, however, metaphors are limited in explaining the key
nature of system under study (Mitleton-Kelly, 2003b).
CAS theory is particularly beneficial to explain non-linear and dynamic
behaviours of adaptive organisations (Anderson, 1999). It is valuable for research
because it offers a new way of thinking about organisations as systems of interacting
agents, such as, human, IT systems, business processes, etc. and helps to explain how
order emerges from the interactions of the agents (Stacey, et al., 2000; Vidgen &
Wang, 2006b). Moreover, CAS theory is well suited to modelling the non-
deterministic behaviors of contemporary organisations characterised by sudden and
substantive changes, which cannot be represented through deterministic system
theories, such as, chaos theory, and general systems theory (Burnes, 2005). Further,
CAS helps to encode non-linear complex phenomena through mathematical models
and facilitates the conduct of computational experiments in a virtual system, which
provides researchers precision and control over the model and helps to investigate the
dynamic relationships of system components (Morel & Ramanujam, 1999).
This dissertation argues that the deployment of digital technologies gives rise to
emergent IT-enabled capabilities, which coevolve each other within organisation and
with the competitors and influence competitive advantage. Therefore, this study adopts
two concepts of CAS theory- emergence and coevolution together to investigate the
dynamics related to BVIT, in particular competitive advantage. In particular, the
10 Chapter 1: Introduction
emergence concept provides a way of explaining complex adaptive behaviors of
interacting system components and overall emergent patterns rise from the
components interactions (Stacey, et al., 2000), which makes it better suited to explain
the emergent rise of IT-enabled capabilities. In addition, the coevolution concept is
better suitable to explain the evolution of one domain or agent in relation to the
evolution of other related domains or agents (Kauffman, 1995a; Kauffman, 1993).
Moreover, others studies have been using these concepts to study complex
organisational phenomena- emergence (e.g. Chiles, Meyer, & Hench, 2004; Choi,
Dooley, & Rungtusanatham, 2001; Kogut, 2000; Lichtenstein, Dooley, & Lumpkin,
2006; Sawyer, 2005) and coevolution (e.g. Huygens, Van Den Bosch, Volberda, &
Baden-Fuller, 2001; Koza & Lewin, 2001; McKelvey, 2002; Pacheco, York, Dean, &
Sarasvathy, 2010). Using the emergence concept of CAS theory (Goldstein, 1999), this
study first explores the way IT-enabled capabilities emerge. It then adopts the
coevolution concept of CAS theory to explore how these IT-enabled capabilities help
organisations to achieve competitive advantage. In particular, with an emphasis on
action-based competitive relationships (D'Aveni, et al., 2010), the coevolution concept
helps to explore how organisations vie for advantage by obtaining valuable and rare
IT enabled capabilities.
The study further adopts NKC model (Kauffman, 1995a) to develop in-depth
insights on the coevolutionary dynamics of the IT-enabled capabilities within
organisation (micro level) and with the competitors (macro level). The NKC model is
particularly beneficial as an in-depth exploratory lens of investigating coevolutionary
order in organisational studies (Baum & McKelvey, 1999c; McKelvey, 1999).
Moreover, it provides a way of modelling real life coevolutionary adaptive
progressions in logical steps within computer simulations and allows to change values
(N,K,C) to test coevolutionary dynamic behaviors of CAS (McKelvey, 2002). Further,
Kauffman’s NKC model can be applied at various organisation levels of analysis
including process microstates, including people skills and experiences represented as
agents as elaborated by (McKelvey, 1999). However, few limitations are also involved
in NKC modelling- problems in operationalising complexities, defining ruggedness
and correlation of fitness landscape concept, the use of proper distribution parameter
etc. (McKelvey, 1997a). Nonetheless, NKC model has been widely used in strategic
management and organisational studies (Baum & McKelvey, 1999c; Levinthal, 1997;
Chapter 1: Introduction 11
McKelvey, 1999; Mckelvey, Li, Xu, & Vidgen, 2013; Siggelkow & Levinthal, 2003),
which indicates its’ potential benefits in understanding complex organisational
coevolutionary dynamics and thus is adopted in this thesis to explore the
coevolutionary dynamics of IT-enabled capabilities and its impact on competitive
advantage (Chapter 6).
The position of the emergence and coevolution concepts in the overall BVIT
framework is shown in Figure 1.2. The high level framework is developed based on
the observation on the prominent BVIT models in IS studies. Please see section 2.3 in
chapter 2 for more detailed discussion on the framework. It is important to note that
the coevolution concept addresses the relationships of at least two elements that
mutually influence each other (Volberda & Lewin, 2003). In Figure 1.2, the
coevolution concept represents both the relationships between two or more mutually
influencing IT-enabled capabilities internal to the organisation, and the reciprocal
influences of one or more IT-enabled capabilities of the focal organisation on one or
more IT-enabled capabilities of competitors, and vice versa.
Consequent research questions are,
RQ 1.1: How do IT-enabled capabilities emerge?
RQ 1.2: How do IT-enabled capabilities influence competitive advantage?
Figure 1.2 The position of the CAS concepts in the high-level conceptual framework of BVIT (The arrows are positioned under the concepts to represent their position in the thesis)
In this thesis, the CAS emergence and coevolution concepts are used to develop
explanatory theory (Gregor, 2006) on how BVIT, more specifically competitive
advantage is created in the contemporary organisations. The emergence concept helps
IT-enabled Capabilities
• IT Assets
• OrganisationalResources
Competitive Advantage
Emergence
Coevolution
12 Chapter 1: Introduction
to explain the process of emergent IT-enabled capabilities (see details in Chapter 4)
and the coevolution concept helps to explain the way IT-enabled capabilities evolve in
relation to each other within organisations and with respect to the competitors and
impact competitive advantage (see details in Chapter 5).
1.4 RESEARCH METHODOLOGY
The study overall employs three research methods in different stages. In the first
stage, a background literature is conducted on broader topic areas- business value of
IT and complexity theories (Chapter 2) and a structured review is conducted on CAS
theory specifically (Chapter 3). In the second stage, a theory development approach is
adopted following Shepherd and Suddaby (2017) review on theory building methods
and tools (Chapter 4 and 5). Finally, NKC model (Kauffman, 1995a) is used to explore
and develop in-depth insights on BVIT, in particular competitive advantage (Chapter
6). The research methods are briefly described below-
1. A background literature in core topic areas- business value of IT and
complexity theories is conducted in Chapter 2. The background literature is
used to develop understanding on the current state of BVIT research and to
understand the use of broader complexity theories in within IS and
organisational studies. In addition, a structured literature review following
the guidelines of Webster and Watson (2002) is conducted on CAS theory
in Chapter 3. The structured review is used to understand CAS theory in
general (including seminal works) and within IS in particular. The structured
CAS literature review helps to identify the major CAS concepts used in
relation to BVIT studies, how they are applied, and the type of theories
developed using the CAS concepts. Moreover, Chapter 4, 5 and 6 contain
in-depth reviews on emergence, coevolution concepts and NKC model
consecutively. These reviews are specifically used to develop in-depth
understandings on the emergence (Chapter 4) and coevolution (Chapter 5)
concepts and NKC model (Chapter 6) and their use in IS studies in
particular.
Chapter 1: Introduction 13
2. The theory development approach based on the Shepherd and Suddaby
(2017) review of methods and tools for theory building is adopted. This
method guides the thesis to develop theories using CAS emergence (Chapter
4) and coevolution (Chapter 5) concepts. This is the core of the research
approach (Figure 1.3), summarized in this chapter and discussed in detail in
Chapter 4 and Chapter 5. I have developed explanatory theories (Gregor,
2006) adopting the CAS emergence and coevolution concepts in Chapter 4
and Chapter 5 consecutively. As a part of the theory development, I have
proposed two frameworks- a complex emergence framework of IT-enabled
capabilities (Figure 4.4 in Chapter 4) and a coevolution framework of IT-
enabled capabilities (Figure 5.5 in Chapter 5). The theory development
using emergence and coevolution concepts also yield propositions
(Summarised in Table 4.3 in Chapter 4 and 5.3 in Chapter 5).
It is important to note that, I have adopted the term ‘framework’ instead of
‘model’ to represent my proposed theoretical knowledge contributions throughout the
thesis. The term framework represents several kinds of information about a particular
situation (Minsky, 1974). The information includes about how to use the framework,
information about cause-effect relations, changes in conceptual viewpoint or synthesis
knowledge from different viewpoints (Minsky, 1974). A framework consists of nodes/
terminals representing some concepts and relations among them. The nodes are
flexible meaning new concepts can be added or concepts can be removed to describe
certain situations. In contrast, a model describes an organised set of parts/ components
and their relationships (Woodward, 2002). Each of the model components can be
generalised under certain interventions and the manipulation of each of the
components of the model changes the overall outputs. In my thesis, the term
framework is used specifically to explain BVIT from CAS conceptual viewpoint, in
particular, the CAS emergence and coevolution concepts are used in the context of IT-
enabled capabilities to explain BVIT, more specifically competitive advantage. IS
scholars have adopted one or more CAS concepts, applied them in different research
context- IS development (Vidgen & Wang, 2006b, 2009), IT use process (Nan, 2011),
intra-firm relationships in mobile ecosystem (Basole, 2009), develop frameworks and
propositions on the research context and provide in-depth explanations. In this study,
14 Chapter 1: Introduction
I have followed a similar approach and develop frameworks and propositions based
on CAS emergence (Chapter 4) and coevolution (Chapter 5) concepts.
3. NKC model translation into the conceptualisation of competitive advantage
based on the McKelvey (1999) approach, which is discussed in Chapter 6.
The NKC model is used as an exploratory lens to develop in-depth insights
on the coevolution of the IT-enabled capabilities via analytical NKC
components and logic. The theories developed in this stage are exploratory
in nature as it extends the NKC logics in the context of coevolutionary
dynamics of IT-enabled capabilities to broadly explain coevolutionary
dynamics in relation to the IT-enabled capabilities and how it impacts
competitive advantage.
In summary, the review on CAS theory in IS research serves broader ideas on
the concepts and features of CAS theory in relation to the BVIT studies and helps to
choose emergence and coevolution concepts for the thesis. The theory development
approach by Shepherd et al. provides an overarching guideline on how to develop
theories following a set of well-structured approaches. Finally, the NKC models serves
as an exploratory lens and gives in-depth insights on the coevolution of the IT-enabled
capabilities drawing underlying analytical logics of NKC model.
The aim of the study is to develop a better understanding of the dynamics related
to BVIT. Review of the BVIT literature reveals the few authors who have attempted
to theorise the dynamics of BVIT in their studies; e.g. the work by Nevo and Wade
(2010) on IT enabled resources using the emergence concept; the Melville, et al.
(2004) discussion focuses on the micro-macro level in their RBV based work
regarding BVIT; and Tanriverdi, et al. (2010) work on the strategic side of BVIT using
the complex adaptive business systems lens. This study uses existing theorising on
BVIT as a starting point and develops a re-conceptualisation of the theories on BVIT
using the CAS lens. In this study, I have adopted the Nevo and Wade (2010) study to
define two core constructs, then follow their ideas to apply my proposed notion of CAS
complex emergence (Halley & Winkler, 2008) to the study of the emergence of IT-
enabled capabilities (Chapter 4). In addition, based on the Melville, et al. (2004)
discussion on domains, the focal firm, competitive environment, and macro
environment, I have proposed two levels, micro (internal to firm) and macro (external
Chapter 1: Introduction 15
to firm) in which the IT-enabled capabilities coevolve with other IT-enabled
capabilities (Chapter 5).
There is a growing literature that offers many tools and approaches to theorising,
for example, metaphor (Cornelissen, 2005) or concepts (Dumont & Wilson, 1967). In
the management discipline, Shepherd and Suddaby (2017) review the literature on
theory building and integrate various ideas about how to build theory. They review
various methods and tools and provide explanation for how and when to use different
tools for theorising and discuss how to evaluate theories. I have constructed my theory
development approach for this study, based on their ideas. Only selected ‘tools’ are
chosen to develop my approach because of the highly conceptual nature of the
dissertation and the focus of the research. My theory development approach consists
of three major steps, 1) defining the narrative conflict, 2) building stories to construct
theories, and 3) evaluating theories. The steps are described below in the context of
this study. Figure 1.3 summarises the research approach.
1.4.1 The Narrative Conflict
Theory development starts with identifying an anomaly or a tension that
motivates the process. Narrative conflict refers to the struggle between two entities,
such as, human vs. human or human vs. nature. In relation to theory, narrative conflict
highlights a struggle between two ways of knowing, such as real world empirical
observation vs. theoretical concepts that attempt to describe the empirical world
(Shepherd & Suddaby, 2017).
In the context of this study, there is a conflict between what we explore in reality
to understand the dynamics in the context of BVIT in existing literature, and the
theories or concepts that help us to explore such dynamics. The existing literature
provides organisational perspectives of BVIT based on internal business processes,
organisational capabilities and organisational practices, from empirical observations
of the real world (Bharadwaj, 2000; Melville, et al., 2004). However, technologies are
changing, proliferating within and among organisations and altering the ways business
is conducted (Merali, et al., 2012). In this fast changing world driven by uncertainty,
dynamism and high interconnectedness, the way business value is created is
increasingly dynamic, as acknowledged by several prominent IS scholars (e.g.
Altschuller, et al., 2010; Chen, et al., 2014; Nevo & Wade, 2010; Schryen, 2012;
Tanriverdi, et al., 2010). Although emerging studies have begun to explore the
16 Chapter 1: Introduction
dynamics and uncertainty related to the BVIT puzzle, existing theories or concepts that
help to explore such dynamics still remain limited and underdeveloped. Moreover, the
world of business has become dynamic, strategies are perishable, and the landscape of
technology and business is rugged (Tanriverdi, et al., 2010). Preparing for ‘knowing
these unknowns’ highlights the need for rethinking existing theory and perhaps the
need to acquire new types of sensing frameworks or perspectives to capture the
unpredictable dynamics in the business landscape (Meyer, et al., 2005).
In chapter 4, I have provided a more specific example of ERP system to highlight
the narrative conflict, which is the tension between the existing literature on
emergence, whether emergence is linear or non-linear (dynamic) and the
conceptualisation of such emergence. In chapter 5, I have adopted the same ERP
system case from chapter 4 to present the narrative conflict, which is the tension
between the existing literature on coevolution, whether the internal and external
coevolution are linear or non-linear (dynamic) and the conceptualisation of such
coevolution.
1.4.2 Building Stories
Building stories refers to building a narrative framework to organise theory
development, emphasising sequential story-telling to weave together prior knowledge
with the construction of new knowledge. It involves four major stages; identifying the
core constructs, determining the narrative settings, drawing boundary conditions, and
applying disciplined imagination (theorising) (Shepherd & Suddaby, 2017). Each of
these stages is discussed below in the context of this study.
Identifying Core Constructs
Identifying the core constructs related to the study is important because it helps
to conceptually separate the phenomenon under study from other phenomena. The core
construct of this study is the business value of IT (BVIT). The study adopts existing
theorising of BVIT as a starting point and then develops a reconceptualization of
BVIT, which is broadly discussed in the next sections.
Determine the Narrative Setting: Shifting Ontology
Determining the narrative setting involves specifying a time and place within
which events occur. It is important to describe the narrative setting, the context of the
study, to explain the reasoning behind the story telling, the credibility of the theoretical
Chapter 1: Introduction 17
argument, and the motivations of the study. Different strategies are used by theorists
to adopt new perspectives by adjusting the philosophical setting. For this study a
shifting ontology strategy is adopted.
Shifting ontology is used to develop creative insights for the development of
theories (Shepherd & Suddaby, 2017). It refers to “changes in the ontological emphasis
that maintain epistemic-ontological alignment” (Thompson, 2011, p. 755). Ontology
refers to the nature of the phenomena under study and epistemology represents the
nature of knowledge on the phenomena; ontology deals with the nature of reality and
reflects an interpretation by an individual about what constitutes a fact (Gioia & Pitre,
1990). It is important to consider both ontology and epistemology together as an
ontological shift changes the epistemology of the study (Thompson, 2011).
In this study, shifting ontology highlights the change from a static-linear view
on BVIT to a more dynamic-complex view on BVIT. As mentioned earlier in section
1.2, in contemporary organisations, technology and business are fused in a way that
causes a step-change in the complexity of the business ecosystem (El Sawy, et al.,
2010) and thus, the way value creation in contemporary organisations has changed.
Subtle change in any of the components in the business environment, can stem not
only from rapid, but also unexpected movements between players in the business
system (Burgelman & Grove, 2007). Thus, a new perspective or alternative approach;
from a static perspective to a dynamic one; is required to better understand interactions
among the different elements in the business environment and how their relationships
influence BVIT (Tanriverdi, et al., 2010).
Figure 1.3 Research Approach
Draw Boundary Conditions: The Story’s Event Sequence
Specifying boundary conditions by relating the sequence in which events occur
is an important consideration in theory development. Theorising can involve shifting
the time sequence in a way that can help to change the ontological perspective and to
1. The Narrative Conflict:
Problematisation
Indetify the Main construct: BVIT
Draw boundary conditions: The
story's event sequence
Apply disciplined Imagination: Theorising via
Metaphor
3. The Evaluation of
Theory
Determine the narrative setting:
Shifting Ontology
2. Building Stories
18 Chapter 1: Introduction
better describe the relationship between constructs (Shepherd & Suddaby, 2017). This
study emphasises the time constraints via explaining event sequences in the context of
the IT-enabled capabilities. It argues that IT-enabled capabilities first emerge from the
interactions between the IT assets and organisational resources. As soon as the IT-
enabled capabilities emerge, they start coevolving with other IT-enabled capabilities
of organisations (see section 1.3). Though the time at which these events (the
emergence of the IT-enabled capabilities and then their coevolution) occur cannot be
easily explicated, the event sequences help to draw the boundary conditions. The
influence of the coevolution of IT-enabled capabilities on competitive advantage can
be considered as another event sequence.
Moreover, another boundary condition related to this study that I have
emphasised above is the strategic perspective on BVIT (the competitive advantage of
organisations), not operational efficiency (the operational perspective of BVIT). In
addition, my focus in the study is on contemporary organisations, which are operating
in moderately to rapidly changing business environments (such as retailing and
financial organisations) and are subject to the disruptive force of digitisation
(Sambamurthy, et al., 2003). The kind of IT focused on in the study includes pervasive
and generative digital technologies that are “dynamic and malleable” (Yoo, et al.,
2012, p. 1399) and provide “software-based digital capabilities” (Yoo, et al., 2012, p.
1398), such as, digital platforms that allow organisations to support their different
functions. These digital technologies are nearly inseparable from core products and
services (El Sawy, 2003) and are fundamentally reshaping organisations (Banker,
Chang, & Kao, 2010; Sambamurthy, et al., 2003).
Apply Disciplined Imagination: Theorising via Metaphor (Analogical Reasoning)
Shepherd and Suddaby (2017) have discussed several approaches to applying
‘disciplined imagination, such as, thought experiments (Weick, 1989), simulation
(Davis, Eisenhardt, & Bingham, 2007) or analogical reasoning (Tsoukas, 1993). This
study adopts an analogical reasoning approach via theoretical metaphors as suggested
by Tsoukas (1993).
Metaphors provide languages or vocabulary to engage, organise and describe the
phenomena under interest (Tsoukas, 1991). Metaphors and analogies guide
imagination, helping to illustrate and describe alternative conceptions of reality by
Chapter 1: Introduction 19
selecting certain features of it and thus forming an explanatory point-of-view of the
world (Tsoukas, 1993). Theorising via metaphors provides new perspectives, images
or concepts to develop creative insights into the social world. This study has adopted
two CAS metaphors (Mitleton-Kelly, 2003b), emergence and coevolution to
understand and theorise the dynamics related to BVIT. Based on the existing literature
on BVIT, as suggested by Mintzberg (2005, p. 362), the theorising process using CAS
metaphors provides structured descriptions of the dynamics related to the BVIT. The
study has applied CAS metaphors to use analogical reasoning to theorise the dynamics
related to BVIT and develop a CAS BVIT model. In chapter 4 and chapter 5, I have
used two CAS metaphors, emergence and coevolution respectively to theorise
dynamics related to the BVIT.
Firstly, the study reviews the existing core BVIT models (mid-range theories) to
determine to what extent the models focus on the dynamics related to the BVIT. An
examination of the BVIT research reveals that there is a growing literature in IS, which
provides hints about the development of the dynamic conceptualisation of BVIT,
though they do not provide an in-depth explanation of BVIT dynamics. This study has
adopted BVIT theorising from two such studies as a starting point, and applied CAS
metaphors for reconceptualization.
Firstly, Nevo and Wade (2010) applied a systems theory lens, more particularly
the emergence concept from systems theory, to explain how IT enabled capabilities
come into existence from the interaction between IT assets and organisational
resources. However, they conceived a static and linear approach to describe the
emergence of IT enabled capabilities. Secondly, although Melville, et al. (2004)
discussed the macro and micro environment, where macro specifies country
characteristics and micro includes focal firm and competitive environment, they
ignored how this micro-macro environment interacts and influences BVIT creation.
Although they started exploring the BVIT puzzle, they did not address the dynamics
in relation to BVIT.
Therefore, to develop and theoretically explain insights into the dynamics and
unpredictable complexities in relation to BVIT, more specifically competitive
advantage, this study has applied CAS theory. In particular, the complex emergence
metaphor of CAS theory is applied to describe how IT enabled capabilities emerge via
a bottom-up process in contemporary organisations (Chapter 4). Moreover, the
20 Chapter 1: Introduction
coevolution CAS metaphor is applied to describe how the IT enabled capabilities
coevolve within and among organisations and influence competitive advantage
(Chapter 5). Together these CAS metaphors- emergence and coevolution will help me
to explore the answer to the research question in section 1.3.
1.4.3 Evaluating Theory
Despite the importance of developing theories and making a theoretical
contribution, the resolution of the story (i.e., what constitutes a theory) varies widely
as does the interpretation of what represents a good story (i.e., a theoretical
contribution) (Shepherd & Suddaby, 2017). The study starts with the concern that the
growing IS literature, although it acknowledges the dynamics in relation to BVIT,
lacks conceptualisation. Therefore, this study will particularly focus on developing
new insights that help to describe the dynamics related to BVIT. So, the study begins
with identifying a problem and its associated assumptions; clarifying and focusing the
problem; and analysing, understanding and making use of analogical reasoning, as
well as evaluating the reliability of the assumptions from the literature available, and
concludes with new insights. Via the critical reasoning (Cederblom, 2012) approach,
the study evaluates what has been claimed during problematising and the insights
provided that help to reduce the research gap.
Illustrative case studies are used to conduct internal validation (Eisenhardt,
1989) of the developed theories. In chapter 4, I have adopted an ERP system case study
by Lokuge (2015) for internal validation (Eisenhardt, 1989) of my developed theories
of the emergence of the IT-enabled capabilities. I have conceptualised the case
narrative in the context of my proposed emergence framework and showed that the
concepts, analytical logic and conditions of my framework are in alignment with the
case study (section 4.4.2, chapter 4). Further, in chapter 5, I have adopted IS
development case study by Montealegre, Hovorka, and Germonprez (2014) for
internal validation (Eisenhardt, 1989) of my theories on the coevolution of the IT-
enabled capabilities. Using the case narrative, I have represented that my proposed
coevolutionary framework can provide in-depth and sense-naking insights on the
coevolution of IT-enabled capabilities and its impact on firm’s competitive advantage
(see 5.6.2, chapter 5).
Chapter 1: Introduction 21
Figure 1.4 Approach to theory development in relation to BVIT
Nev
o &
Wad
e(2
010)
Mel
ville
(200
4)
Emer
genc
e
Mic
ro-m
acro
le
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1.Th
e N
arra
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Con
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2. B
uild
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ies:
-Def
ine
BVIT
-D
eter
min
e nar
rativ
e se
tting
s
2.Bu
ldin
g St
orie
s: D
raw
bo
unda
ry co
nditi
ons &
app
ly
Disc
iplin
ed Im
agni
atio
n vi
a CA
Sm
etap
hors
Com
plex
Em
erge
nce
Coe
volu
tion
New
Insig
hts:
Em
erge
nce
of IT
en
abled
cap
abili
ties
-Con
trolli
ng fa
ctors
re
lated
to em
erge
nce
Cor
e BV
IT
mod
elsN
ew In
sight
s:
Coev
olut
ion
of IT
en
abled
cap
abili
ties
-Coe
volu
tiona
ry
Dyn
amics
3. N
ewIn
sight
s (Th
eory
) an
d Ev
alua
tion
Orig
inal
Th
eory
Re-
desig
ned
Theo
ryA
nalo
gica
lR
easo
ning
via
CA
S Th
eory
Stat
ic &
Lin
ear
Dyn
amic
and
com
plex
How
do
IT en
able
dca
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s em
erge
?
How
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IT en
able
dca
pabi
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s co
evol
ve a
nd
influ
rnce
co
mpe
titiv
e ad
vant
age
22 Chapter 1: Introduction
The study has thus used existing theories related to BVIT, identified the problem
(the static and linear view of BVIT), and applied CAS metaphors as analogical
reasoning to theorise and develop new insights- re-designed theories (a dynamic and
complex view of BVIT), which are explanatory type (Gregor, 2006). After then, NKC
representation of BVIT is used to explore greater in-depth insights on the dynamic
BVIT creation. The theory development flow diagram is illustrated in the following
Figure 1.4 with the research methodology embedded within it.
1.5 RESEARCH DESIGN
The research design (Figure 1.5) includes six phases:
1. Define the research problem,
2. Propose the conceptual model of BVIT,
3. Develop an emergence perspective of IT-enabled capabilities,
4. Develop a coevolutionary perspective of the IT-enabled capabilities,
5. Operationalise the coevolutionary perspective of the IT-enabled capabilities,
and
6. Present CAS based understanding of BVIT. The phases are described below-
Phase 1: Define the research problem
In this phase, I identified i) Research motivation(s), ii) Research problem &
context, iii) Research question(s), and iv) Research Objectives. Based on an extensive
review of IS and strategic management literature on BVIT, I have been able to identify
the current state of BVIT studies and the research gaps to which this study will
contribute. Topics reviewed are: i) existing BVIT studies (Chapter 2), ii) prominent
BVIT models (Chapter 2), iii) dynamic and non-linear approaches related to the
investigation of BVIT (Chapter 2), iv) complexity science and its relation to the BVIT
research (Chapter 2), and (v) CAS theory and its status in IS research (Chapter 3).
Phase 2: Propose a conceptual framework of BVIT
The BVIT conceptual framework is proposed based on the literature review of
the prominent strategic BVIT models in IS research (See Figure 1.1). This review
revealed three key parts to the models, where the 1st part contains IT related assets and
Chapter 1: Introduction 23
other organisational resources, the 2nd part emphasises the different capabilities
derived from IT, and the last part includes the organisational performance, competitive
advantage in particular. (See section 1.4)
Figure 1.5 An overview of Research Design
Phase 3: Develop an emergence perspective on IT-enabled capabilities
Based on the theoretical concept of Nevo and Wade (2010), a study for
understanding strategic BVIT, I have first proposed a complex emergence model of
IT-enabled capabilities, which shows how IT enabled capabilities emerge (See Chapter
Define ContextResearch Context
Research questions/ Objectives
Review Literature
Complexity TheoriesBVIT
Develop LR protocol for CAS in
ISKeyword Search
protocol documentation
Conduct review on CAS in IS
Phase 3:Emergence persp.
on IT-enabled capabilities
Data gathering and analysis protocol
Data reporting strategy Issues
Conceptual analysisTheoretical and methodological
approachesContextual Analysis Theory types
Emergence framework on IT-enabled
capabilities
Phase 4: CAS coevolutionary
persp. of IT enabled capabilities
Interpret Propositions Implications for
theory and practice
Phase 6: A CAS understanding on
BVIT
Phase 2:Propose BVIT conceptual
franework
Phase 1
NKC Translation of coevolution
Phase 5
Coevolution framework on IT-enabled
capabilities
Emergence Propositions related to IT-enabled
capabilities
Coevolution Propositions related to IT-enabled capabilities
24 Chapter 1: Introduction
4). This emergence model is expected to serve as an ideal approach for encoding a
bottom-up view of IT enabled business capabilities into a formal model, which can be
used to gain deeper insights related to BVIT in the next phase 4.
Phase 4: Develop a coevolutionary perspective of IT-enabled capabilities
Based on Melville, et al. (2004) discussion on domains, the focal firm,
competitive environment and macro environment to define the focus of BVIT creation,
I have proposed two levels, micro (internal to firm) and macro (external to firm) in
which the IT-enabled capabilities coevolve with other IT-enabled capabilities (Chapter
5). A Micro coevolutionary perspective based on variation, selection and retention
mechanisms is discussed in relation to the IT-enabled capabilities following Chae
(2014). Moreover, a macro coevolutionary dynamics perspective in relation to the IT-
enabled capabilities is discussed by adopting the Red Queen effect, competitive
exclusion and niche separation concepts from (McKelvey, 2002). How firms achieve
competitive advantage by obtaining valuable and rare IT enabled capabilities is also
discussed, with the emphasis on action-based competitive advantage approach
(D'Aveni, et al., 2010).
Phase 5: Operationalise the coevolutionary perspective of the IT-enabled capabilities
I have used Kauffman’s NKC model (Kauffman, 1993) to operationalise the
coevolutionary perspective of the IT-enabled capabilities in this phase. I have first
translated the coevolution of the IT-enabled capabilities using the parameters of NKC
model following McKelvey (1999). Then, I have followed the Baum and McKelvey
(1999c) approach to formalise strategies on whole-part coevolutionary competition.
Several strategies are proposed in this phase (See Chapter 6).
Phase 6: A CAS understanding of BVIT
In this phase (See Chapter 7), the emergence perspective of IT from phase 3, the
coevolutionary perspective on IT- enabled capabilities from phase 4, and the
operational NKC model of IT-enabled capabilities from phase 5, are together used to
provide and in depth answer to the research question- how is BVIT created in the
dynamic business-IT environment?
Chapter 1: Introduction 25
1.6 CHAPTER SUMMARY
In summary, this chapter presents an overview of the dissertation. In section 1.1,
an overview of the research related to the BVIT topic is provided; focusing on what is
BVIT, why does it matter and how it is studied via different approaches across IS
studies.
The subsequent section highlights the motivation behind this research, which is,
that the dynamic business environment has changed the way by which IT influences
the creation of business value in contemporary organisations, and thus a
reconceptualisation of BVIT is required, as advocated by prominent IS scholars.
Section 1.3 addresses the overarching research problem.
Section Error! Reference source not found. broadly discusses the overall
research question and the two sub questions. It also briefly explains that this study has
adopted CAS theory, in particular the emergence and coevolution concepts, to explore
the dynamics related to the BVIT.
Section 1.4 broadly discusses my proposed research methodology based on the Section 1.4 broadly discusses my proposed research methodology based on the
ideas of Shepherd and Suddaby (2017) regarding the methods and tools for theory
building. The subsequent section presents a brief overview of the six phases of my
proposed research design.
In the next chapter I present a review of the literature to determine the status of
BVIT research and complexity theories in the IS discipline.
Chapter 2: Background Literature 27
Chapter 2: Background Literature
Chapter 2 Summary
What was done in the previous chapter: The previous chapter sets up the
research context by defining the overarching research problem, research questions
pertaining to the problem, research method and design.
What this chapter does: This chapter presents the extant literature related to
BVIT and complexity theories to discuss the research background.
What is still outstanding in later chapters:
Chapter 3: Contains a structured literature review on CAS theory in IS.
Chapter 4: An emergence perspective of IT-enabled capabilities.
Chapter 5: A coevolutionary perspective of IT-enabled capabilities and how
it influences competitive advantage.
Chapter 6: An operational (NKC) coevolutionary model of IT-enabled
capabilities.
Chapter 7: A CAS based framework on competitive advantage and a
discussion on the overall insights that I have developed in relation to BVIT.
Chapter 2 contains an overarching literature review on BVIT and broader review
on complexity theories in IS and referral disciplines. This chapter begins with a
historical background and reviews literature on the following topics: business value of
information technology and complexity theory. The complexity theory has been
chosen as an overarching theoretical base as it helps to conceptualise a system as
complex adaptive system (CAS) (Burnes, 2005). The CAS theory is a branch of
complexity theory that helps to model a particular phenomenon by using agent based
approach and CAS concepts. As I have conceptualised BVIT using two CAS concepts-
emergence and co-evolution, therefore a background review on broader complexity
theory is presented in this chapter. Moreover, both BVIT and complexity literature
helps to better understand the studies conducted in relation to BVIT, identify the
28 Chapter 2: Background Literature
research gap and relate how CAS, a branch of complexity theory can help to better
understand the issue.
The following section first provides a historical background on BVIT related
research. Then it discusses the core BVIT models in IS literature. The following
section presents a high level conceptual framework with a particular focus on strategic
side of BVIT. After then, a review on broader complexity theories is presented. The
chapter concludes with a summary.
2.1 HISTORICAL BACKGROUND
The main objective of this study is to develop an in-depth understanding of the
dynamic side of business value of IT (BVIT) in contemporary business organizations,
which has received less attention in IS research. To do so, BVIT related literature is
explored (section 2.1) to develop a thorough understanding on various types of
research conducted on BVIT in IS. After investigating the prominent models of BVIT,
the chapter presents a high level conceptual framework on BVIT in section 2.3. The
conceptual model is intended to present a common understanding of scholars on the
strategic side of BVIT, which is how organisations achieve competitive advantage by
IT deployment (Porter & Millar, 1985).
From the review, it is identified that the traditional literature on BVIT
emphasises the more static side of BVIT (Melville, et al., 2004), where organisational
resources, capabilities, routines, etc. are considered as static over a period and
researchers adopt different approaches such as process, variance or systems
approaches to study their effect on organisational performance. Few IS research
scholars (e.g. El Sawy, et al., 2010; Tanriverdi, et al., 2010; Yoo, et al., 2012) have
addressed this particular issue – that emerging digital IT and their deployment in
organisations have given rise to a step change in relationships among different
organisational business components, such as resources and capabilities, IT
competencies and strategic potential. Consequently, they have called for alternative
methodological and conceptual approaches to deal with these changes.
The authors in this stream assert the importance of understanding the dynamic
nature of relationships between different resources and their organisations, and
between organisations and their environment (Merali, et al., 2012). They recommend
that at a more general level there is a concern with the need for systemic and complex
Chapter 2: Background Literature 29
theory building to understand such dynamic relationships. For instance, El Sawy, et al.
(2010) advocate the use of configuration theories to describe the pattern of interactions
among environmental turbulence, dynamic capabilities and IT systems, while,
Tanriverdi, et al. (2010) adopt complex adaptive systems theory to reframe three IS
strategy quests; strategic alignment, integration and sustained competitive advantage.
Whilst they differ in focus and their prescriptions, the recommendations of these
authors draw on systems and complexity thinking for understanding dynamics related
to different organisational phenomena. This study adopts their recommendations and
adopts CAS theory, a branch of complexity theories (Burnes, 2005) to explore the
dynamics related to the BVIT. Therefore, this chapter reviews complexity theories
(Burnes, 2005) as well (section 2.4) because it is important to know the various
complexity concepts or metaphors that help to deal with the implicit dynamic and non-
linear nature of different organisational phenomena (Mitleton-Kelly, 2003b).
2.2 BUSINESS VALUE OF INFORMATION TECHNOLOGY (BVIT)
The following sections review the definition of BVIT, the theoretical paradigms
in relation to BVIT and the core models of BVIT.
2.2.1 Definition of BVIT
The term ‘business value of IT’ (denoted as BVIT throughout the dissertation)
is used to refer the organisational performance impacts of IT, including performance
enhancement, profit improvement, cost reduction and other metrics of performance
(Kohli, 2003; Lin & Shao, 2006; Melville, et al., 2004). The analysis of IS literature
reveals diverse connotations, definitions and notions of economic and non-economic
consequences of IS investments as BVIT. Scholars have embraced conceptual,
theoretical and analytical approaches to measure BVIT at different levels of an
organisation (Melville, et al., 2004). For example, many empirical studies have used
econometric approaches to explore the relationship between IT investment and
performance, such as productivity (Hitt & Brynjolfsson, 1996), return on sales
(Bharadwaj, 2000) or sales growth (Weill, 1992). Other studies go beyond financial
measures to examine intangible assets like organisational capabilities (Kohli &
Grover, 2008) or employee satisfaction (Bulchand-Gidumal & Melián-González,
2011). Much of their effort to measure BVIT is valuable, though IS literature still lacks
a consistent and widely accepted definition of IT business value (Oz, 2005). Lack of
30 Chapter 2: Background Literature
theoretical understanding (Gable, Sedera, & Chan, 2008), inappropriate measures of
BVIT (DeLone & McLean, 1992) and inconsistencies in human judgement (Davern &
Wilkin, 2010) are some of the fundamental reasons for variations in defining BVIT.
For the purpose of this research, Melville’s definition of BVIT has been adopted-
, “…organisational performance impacts of information technology at both the
intermediate process level and the organisation wide level, and comprising both
efficiency impacts and competitive impacts ” (Melville, et al., 2004).
2.2.2 Theoretical paradigms in BVIT research
The vast majority of BVIT related IS research reveals that researchers have
followed various theoretical paradigms to trace the path of BVIT from IT investment
e.g. resources-based view (RBV), industrial organisation theory, micro-economic
theory, organisational behaviour, socio-political paradigms etc. RBV theory (Barney,
1991; Wernerfelt, 1984) has been adopted to explore the operational efficiency and
competitive advantage of firm resources (Mata, et al., 1995; Porter & Siggelkow,
2008). This particular theory is useful to better understand whether specific IT
resources and capabilities possess advantages among competing firms (Melville, et al.,
2004). IS researchers have been using the RBV for developing in-depth understanding
of BVIT (Altschuller, et al., 2010; Benitez-Amado & Walczuch, 2011; Bharadwaj,
2000; Mata, et al., 1995; Ravichandran & Lertwongsatien, 2002). As mentioned in
(Peteraf & Bergen, 2003) and cited in (Melville, et al., 2004)the “integration of
management perspective with an economic perspective” of RBV is very useful for the
development of the BVIT model.
Rooted in RBV, dynamic capabilities theory (Eisenhardt & Martin, 2000) also
has been popular to explore the strategic role of IT in shaping competitive advantage.
Dynamic capabilities are the organizational and strategic routines by which managers
alter their resource base—acquire and shed resources, integrate them together, and
recombine them—to generate new value-creating strategies (Grant, 1991). They help
firms to integrate or reconfigure organisational resources within firms to achieve
superior competitive advantage (Eisenhardt & Martin, 2000).
Microeconomic theorists have applied rich mathematical specifications and
modelling to study BVIT. The theory of production was applied to investigate the
production process and its economic impact on IT (Brynjolfsson, 1993; Brynjolfsson
Chapter 2: Background Literature 31
& Hitt, 1998; Dedrick, Gurbaxani, & Kraemer, 2003; Hitt & Brynjolfsson, 1996).
Researchers have also used growth accounting (Brynjolfsson & Hitt, 2003), consumer
theory (Benaroch & Kauffman, 1999; Hitt & Brynjolfsson, 1996) and Tobin’s q
(Bharadwaj, et al., 1999) to understand performance implications of IT. Although the
focus of the micro economic theory is quite specific to the production process, its
application in BVIT research has enhanced our understanding on different phenomena
(Melville, et al., 2004). Devaraj and Kohli (2000) applied organisational behaviour
theory to investigate IT payoff in healthcare industry. Very few of the research
paradigms considered the notion of sociology and the socio political perspective of
BVIT (Hoogeveen & Oppelland, 2002b).
The theoretical paradigms have been applied for a better understanding of
organisational performance related to IT ( i.e. BVIT) in organizations stem from
different perspectives. Although research into BVIT leads to different streams of
thoughts on BVIT, a unified and coherent BVIT theoretical framework is still missing
in the literature, as has been acknowledged by several researchers over the years
(Melville, et al., 2004; Schryen, 2012). The next section discusses the core BVIT
models in the IS literature.
2.2.3 Core Models of BVIT
Several different BVIT models exist in the IS literature. These models differ by
research focus, phenomena under study, theoretical lens and approaches, such as,
process or variance, applied in the research (Melville, et al., 2004). However, the
prominent models of BVIT can be largely categorised into two types having two
perspectives-
1. Operational model: BVIT models that are operational and process-centric,
representing how, when and why IT investment is converted to favourable
organisational performance (Melville, et al., 2004). The models under this
category holds an operational perspective of BVIT.
2. Strategic Model: BVIT models that are strategic focusing on how
organisations can achieve superior competitive advantage over their rivals by
deploying IT systems (Porter & Millar, 1985). The majority of the strategic
BVIT models adopt RBV theory (e.g. Melville, et al., 2004; Tebboune &
Urquhart, 2016). Some models adopt dynamic capability theory (e.g. Foss &
32 Chapter 2: Background Literature
Ishikawa, 2007; Wheeler, 2002). The models under this category holds a
strategic perspective of BVIT.
The following paragraphs briefly discuss one process centric BVIT model
(operational), one dynamic capability based BVIT model (operational) and two RBV
based strategic models of BVIT.
Soh & Markus (1995) Process-oriented BVIT Model
The Soh and Markus (1995) model of BVIT is one of the earliest prominent
BVIT models in IS literature. They followed a process-oriented approach to represent
how, when and why IT investment is converted to favourable organisational
performance. The model contains three major parts, IT conversion process, IT use
process and the competitive process. In the IT conversion process, investment is made
in IT and IT is incorporated with products and services or to redesign business
processes, better decision making and improved coordination leading to IT assets. In
the IT use process, appropriate use of the IT assets is ensured for IT better impacts to
occur. Finally, IT assets cause some impacts on organisational performance as well as
influence the competitive position of the organisation in the market. This model has
been used as an empirical guideline to develop other models, such as the Dehning and
Richardson (2002) process-centric model to represent a multi-path approach of IT-
performance measurement and Dedrick, et al. (2003) production oriented model of
organisational outcomes. However, the Soh and Markus (1995) model is criticised for
being linear as resources are considered stable in the model (Helfat & Peteraf, 2003).
To emphasise the dynamic nature of organisational resources, IS scholars have
therefore applied dynamic capability theory in their research.
Melville et al. (2004) RBV based Strategic BVIT Model
One of the most recognised BVIT models developed by Melville, et al. (2004)
is based on a resource-based view (Wernerfelt, 1984) of an IT firm. It provides a wide
view of BVIT generation process. Melville, et al. (2004) derive three domains in their
proposed model- focal firm, competitive environment and macro environment. The
model describes how each domain shape the relationship between IT and
organizational performance. The focal firm invests in IT, the competitive contains the
environment where focal firm operates and it includes industry and trading partner
characteristics and macro environment contains country factors or social and cultural
contexts that may influence BVIT. Regarding the BVIT creation mechanisms, they
Chapter 2: Background Literature 33
focus on two important aspects. First, they argue that synergistic relationships of IT
and organisational resources lead to a high degree of complexity, but they did not
provide explanations of this complicacy. Second, they highlight the existence of micro
(focal firm) and macro levels (the broader business environment) in relation to BVIT;
however, they hardly explain the BVIT creation mechanisms.
Nevo & Wade (2010) RBV-Systems Thinking based Strategic BVIT Model
The Nevo and Wade (2010) study on BVIT is motivated by earlier literature
suggesting that analysing the effect of IT assets on the strategic potential of
organisational resources might help to identify more endurable IT-based
organisational benefits (Hackney, Burn, & Salazar, 2004). The authors develop a
theoretical model by conceptualising a path from IT assets to profitability through a
synthesis of systems theory and a resource-based view of the firm. In particular, the
work argue that it is not individual capabilities or organisational resources or IT assets
that contribute to the strategic potential, but the emergent capabilites that arise from
their combination.
In order to provide a more complete conceptual picture of BVIT, Nevo and Wade
(2010) adopt systems thinking concepts, more precisely, emergence concept with RBV
theory and propose that IT assets can be placed in a relationship with organisational
resources, thereby creating synergistic IT enabled resources, the emergent properties
(capabilites) of which facilitate an organisation to achieve profitability. They argue
that IT assets derive their business value from the impact they make on the
organisational resources with which they interact. Thus, the intrinsic capabilities of the
IT assets should not be used in isolation to infer their business value; instead, the
emergent capabilities arising from their relationships with organisational resources
should be examined and evaluated. The authors conclude that emergent capabilites
that are beneficial or positive have the potential to help IT-enabled resources to achieve
organisational goals.
Although, the authors acknowledged that there is a need to take an alternative
approach to understanding BVIT in this dynamic and contemporary business
environment and adopted systems theory based emergence concept, the emergence
concept of systems theory is largely linear (Goldstein, 1999). It is used mainly to focus
on close to equilibrium situation and used in describing simpler systems (Halley &
Winkler, 2008). In contrast, I have proposed a complex emergence perspective
34 Chapter 2: Background Literature
(Chapter 4) that helps to explore the BVIT related dynamics which are non-linear in
nature and far from equilibrium conditions due to rapid movements of components in
business systems.
In addition to the above core models, there are many streams of BVIT models
in the literature. For example, few studies that adopt variance theories explore
variations in the magnitude of particular outcomes of performance i.e. BVIT under
certain and sufficient conditions (Markus & Robey, 1988). Another stream of BVIT
researchers focus on IS success, beyond financial measures to intangible measures
(DeLone & McLean, 1992). However, I have mainly focused on the strategic BVIT
models in this study.
Wheeler (2002) Dynamic Capability based Strategic BVIT Model
Wheeler (2002) Net-Enabled Business Innovation Cycle (NEBIC) is an applied
dynamic capability-based model for measuring, predicting, and understanding a firm’s
ability to create customer value through the business use of digital networks. It
identifies four sequenced constructs: Choosing new IT, Matching Economic
Opportunities with technology, Executing Business Innovation for Growth, and
Assessing Customer Value, along with the processes and events that inter-relate them
as a cycle. Together these four cycles provide a practical lens to understand what are
the emerging technologies, how to match them with economic opportunities and
business innovation growth and how to assess customer centric value. However, the
NEBIC model is also criticised for being too linear and static because it does not
consider what will happen if any organisational resources or capabilities change before
matching the IT capabilities with economic opportunities However, it does tell a step-
by-step practical story about how to achieve customer value via net-enabled business
innovation (Bharadwaj, El Sawy, Pavlou, & Venkatraman, 2013; Sambamurthy, et al.,
2003).
To summarise the review of BVIT related literature in the above section-
• BVIT is a well understood and established concept in the literature in relation
to stable , non-dynamic environment (Schryen, 2012). However, it has been
relatively underexplored in the context of dynamic business environment and
therefore, a stream of prominent IS scholars (e.g. El Sawy, et al., 2010;
Tanriverdi, et al., 2010) have called for adopting methodological and
Chapter 2: Background Literature 35
conceptual alternatives in conceptualising BVIT, as contemporary digital
technologies and their adoption gives rise to a step change in complexity,
dynamism and unpredictability in social systems.
• Few research studies have been conducted to explore the dynamics related to
the BVIT puzzle using alternative conceptual alternatives (e.g. Chae, 2014;
Nevo & Wade, 2010; Tanriverdi, et al., 2010). Although the majority of the
researchers adopted the innovative approach, they rarely describe the implicit
dynamics in relation to BVIT (which has been discussed in section 2.2.3).
• This study has particularly taken motivation from two particular studies as a
starting point-
o First, the study of strategic advantage of IT enabled resources by Nevo
and Wade (2010) as a starting point to define emergence of IT-enabled
capabilities (See Chapter 4, pages 11-12).
o Second, Melville, et al. (2004) RBV based BVIT model as a starting
point to define micro (internal) and macro (external) levels of
organisations (See Chapter 5, page 1).
The above discussion provides an overview of the prominent BVIT models.
Based on the observation of the prominent models, I have proposed a high-level
conceptual BVIT framework in the next section.
2.3 A HIGH LEVEL CONCEPTUAL FRAMEWORK OF BVIT
This section broadly discusses a high level BVIT conceptual framework based
on observation on the prominent BVIT models in IS. As mentioned in the preceding
chapter, this study focuses on the strategic side of BVIT. The high level BVIT
conceptual framework is proposed that emphasises the strategic role of IT assets in
shaping competitive advantage (Bharadwaj, 2000; Wade & Hulland, 2004). The
proposed framework presents a chain of relationships involving IT assets and other
organisational resources and IT-enabled capabilities that lead to firm performance, in
particular competitive advantage. Widely applied in strategic management literature,
the RBV of the firm assumes that firms compete with each other on the basis of
valuable, rare, difficult to imitate and non-substitutable resources (Barney, 1991;
Barney, 2001).
36 Chapter 2: Background Literature
The model also serves as a structure for the thesis. In chapter 4, the model is
used to theorise how IT-enabled capabilities emerge and in Chapter 5, the model is
used to theorise how the IT-enabled capabilities co-evolve with other IT-enabled
capabilities and influence the firm’s competitive advantage.
From the literature review on the strategic side of BVIT, it is found that the
majority of BVIT models have three key parts. In the first part, the model contains IT
related resources or assets and organisational resources (e.g. Melville, et al., 2004;
Nevo & Wade, 2010; Wade & Hulland, 2004). The second part focuses mostly on the
underlying capabilities, competencies and processes and paths that ensure how the
resources can be used or employed appropriately and efficiently in the organization so
that it can achieve improved performance (Kim, et al., 2011; Melville, et al., 2004).
The last part of the model assesses the outcomes and organisational performance via
different performance measures such as productivity, profitability and intangible
benefits (Baker, Song, & Jones, 2008; Bardhan, Krishnan, & Lin, 2013; Bharadwaj,
2000; Masli, Richardson, Sanchez, & Smith, 2011).
Based on the findings from the literature on the major RBV based BVIT
models, the proposed conceptual framework on the strategic side of the BVIT includes
three key parts; which are termed lenses in this dissertation. The lenses are described
in the following section.
2.3.1 IT Assets and Organisational Resources
IT assets and organisational resources is the first lens of the proposed
conceptual framework of BVIT. I have conceived these two constructs from Nevo and
Wade (2010), who argue that though IT has become a core contributor to business
performance, the strategic link from IT assets towards competitive advantage is
elusive. They propose that IT assets derive from business value interacting with
organisational resources. The core reason behind choosing these two particular
constructs is that; the IT assets help me to define only IT related components,
resources, capabilities or even human IT skills. Whereas, the organisational resources
only refer to the resources except IT. This differentiation is particularly important
when I apply CAS lens to explore BVIT as CAS conceptualises a system as a set of
interactions between heterogeneous components.
Chapter 2: Background Literature 37
Following Wade and Hulland (2004), IT assets refer to anything tangible or
intangible related to IT that can be used in organizational processes for creating,
producing, and offering products and services. Tangible IT assets include hardware,
network infrastructure, and human resources, and intangible IT assets include
software, information assets, and employees’ IT skills (Melville, et al., 2004). Tangible
IT assets have been a main focus of research, possibly due to the more abstract nature
of intangible assets (Piccoli & Ives, 2005) and given the dynamic relationship between
IT assets and competitive advantage of firms are elusive (Schryen, 2012). This study
seeks to shed light on the complex and dynamic process.
Organisational resources are central to the competition between firms, and
scarce, valuable, and imperfectly imitable resources are key factors of creating
sustained competitive advantage (Barney, 1991; Wernerfelt, 1984). Grant (1991)
divide organisational resources into tangible, personnel and intangible resources,
whereas, Barney (1991) classified organisational resources into physical capital,
human capital, and organizational capital resources. The taxonomy schemes, although
they differ in terminology are almost similar in that they present physical (e.g.
infrastructure), human (e.g. individual skills) and organisational resources (e.g. rules,
organisational culture) (Kim, et al., 2011). Organisational resources in this study are
defined as, “tangible or intangible factors of production that organizations own,
control, or have access to on a semi-permanent basis” (Nevo & Wade, 2010, p. 164).
The following Table 2.1 presents a summary of the IT resources or capabilities
in IS studies. It can be observed from the table that most of the studies map physical
and human resources/ capabilities on to IT functions. Whereas, the relation of
organisational resource/ capabilities with IT function is generally lacking (Melville, et
al., 2004). The IT function involves tasks that are highly distinct from other business
functions (Kim, et al., 2011). For instance, IT function has its own structures (e.g.
hardware and IT infrastructures), its own rules (e.g. performance of IT staffs) and other
characteristics (e.g. regulation and IT budget) necessary to support different business
functions (Sambamurthy, et al., 2003). Majority of the organisational resources are
related to the governing and managing overall organisations such as, investment
decision making, coordination and control (Kim, et al., 2011). In this study, I have
considered IT assets as combinations of physical and human IT resources and
38 Chapter 2: Background Literature
organisational resources are those which complement the IT assets for overall
functioning of organisations (Melville, et al., 2004).
Related Studies Typologies
Physical (IT) resources
Human (IT) resources
Organisational resources
(Mata, et al., 1995)
Proprietary technology
• Technical IT skills • Managerial IT skills
• Access to capital
• Customer switching costs
(Ross, Beath, & Goodhue, 1996)
Technical assets Human IT assets Relationship assets
(Bharadwaj, 2000)
Tangible resources
Human IT resources
Intangible IT-enabled resources
(Tippins & Sohi, 2003)
IT objects IT knowledge IT operations
(Melville, et al., 2004)
Technical IT resources
Human IT resources
Complementary organisational resources
(Bhatt & Grover, 2005)
IT infrastructure IT business experience
Relationship infrastructure
(Pavlou & El Sawy, 2006)
IT resources Human IT resources
Deployment of resources
(Aral & Weill, 2007)
IT assets • IT skills
• IT management skills
Culture of IT use
Table 2.1 Typologies of IT assets and organisational resources (Adapted from (Kim, et al., 2011))
2.3.2 IT-enabled Capabilities
The second lens of the proposed conceptual model is IT-enabled capabilities.
Capabilities are defined as, an “organization's ability to assemble, integrate, and
deploy valued resources” (Bharadwaj, 2000). There are organisational routines that
moderate the relationships between IT investments and different firm performance
outputs and outcomes (Aral & Weill, 2007; Bharadwaj, 2000). Much research has
attempted to understand the role of IT in enabling organisational capabilities and
Chapter 2: Background Literature 39
reinforcing the firm’s competitive position (Kohli & Grover, 2008). Firms that are able
to utilise IT resources in support of organisational capabilities are more likely to realise
value from IT resources and the relevant competencies that they provide
(Sambamurthy, et al., 2003). Pavlou and El Sawy (2006) refer to this ability of
effectively implementing IT functionality in support of an organizational capability as
an IT leveraging competence. (Nevo & Wade, 2010) suggest IT assets and
organisational resources give rise to IT enabled resources, which have certain
emergent properties, which they name as emergent capabilities.
Following (Pavlou & El Sawy, 2006), I have defined, IT-enabled capabilities as,
the ability to effectively use IT assets to support the organisational resources for the
benefit of organisation. Chapter 4 includes broad discussion on how IT-enabled
capabilities emerge in firms.
2.3.3 Competitive Advantage
The last lens of the proposed framework includes the outcome - the impacts of
IT as competitive advantage. Ma (1999, p. 259) defines competitive advantage as- “the
asymmetry or differential in any firm attribute or factor that allows one firm to better
serve the customers than others and hence create better customer value and achieve
superior performance”. Competitive advantage is a relative concept; the advantage of
one firm over another in a given market, strategic group or market (Kay, 1993). It is
rooted in the deployment of idiosyncratic, valuable, and inimitable resources (Bhatt
& Grover, 2005). The RBV contends that firms possess heterogeneous distinct
resources, and develop and nurture valuable capabilities; therefore, they are likely to
have different potential in leveraging competitiveness (Barney, 1991; Bharadwaj, et
al., 1993; Mata, et al., 1995). A firm is said to have sustainable competitive advantage
if its value creation strategy is not being simultaneously created by one of its
competitors (Barney, 1991). The earlier perspectives on competitive advantage
focused on the external position of the firms compared to their competitors; the more
recent RBV perspective emphasises the importance of firm resources and capabilities
in achieving competitive advantage (Bhatt & Grover, 2005). It is important to note that
the competitive environment in which focal firm operates has two major components-
industry characteristics and trading partners following (Melville, et al., 2004). The
industry characteristics include competitiveness, digitally enabled processes and rapid
technological innovation that shape the way IT assets are deployed in the focal firm to
40 Chapter 2: Background Literature
generate business value (Kohli & Devaraj, 2003; Melville, et al., 2004). Moreover,
when IT systems span firm’s boundary via software applications or electronic markets
and blend with the business processes of trading partners; the IT and non-IT resources
of trading partners also impact business value of IT, in particular competitive
advantage of focal firm (Mukhopadhyay & Kekre, 2002).
Table 2.2 summarises the high level BVIT framework.
IT assets
Anything tangible or intangible related to IT that can be used
in organizational processes for creating, producing, and
offering products and services (Wade & Hulland, 2004).
• Tangible IT assets- hardware, network infrastructure,
or human resources
• Intangible IT assets- software, information assets,
employees’ IT skills in IT functions (Melville, et al., 2004).
Organisational Resources “tangible or intangible factors of production that
organizations own, control, or have access to on a semi-
permanent basis” (Nevo & Wade, 2010, p. 164)
IT-enabled capabilities The ability to effectively use IT assets to support the
organisational resources for the benefits of organisation
(Pavlou & El Sawy, 2006).
Competitive advantages Ma (1999, p. 259) defines competitive advantage as- “the
asymmetry or differential in any firm attribute or factor that
allows one firm to better serve the customers than others and
hence create better customer value and achieve superior
performance”.
Table 2.2 Summary of the High Level BVIT Framework
2.4 COMPLEXITY THEORIES
The preceding section presents a high-level BVIT framework. This section
provides an overview of complexity theories.
The application of complexity theory has recently gained attraction in the field
of social science and organisational studies. Rooted in evolutionary biology
(Kauffman, 1995a), the term ‘complexity theories’ is a label (Burnes, 2005) that
Chapter 2: Background Literature 41
represents a number of theories, ideas and research programmes from diverse
disciplines including physics, mathematics, thermodynamics, astrology, etc.
(Kauffman, 1995a; Kauffman, 1993; Prigogine, 1984; Waldrop, 1992). Research work
related to two major school of thoughts are prevalent in complexity theories, which
includes the scientific research conducted by the scientists of the Santa Fe Institute
(SFI) in USA, particularly the work of Stuart Kauffman (Kauffman, 1995a; Kauffman,
1993), John Holland (Holland & Mallot, 1998; Holland, 1992, 1995), Chris Langton
(Waldrop, 1992), and (Gell-Mann, 1994) on complex adaptive systems (CAS) and the
work of scientists based in Europe such as (e.g. Axelrod, 1997a; Axelrod, 1997b; Casti,
1997; Casti, 1994; Casti, 1992; Haken, 1977; Niculescu, Shin, & Whang, 2012;
Prigogine, 1984; Stengers & Prigogine, 1997), Prigogine (1984) work on dissipative
structures; work by Humberto Maturana, Francisco Varela (Varela, Maturana, &
Uribe, 1973) and Mingers (1997) research on autopoiesis, Cramer (1993) work on
chaos theory and that on economic and increasing returns by (Arthur, 1989).
Manson (2001) argues that complexity theories consist of a number of theories
from different disciplines, which together represent complexity research. One of the
significant things that strike readers when dealing with complexity theories for the first
time are the strange terms such as fitness, landscape, edge of chaos, bifurcation point,
co-evolution etc. (Kauffman, 1993; McKelvey, 1997c; Van Valen, 1983; Waldrop,
1992). Most of these terms have come from biology and mathematics and later found
their way into the strategic management and organisational science disciplines. Thus,
Burnes (2005, p. 77) mentions “without mathematics, there would be no complexity
theories”. Given the vast interest and applications of complexity theories in 1990s, a
large number of definitions and conceptualisations were developed then and are still
present in the literature (Mitleton-Kelly, 2003b; Stacey, et al., 2000).
Complexity theories have received increased attention in IS and referral
disciplines over the last two decades. Books have been written, special journals issues
on the application of complexity theories have been published, and articles applying
complexity theories have been appearing in top journals (Maguire, McKelvey,
Mirabeau, & Öztas, 2006). A few of the popular topics that have employed complexity
theories are organisational change (Burnes, 2005; Stacey, 2003), supply chain (Choi,
et al., 2001), human resource management (Colbert, 2004), software development
42 Chapter 2: Background Literature
(Vidgen & Wang, 2006b, 2009), innovation (Habib, 2008), and organisational
management (Morel & Ramanujam, 1999), etc.
Complexity theories deal with dynamic and non-linear systems where order
emerges from the interaction of system components at the edge of chaos (Holland,
1995), more specifically systems which are constantly changing and where the cause-
effect laws do not apply (Burnes, 2005). Order emerges in the dynamic systems in an
unpredictable manner through a process of self-organisation, which is governed by a
number of simple order generating rules (Haken, 1977; Kauffman, 1993; Morel &
Ramanujam, 1999). Mitleton-Kelly (2003a) stated, “Complexity is not a methodology
or a set of tools (although it does provide both). It certainly is not a ‘management fad’.
The theories of complexity provide a conceptual framework, a way of thinking, and a
way of seeing the world”.
Despite the disparity of ideas, concepts and theories under complexity theories,
Stacey, et al. (2000) mentions that there are three key theories - chaos, dissipative
structure theory and complex adaptive systems (CAS) theory. These theories are
briefly discussed in the next subsections.
2.4.1 Chaos Theory
Chaos theory (Gleick & Berry, 1987) is a notion of dynamic systems that
represents the deterministic behaviours of complex systems (Mitleton-Kelly, 2003a).
The term ’chaos’ was first coined by Chris Langton (Waldrop, 1992) (cited in
(Mitleton-Kelly, 2003b)). Chaos theory represents the region where emergent order
coexists with disorder at the edge of chaos. When a system changes its state from a
state of order towards disorder, there can be a transition state where both order and
disorder regimes exist together; this particular region is called edge of chaos (Boisot,
2006).
However, chaos theory is distinct from complexity (Maguire, et al., 2006;
Mitleton-Kelly, 2003b) and the two concepts needs to be distinguished when applied
in research. Chaos theory describes non-linear dynamic systems in terms of complex
mathematical equations or simple rules of interactions; both types of representation
give rise to sophisticated patterns or behaviours like fractals in flower. Lorenz (1963)
found in his research on weather systems that even a small event, like the flapping of
butterfly wings can lead to unpredictable consequences. However, the chaotic system
Chapter 2: Background Literature 43
follows rules of interaction, the pattern of behaviours or order emerges in the systems
over and over again, which leads to a coherent order (Goodwin, 1997). Because of this
closeness to deterministic behaviour, chaotic systems are quite similar to linear
systems in an ontological sense (Dooley & Van de Ven, 1999). Applying chaos theory
in social and organisational systems therefore may not always be appropriate because
organisations do not follow any simple rules or mathematical formulae. Organisational
goals, competencies and practices are always evolving in a way that changes the order
in the organisation.
2.4.2 Dissipative Structure Theory
Anderson (1999, p. 222) refers to dissipative structure as “an organized state
that arises when a system is maintained far from thermodynamic equilibrium because
energy is constantly injected into it.” Dissipative structures are mostly related to the
work of Ilya Prigogine and his colleagues (Prigogine, 1984; Stengers & Prigogine,
1997) on Bénard cell in which they showed that under appropriate conditions,
chemical molecules react and spontaneously organized themselves into a dissipative
structure (Mitleton-Kelly, 2003b). In dissipative structure, system components reach
towards a ‘bifurcation point’ from where they can spontaneously organise to create an
emergent order that cannot be predicted from the history of a previous state (Stacey,
2003). Symmetry breaking happens at this particular point and a new pattern appears
(Mitleton-Kelly, 2003b). This particular theory has been used in strategic management
and organisational studies to explore organisational transformation (Leifer, 1989;
MacIntosh & MacLean, 1999; Todd H. Chiles, Alan D. Meyer, & Hench, 2004).
However, both chaos and dissipative structure theory deal with non-linear,
dynamic and deterministic systems (Burnes, 2005; Todd H. Chiles, et al., 2004), and
complex adaptive systems (CAS) theory seeks to understand the unpredictable nature
of non-deterministic systems (Keskinen, Aaltonen, & Mitleton-Kelly, 2003; Mitleton-
Kelly, 2003b), briefly discussed in the next subsection.
2.4.3 Complex Adaptive Systems Theory
Complex adaptive systems (CAS) theory (Holland & Mallot, 1998; Holland,
1995) is a branch of complexity science that represents dynamic non-linear and non-
deterministic systems. A CAS is composed of three main elements – (1) heterogeneous
interconnected elements or agents, (2) interactions, and (3) the environment (Dooley,
44 Chapter 2: Background Literature
1996; Holland, 1995) as summarised in Table 2.3. Agents are the basic elements that
represent individuals, objects, companies, or concepts. Each agent has its inherent
attributes and an agent’s behaviour is constrained by a set of behavioural rules, which
decide how they will interact with other agents and the environment. For example, an
agent can only interact with other agents residing within 10ft of its position.
Interactions represent the relations, activities of agents and connections among
themselves or with the environment. In CAS, connection labels the possible medium
where interaction can take place as well as the mutually adaptive behaviours of agents
(Nan, 2011). Interactions also reflect flows - the movement of information and
resources through agents’ connections (Holland, 1995). Another component of CAS
is Environment, where agents reside and interact with each other. Environment has its
own attributes, structures and rules, and its behaviour is constrained by the
environmental rules. Structure provides the ground for residing agents.
Table 2.3 Basic building blocks of complex adaptive systems (CAS) theory
There is no universally agreed upon framework for CAS theory (Curşeu, 2006);
it shares all the features and characteristics of complexity science (Mitleton-Kelly,
2003b). The CAS features and characteristics are broadly described in Chapter 3 via a
structured literature review. This dissertation has adopted the concepts of emergence
Basic Elements Description Examples
Agents Semi-autonomous entities of actions People, organisation, concepts
Attributes Properties of the agents Skills, size, etc.
Behaviour rules Rules that govern agents’ behaviours Connection pattern
Interaction Mutual behaviours of agents Cooperation, decision making
Connection Links that connects agents to interact Decision making, friendship
Flows Movement of information or resources Messages, food web
Environment Context where agents reside to interact each other
Organisation, Land scape
Structures Contour of an environment and agents interaction with it
Contextual environment
Chapter 2: Background Literature 45
and co-evolution (Lewin, et al., 1999) to better understand the implicit complexities
and dynamics related to BVIT in contemporary business environment.
In summary-
• Complexity theories include a large number of complex concepts or metaphors
from various disciplines such as, mathematics, physics, biology,
thermodynamics. The concepts of complexity theories have been used in
strategic management and organisational science disciplines have become
more popular in the last two decades (Manson, 2001).
• Complexity theories include a wide range of ideas, concepts and theories but
the three key theories are chaos, dissipative structure and complex adaptive
systems (CAS) theory (Stacey, et al., 2000). More importantly, though the three
theories deal with non-linear and dynamic systems, only CAS theory focuses
on the unpredictable nature of non-deterministic systems (Keskinen, et al.,
2003; Mitleton-Kelly, 2003b), while the others two, chaos and dissipative
structure, focus only deterministic behaviours (Burnes, 2005).
• This study has adopted CAS theory to understand the dynamics related to the
BVIT as has been advocated by several prominent scholars (McKelvey, 1999;
Tanriverdi, et al., 2010). In particular, this study has adopted two CAS
concepts-
o First, it has adopted the complex emergence concept of CAS theory to
describe how IT-enabled capabilities emerge through a bottom-up
process in contemporary organisations (refer to motivation 1 in section
2.2.3). This is discussed in Chapter 4.
o Second, it has engaged co-evolution CAS concept to describe how IT-
enabled capabilities co-evolve with other IT-enabled capabilities
internal and external to organisation and influence competitive
advantage (refer to motivation 2 in section 2.2.3). This is discussed in
Chapter 5.
2.5 CHAPTER SUMMARY
To summarise the chapter, the review of BVIT in section 2.2 provides a high
level picture of the BVIT research in the IS discipline, including different theoretical
46 Chapter 2: Background Literature
paradigms and core models. Section 2.2.3 introduces the key core BVIT models and
helps to narrow down the two key motivations of this study, the creation of IT-enabled
business capabilities and its reciprocal changes with other organisational capabilities
internal and external to organisations. The research motivations are broadly discussed
in section 1.2 in chapter 1.
Section 2.4 presents a high level BVIT conceptual framework based on
observation on the prominent BVIT models in IS. The high level BVIT conceptual
framework is proposed with the emphasis on the strategic side of BVIT, the role of IT
assets in shaping competitive advantage (Bharadwaj, 2000; Wade & Hulland, 2004).
The proposed framework presents a chain of relationships involving IT assets and
other organisational resources and IT-enabled capabilities that lead to firm
performance, in particular competitive advantage. The framework also serves as a
structure for the thesis. In chapter 4, the model is used to theorise how IT-enabled
capabilities emerge and in Chapter 5, the model is used to theorise how the IT-enabled
capabilities co-evolve with other IT-enabled capabilities and influence the firm’s
competitive advantage.
Section 2.4 introduces complexity theories; in particular, it introduces three
major theories, chaos theory, dissipative structure theory and complex adaptive
systems theory and justifies the choice of CAS theory as a core theory to explore the
research areas.
Overall, Chapter 2 focuses on the major BVIT studies in IS literature, helps to
describe research motivations based on the understandings on the BVIT literature. The
inclusion of a broader view of complexity theory helps to develop how complexity
theory has found it’s way into IS studies and how concepts and features of the broader
complexity theories can help us to better investigate dynamic side of BVIT.
The next chapter provides an in-depth structured literature review of CAS
theory particularly within the IS discipline. The chapter is intended to introduce with
a broader use of CAS theory in IS research and helps to apply the emergence and co-
evolution concepts in the Chapter 4 and 5 respectively
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 47
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory2
Chapter 3 Summary
What was done in the previous chapter: The previous chapter sets up the
research background by introducing BVIT studies in IS, describing core BVIT
models and highlighting the motivation. It also provides a high level overview of
complexity theories and gives hint on the two CAS concepts- emergence and
coevolution that help to explore key focus of the research.
What this chapter does: This chapter presents an in-depth and structured
literature review on CAS theory in IS discipline. It introduces with key CAS
concepts & their relative contributions, theories and approaches and related context
of CAS based IS research. The chapter helps to narrow down conceptual focus on
two specific CAS concepts- emergence and coevolution.
What is still outstanding in later chapters:
Chapter 4: An emergence perspective of IT-enabled capabilities.
Chapter 5: A coevolutionary perspective of IT-enabled capabilities and how
it influences competitive advantage.
Chapter 6: An operational (NKC) coevolutionary model of IT-enabled
capabilities.
Chapter 7: A CAS based framework on competitive advantage and a
discussion on the overall insights that I have developed in relation to BVIT.
2 The earlier version of this chapter is published in PACIS 2017. Appendix A contains the list of PACIS publications and their abstract.
48 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
3.1 INTRODUCTION
Complex adaptive systems theory (CAS) offers a new way of thinking about
systems of interacting agents and how order emerges in systems from the interactions
of agents, which is very useful in dynamic environments where organisations and
information systems have to be responsive and adaptive. While CAS offers valuable
insights and has been widely applied in related disciplines like management and
organisational studies, its application in the information systems (IS) discipline is
limited (Mitleton-Kelly, 2014). In this chapter, I set out to better understand and
advance the use of CAS in IS by conducting a literature review.
A special branch of complexity theory, CAS is used to investigate how complex
systems become adaptive to their environment and how properties emerge from the
interactions of the system components (Vidgen & Wang, 2006b). CAS can be valuable
for research because of its suitability for modelling non-deterministic behaviors, the
possibilities of sensitivity analysis, the use of mathematical and computational models,
and its multi-level nature (Stacey, 2003).
Cybernetics, chaos theory, and general systems theory all focus on deterministic
dynamic systems, where a set of equations are used to determine how a system changes
(i.e. experimenting with linear behaviour under some predefined conditions) in a given
time space. CAS provides another way of simplifying a complex system into a formal
system (Anderson, 1999). Organisations today potentially face sudden and substantive
change. Reasons include digitization, globalization, process re-engineering, quality
improvement, and greater workforce diversity. Organisations need to be more adaptive
and responsive to these dynamics (Cohen, 1999). CAS theory is well suited to
modelling the non-deterministic behaviors of such dynamic systems, which cannot be
represented through a deterministic set of equations. By undertaking sensitivity
analysis and varying the assumptions of basic properties of CAS components e.g.
fitness value, schemata or population dynamics, it is possible to explore and better
describe the complex behavior of dynamic systems (as opposed to evidencing causal
relationships).
Further, CAS can usefully represent complex systems through mathematical or
computational models and such models are crucial for the analysis of dynamic
processes that are too complex to be understood with language (Morel & Ramanujam,
1999). CAS helps to encode non-linear complex phenomena through mathematical
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 49
expressions and facilitates the conduct of computational experiments in a virtual
system. Thus the computational approach provided by CAS gives researchers
precision as well as control over the implemented model and helps to investigate the
myriad contingencies that may arise from the dynamic relationships of system
components. Such contingencies are difficult to explore in field studies and more
readily realized in a virtual system. Moreover, CAS is inherently multi-level in nature,
facilitating investigation of collective-level behavior that emerges from the lower-level
interactions of systems components.
Although CAS was first popularized in the field of evolutionary biology, several
CAS principles have been widely applied in the strategic management discipline to
understand the dynamic behaviors of complex systems e.g. supply chain networks
(Choi, et al., 2001), leadership (Schneider & Somers, 2006) and organisational
learning (Kane & Alavi, 2007). The application of CAS also has a long history in the
social sciences and organisational studies (Anderson, 1999; Brown & Eisenhardt,
1998; Morel & Ramanujam, 1999). For decades, organisational researchers have
employed concepts from complexity theory such as adaptation, self-organisation and
evolution (Casti, 1994; Gell-Mann, 1994) to analyse dynamic non-linear phenomena
in complex systems.
The employment of CAS theory in the Information Systems (IS) research
domain is more recent. The importance of CAS and encouragement of its broader
adoption in IS has been argued in several journal special issues, such as Journal of
Information Technology (Merali & McKelvey, 2006) and Information Technology &
People (Jacucci, Hanseth, & Lyytinen, 2006). More recently, IS researchers have
employed CAS principles to investigate the complex behaviour of processes like agile
software development (Vidgen & Wang, 2006b; Wang & Conboy, 2009), information
systems development (Allen & Varga, 2006; Kautz, 2012) and organisational
knowledge processes (Habib, 2008; Merali, 2002). These research areas involve a
myriad of complex processes and activities; CAS principles and concepts align well
with the exploration of such unpredictable patterns. The concepts of CAS theory have
also been used in conjunction with other theory e.g. resource based theory (RBV)
(Barney, 1991) to study sophisticated business processes like the generation of
business value using IT (Nevo & Wade, 2010). Moreover, CAS provides a new way
of exploring contemporary dynamic phenomenon, such as- IT use processes (Nan,
50 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
2011), systems dynamics (Hildebrand, Hofstetter, & Herrmann, 2012), and agile
processes (Vidgen & Wang, 2009). In addition, CAS concepts and ideas are used for
theory building, sometimes in conjunction with case study research (e.g. Nan, 2011).
While CAS has found its inroad into IS, the first impression is that its use is
limited and fragmented. A search of mainstream IS journals and conferences revealed
few papers (36 papers) that apply CAS theory3. However, a total of 220 papers
encountered in the sample search, which suggests that the CAS theory is relevant in IS
discipline. Moreover, a further investigation of the papers reveals that our
understanding is limited with respect to what CAS theory is, why CAS theory is
applied and how CAS theory is applied. These fundamentals require attention in order
to advance our understandings on CAS theory. Moreover, several scholars in IS (e.g.
Merali, 2006; Vidgen & Wang, 2009) also suggested the limited use and inadequate
understanding of the theory in IS discipline.
This chapter entails a structured literature review of CAS studies in Information
Systems. Guided by, Levy and Ellis (2006), Webster and Watson (2002) and Paré,
Trudel, Jaana, and Kitsiou (2015) suggestions in relation to developing structured
literature review, the aim of the review includes following-
1. To systematically collect, analyse and synthesise all CAS theory related
literature within the IS discipline,
2. To understand the current status of CAS theory in IS,
3. To provide a firm foundation to the basic understanding of CAS theory,
4. To identify theoretical and methodological approaches related to the CAS
application in IS, and
5. To identify what research exists (i.e. what is already known?) and where new
research is needed (i.e. what is needed to be known?).
I believe this is the first such review comprehensively focusing on CAS theory
in IS discipline.
3 This statement about the status of CAS research in IS discipline is further discussed broadly in the rest of the paper.
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 51
The remainder of this paper proceeds as follows. The section 3.2 contains an
overview of the CAS theory. Subsequently, I present the review design used to conduct
the review in section 3.2. I then address the current status (section 3.4) of and
conceptual perspectives (section 3.5) on CAS theory. The following section 3.6
overviews the objectives of CAS theory in IS. The theoretical and methodological
approaches to the use of CAS in IS are presented in section 3.7 and section 3.8
respectively. Finally, the context of CAS theory in IS is discussed in section 3.9 and
the chapter concludes with a summary in section 3.10.
3.2 BACKGROUND LITERATURE
A special branch of complexity science, CAS is a new way of thinking about
systems of interacting agents and how order emerges in systems from the interactions
of agents. Authors such as, Holland (1995), Gell-Mann (1994) and Dooley (1997) were
among the first to inspire organisational researchers to adopt CAS theory for
investigating non-deterministic, dynamic phenomena in organisations.
There are many accounts of CAS theory, the general view across the broader
community of CAS scholars being that there is no single theory of CAS (Anderson, et
al., 1999; Vidgen & Wang, 2006b). In practice, few scholars explicitly represent a
CAS theory. Nonetheless, all imply that a CAS is composed of agents that interact.
Holland (1995) alludes to a definition of CAS as- a single coherent system that
emerges over time from the interactions of its components (agents) and adapts and
organizes itself within an environment. A CAS is composed of three main elements –
(1) heterogeneous interconnected elements or agents, (2) interactions, and (3) the
environment. He also explains the basic characteristics and mechanisms of CAS
through its seven basics- aggregation, flows, nonlinearity, diversity, tagging, internal
models, and building blocks. The basic building blocks of CAS are agents (Dooley,
1997). Each agent has inherent attributes and schemata, which are the cognitive
structures by which agents choose to interact with other agents and with the
environment. Interactions represent the relations: activities of agents and connections
among agents or with the environment. Environment is the space in which the agents
reside. Authors like Cilliers (1998) and Mitleton-Kelly (2003a) describe the major
features and principles of CAS, such as open systems, non-linearity, feedback loops,
etc. In short, CAS refers to a system that is adaptive to its environment where
52 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
properties emerge in the system from the interactions of its components (Vidgen &
Wang, 2006b).
Though a widely accepted definition of CAS theory is yet lacking, review of the
views of main CAS theorists reveals several key concepts and properties that
characterise CAS. These concepts and principles are used to interpret how complex
non-linear systems with interacting agents function to produce orderly but
unpredictable behaviour (Alaa & Fitzgerald, 2013). Many of the concepts are
prominent in previous theoretical frameworks; for example, the concepts of
emergence, connectivity, interdependence, and feedback are familiar from systems
theory. Nonetheless, CAS theory extends these theories with additional concepts like
co-evolution, self-organisation and edge of chaos, which enriches systems thinking
concepts and emphasizes their inter-relationship and interdependence. The CAS
concepts are tightly associated with each other, bringing into question any attempt to
isolate and concentrate on one concept such as emergence or co-evolution, and exclude
the others (Mitleton-Kelly, 2003a).
Below, the major CAS concepts are described, cross-referenced with the core
papers such as- (Holland, 1995), (Morel & Ramanujam, 1999), (Mitleton-Kelly,
2003a), (Cilliers, 1998) and (Gell-Mann, 1994) from which they have been derived.
As discussed in the Chapter 1, the emergence and coevolution CAS concepts are
adopted in this study. The emergence CAS concept helps to explain the emergent rise
of IT-enabled capabilities from the interactions of IT assets and organisational
resources in chapter 4 and the coevolution concept provides a way of explaining the
evolutionary dynamics among various IT-enabled capabilities inside organisation and
with the competitors and its effect on competitive advantage in chapter 5. These two
concepts are widely used in IS referral disciplines to the study of similar complex
phenomena- emergence (e.g. Chiles, et al., 2004; Choi, et al., 2001; Kogut, 2000;
Lichtenstein, et al., 2006; Sawyer, 2005) and coevolution (e.g. Huygens, et al., 2001;
Koza & Lewin, 2001; McKelvey, 2002; Pacheco, et al., 2010) and they are better suited
to explain the core focus of this study, which is understanding the dynamics of BVIT,
in particular competitive advantage. The reason to include the other CAS concepts in
the review is to provide background for the explication of the status of CAS in IS.
Co-evolution- Each component (agent) of the CAS environment influences each
other component; in turn, the environment influences all components of which it is
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 53
comprised (Anderson, 1999). When a component changes to ensure best fit in the
landscape, the environment also changes, and those changes are likely to result in
further system changes and this process goes on causing continual changes in the
system (Kauffman, 1993).
Emergence- refers to the phenomenon whereby macroscopic patterns arise from
the interactions of micro-level components (Morel & Ramanujam, 1999). CAS
components interact with each other; their interactions collectively giving rise to
emergent properties.
Self-organisation- is the ability of complex systems to evolve dynamically in an
organized form, changing their internal structures and patterns of behaviour, from the
interactions of autonomous agents (Anderson, et al., 1999). “Self-organisation can
lead to fundamental structural development...is ‘spontaneous’ or ‘autonomous’,
arising from the intrinsive iterative nonlinear nature of the system”- (Stacey, 2007, p.
196).
Fitness landscape- conceptualises a CAS system as having N decision variables
(agents) and K interactions among the variables (Kauffman, 1993). Each configuration
of a set of decision variables is associated with a fitness value representing
performance if that particular configuration is enacted. The system uses different
techniques e.g. – hill climbing or long jumps, in the fitness landscape to find positions
with higher fitness value. When, there is little interaction among decision variables
(i.e. low K), the resulting fitness landscape is “smooth”. Higher interactions (i.e. high
K) among the variables cause the landscape to be “rugged”.
The edge of chaos- Systems that are too simple are static, and systems that are
too active become complex or chaotic. The edge of chaos is a region between these
two, where a system is neither too simple nor too complex, and can undertake
productive activity (Miller & Page, 2009, p. 129). “Organisations never quite settle
into a stable equilibrium but never quite fall apart, either” (Brown & Eisenhardt, 1998,
p. 12).
Dynamism and non-linearity- CAS is different from a traditional process model
consisting of interrelated variables that result in deterministic outcomes; it is
comprised of interconnected autonomous agents, which show non-linear behaviors.
The whole is greater than the sum of its parts (Holland, 1995). As a dynamic approach,
54 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
the tenets of CAS theory are used to model complex social systems and to investigate
and understand the dynamic properties of complex systems.
Adaptation- is the process through which CAS maintains fitness in the
competitive landscape (Kauffman, 1993). A CAS changes its structure in the fitness
landscape through its interactions with other CAS. Adaptation by a CAS changes the
structure of another CAS, which further leads to a process of mutual adaption.
As a branch of complexity science, CAS has received increased attention in
diverse academic fields including strategic management and organisational science.
The concepts and principles of CAS have been used to study a growing range of
contemporary IS phenomena such as agile software development (Vidgen & Wang,
2009), IT supported organisational processes (Canessa & Riolo, 2006) and IT enabled
organisational learning (Kane & Alavi, 2007). Several IS referent disciplines,
including strategic management (Burgelman & Grove, 2007), organisation science
(Frank & Fahrbach, 1999) and management science (Rivkin & Siggelkow, 2007), have
also benefitted from the use of concepts and features of CAS. Several journal special
issues have been published, such as Journal of Information Technology (Merali &
McKelvey, 2006) and Information Technology & People (Jacucci, et al., 2006) to
demonstrate the value of CAS while encouraging its broader adoption in IS research.
Significant arguments advocating for increased employment of CAS theory in
information systems management and organisational studies, include: limited success
of traditional theories, non-linear changes to organisational environments that require
increased appreciation of dynamic formal methods e.g. simulation, emphasis on
bottom-up agent-based and rule governing behaviours and increasing appreciation of
the need for holistic research (Maguire, et al., 2006).
Yet research employing CAS in the IS discipline remains limited and
fragmented. A search of top IS outlets revealed few papers that apply CAS theory.
Possible reasons are several, the foremost likely being that CAS is not well understood
by many IS researchers. There seems to exist confusion about the concepts central to
the theory; those concepts not being intuitive nor easy to measure, in particular as they
are tightly intertwined (Vidgen & Wang, 2006b). Further, researchers may be aware
of CAS theory but are unsure of its potential. Those who attempt CAS research often
face difficulties knowing where to start, what methodology to follow, etc. A common
mis-conception is that the sole purpose of CAS is to model real world phenomena
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 55
computationally, many perceiving computational modelling as foreign or irrelevant to
IS research. To better understand CAS theory and make it more accessible to IS
researchers, this review of the IS literature using CAS theory is developed. This review
contributes to laying the foundation of CAS theory in IS research by synthesising the
current literature. The next section presents the review design.
3.3 REVIEW DESIGN
A review of the prior literature provides a firm foundation to understand the
current status of a research field. It facilitates theory development, represents the areas
where a plethora of research exists and helps to discover areas where research is
needed (Webster & Watson, 2002). Following the review guidelines by Levy and Ellis
(2006) and Webster and Watson (2002) the review followed a structured method
consisting of three steps to extract, analyse and report the literature based findings. In
the extraction phase, a methodological search were conducted to identify and extract
relevant articles from the IS top outlets to include them in this review. In the
subsequent analysis phase, the articles were prepared for analysis; an appropriate
classification and coding scheme was developed and maintained to match the study
objectives and conducted the analysis accordingly. In the findings and interpretation
phase, findings on the papers were gathered and interpreted for unfolding deeper
insights on the CAS in IS. The next sections describe each phase of the research design
in detail.
Figure 3.1 Overview of sampling sources
(1) IS senior scholars basket of
8 journals
(2) Top 3 IS journals
I&M, I&O and DSS
(3) Top 2 IS referent
Management
journals MS and
OS
+ + +
2 top AIS conferences
ICIS and ECIS
(i) Journals (ii) Conferences
56 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
3.3.1 Extraction of Papers
A well-structured method is important for a comprehensive literature review
(Levy & Ellis, 2006) - a step-by- step procedure of collecting, synthesising and
analysing relevant data from the body of knowledge. As the aim of this review is to
investigate and synthesise CAS based IS research only within IS discipline, the
literature sources have been targeted at the IS community only. Selecting targeted a
set of outlets within a predetermined scope, has been practised in past literature studies
(e.g. Fielt, Bandara, Miskon, & Gable, 2014; Zhang & Gable, 2014). Thus,
academically refereed, full text papers were searched from the top IS outlets, that
includes a list of top IS journals and selected conferences. The study started in 2014
and hence the selected outlets were defined based on the information available then.
The extraction and analysis of the articles were continued since then and reported
herein based on the data extracted from the selected outlets through to December 2018.
The review explored a complete set of high quality papers from top IS outlets.
Thus, it included articles published in the AIS Senior Scholars’ Basket of Eight
Journals4 endorsed by the Association for Information Systems (AIS) as high quality
journals in the IS discipline. An extended search in other well established IS journals
was conducted, such as Information and Management (I&M), Information and
Organisation (I&O) and Decision Support Systems (DSS), given their high quality and
high receptivity to the social research in IS. As the application of CAS also has a long
history in the social sciences and organisational studies (Anderson, 1999; Brown &
Eisenhardt, 1998; Morel & Ramanujam, 1999), two journals on management and
organisational studies, Management Science (MS) and Organisational Science (OS)
were considered as both of them are also highly cited within IS discipline. Thus, a total
of 13 top IS journal outlets is included in this review.
Given the relative limited use of CAS theory in IS and to ensure that the literature
reviewed is as current and inclusive as possible, the proceedings from the top IS
conferences affiliated with the AIS were also included. The review surveyed two IS
4 4Senior Scholars’ Basket of Eight journals are- MIS Quarterly (MISQ), Information Systems Research (ISR), Journal of Management Information Systems (JMIS), European Journal of Information Systems (EJIS), Information Systems Journal (ISJ), Journal of the Association for Information Systems (JAIS), Journal of Information Technology (JIT), and Journal of Strategic Information Systems (JSIS). See further details at- https://aisnet.org/?SeniorScholarBasket
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 57
conferences- International Conference on Information Systems (ICIS) and European
Conference on Information Systems (ECIS), representative of quality conferences in
IS (Webster & Watson, 2002). The review commenced search with the basket of eight
journals, then the top 5 IS related management journals, later extending to the
mentioned AIS conferences (see Figure 3.1).
In order to identify publications that use CAS as a core theory, the search was
conducted using keyword search (Levy & Ellis, 2006), i.e. the use of a specific word
or phrase5 - “Complex Adaptive System*”6 in the title, abstract and full text sections
of the databases. The Proquest database returned 53 articles for seven of the basket of
eight journals, with 44 articles found from Science Direct database for JSIS. The
Science Direct database also returned 61 articles for I&M, I&O and DSS. Further, the
JSTOR database returned a total of 12 articles for MS and OS journals. Additionally,
ICIS and ECIS returned 59 and 45 conference papers respectively. Thus, the initial
search yielded 274 articles in total, which mentioned complex adaptive system*
somewhere in the text. All the papers were carefully reviewed to anticipate their
relevance to this study. Although a comprehensive approach was followed to extract
relevant articles that are most suited for this study, the review acknowledges that there
may be some papers relevant to this study, still unidentified and excluded due to the
defined scope and applied research approach. This can be expected in any literature
review (Webster & Watson, 2002).
3.3.2 Analysing the Papers
The review employed a formal coding scheme to ensure a consistent, structured
process for extracting and recording all relevant information from the pool of papers.
I analysed the title, abstract, keywords and full text of the articles for the relevance of
content. To be included in the sample, a candidate article must have adopted CAS as
a base theory or used at least one concept of CAS to theorise phenomena. In terms of
duplicate publications, articles published in conference proceedings and journals, the
review considered the journal paper as normally conference proceedings are extended
5 Please note that ‘keyword’ refers here to the search string, not to the keywords property of the documents that we searched (as stated, we searched in the title, abstract and full text properties of the documents). 6 The asterisk symbol ‘*’ used in the Boolean keywords of the search string combination allows for the inclusion of derivatives in the search criteria.
58 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
and published as journal articles. No research in progress papers was considered in the
sample set.
For analysing the contents of the papers, a combined a top-down and bottom-up
approach was followed so that the relevant information from the paper can be
identified. It also ensures the legitimacy of the analysis. A database was maintained of
the codified contents. A total of 40 articles (24 journals and 16 conference papers)
were selected from the original dataset of 274 papers after the analysis. The database
fields populated are - keywords, research topics, concepts from CAS, journal/
conference name, year of publication, definitions, methodologies, theoretical
approaches, objectives, and important key findings and notes extracted (a summary for
later reference) from each research article.
3.4 THE STATUS OF CAS THEORY IN THE IS DISCIPLINE
This section presents an overview of CAS theory literature in the IS discipline.
A descriptive overview of the literature helps to present the detailed research findings
as it positions the data-contexts from which the analysis is drawn (Fielt, et al., 2014).
Recall that a total of 40 articles on CAS theory were extracted from the pool of
IS outlets as a result of our analysis, where 24 are journal articles and 16 are conference
papers. Table 3.1 illustrates the number of CAS articles published in the sampled
outlets. The frequency of CAS related studies in IS is relatively small. One of the
earliest articles that embraced CAS theory appeared in EJIS 2002 (Merali, 2002).
Nothing on CAS was published in the subsequent three years (2003-2005). In 2006,
eight articles were published, five of which appeared in a special issue of Journal of
Information Technology (JIT) on Complexity Science (that special issue was intended
to evidence the significance of, and encourage the adoption of, complexity theory in
IS). The number drops to 3 in 2007 then ranges between 3 and 4 over the subsequent
7 years (2008-2014). The number of studies varies across journals; JIT publishing the
most (7 - 5 of which are in the special issue), followed by DSS (5 papers) and
subsequently JAIS, MISQ and ISR (each with 2). ISJ and JMIS have published nothing
on CAS. The two prominent AIS conferences ICIS and ECIS published 16 (40%) of
the total set of 40 papers over the past 13 years. ICIS first published two CAS articles
in 2008 and has averaged 1/year since, whereas ECIS first published on CAS in 2006
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 59
(averaging 0.5/year since). Relatively, these are not large numbers, with CAS research
representing a niche area of research in IS.
Outlet 2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Total
MISQ 1 1 2 ISR 1 1 2
JMIS 0 EJIS 1 1 ISJ 0
JAIS 1 1 2 JIT 5 1 1 7 JSIS 1 1 2 I&M 1 1 2 I&O DSS 1 1 1 1 1 5 MS 1 1 OS 0
ICIS 2 1 2 1 1 1 2 1 11 ECIS 2 1 1 1 5 Total 1 0 0 0 8 3 3 4 4 2 4 2 3 1 1 40
Table 3.1 Journal/ conference and year wise distribution of CAS article
3.5 THE CONCEPTUAL PERSPECTIVE OF CAS IN IS
The previous section addresses the status of CAS theory in IS discipline. This
section presents current understandings on CAS theory by exploring concepts used in
IS studies.
The review followed a combined top-down and bottom-up approach to identify
the key CAS concepts used in IS research. It commenced with identifying key concepts
from the core papers on CAS like- (Holland, 1995), (Morel & Ramanujam, 1999),
(Mitleton-Kelly, 2003a) and (Gell-Mann, 1994), subsequently moving to the sample
CAS-IS papers to identify the similar CAS concepts used. It screened the core CAS
and CAS-IS papers back and forth several times to get the list of key CAS concepts.
Six main concepts of CAS in IS papers were identified as a result of this analysis.
Based on the 6 key concepts, the CAS-IS studies were then grouped and represented
in a tabular framework (see Table 3.2) using the concept matrix suggested by Webster
and Watson (2002). Note that some papers use multiple CAS concepts in combination
to explain particular phenomena; therefore, the same paper may appear in multiple
places in the table.
60 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
CAS concept Reference Summary of research contributions
1. C
o-E
volu
tion
(Allen & Varga, 2006)
Through an agent based view of the organisation, discussed the co-evolution of IS and the importance of understanding it for strategic thinking and decision making
(Benbya & McKelvey, 2006b)
Focus on co-evolution based self-organized emergent behaviour and structure of sustainable IS alignment
(Vessey & Ward, 2013)
Sustainable IS alignment occurs when organisation’s IS co-evolve with the organisation to meet its goals
(Kim & Kaplan, 2006)
IS engagement is a co-evolutionary process, where software systems, vendors and organisations adapt dynamically with the changing nature of one another CAS theory to incorporate evolutionary and teleological motors, and actor-network theory to incorporate dialectic motors to understand how systems and organisations co-evolve
(Vidgen & Wang, 2009)
Volberda's three principles of co-evolving systems are used to understand agile software development
(Tanriverdi, et al., 2010)
IS strategy should be co-evolved with the evolving, rugged, competitive landscape to maximize a firm’s agility for achieving profitability
(Chae, 2014)
Uses co-evolution concept to explain the process of IES innovation. The steps of coevolutionary processes are variation, selection and retention
2. E
mer
genc
e
(Curşeu, 2006)
In virtual teams, team cognition, trust, cohesion, and conflict are interdependent states that emerge from the interactions of team members
(Nan, 2011)
Seeks to highlight the emergent properties that rise from the individual- level IT use behavior- patterns to collective- level IT use patterns
(Lanham & McDaniel Jr, 2008)
How heterogeneous IT use emerges at individual and group levels
(Basole, 2009) Seeks to discover the relations of existing and emerging segments of the mobile system
(Vidgen & Wang, 2009)
Seeks to understand the emergent capabilities of agile software development teams
(Kautz, 2012)
Uses emergence concepts along with other concepts for comprehending the characteristics and practices of the IS development process
(Förderer, Kude, Schütz, & Heinzl, 2014)
Seeks to investigate the emergence of generativity from the interactions between platform and partners in micro and macro levels
(Huang, Rand, & Rust, 2016)
Seeks to investigate how different innovation speeds and qualities emerge from the competition when firms differing in IT capabilities competing in markets varying in uncertainty under different conditions
(Someh, Songhori, Wixom, & Shanks, 2018)
Focuses on the embeddedness of data and non-data teams within an organizational network, and it examines how the two teams connect and collectively influence organizational performance
3. S
elf-
Org
anis
atio
n
(Vidgen & Wang, 2006b)
Self-organisation with other CAS concepts- coevolution, edge of chaos, etc. to investigate system level emergence of agility
(Vidgen & Wang, 2009)
Use the principles of co-evolving systems to develop more coherent understandings of the properties of agility e.g. emergent capabilities
(Kautz, 2012)
Uses self-organisation concepts along with other concepts for comprehending the characteristics and practices of the IS development process
(Vessey & Ward, 2013)
Use self-organisation along with other CAS concepts to investigate how sustainable IS alignment occurs in organisations
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 61
(Nan & Lu, 2014)
Use the self-organisation concept to explore the possibility of orderly crisis management of organisations
4. F
itnes
s lan
dsca
pe (Hahn &
Lee, 2010) Use NK model to investigate how knowledge overlaps influence information systems development processes under some pre-defined conditions
(Tanriverdi, et al., 2010)
Use fitness landscape, suggests shift to three research quests of IS strategy in the highly dynamic and co-evolving competitive performance landscapes of products and services
(Rivkin & Siggelkow, 2007)
Develop simple, intuitive rules of thumb that allow to examine two interaction patterns and determine which warrants greater investment in broad exploration
5. D
ynam
ism
(Benbya & McKelvey, 2006b)
Focus on co-evolutionary based self-organized emergent behaviour and structure of IS alignment to uncover dynamics of IS alignment
(Canessa & Riolo, 2006)
Discuss how the dynamics generated by agent based modelling can be utilised to gain deeper understanding of computer mediated communication
(Curşeu, 2006)
Conceives the virtual team as CAS and seeks to provide better understanding of virtual team dynamics through artificial simulation
(Hanseth & Lyytinen, 2010)
Use CAS to recognize factors that generate the dynamics associated with the bootstrap and adaptability problems in information infrastructure
(Hildebrand, et al., 2012)
Develop a simulation model to provide explanations to viral marketing dynamics in social network
6. T
he e
dge
of c
haos
(Vidgen & Wang, 2006b)
Use edge of chaos and five other CAS concepts to explore the system level emergence of agility
(Vidgen & Wang, 2009)
Draw edge of chaos and other CAS concepts to build an organizing framework for agile software development
(Kautz, 2012) Uses edge of chaos to explain the region of complexity in OMS project
Table 3.2 Classification of papers based on CAS concepts in IS literature
From the analysis, the review has identified six major CAS concepts that are
frequently used in IS research. The concept of emergence has been used most in 9
studies within 40 papers, while co-evolution (7 studies) is the second highest one.
Self-organisation and dynamism, are used in 5 studies. However, it is too difficult to
assess how many times all of these concepts are used in IS studies as the CAS concepts
are highly intertwined with each other (Vidgen & Wang, 2006b). For instance, the
concept of adaptation is implicit within the concept of coevolution as co-evolution
takes place when some components adapt to each other over a specific period of time
(Mitleton-Kelly, 2003a). The analysis of the papers also reveals that not all the CAS
concepts from the core CAS studies and referent disciplines are explicitly represented
in the IS research. For instance, feedback process is an inherent characteristic of CAS,
which is frequently used in the CAS based IS studies but is not explicitly described in
research.
62 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
Overall the review shows that the majority of IS studies has adopted one or more
CAS concepts and then extended the concept(s) to explore the phenomena under study.
The particular section informs how CAS concepts are used for theory development
related to different dynamic phenomena. In addition, it also helps to relate the
contributions derived using each of the CAS concepts. The conceptual perspective
helps to identify the CAS concepts that are frequently used in IS research and
determine the concepts that can be adopted in my dissertation, in this case, the study
overall two key CAS concepts, emergence and coevolution. Moreover, it also
addresses the concepts related studies in IS, which helps to determine, how the
emergence and coevolution concepts are used in IS studies, such as, to broadly explore
the phenomena like dynamic relations over fitness landscape(Tanriverdi, et al., 2010)
and explain dynamic processes of evolution of system components (Chae, Koh, &
Prybutok, 2014).
It is important to highlight that, the CAS concepts are highly interrelated and
they are sometimes used together or separately in literature. For instance, the self-
organisation concept is used independently (Kauffman, 1995a; Kauffman, 1993) and
together within emergence concept (Goldstein, 1996, 2005) (I have adopted the later
view in this thesis) in broader complexity literature. This particular scenario brings to
attention that CAS related literature is highly inconsistent as acknowledged by other
scholars (Stacey, et al., 2000; Vidgen & Wang, 2006a). A broader conceptual
framework consolidating all CAS concepts by complexity theory experts and thought
leaders may resolve this inconsistent interpretation.
The primary reason of exploring the CAS concepts and their relative
contributions is to understand how the concepts can be applied in understanding a
complex phenomenon, in particular in the context of BVIT. However, after the
analysis of the CAS concepts in IS studies and specially in relation to the BVIT studies,
it is found that majority of the BVIT studies in strategic management discipline adopt
coevolution and fitness landscape concepts to explore BVIT, particularly competitive
advantage. Besides, the emergence concept have been used few cases (e.g. Huang, et
al., 2016) to explore strategic side of BVIT. Based on the above observation, I have
chosen two key concepts- emergence and coevolution, to explore the dynamics related
to the BVIT (broadly discussed in Chapter 4 and 5). The next section broadly discusses
the objectives of CAS theory in IS research.
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 63
3.6 THE OBJECTIVES OF CAS THEORY IN THE IS RESEARCH
This section presents the objectives of CAS theory in IS. To identify the major
objectives with CAS theory in IS literature, I first analysed the introduction section of
the papers, later exploring their full text. The preliminary analysis identified two major
goals associated with the use of CAS in IS. Subsequent analysis of the full text
identified six more objectives. The analysis also discerned a range of distinctive
characteristics among the objectives. I categorised the objectives according to their
characteristics, yielding three groupings. The first group contains two objectives,
which are more specifically the key goals of applying CAS theory in IS; I named this
group goals. The second group consists of three objectives, which are more
specifically the types of theory generated from applying CAS in IS research; I labeled
this group as theory types. The remaining three objectives I grouped as stages (see
following).
The purpose of this section is to show how these objectives of CAS theory
helps to guide my research direction. It also represents the type of IS theory this thesis
emphasises at the end of the section.
3.6.1 Objectives as Goals
My analysis suggests two key goals of CAS theory use in IS research: (i) to develop
novel theory and (ii) to test existing theory through simulation.
Theory Building
The elements and concepts of CAS are used for developing new theories in IS research.
Nan (2011) develops a theoretical framework drawing on the concepts and the
analytical tools of CAS; A CAS model of IT use that encodes a bottom-up IT use
process into three interrelated elements- agents, interactions and environment. Agent
based modeling (ABM) is performed for computationally representing and examining
the CAS model of IT use. The CAS model is operationalised and the analytical tool
ABM is demonstrated through a theory-building exercise, translating an interpretive
case study of IT use to a specific version of the CAS model. This theory building study
represents the bottom-up nature of IT use process, further demonstrating that collective
level patterns of outcomes are logical and often unpredictable as a consequence of
individual level behaviors. Chae (2014) conceptualises IT enabled services (IES) as
CAS with such properties and behaviors as diverse adaptive elements, nonlinear
64 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
interaction, self-organisation, and adaptive learning, and IES innovation as a co-
evolutionary process of variation, selection, and retention (VSR). He proposes a novel
framework of IES and IES innovation and develop a set of theoretical propositions
(theories) using business analytics (BA) as a new kind of decision support service.
This particular objective helps me to analyse and understand the processes of theory
building using CAS concepts in every surveyed paper.
Theory Testing
The key elements of CAS - agents, interactions and environment, allow researchers to
capture interactions among the basic entities of actions and relationships, and between
these entities and an environment in a virtual platform, and analyse their patterns of
behaviors under certain conditions. CAS theory serves as an ideal approach to encode
real life processes or activities into the computational model and enable analysis of the
properties, complex mechanisms, and dynamics in a virtual environment (Merali,
2004). As it is hard to represent every aspect of real life phenomenon in a virtual
environment, researchers specify a set of assumptions that portray the theoretical logic
of real life and test them in the simulation. For example, Hahn and Lee (2010) argue
that knowledge overlaps between business and IS, play an important role in the
Information Systems Development (ISD) process. Using an NK fitness simulation,
they seek to investigate how knowledge overlaps influence IS performance under
various levels of interdependencies, distributions of interdependencies, and levels of
inter-unit trust. The results of the simulation are analysed to developing deep
theoretical insights. The findings yield a set of testable propositions, which are further
tested in the simulation environment. Basically, my analysis of the papers shows that
majority of the papers that engage computational modeling and simulation test
hypothesis and theories by modeling them in the virtual environment. I will broadly
discuss this issue at the end of this section.
3.6.2 Objectives as Theory Types
My analysis suggests that applying CAS theory in IS yields three types of theory-
exploratory, explanatory, and design theory, which are also objectives of CAS in IS
research.
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 65
Exploratory Theory
Most CAS studies that use empirical data are exploratory in nature. These studies
typically first entail one or multiple case studies to collect data about the phenomenon
and then apply the CAS lens to explore theoretical insights from the data. Vidgen and
Wang (2006b) argue that the theoretical foundation of agile software development
(ASD) has not been articulated systematically, and propose a conceptual framework
to study agile software development based on CAS. They follow an interpretive
approach for collecting empirical data through a case study of an ASD team. They
identify several agile practices from the CAS perspective as a result of analysis.
Moreover, CAS studies that include simulation are also exploratory in nature, as a real-
life phenomenon is encoded in the computational model; and by running the model in
simulation it can be clearly depicted how a process unfolds and evolves over time;
something much more difficult to understand through verbal communication or
observation. This theory type is highly related to chapter 6, where I have adopted NKC
model as a lens to explore the coevolutionary dynamics of IT-enabled capabilities in
micro and macro levels of organisations. The NKC models helps to translate the
components of NKC and analytical logic to develop strategies based on the simulation
outcomes from (Kauffman, 1995a) simulation. A detailed discussion is available in
Chapter 6.
Papers Objectives of CAS
Goals Theory Types Stages
The
ory
build
ing
The
ory
test
ing
Exp
lora
tory
Exp
lana
tory
Des
ign
Con
cept
ualis
atio
n
CA
S Fr
amew
ork
or m
odel
ing
Sim
ulat
ion
(Merali, 2002) ✓ ✓ ✓ ✓ (Allen & Varga, 2006) ✓ ✓ ✓ (Benbya & McKelvey, 2006b) ✓ ✓ ✓ ✓ (Canessa & Riolo, 2006) ✓ ✓ ✓ ✓ ✓ ✓ ✓ (Curşeu, 2006) ✓ ✓ ✓ ✓ ✓ ✓ ✓ (Kim & Kaplan, 2006) ✓ ✓ (Merali, 2006) ✓ ✓ ✓ (Vidgen & Wang, 2006b) ✓ ✓ ✓ ✓ (Wang & Vidgen, 2007) ✓ ✓ ✓ ✓ (Habib, 2008) ✓ ✓ ✓ ✓ ✓ ✓ ✓
66 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
(Lanham & McDaniel Jr, 2008) ✓ ✓ ✓ (Basole, 2009) ✓ ✓ ✓ ✓ ✓ ✓ ✓ (Vidgen & Wang, 2009) ✓ ✓ ✓ ✓ (Wang & Conboy, 2009) ✓ ✓ ✓ ✓ (Hahn & Lee, 2010) ✓ ✓ ✓ ✓ ✓ ✓ ✓ (Hanseth & Lyytinen, 2010) ✓ ✓ ✓ ✓ (Tanriverdi, et al., 2010) ✓ ✓ ✓ (Nan, 2011) ✓ ✓ ✓ ✓ ✓ ✓ ✓ (Grover, 2012) ✓ ✓ (Hildebrand, et al., 2012) ✓ ✓ ✓ ✓ ✓ ✓ ✓ (Kautz, 2012) ✓ ✓ ✓ ✓ (Merali, et al., 2012) ✓ ✓ (Khanna & Venters, 2013) ✓ ✓ ✓ (Vessey & Ward, 2013) ✓ ✓ ✓ (Förderer, et al., 2014) ✓ ✓ ✓ ✓ (Nan & Lu, 2014) ✓ ✓ ✓ ✓ (Ozer & Anderson, 2015) ✓ ✓ ✓ ✓ ✓ ✓ ✓ (Huang, et al., 2016) ✓ ✓ ✓ ✓ ✓ ✓ ✓ (Chae, 2014) ✓ ✓ ✓ ✓ - (Schramm, Trainor, Shanker, & Hu, 2010)
✓ ✓ ✓ ✓ ✓ ✓ ✓
(Wang, Gwebu, Shanker, & Troutt, 2009)
✓ ✓ ✓ ✓ ✓ ✓ ✓
(Khouja, Hadzikadic, Rajagopalan, & Tsay, 2008)
✓ ✓ ✓ ✓ ✓ ✓ ✓
(Klashner & Sabet, 2007) ✓ ✓ ✓ ✓ (Sherif & Xing, 2006) ✓ ✓ ✓ ✓ (Adler, Baets, & König, 2011) ✓ ✓ ✓ ✓ ✓ ✓ ✓ (Rivkin & Siggelkow, 2007) ✓ ✓ ✓ ✓ ✓ ✓ (Someh, et al., 2018) ✓ ✓ ✓ ✓ ✓ ✓ (Tanriverdi & Lim, 2017) ✓ ✓ ✓ ✓ (Schilling, Beese, Haki, Aier, & Winter, 2017)
✓ ✓ ✓ ✓
(Marjanovic & Cecez-Kecmanovic, 2017)
✓ ✓ ✓ ✓
Table 3.3 CAS objectives in IS research Explanatory Theory
The concepts and principles of CAS are suitable for explaining complex phenomena
and thus IS researchers have been using it for analysing sophisticated organisational
processes like agile software development (ASD) and IS alignment or service
platforms. The objective of this type of research is to explore something that was
imperfectly or poorly understood beforehand (Gregor, 2006). The purpose is to
identify and explain how and why particular phenomenon happens using CAS lens.
For instance, Wang and Vidgen (2007) argue that the agile processes are marked by
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 67
some chaotic processes and are contrasted to waterfall approaches. They use the edge
of chaos concept from CAS to analyse the role of structure and planning in software
development (SD) processes. They gather data on the project structure and planning
of SD processes of two teams from a major IT company, who often use both agile and
waterfall approaches and compare them from a CAS perspective. The analysis shows
structure and planning is essential to agile processes and takes different forms from
the waterfall model. CAS is predominantly used as an explanatory theory to describe
complex phenomena in IS studies, which is revealed though my analysis. I have found
that majority of the IS studies have used one or more CAS concepts to broadly explain
phenomena under study.
Design Theory
Only one paper was identified that used CAS theory to derive design
principles; more precisely, as design theory in IS research. Hanseth and Lyytinen
(2010) argue that contemporary IT systems involve complexity that extends beyond
what can be addressed by traditional design approaches. They seek to develop a design
theory based on CAS theory that tackles information infrastructures’ dynamic
complexity. By exploring the design histories of infrastructures and reviewing the
principles of CAS theory, and illustrated by analysing the history of Internet exegesis.
3.6.3 Objectives as Stages
Applying CAS theory in IS research involves two main stages; (i) conceptualisation
and (ii) modeling of the phenomena of interest. Some studies involve only stage 1
conceptualisation. Studies that entail stage 2 modeling of the phenomena must be
preceded by stage 1. A third stage (which demands prior completion of the 1st two
stages) may follow, which entails computationally representing the phenomena from
the conceptual model in a simulation of the virtual environment; we broadly name this
stage simulation. Very few of the studies engage in this stage of the research. These
three stages represent three CAS objectives.
Conceptualisation
The analysis shows that most of the IS studies use CAS or CAS concepts to
conceptualise phenomenon and theoretically explain them. For example- Vidgen and
Wang (2006b) conceptualise agile software development as CAS and propose a
theoretical framework. The framework is used as a sensitizing device for collecting
68 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
data and carrying out analysis in an interpretive case study. As a result of their analysis,
several agile practices are identified, and reflected on, from the theoretical perspective
of CAS.
CAS Framework or Modeling
The analysis of the papers suggests that the CAS concepts and key elements are used
for conceptual or theoretical frameworks or modeling of complex business processes
like IT use (Habib, 2008; Nan, 2011) or computer information systems (Canessa &
Riolo, 2006). For example, Curşeu (2006) uses the CAS perspective to integrate the
literature on emergent states in virtual teams (VT). She uses the concept of emergence
to develop a CAS framework and provide a new theoretical understanding for some of
the phenomena of VTs’ dynamics that were previously studied in isolation. By
combining the insights from the CAS framework with the empirical data, the study
seeks to provide a basis for matching emergence in VT with the virtual simulations.
Simulation
As an analytical theory, CAS provides a way of encoding and presenting real
life complex processes through a computational model, then in virtual simulation
(Merali, 2004). The elements of CAS theory, agents, interactions and environment,
have been applied in IS research to understand the underlying complexities of different
contexts, computer information systems (Canessa & Riolo, 2006), virtual teams
(Curşeu, 2006), viral marketing dynamics (Hildebrand, et al., 2012), innovation
diffusion (Schramm, et al., 2010), decision making (Adler, et al., 2011) etc.
Researchers have employed different computational modeling or simulation
techniques in IS research, such as Agent based modeling (ABM) (Bonabeau, 2002),
NK modeling (Kauffman, 1993) and MySQL simulation. The theoretical propositions
of real life processes are outlined under certain assumptions and conditions in the
model. The model is executed to explore a wide range of possible contingencies that
are difficult to assess in a laboratory setting or through field studies (Nan, 2011).
From Table 3.3, it can be observed that CAS studies that adopt the simulation
method appear relatively more versatile than the other studies. The simulation based
CAS studies employed in attention to all but 1 of the 8 objectives. The reason seems
clear, as a real world complex phenomenon can be conceptualised theoretically (1.
conceptualisation), modelled (2. conceptual model), explained (3. explanatory)
computationally represented, run (4.simulation), and tested in simulation with specific
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 69
assumptions (5. theory testing), and the results of the simulation are analysed (6. theory
building) for in-depth understandings about the phenomena (7. explanatory) (e.g. Nan,
2011). This review also found that a limited number of design research studies have
been conducted in IS discipline using CAS theory. I identified only a single study i.e.
(Hanseth & Lyytinen, 2010) that used CAS to derive design principles, a.k.a. design
theory. This may suggest an opportunity to further apply CAS theory in design science
research.
In summary, the identification of the CAS theory objectives in IS research
helps me to better shape my research direction. Firstly, in a higher level, the objective
as goal helps me to develop my thesis as a theory building exercise. It helps me to
understand how CAS theory can be used to develop theories in IS from the analysis of
the CAS based IS studies. Secondly, the theories developed from my thesis (in Chapter
4 and 5) are explanatory type (Gregor, 2006) as it helps to explain why BVIT process
has become dynamic in contemporary organisations and how we can use CAS features
and concepts to better understand the complex process. In addition, NKC model
adopted in Chapter 6 is used as an exploratory lens to further develop greater insights
on the coevolution perspective of IT-enabled capabilities and its impact on competitive
advantage. The theories in this chapter are exploratory in nature, which follow my
proposed theory types in section 3.6.2. Moreover, the CAS objectives also has guided
how to conceptualise BVIT process via two CAS concepts- emergence and
coevolution, develop CAS based framework and guidelines.
3.7 THE THEORETICAL PERSPECTIVES OF CAS RESEARCH IN IS
In the preceding section, I discussed different methodological approaches that
researchers follow in CAS-IS research. In this section, I present the theoretical
approaches of applying CAS in IS research. For the theoretical approaches, it was
necessary to consider the full text of the surveyed papers. As a result of the analysis, I
identified two major theoretical approaches- only CAS theory and CAS with other
theories. Of the 40 papers, 34 papers used one or more of the CAS concepts and
principles. Only 6 papers used other theories along with CAS theory.
3.7.1 CAS Theory Only
This class of research engages only the basic concepts or principles of CAS
theory to conceptualise complex phenomena and for analysis to develop in-depth
70 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
understanding. These papers followed all the methodological approaches reported in
this chapter, empirical (e.g.Kim & Kaplan, 2006; Vidgen & Wang, 2006b), conceptual
(e.g.Allen & Varga, 2006; Benbya & McKelvey, 2006b) and computational (e.g. Hahn
& Lee, 2010; Nan, 2011). Tanriverdi, et al. (2010) (mentioned earlier) conceptualise
business systems as CAS in order to theorise about IS strategic alignment. In another
study, Allen and Varga (2006) explain the construction and development of IT systems
from the co-evolutionary perspective of CAS. They conceptualise organisations as
CAS and individuals as agents to develop understandings of the evolution of IS from
the interactions of agents and other constructs, such as IT systems in organisations.
The analysis of the theoretical perspective of CAS theory helps me to apply CAS
theory to conceptualise BVIT and later on, I have used CAS concepts- emergence and
coevolution for developing in-depth understanding on BVIT.
3.7.2 CAS with Other Theories
The objectives of studies that use CAS with other theories are similar to those which
use CAS alone. For example- Benbya and McKelvey (2006b) present a view of IS
alignment in organisations drawing on the co-evolution concept of CAS theory,
especially focusing on co-evolution based self-organized behaviour, which provides
important insights on the emergent nature of IS alignment. This view considers
business/ IS alignment as a series of adjustments at three levels of analysis- individual,
operational and strategic. Drawing on scale free dynamics theory and principles of
adaptation, they suggest several enabling conditions to speed up the adaptive co-
evolutionary dynamics among the three levels.
Theoretical Approaches Studies
CAS theory only (34 out of 40)
(Allen & Varga, 2006);(Canessa & Riolo, 2006);(Curşeu, 2006); (Merali, 2006);(Vidgen & Wang, 2006b);(Wang & Vidgen, 2007);(Habib, 2008);(Basole, 2009);(Vidgen & Wang, 2009); (Wang & Conboy, 2009);(Hahn & Lee, 2010);(Hanseth & Lyytinen, 2010);(Tanriverdi, et al., 2010);(Nan, 2011); (Grover, 2012);(Hildebrand, et al., 2012);(Kautz, 2012);(Merali, et al., 2012);(Khanna & Venters, 2013);(Vessey & Ward, 2013);(Förderer, et al., 2014);(Nan & Lu, 2014);(Ozer & Anderson, 2015);(Huang, et al., 2016);(Chae, 2014);(Wang, et al., 2009);(Khouja, et al., 2008);(Sherif & Xing, 2006);(Adler, et al., 2011);(Rivkin & Siggelkow, 2007); (Schramm, et al., 2010); (Klashner & Sabet, 2007)
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 71
CAS with other theories (6 out of 40)
(Merali, 2002);(Benbya & McKelvey, 2006b);(Kim & Kaplan, 2006);(Lanham & McDaniel Jr, 2008); (Schramm, et al., 2010); (Klashner & Sabet, 2007)
Table 3.4 Theoretical approaches in CAS research in IS
3.8 THE METHODOLOGICAL APPROACHES OF CAS IN IS RESEARCH
This section presents the methodological approaches researchers follow to
conduct CAS-based IS research. The purpose is to determine the nature of CAS
research by identifying the research approaches in the IS literature. In order to identify
the methodological approaches, I analysed the research method or methodology
section of the papers. Following Chen and Hirschheim (2004), I classified the papers
into two broad methodological classes, empirical and non-empirical. In addition, I
added another category termed computational; those papers that use computational or
simulation method to model real world phenomena.
The empirical papers were classified into sub categories using the framework
developed by Chen and Hirschheim (2004). In addition to the original sub categories
of survey, case study, experiment, field study, action research, I have included another
sub category as archival analysis following Fielt, et al. (2014). I also categorised the
computational studies based on the computational modeling (simulation) approach.
The majority of the papers followed agent based modeling (ABM) Therefore, I
classified computational studies into two sub-categories; agent based modeling and
other approaches.
Studies Empirical Conceptual Computational
Cas
e st
udy
Surv
ey
Exp
erim
ent
Arc
hiva
l an
alys
is
Fiel
d St
udy
Act
ion
rese
arch
O
ther
s
Age
nt b
ased
m
odel
ing
Oth
ers
(Merali, 2002) ✓
(Allen & Varga, 2006)
✓
(Benbya & McKelvey, 2006b)
✓
(Canessa & Riolo, 2006)
✓
(Curşeu, 2006) ✓
(Kim & Kaplan, 2006)
✓
(Merali, 2006) ✓
(Vidgen & Wang, 2006b)
✓
72 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
(Wang & Vidgen, 2007)
✓
(Habib, 2008) ✓ ✓
(Lanham & McDaniel Jr, 2008)
✓
(Basole, 2009) ✓ ✓
(Vidgen & Wang, 2009)
✓
(Wang & Conboy, 2009)
✓
(Hahn & Lee, 2010) ✓
(Hanseth & Lyytinen, 2010)
✓
(Tanriverdi, et al., 2010)
✓
(Nan, 2011) ✓ ✓
(Grover, 2012) ✓
(Hildebrand, et al., 2012)
✓
(Kautz, 2012) ✓
(Merali, et al., 2012)
✓
(Khanna & Venters, 2013)
✓
(Vessey & Ward, 2013)
✓
(Förderer, et al., 2014)
✓
(Nan & Lu, 2014) ✓
(Ozer & Anderson, 2015)
✓
(Huang, et al., 2016)
✓
(Chae, 2014) ✓
(Schramm, et al., 2010)
✓
(Wang, et al., 2009) ✓
(Khouja, et al., 2008)
✓
(Klashner & Sabet, 2007)
✓ ✓
(Sherif & Xing, 2006)
✓
(Adler, et al., 2011) ✓
(Rivkin & Siggelkow, 2007)
✓
Table 3.5 Overview of methodologies in CAS based IS research
The analysis of the papers based on the classification of research
methodologies yielded 16 empirical papers in total of which 13 were case study based
papers, 1 field study based, 1 action research based and 1 used social network data,
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 73
which is positioned under others column within empirical method (see column 8 of
Table 3.5). No surveys, experiments or action research studies were encountered in
the sample of papers.
The analysis also reported 14 computational based studies in total, in which 13
studies adopted ABM approach and only one study followed more than one approach,
Basole (2009) used both MySQL and simulation together. Moreover, I found 10
conceptual papers. Noted that all 4 studies using multi-method (greyed boxes in Table
3.5), used 2 methods. Two papers used case study and simulation methods together to
develop a computational model based on the case data; I marked them as
computational studies because the ultimate objective of these studies is to build and
simulate computational models based on empirical evdience. For the same reason I
have placed another study into the category computational studies, that used archival
data for developing a computational model. One paper used field data to develop
conceptual understanding of a phenomenon; I classified this as conceptual study
because the overall intention of this study is to develop conceptual understanding on
the phenomenon under study.
3.8.1 Empirical
The empirical papers contain observations and data (primary or secondary
data) that provide strong evidence for testing theories. Typically, one or multiple case
studies are conducted to gather empirical data about the phenomenon. CAS is used as
a theoretical lens to provide an in depth theoretical description of the phenomena
(Courtney, et al., 2008; Merali, 2004). The description contains detailed explanation
of the phenomena; what it is, how, why, when and where. For example, Vidgen and
Wang (2006b) propose a theoretical framework of agile software development using
CAS. An interpretive case study is conducted to gather data on a software development
process. The framework is used as a sensitizing device for data collection and analysis.
Several agile practices are identified and reflected on from the theoretical perspective
of CAS.
3.8.2 Non-empirical or Conceptual
The non-empirical papers develop new concepts and theories; I refer to these
as conceptual papers. CAS theory is used to conceptualize a phenomenon, explore it
74 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
and then provide an in depth explanation of it. One or more CAS concepts are used to
investigate and provide theoretical statements on the phenomena. The outcome of the
analysis generates new insights, concepts and theories. For example, Tanriverdi, et al.
(2010) employ CAS to theorize about IS strategic alignment. They suggest
organisations consider three quests of IS strategy- strategic alignment to co-evolution,
integration to reconfiguration and sustained competitive advantage to renewal; in the
competitive performance landscapes of products and services, which are highly
dynamic and co-evolve in nature. It is important to note that, this study on BVIT using
CAS theory is a conceptual research.
3.8.3 Computational
These studies employ computational models to represent the phenomena under
study, and using empirical or non-empirical data (Davis, et al., 2007), test models to
gain deep understandings of the phenomena and develop new concepts and theories.
As described above, the computational studies may use empirical data, yet we
categorise them as computational because the ultimate objective of these studies is to
build and simulate computational models based on empirical evidences. For example,
Nan (2011) uses secondary empirical case data to explore bottom-up emergence of IT
use in organisations. She develops a computational model using ABM to represent the
IT use process, operationalises the model using empirical data and emulates it in a
virtual platform for studying the properties and mechanisms of bottom-up IT use
processes. For instance, her findings from the simulation reveal that the IT-based
organisational transformation does not depend on organisations with high employee
learning rates, high IT flexibility, and low workplace rigidity; it can occur in any
organisation permitting mutually adaptive interactions among human actors, IT
features, and environmental structures.
The analysis shows that case studies make up the majority (13 out of 16) of
empirical studies in CAS. They are a popular and appropriate empirical research
method for a new area of research (Yin, 2013). and and help to understand the
dynamics present is a single setting and also help to generate novel theory (Eisenhardt,
1989)., which is the focus of the majority of the studies under the analysis. In addition,
case studies are also good to “explore complexities that are beyond the scope of more
'controlled' approaches” (Gillham, 2010). Moreover, the analysis of the set of papers
reveal that the majority of the papers are exploratory in nature containing how and why
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 75
research questions to investigate complex contemporary phenomena; these types of
questions deal with operational links that need to be traced over time (Yin, 2003).
Case studies help researchers to gather primary evidence from the research settings
(Gillham, 2010), and using the CAS lens, they can inductively develop theory that is
grounded in the evidence.
The 14 computational CAS studies reviewed are truly exploratory in nature.
The computational papers employ simulation methods to virtually represent real world
problems with some predefined constructs and their relationships under some
conditions and then run the model for superior insight into complex theoretical
relationships among constructs, especially when challenging existing empirical data
limitations (Zott, 2003). According to Davis, et al. (2007, p. 483), “Simulation is
particularly suited to the development of simple theory”. My analysis also showed that
though the studies are exploratory, the main focus of the computational studies under
my investigation is to develop theory and extension to the existing theories. CAS
studies deal with phenomena involving multiple interacting components and
processes, feedback loops, and bottom-up emergence, and simulation is especially
useful for studying these type of situations as it is likely to reveal complexities that are
difficult to identify and understand using other methods.
My analysis identified methodological triangulation (Denzin, 1978) - the use
of multiple methods. There are several overriding purposes for methodological
triangulation. The preliminary purpose is to eliminate or reduce biases and ensure the
validity of the study (Jonsen & Jehn, 2009). Another purpose is to ensure the richness
and in-depth understanding of the study. These papers use case study and the
simulation methods together; the case study is conducted as an exploratory device to
gather primary evidence on the phenomena, the gathered data are inductively analysed
using CAS lens to identify simple theories that have modest empirical grounding such
that propositions are likely to be correct, but are limited by weak conceptualisation
(Davis, et al., 2007). Using the data with the simple theories’ constructs, relationships
are defined in the simulation model and run in the virtual environment to uncover non-
intuitive explanations of the simple theories. Using the case data in the simulation
model and analysing it by running the model enriches the understanding of the
researchers and also ensures that the simulation result satisfies the theoretical logics of
the case findings, and thus establishes the validity as well (Davis, et al., 2007).
76 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
Therefore, the analysis also explains that the case study together with the simulation
method (2 out of 14 computational studies) provides a better way of investigating
complex phenomena.
The analysis of the methodological approaches of CAS theory has facilitated
my research design (section 1.5 in chapter 1); in particular, the phase 3 and phase 4-
developing emergence and cooevolution perspectives on IT-enabled capabilities
respectively of my research design. The analysis provides me ideas on how to apply
CAS concepts- emergence and coevolution in a conceptual way and develop new
insights, concepts or theories in relation to the dynamics of BVIT. Moreover, the
analysis of the computational papers also provides ideas on how to conceptualise and
translate simulation outcomes for generating new insights. Though, I followed both
McKelvey (1999) and Baum and McKelvey (1999c) studies in strategic management
area as guidelines (section 6.3.1 and 6.3.2 in chapter 6) to understand the translation
process and developing strategies respectively, it was important to check back and
forth whether the way simulation is used to generate insights in IS is same as strategic
management.
3.9 CONTEXT OF THE CAS THEORY IN IS RESEARCH
For the contextual analysis, I categorized the papers based on the topics. A
single paper sometimes contains multiple topics; I put them in more generic type to
cover the multiple topics. Table 3.6 contains the list of major CAS research topics
identified from the review. The most highly represented topics identified are agile
Software Development, information structures, conceptualisation of IS domain, each
of which are 10% (4 out of 40). A more general focus-area is information systems
development (ISD) (7.5%), which could be considered to subsume agile software
development. Together they encompass more than 37% of CAS related IS studies in
the sample. The modern ISD process is considered a combination of complex activities
(Highsmith, 2000). Turbulent business environments, changing customer
requirements, pressure for short-time delivery, and rapid evolution of information
technologies make the ISD process more complex (Baskerville, Levine, Pries-Heje,
Ramesh, & Slaughter, 2001; Benbya & McKelvey, 2006b). The debate between agile
versus plan-driven software practices in organisations reflects the lack of theoretical
understanding of the ISD process (Highsmith, 2000). It is in this context that CAS can
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 77
provide deeper insights. These are some of the primary reasons for conducting CAS
based research in the ISD domain. Topic References # Percent
(%) Agile Software Development
(Vidgen & Wang, 2006b); (Wang & Vidgen, 2007); (Vidgen & Wang, 2009); (Wang & Conboy, 2009) 4 10
Information Structures (Hanseth & Lyytinen, 2010); (Khanna & Venters, 2013); (Schilling, et al., 2017); (Marjanovic & Cecez-Kecmanovic, 2017) 4 10
Conceptualization of IS Domain (Merali, 2006); (Grover, 2012); (Tanriverdi, et al., 2010); (Merali, et al., 2012) 4 10
Information Systems development (Allen & Varga, 2006); (Hahn & Lee, 2010); (Kautz, 2012) 3 7.5
IT Use Process (Canessa & Riolo, 2006); (Lanham & McDaniel Jr, 2008); (Nan, 2011) 3 7.5 Information Systems Alignment (Benbya & McKelvey, 2006b); (Vessey & Ward, 2013) 2 5.0
Organisational Knowledge Processes (Merali, 2002); (Habib, 2008) 2 5.0
Social Network (Hildebrand, et al., 2012); (Nan & Lu, 2014) 2 5.0 Decision making (Rivkin & Siggelkow, 2007); (Adler, et al., 2011) 2 5.0 Information Systems Engagement (Kim & Kaplan, 2006) 1 2.5
IT- enabled service (Chae, 2014) 1 2.5 Service Platform (Förderer, et al., 2014) 1 2.5 Virtual Teams (Curşeu, 2006); (Marjanovic & Cecez-Kecmanovic, 2017) 1 2.5 Innovation Diffusion (Schramm, et al., 2010) 1 2.5 Knowledge Sharing (Wang, et al., 2009) 1 2.5 Copyrighted information goods (Khouja, et al., 2008) 1 2.5
ICT use in mission critical infrastructure (Klashner & Sabet, 2007) 1 2.5
Knowledge creation (Sherif & Xing, 2006) 1 2.5 Inter firm relations of mobile ecosystem (Basole, 2009) 1 2.5
IS capabilities (Schilling, et al., 2017) 1 2.5
Table 3.6 Context of CAS theory in IS Another major topic is conceptualization of the IS domain as CAS (12%).
Merali, et al. (2012)) argue that the IS domain has sufficient adaptive capacity to
evolve in the emerging competitive landscape, challenging the increased turbulence,
uncertainty and dynamism of IS research. The field of IS research I s highly diversified
and dynamic, with new topics emerging constantly, thus the landscape of IS research
is always changing with scholars shifting attention to investigate new IS and IS
phenomena. Grover (2012, p. 259) mentions that the IS field is currently adapting to
the complex research environment and the field itself is responsive, and exhibits
rational adaptation and learning behaviours to deal with new research topics and
emerging phenomena. This dynamism leads IS researchers to conceptualize the IS
domain as a complex system.
Another focus of CAS research is the IT Use Process 8.6% (3 out of 36). CAS
as a theory is inherently multi-level in nature and facilitates exploration of macro-level
properties that emerge from micro-level dynamics. The traditional IT use literature
tends to capture snapshots of discrete elements of the IT use construct, such as users,
system or tasks using variance based models as suggested by the recent system usage
78 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
literature (Burton-Jones & Straub Jr, 2006). Several researchers e.g. Nan (2011) is
dissatisfied with this fragmented understanding of one or two selective elements of the
IT use construct and seeks to explore more comprehensive conceptualizations of this
construct. As CAS helps to study collective level phenomena where emergent
properties arise from lower level elements, researchers become more interested in this
theory.
Other papers address such topics as Information Systems Alignment,
Organisational Knowledge Processes, Social Networks, decision-making and
Information Structures (2 papers each or 5.8%). Topics represented by a single paper
(3%) are virtual teams, IT-enabled service, information systems engagement,
innovation diffusion, knowledge sharing and service platforms.
One of the key findings is that there is a lack of studies directly related to the
BVIT. Few studies can be considered within BVIT umbrella. For instance, Tanriverdi,
et al. (2010) study on the strategic advantage of firms over competitive performance
landscape, in which authors suggest that firms operate in a complex adaptive business
systems. The firms follow coevolution quest that continuously identifies profitable
positions over landscape, reconfiguration quest that supports the profitable positions
and renewal quest that supports dynamic and agile changes due to positioning. Overall
firms attempt to achieve a superior position in contemporary environment via
dynamically aligning IS and corporate strategies. The strategic alignment of IS and
business study by Benbya and McKelvey (2006b) can also be considered as a BVIT
related work. Moreover, prominent management scholars, such as, Rivkin and his
colleagues (e.g. Rivkin, 2000, 2001; Rivkin & Siggelkow, 2007) have been working
on Kauffman’s simulation model (Kauffman, 1993) to derive strategies for
organisations to obtain better competitive advantage on the landscape of products and
services for the last two decades. Therefore, it can be argued that IS scholars more
recently have started realising the potential of adopting a dynamic view on strategic
perspective of BVIT, but the number of studies is still limited and the core dynamic
mechanisms related to the BVIT remain underexplored, which I am attempting to
focus in my thesis.
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 79
3.10 CONCLUSION
This chapter explores the current understanding on CAS theory in IS research.
This chapter is distinct from Chapter 2 in terms of the contents of the review items.
This chapter only contains CAS related IS and IS referral studies- strategic
management and organisational research and the surveyed studies are used to
understand CAS theory in general (including seminal works) and within IS in
particular. Though the applications of CAS theory in IS discipline have achieved
increased attention in recent years, the current body of knowledge regarding CAS
theory within the IS discipline remains limited and fragmented. The lack of maturity
of CAS theory within IS research has been recognised by other researchers over the
years (e.g. Merali, 2004, 2006; Mitleton-Kelly, 2014; Tanriverdi, et al., 2010; Vidgen
& Wang, 2009). Therefore, this chapter synthesises and explores CAS based IS studies
to develop a better understanding of the what (conceptions of CAS theory in section
3.5), why (objectives of CAS theory in Section 3.6), and how (theoretical and
methodological aspects of CAS theory in section 3.7 and 3.8). To my knowledge this
is the first such comprehensive review of CAS related IS studies.
It is important to note that there are still confusions around CAS- whether this
is a theory or a concept of complexity theories in the broader complexity literature. A
number of researchers such as, Merali (2006) and McKelvey (2002) consider CAS as
a concept of complexity science and few researchers, such as, Stacey, et al. (2000)
consider CAS as a theory; I have adopted Stacey et al.’s view, which is mentioned in
section 1.4. According to Stacey, et al. (2000), any review on CAS theory may
implicitly contain ontologically inconsistent interpretations of CAS, which may draw
invalid conclusions. These ontological and teleological assumptions are not easy to
derive from individual papers, but requires an in-depth analysis of the core body of
complexity science research over many years by complexity experts and this is a
limitation of my CAS review on IS.
Section 3.5 provides an overall overview of the key CAS concepts used in IS
research. This section is intended to consolidate the major CAS concepts and then
choose the concept(s) that can be used to explore the dynamics of BVIT. I have
adopted emergence and coevolution concepts to study the dynamics of BVIT (a more
detailed discussion is below). Section 3.5 broadly analyses the objectives of CAS
theory in IS research and classifies them as goals, theory types and stages. This section
80 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
is highly relevant to the Chapter 4, 5 and 6 as section 3.6.1 establishes the base that I
have used emergence and coevolution concepts for theory building studies in chapter
4 and 5 consecutively. Moreover, section 3.6.2 highlights that I have used emergence
and coevolution concepts to develop explanatory theories (Gregor, 2006)and NKC
model to develop exploratory theories (Chapter 6). Section 3.7 presents that CAS
theory can be used in isolation or with other theories. This section is intended to relate
that this thesis has only used CAS theory, more specifically, emergence, coevolution
concepts and NKC model; other dynamic theories/ concept such as, cynefin framework
(Merali, 2002) can also be used with CAS to develop insights from different viewpoint
(Woodward, 2002). Section 3.8 represents that CAS can have three major types of
methodologies- empirical, conceptual and computational. In this study, I have adopted
conceptual approach in applying emergence and coevolution concepts in Chapter 4
and 5 consecutively and a combination of computational and conceptual approach in
applying NKC model in the context of coevolutionary dynamics of IT-enabled
capabilities in Chapter 6. Finally, section 3.9 aims to reflect upon the context of CAS
based studies. The analysis of the context helps me to identify BVIT related studies
which adopt CAS concept and adopt their approach in my thesis, which is described
in below paragraph.
The overall observation of the literature on CAS related studies in IS is that
BVIT has not been explicitly explored. However, there are still some studies that
particularly emphasise the strategic perspective of the BVIT, competitive advantage
(e.g. Rivkin, 2000; Rivkin, 2001; Rivkin & Siggelkow, 2007; Tanriverdi, et al., 2010).
Another crucial observation is that the concept of emergence has been used most in 9
studies within 40 papers, while co-evolution (7 studies) is the second highest one
(section 3.5). There are some related works in relation to the strategic perspective of
BVIT, competitive advantage both in IS and strategic management mentioned in
section 3.9, that highly used coevolution concept, NKC theorising (Tanriverdi, et al.,
2010) and simulation outcomes (Rivkin, 2001). Section 3.9 reflects that the
coevolution concept is used in many studies in strategic management and
organisational studies (Chae, 2014; Rivkin, 2001), but not in abundant in IS studies
(Benbya & McKelvey, 2006b), in particular, in the context related to BVIT. Moreover,
the emergence concept though not highly used, but have been adopted to explore how
different innovation speeds emerge from different innovation speeds of firms with
Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory 81
varying IT capabilities and their role in competitive advantage (e.g. Huang, et al.,
2016). Beyond that, the emergence (systems thinking based) concept has also been
used in exploring competitive advantage in traditional IS study (e.g. Nevo & Wade,
2010).
Based on the observation of the CAS literature in IS, I have decided to adopt two
CAS concepts- emergence and coevolution to explore the dynamics related to the
BVIT. The emergence concept is highly beneficial in explaining emergent patterns/
behaviors from the interactions of system components (Stacey, et al., 2000) and hence,
I have chosen the emergence concept in explaining the emergence of IT-enabled
capabilities (Chapter 4). Further, the coevolution concept is widely used to explain
evolutionary adaptive dynamics between one or more domains (McKelvey, 2002), and
therefore, I have chosen the coevolution concept to explain micro and macro level
coevolutionary dynamics of IT-enabled capabilities and their impact on competitive
advantage (Chapter 5).
As such, the literature review of CAS in IS also provides a starting point for how
this study can build on and extend existing work on CAS in IS. Taking Nevo and Wade
(2010) systems thinking based study on competitive advantage as a starting point, I
have adopted the emergence concept to explore how IT-enabled capabilities emerge
from the interactions between two elements IT assets and organisational resources,
which is broadly discussed in chapter 4. I have also adopted coevolution concept to
further explore how these IT-enabled capabilities coevolve with other IT-enabled
capabilities in organisations and with competitors and influence competitive
advantage. I have adopted Melville, et al. (2004) RBV based model on competitive
advantage as a starting point because it helps me to define two levels- micro (internal
to firm) and macro (external to firm) in organisations and then, I have applied
coevolution lens in both with the argument that IT-enabled capabilities coevolve in
these two levels and ultimately influence competitive advantage, which is broadly
discussed in chapter 5. Moreover, as discussed in section 3.6.3, the simulation model
has the potential to develop deeper insights on the phenomenon under study and it has
been widely used for theory development on competitive advantage, therefore, I have
also used simulation outcomes from Kauffman’s NKC model (Kauffman, 1993) and
followed Baum and Mckevely’s approach (Baum & McKelvey, 1999c) to propose
some strategies in managing the coevolution of the IT-enabled capabilities, which is
82 Chapter 3: A Structured Literature Review on Complex Adaptive Systems Theory
broadly discussed in chapter 6. It is important to highlight that Chapter 4, 5 and 6
contain in-depth reviews on emergence, coevolution concepts and NKC model
respectively. These reviews are specifically used to develop in-depth understandings
on the emergence (Chapter 4) and coevolution (Chapter 5) concepts and NKC model
(Chapter 6) and their use in IS studies in particular.
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 83
Chapter 4: An Emergence Perspective on IT-enabled Capabilities
Chapter 4 Summary
What was done in the previous chapter: The previous chapter presents an
in-depth structured literature review of CAS theory in IS discipline.
What this chapter does: This chapter presents a complex emergence
perspective on IT-enabled capabilities. It highlights how IT-enabled capabilities
emerge dynamic and non-linear way from the interactions between IT assets and
organisational resources.
What is still outstanding in later chapters:
Chapter 5: A coevolutionary perspective of IT-enabled capabilities and how
it influences competitive advantage.
Chapter 6: An operational (NKC) coevolutionary model of IT-enabled
capabilities.
Chapter 7: A CAS based framework on competitive advantage and a
discussion on the overall insights that I have developed in relation to BVIT.
4.1 INTRODUCTION
In this chapter, an emergence perspective of IT-enabled capabilities is discussed.
Based on the ideas of Nevo and Wade (2010) as a way of understanding IT-enabled
capabilities, this chapter will focus on first subset of the BVIT model presented in the
Figure 1.2 in Chapter 1. Nevo and Wade (2010) apply systems thinking (Ackoff, 1971)
together with RBV (Barney, 1991) to explore strategic potential of IT enabled
resources and their effect on competitive advantage in organisations. They have
adopted a systems thinking based emergence concept (Ackoff, 1971) that is simple and
84 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
linear (Goldstein, 1999; Halley & Winkler, 2008) and considered IT assets and
organisational resources as stable and the outcome of their interactions give rise to the
intended IT enabled resources, which leads to an equilibrium situation. However,
prominent IS scholars (e.g. El Sawy, 2003; El Sawy, et al., 2010; El Sawy & Pavlou,
2008; Tanriverdi, et al., 2010) argue differently and suggest that in contemporary
organisations, IT assets, organisational resources, capabilities and competencies are
continuously changing and thus their interactions need to be considered as dynamic
and non-equilibrium in nature (Merali, et al., 2012). These IS scholars further suggest
to adopt holistic and systemic approaches to understand such dynamic and non-linear
interactions.
Consequently, in this study, I have taken a dynamic and non-linear view as
suggested by the prominent IS scholars. In particular, I have proposed a CAS theory
based emergence (complex emergence) perspective (Goldstein, 1999) to study how
IT-enabled capabilities emerge from the interactions between IT assets and
organisational resources. I have adopted a complex emergence perspective as it
conceives a non-linear and dynamic view of the phenomenon under study (Goldstein,
1996; Halley & Winkler, 2008). In addition, I have adopted Nevo and Wade (2010)
model to explain the two concepts, IT assets and organisational resources. The
complex emergence lens is applied into the first subset of the generic BVIT framework
presented in the Figure 1.2 in Chapter 1 (Figure 4.1). The research subquestion for this
study is-
Research subquestion 1.1: How do IT-enabled capabilities emerge?
Figure 4.1 A Subset of the BVIT framework (Figure 1.2 in Chapter 1)
IT-enabled Capabilities
• IT Assets
• OrganisationalResources
Competitive Advantage
Emergence
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 85
Using Shepherd and Suddaby (2017) ideas on theory development, I have
developed my research method for this study. A broad discussion of the overall
research method is discussed in Figure 1.4 in the Chapter 1. For this chapter, a subset
of the research method, specifically focused on emergence is applied as shown in
Figure 4.2.
In brief, the research method includes-
1. The narrative conflict: As described in section 1.5.1 in the Chapter 1, the
overarching narrative conflict of this study is the tension between the existing
literature on BVIT and the conceptualisation of BVIT. I provide a more
specific example in relation to ERP system (IT assets) and emergence of IT-
enabled capabilities, which highlights that adoption of a new feature triggers
new IT-enabled capabilities (e.g. ERP-enabled logistics management) that
further triggers other IT-enabled capabilities (e.g. ERP-enabled production
management> purchase management> sales order management and so on).
However, current IS literature conceives that such phenomenon occurs in a
linear way, but there are chains of phenomena occur because of the new feature
adoption in ERP system (as discussed in more detail below). So, the narrative
conflict for this chapter is the tension between the existing literature on
emergence, whether emergence is linear or non-linear (dynamic) and the
conceptualisation of such emergence.
2. Building stories: It involves four stages-
o Identifying core constructs: Three major constructs are defined for this
chapter- IT assets, organisational resources and IT-enabled capabilities.
They are broadly discussed in section 2.3 in Chapter 2.
o Determine the narrative settings: For this study a shifting ontology
strategy is adopted to determine the narrative settings. In this chapter,
shifting ontology highlights the change from a static, linear view to a
dynamic, non-linear view on the complex emergence of IT-enabled
capabilities.
o Draw boundary conditions- The story’s event sequence: The event
sequence here is- first, IT assets and organisational resources interact
in a dynamic and non-linear way and second, their interactions give rise
86 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
to the IT-enabled capabilities, which can be unpredictable. This is
briefly discussed in the first paragraph of this section.
o Apply disciplined imagination- theorising via metaphors (analogical
reasoning): In this chapter, complex emergence metaphor of CAS
theory is applied to describe how IT-enabled capabilities emerge from
the interactions between IT assets and organisational resources. The
complex emergence theorising of the IT-enabled capabilities is broadly
discussed in section 4.4.
3. New insights: The application of complex emergence perspective gives new
insights in relation to the dynamic rise of IT-enabled capabilities. The theories
developed using CAS complex emergence are explanatory type theories
(Gregor, 2006) as they help to provide greater explanations on how IT-enabled
capabilities dynamically emerge from lower level interactions of IT assets and
organisational resources. Few propositions are proposed in this phase. I have
also internally validated the proposed propositions using an exemplary case
narrative as first. In section 4.4.2, the narrative has established an internal
validity of the proposed complex emergence framework as it helps to provide
a good understanding of the dynamics of underlying relationships that is ‘why’
and ‘how’ the emergence phenomenon is happening (Eisenhardt, 1989). It is
important to note that, the internal validation using the case study is a first step
of the validation process.
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 87
Figure 4.2 A Subset of Research Method (see Figure 1.3 in Chapter 1)
Nevo
& W
ade
(2010
)Sim
ple
Emerg
ence
1.Th
e Nar
rativ
e Co
nflic
t2.
Build
ing st
ories
2.Bu
lding
Stor
ies: D
raw
boun
dary
cond
itions
&
apply
Disc
ipline
d Im
agnia
tion
via C
ASme
tapho
r
Comp
lex
Emerg
ence
New
Insig
hts:
-Com
plexe
merge
nce
of IT
enab
led
capa
bilitie
s
Core
BV
IT
mode
l
3. Ne
wIn
sight
s (Th
eory
) an
d Eva
luatio
n
Exist
ingTh
eory
Re-d
esign
edTh
eory
Analo
gical
Reas
oning
via
CAS T
heor
y
Static
& L
inear
Dyna
mic a
nd
comp
lex
How
do IT
en
abled
ca
pabil
ities
em
erge?
88 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
To exemplify the narrative conflict in relation the tension between the existing
literature on BVIT and the conceptualisation of BVIT (section 1.5.1), I use enterprise
resource planning (ERP) system as an example. ERP system is a customisable and
standard application software that integrates core business processes within and across
functional areas in an organisation The ERP solution provides capabilities that ensure
customers business needs and can adapt with the changing needs dynamically so as to
provide the services and products for their customers efficiently. Although emerging
research have focused on understanding the factors and their role in contributing to
ERP system benefits (Seddon, Calvert, & Yang, 2010; Staehr, Shanks, & Seddon,
2012) from a linear point of view, little work has been done from a dynamic point of
view to gain deeper understanding on the process that contributes to the business value
i.e. the conceptualisation of BVIT requires rethinking from dynamic viewpoint. As a
first step, in this chapter, I have adopted CAS emergence concept to conceptualise the
dynamic process of emergent IT-enabled capabilities. The narrative conflict here is
that the existing literature argues that IT-enabled capabilities emerge in a linear way
(Nevo & Wade, 2010). However, in real world, the IT assets and organisational
resources are continuously changing and thus it impacts the emergent rise of the IT-
enabled capabilities and makes it dynamic. For instance, adopting the ERP system,
such as, Epicor in inventory management triggers improved logistics, which further
triggers better production management via Epicor. The improved production
management provided by Epicor may also improve better purchase management,
which may further improve sales order and quote management. This example shows
that adoption of ERP (IT system) improves better logistic management (IT-enabled
capabilities), which further may improve production management, and then, purchase
management and so on. It reflects the emergent nature of IT-enabled capabilities in
ERP system in contemporary organisations, which requires re-conceptualisation from
a dynamic perspective. Therefore, the narrative conflict in this chapter is the tension
between the existing literature on emergence, whether emergence is linear or non-
linear (dynamic) and the conceptualisation of such emergence. It is important note that,
emergence phenomenon can also conceptualised as being simple and linear such as,
Nevo and Wade (2010) did in their study on the emergence of IT enabled resources
and its’ impact on the competitive advantage. However, in this study, I have only
focused on the non-linear type of emergence in contemporary organisations and this
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 89
conceptualisation is also consistent in the ERP system example that I have used as a
narrative conflict in this chapter.
The rest of the chapter is as follows- first, section 4.2 presents an overall
overview of the emergence concept and its applications in IS and broader
organisational studies. The next section 4.3 provides a recap of Nevo and Wade (2010)
model of BVIT and addresses the complex emergence concept of CAS and highlights
the enabling conditions related to it. The following section 4.4 presents a complex
emergence model of IT-enabled capabilities and the chapter concludes (section 4.5)
with a chapter summary.
4.2 OVERVIEW OF EMERGENCE
This section presents an overview of the concept of emergence , firstly . in
relation to CAS studies. Then it briefly highlights the typologies of emergence with
the emphasis on complex emergence. Finally, a review is presented of the use of the
emergence concept in CAS studies across IS and the organisational research domain.
4.2.1 The Basics of Emergence
The term ‘emergent’ (and by extension ‘emergence’) was coined in 1875 by the
philosopher Lewes (1875) to discuss on the changing nature of causality. Since then,
the idea has been proposed as a supplement to Darwin’s selection theory to describe
the mechanistic and incremental view of evolution (Goldstein, 2011). Emergence is
broadly defined as “coming into being of qualitative novelty” (Bunge, 2003), with the
view that a whole is formed from the interactions of parts. Casti defines emergence as
“the way the interactions among system components generates unexpected global
system properties not present in any of the subsystems taken individually” (Casti, 1997,
p. 91).
Emergence has been a central phenomenon in many studies that are concerned
with CAS (Goldstein, 2011), self-organization (Nan & Lu, 2014), and the origins of
novel entities, properties, or processes (Bunge, 2003). The notion of a “whole before
the parts” can be traced back to Aristotle (Hovorka, 2013), but the modern conception
of the dynamic perspective of emergence is credited to philosopher G. H. Lewes
(Goldstein, 1999). In the dynamic emergent perspective, emergence is broadly
concerned with the properties of dynamic systems that arise from interactions of the
parts but cannot be predicted from the properties of those parts (Casti, 1997).
90 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
Emergence phenomena are characteristic of complex adaptive systems (CAS)
(Mitleton-Kelly, 2003b). The concept of emergence in CAS has very diverse scientific
and mathematical roots: cybernetics, solid state/ condensed matter physics,
evolutionary biology, artificial intelligence, artificial life, etc. There are four major
school of thoughts that influence the way emergence is studied:
1. Complex adaptive systems theory; research conducted by Santa Fe Institute
researchers which explicitly uses the concept of emergence to define macro-
level properties arising from interacting agents (Weisbuch & Ryckebusch,
1991).
2. Nonlinear dynamical systems theory and Chaos theory; both theories use a
the concept of ‘attractor’, a special behaviour to which system evolves and one
kind of attractor is called strange attractor (Young, 1991), which is classified
as an emergent phenomenon (Goldstein, 1996; Young, 1991).
3. The synergetics school, which focuses primarily on emergence related to
physical systems. They used an order parameter that highlights which macro
level phenomena a system exhibits (Haken, 1977).
4. Far-from-equilibrium thermodynamics; The studies in thermo-dynamics
by Prigogine and his colleagues refer to emergent phenomena as dissipative
structure, arising from far from equilibrium conditions (Nicolis, Prigogine, &
Nocolis, 1989; Prigogine, 1984; Stengers & Prigogine, 1997).
In summary, the emergence concept refers to two important aspects: a global
behaviour or pattern firstly, that arises from the interactions of local elements and
secondly that cannot be traced back to the individual elements (Bunge, 2003; De Wolf
& Holvoet, 2004).
4.2.2 Typologies of Emergence
Studies of different types of emergence can be found in a IS and organisational
studies related literature. All these types of emergence share the similar conception
that novel structure or properties or behaviours arise at high level from as a result of
interactions in constituent components at lower level (Bunge, 2003; Goldstein, 2000).
However, researchers differentiate types of emergence based on the emphasis on
research focus and context. Goldstein (2011) derives a set of six prototypical
conceptualisations on emergence- phase transition, self-organising physical systems,
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 91
mathematical, computational, social and biological emergence. Lichtenstein and
McKelvey (2011) develop a typology that defines four increasingly demanding
definitions of emergence, and use this typology to organise a review of the complexity
literature, focusing on computational models that have been utilised by management
scholars (Burt, 1992; Mintzberg & McHugh, 1985; Wasserman, 1994). Moreover, Hovorka
(2013) defines three forms of emergence and provide both research exemplars and a
framework for categorizing emergent phenomena to better articulate and refine how
researchers understand emergent phenomena in Information Systems. Table 4.1
summarises the above-mentioned conceptualisations and typologies.
Authors Typologies of Emergence
Goldstein (2011) identified at least six prototypes on emergence with the emphasis on the research into the emergence phenomenon in complex systems.
1. Phase transitions, e.g. symmetry breaking (Anderson, 1972), change of orders, (Holland & Mallot, 1998), reformalisation of groups and criticalisation (Mckelvey, et al., 2013). 2. Self-organising physical systems, where dissipative structure exists (Nicolis, et al., 1989); far from equilibrium conditions (Meyer, et al., 2005) and self-organisation (Ashby, 1968). 3. Mathematical emergence, e.g. nonlinearity; phase space (Morel & Ramanujam, 1999); bifurcations; attractors; and chaos (Gleick & Berry, 1987).
4. Computational emergence, e.g. neural network (Holland & Mallot, 1998), artificial intelligence, game of life (Sigmund, 1994) and computational mechanics. 5. Social emergence, e.g. social networks (Nan & Lu, 2014), cooperation (Sawyer, 2005), system usage (Nan, 2011).
6. Biological emergence, e.g. new species, morphogenesis; symbiogenesis; and hierarchical constructions (Kauffman, 1995a; Kauffman, 1993).
92 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
Lichtenstein and McKelvey (2011) classify four types of emergence according to heuristics developed by philosophers focusing on exploring nature and properties of emergence.
7. Type 1- emergent network; explanations of collective actions of social structure, such as, social network emergence (Burt, 1992; Wasserman, 1994).
8. Type 2- emergent hierarchies; an emergent property or structure is defined as ‘different in kind’ from its components, e.g. emergent strategy formation (Mintzberg & McHugh, 1985).
9. Type 3- emergent causalities. Upward effects that cause interactions between system components to constitute higher structures including the non-linear effects that the emergent structures may have on its components. It depicts coevolutionary causal effects both ways bottom-up and top down. Studies related to institutional emergence, such as, where scholars examine how macro-level (institutional) structures supervene on micro-level (individual) behaviour (Contractor et al., 2000). 10. Type 4- emergent purposeful CAS. it combines type 2 and type 3 emergence together. It combines purposefulness and multiple causal cycles which makes this emergence non-linear, e.g. (Siggelkow, 2002) study on Vanguard group, which includes multiple coevolving causalities such as material, final, formal and efficient across multiple levels.
Hovorka (2013) develops a framework highlighting two major types of emergence in IS research.
1. Simple emergence - properties of the whole can be predicted by knowing the properties of the parts.
o Perceptual emergence (internal)- something that was obscured becomes visible to the researchers. o Associative emergence (external)- parts are aggregated such that the properties of the whole can be predicted by analysing the properties of the constituent parts (e.g. Burton-Jones & Straub Jr, 2006).
2. Complex emergence- Properties of the whole are distinct from its constituent components.
o Emergence as process- Focuses on patterns, timing, and intensity of interactions of constituent parts. Interactions may be planned or unplanned (e.g. Nan, 2011). o Constituent parts are combined or fused such that the properties of the whole are distinct from the properties of the parts, and the parts themselves are transformed (e.g. Nevo & Wade, 2010).
Table 4.1 Typologies of Emergence
Based on the above discussion, it is evident that extant literature on complexity
science, IT and organisational studies provide different typologies of emergence with
common understanding that novel properties arise from the interactions between lower
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 93
level components. Though the emergence concept has been used across different
disciplines and various typologies have been suggested, still it shares some common
characteristics, such as, macro level properties from micro level interactions,
unpredictability, and dynamical in the sense of coming to be over time (Goldstein,
1999).
However, this study particularly focuses on the emergence of IT-enabled
capabilities based on the ideas of the Nevo and Wade (2010) study on IT enabled
resources and their strategic contribution to competitive advantage. I have proposed
that the authors’ ideas about exploring the emergence of IT enabled resources and
synergistic capabilities are largely linear (Simple emergence) as they scarcely consider
the changes in IT assets and organisational resources from which the IT enabled
resources appear. Consequently, I have proposed a dynamic lens, in particular a
complex emergence perspective that considers the dynamic and continuous changes in
the components of IT assets and organisational resources which together give rise to
the emergent IT-enabled capabilities. Therefore, I have considered simple vs. complex
emergence and adopted a complex emergence perspective in the context of IT-enabled
capabilities. The following section briefly discusses the differences between simple
vs. complex emergence in relation to IS and organisational research.
4.2.3 The Use of Emergence in IS and Organisational Research
Emergence has been used in disciplines ranging from biology to physics and
organizational studies to Information Systems (IS). The emergence concept has gained
popularity in IS recently to understand novel phenomena where technologies,
business, and organisations are all interacting within business ecosystem (El Sawy, et
al., 2010). It has been used along with resource based view theory to explore how
synergies from IT enabled resources positively influence competitive advantage in
organisations (Nevo & Wade, 2011; Nevo & Wade, 2010). The applications and
contributions derived using emergence concept in IS research have been broadly
discussed in Chapter 3. Here, I have focused on different emergence models and their
use in extant research, whereas the Chapter 3 focuses only contributions derived using
emergence concept in IS research. Emergence is an important construct in studies of
organizational dynamics and leadership in particular (e.g. Benbasat, Goldstein, &
Mead, 1987; Chiles, et al., 2004; Goldstein, 1996; Lichtenstein & McKelvey, 2011;
MacIntosh & MacLean, 1999). Lichtenstein, et al. (2006) use emergence via time
94 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
series analysis along with multi-level longitudinal analysis in the context of
organisations.
One of the dominant models of emergence, the dissipative structure model
(Prigogine, 1984; Stengers & Prigogine, 1997) of emergence has widely used in
organisational studies. For instance, the Chiles, et al. (2004) study on music theatre
which adopts the dissipative structure model of emergence, reveals that the sundries
related to country music have been attracting over 6 million visitors annually to the
town of Branson, Missouri. This collective behaviour has arisen without any
centralised hierarchical guiding facility; it appears in a self-organised way.
Following Chiles, et al. (2004), Lichtenstein and Plowman (2009) use the ideas
of emergence in leadership and identify four conditions of emergence, the
disequilibrium state, amplifying actions, self-organisation and stabilising feedback.
The studies by Chiles, et al. (2004), Lichtenstein and Plowman (2009) and Lichtenstein
and McKelvey (2011), show that they understand emergence as involving self-
organising logic or process, entailing a combined set of configurations that are neither
planned nor created through human design (Chiles, et al., 2004).
In fact, the majority of organisational scholars holds the similar view that self-
organisation processes are related to the emergence concept (Goldstein, 2011). Self-
organisation processes appear spontaneously when command and control mechanisms
are relaxed or absent. Such a perspective suggests a passive leadership style in self-
organised based emergence (Goldstein, 2011). Goldstein (2011) has suggested to
consider self-organising logic in emergence model recognisable in majority of
complexity-based research related to emergence for better constructional operations.
Based on the self-organising logic, emergence can be classified into two high
level categories (Table 4.1) (Halley & Winkler, 2008; Hovorka, 2013)-
Simple emergence
The emergent phenomena whose properties are close to linear and relatively
predictable from the constituent components. The model properties can be modelled and
can be predicted from the interactions of components. For instance, Nevo and Wade
(2010) discuss the emergence of IT enabled resources (e.g. IT enabled customer
service), which are combinations of IT assets (e.g. IT systems, IT people) and
organisational resources (department, unit, business processes). The properties of IT
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 95
enabled customer service can be predictable, such as, fast/slow response to customer
inquiries.
Complex emergence
The emergent phenomena might exhibit non-linear behaviour and are often
unpredictable. The emergent order tends to remain in a far from equilibrium region
containing self-organised logic in more than a level in lower level from where the order
emerges (Goldstein, 1996). For instance, in Orlikowski (1996) study on organisational
transformation, she identified that different organisational practices of actors such as,
leadership emerges in a way in relation to contingencies, breakdowns or opportunities
and any unintended consequences, that is, in an unpredictable way. Although the
combinations of parts, e.g. actors’ actions or decisions can be understood, the trajectory
of situated change was not predictable by knowing the characteristics of the technology
or the work practices.
The key differences between simple and complex emergence lie in a few important
characteristics. Simple emergence is largely linear and the emergent patterns stay close
to an equilibrium state, while complex emergence produces novel patterns in a region
which is far from equilibrium state, a region between stability and instability, the edge
of chaos (Waldrop, 1992). The complex emergence gives rise to unpredictable patterns
because of complex causality. Complex causality refers to the ambiguity concerning the
nature of the causal connections between actions and results (Lippman & Rumelt, 1982).
The emergent patterns might not be as expected from the interactions in constituent
components is lower levels. The simple emergence is similar to the ‘Simple’ or ‘Known’
domain of Cynefin framework (Snowden, 2002), in which the relationship between
causes and effect is pretty obvious. In a similar way, complex emergence refers to the
‘Complex’ Cynefin domain, in which the relationship between cause and effect can be
perceived in retrospect, but not in advance. For instance, the use of new incident tracking
support system (ITSS) has improved the rate of resolving incidents, which was an
expected outcome for Zeta (Orlikowski, 1996). To understand complex emergence,
suppose, ITSS is a cloud based modular ERP and a series of new modules, such as, sales
and marketing, inventory, finance modules are introduced in the system, the expected
benefits may vary due to the various dynamics, such as, IT maturity, organisational
learning, organisational innovation, change management (Teo, 2017).
96 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
The following Table 4.2 summarises the differences in properties of simple and
complex emergence based on Halley and Winkler (2008), Goldstein (1996) and
Hovorka (2013)-
Characteristics Simple emergence Complex emergence
Type of systems Simple system Complex system
Linearity Largely linear Non-linear
Equilibrium state Close to
Equilibrium
Far from Equilibrium
Self-organisation No Yes
Predictability of
properties
Yes No
Causality Simple Complex
Table 4.2 Simple vs Complex Emergence
Based on the above discussion of complex emergence and following Nevo and
Wade (2010) ideas on the emergence of IT enabled resources (Chapter 2), this study
argues that the creation of IT-enabled capabilities from the interaction of IT assets and
organisational resources is non-linear and has largely exhibit unpredictable properties.
Therefore, the complex emergence perspective is adopted following Halley and
Winkler (2008), Goldstein (1996) and Hovorka (2013) to provide insights into the
dynamic side of the emergence of IT-enabled capabilities.
It is very important to note that, this study does not disregard the existence of
simple emergence of IT-enabled capabilities such as Nevo and Wade (2010) did in
their study on the emergence of IT-enabled capabilities. The authors only focused on
the simple emergence of IT-enabled resources in organisations and they have
acknowledged that their study intuitively contribute to the discussion on dynamic type
of resources as raised by other IS researchers (Wade & Hulland, 2004). In a similar
way, in this chapter, I have narrowed down my focus only on the complex emergence
of the IT-enabled capabilities. I have acknowledged that the emergence of IT-enabled
capabilities scenario may also contain simple emergence, which can be dealt with
generic systems view point as the way Nevo and Wade (2010) did in their study.
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 97
4.3 RECAP OF NEVO AND WADE (2010) MODEL
The Nevo and Wade (2010) model is broadly discussed in the Chapter 2 (see
Figure 4.3). In brief, they have argued that IT assets derive their strategic potential via
interacting with commodity type organisational resources and influence competitive
advantage. They propose that when the components of IT assets and organisational
resources are compatible, and managers support (‘integration effort’) the interactions,
then IT enabled resources and their emergent capabilities emerge as a result. The
compatibility between IT assets and organisational resources and support from
managers, which is termed ‘integration effort’ are the two key enabling conditions of
the emergence of IT enabled resources.
This study proposes that the emergence of IT-enabled capabilities from the
interactions of IT assets and organisational resources are non-linear. It is non-linear
and dynamic because the components of IT assets and organisational resources are
always changing, and they give rise to IT-enabled capabilities, which are sometimes
unpredictable in nature. Therefore, I propose to adopt complex emergence lens to
explore the dynamic emergence of IT-enabled capabilities.
Figure 4.3 (Nevo & Wade, 2010) Model on Competitive Advantage
In this study, to understand the complex emergence of IT-enabled capabilities-
o I have adopted similar ideas suggested by Nevo and Wade (2010), i.e. the
compatibility condition as an enabling condition that ensures the interactions
between IT assets and organisational resources. However, I have replaced the
integration effort condition with self-organised management, as ’integration
effort’ is planned and it is considered to be prone to command-control
Organisational Resources
IT Assets
Compatibility
Integration effort
Value
Rarity
Non-subsitutability
Inimitability
Rea
lised
Syn
ergy
Sust
ainb
le C
ompe
tetit
ive A
dvan
tage
Systems TheoryResource
Based View
98 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
mechanism (Goldstein, 2011). The self-organised management condition is
neither planned not controlled through human design and supports the non-
linear emergence of IT-enabled capabilities. The two enabling conditions are
broadly discussed in the next section.
o I have applied the complex emergence concept to understand the emergence of
IT enabled capabilities and the dynamics related to it. In particular, I have
followed Goldstein (2011) ideas of self-organising, logic based complex
emergence in the context of IT-enabled capabilities.
The next section provides a broader overview of the adoption of the complex
emergence concept in the context of IT-enabled capabilities.
4.3.1 Adoption of Complex Emergence in IT-enabled Capabilities Context
As discussed in the previous section, complex emergence involves complex
causality that refers that the causal connections between actions and outcomes are not
same, they can be non-deterministic (Goldstein, 2011; Lippman & Rumelt, 1982).
Consistent with this logic, I have proposed that complex causality logic needs to be
considered while exploring IT-enabled capabilities via the complex emergence lens,
as the resultant capabilities might not be as expected.
The two enabling conditions and the complex causality logic are briefly
discussed below-
Compatibility between IT assets and Organisational Resources
To interact between each other and to develop synergistic relationships,
components need to be compatible with each other (Singh, 1997). Compatibility
between two components is defined as “an assessment of the ability of a system’s
components to interact—that is, form a relationship; it is not an assessment of the
outcome of the interaction” (Nevo & Wade, 2010). Compatibility must exist between
IT assets and the organisational resources with which they are combined (Markus &
Robey, 1988). Orlikowski (1996) case study on the Zeta corporation reflects the notion
of compatibility in the context of new incident tracking system software (ITSS) and
the customer service department (CSD). The ITSS software is developed in a way that
it is compatible with operational and business requirements of the CSD. The
compatibility notion is inherent in alignment literature (Peppard & Breu, 2003), in
which IT and business elements need to be aligned. Moreover, the compatibility
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 99
condition has been recognised as an essential factor in building synergistic
relationships between multiple components in different circumstance (Sarkar,
Echambadi, Cavusgil, & Aulakh, 2001). In summary, once the IT assets and
organisational resources are compatible, they interact and their interactions give rise
to IT-enabled capabilities. As the components of the IT assets and organisational
resources are continuously changing, this can be theorised using the complex
emergence perspective as it acknowledges implicit dynamic changes in the constituent
components (Halley & Winkler, 2008).
Self-organised Management
“Self-organization is the ability of interconnected autonomous agents of a
complex adaptive system to evolve into an organized form without external force”-
(Vidgen & Wang, 2009). Agents are autonomous because they can intervene in the
status of the environment and take appropriate actions from the perceptions of
environment (Mitleton-Kelly, 2003b). In the context of agile management, for
instance, self-organisation refers to the spontaneous formation of a group to achieve
some goals; the group members decide within themselves what to do, how to do it,
assess the context of dynamics and initiate proper actions based on their consciousness
of the environment (Vidgen & Wang, 2009).
From the traditional systems perspective, management is largely planned-driven
and more prone to control-command; it is considered as a mechanism for transforming
the organisation’s numerous parts into an organized whole in order to organise
unrelated and unused components in a manner that can accomplish more goals
(Johnson, Kast, & Rosenzweig, 1964). The integration effort condition in Nevo and
Wade (2010) BVIT model highlights the role of management in estimating a
relationship between IT assets and organisational resources that is congruent with
organisation goals.
This study argues that ‘integration effort’ is planned driven and controlled by
traditional managerial practices, following a traditional leadership style (Goldstein,
2011) and proposes that the emergence of IT-enabled capabilities is facilitated by self-
organisation logic, which is neither planned, controlled nor created through human
designs and composed of a set of ‘hodgepodge’ configurations (Chiles, et al., 2004).
Self-organisation signifies a departure from the traditional command and control
philosophy driven by hierarchical bureaucratic organizations Anderson (1999);
100 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
Volberda and Lewin (2003). Goldstein (2011) refers to such a perspective, as a
“laissez-faire” or passive leadership style.
Researchers have acknowledged that it is difficult to predict emergent order in
complex adaptive organisations (Anderson, 1999). Thus, this study proposes a new
condition, which is termed as, ‘self-organised management’ that is characterised as
spontaneous, dynamic and relaxed, all of which support dynamic emergence of IT-
enabled capabilities. It works as relaxed and flexible management practices that
facilitate the dynamic changes in IT assets and organisational resources and the related
emergent IT-enabled capabilities. The idea of self-organised management is widely
used in agile development, where it is widely referred as self-organisation and
considered as truly emergent management practices that arises depending on situations
(Vidgen & Wang, 2006b, 2009; Wang & Vidgen, 2007). I have adopted a similar idea
of the self-organisation here, but termed as self-organised management in this research
context. The underlying assumption entails, while IT assets and organisational
resources change continuously, the emergent IT-enabled capabilities also change with
them and self-organised management serves as a catalyst providing necessary support
for the interactions to occur.
Accordingly, self-organised management is different from the traditional
integration effort that is deliberately decided, it dynamically adjusts in a way that
provides necessary conditions for the dynamic interactions between IT assets and
organisational resources (Stacey, 2003). For the purpose of this study, self-organised
management is defined as flexible and spontaneous managerial practices that support
and guide the dynamic relationships between IT assets and organisational resources
following Stacey (2003).
Complex Causality
The complex emergent phenomena involves unpredictability that is caused by
disruptions in the chain of cause and effect in the component relationships (Goldstein,
1996). Stacey (1996) addresses this particular phenomenon and argues that emergence
in complex systems indeed demands complex causality. In fact, the causal explanation
in complex systems is indeed problematic, though Goldstein (1996) argues that the
unpredictability might not be the only reason behind this problem; the emergent
phenomenon itself might be responsible for the causal ambiguity because a radically
new pattern arises due to the emergent phenomenon. Regarding the relationship
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 101
between unpredictability and the unique outcome that is due to the emergence, it can
be argued that this unpredictability comes from the way emergence can incorporate
randomness into the formation of totally new order (Stacey, 1996). According to
Nicolis (1989), a system under the influence of randomness within an unpredictable
environment may create a temporary emergent structure (complex emergence) for a
small period of time.
Therefore, complex emergent phenomena seem to violate the conventional
notion of causality, whereby something new and completely different emerges from
the causal chain (Goldstein, 1996). This study follows that complex emergence
involves complex causality which refers to a particular ontological specification, a
different understanding of causality than traditional approaches to explore cause and
it also includes a unforeseeable outcomes (Byrne, 2005; Byrne, 2011). Because,
according to Bunge (2003), linear causality (traditional) remains trapped in the chain
between cause and effect, where complex causality can direct the emergent phenomena
in multiple directions. For the purpose of the study, complex causality is defined as,
the causality concerning the emergence of unpredictable outcomes from the results of
interactions between components of the IT assets and organisational resource
following Lippman and Rumelt (1982). Further, I have assumed that as the outcomes
of certain contexts are unforeseen, decision makes intervene (self-organised
management), investigate while making necessary adjustments based on semi
structures and simple rules (Snowden, 2002), which are discussed in section 4.3.3.
The preceding discussion addresses two enabling conditions compatibility and
self-organised management and complex causality logic that facilitate complex
emergence of IT-enabled capabilities. However, Goldstein (2011) suggests that the
emergence concept contains few ‘folklores’- myths, which must be addressed before
applying it in organisational context. The next section highlights these folklores.
4.3.2 Folklores related to Emergence
One of the renowned scholars in complexity research Goldstein (2000) has
argued that the notion that emergence contains conceptual snares and ambiguous
threads is derived from misinterpretations. He advocates that these ‘folklores’ must
be addressed before applying complexity theory in organisational contexts. This
section first briefly discusses the folklores.
102 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
The four folklores addressed by Goldstein (2000) are-
1. Complexity arises suddenly from simplicity: This folklore concerns that
complexity can manifest as an emergent and random dynamic phenomenon
spontaneously and suddenly from very much simpler dynamics. This
interpretation is quite similar to the mathematical ‘chaos’ theory (Prigogine,
1984), where technical chaos is considered as an unpredictable emergent
phenomenon raised through simple mathematical equation. Such a sudden and
unpredictable outcome from the interactions of system components however
does not mean novelty arises without any cause (Goldstein, 1999). Looking
closely at the system reveals some intermediary phases, which can be explained
by the dissipative structure model of a Bérnard cell (Nicolis, et al., 1989;
Prigogine, 1984; Stengers & Prigogine, 1997). In brief, while many complexity
scholars argue that complexity arises from suddenly from simplicity (e.g.
Kauffman, 1993), this may not always be the case and complexity may rise
from intermediary complexifying operations, such as bifurcation point
(Prigogine, 1984).
2. Order for free: The emergence of a new form or structure in complex adaptive
systems is thought to obtain new order without any pre-set design rules
(Kauffman, 1995a). Kauffman (1993) in his book of ‘Origins of Order: Self-
Organization and Selection’ argues that Darwinian natural selection is a “single
singular force” that is inadequate to identify, stress and incorporate the
possibility that emergence in a complex adaptive system (CAS) exhibits order
spontaneously. He claims that the spontaneous order in the CAS occurs through
a self-organised emergent process. Emergent patterns and properties arise from
the interactions of system elements and are greater than the sum of their parts
and it is difficult predict the emergent nature by investigating individual
elements. Emergence is the process that creates new order together with self-
organisation (Kauffman, 1993). In summary, Goldstein argues against the
many scholars who consider that orders are free (e.g. Kauffman, 1993) thus,
there is a necessity to understand what enables orders to be arose.
3. The edge of chaos: The edge of chaos is a zone between total order and
complete disorder. It is the zone in which a system shows bounded instability
because it shows stable and instable behaviours at the same time. It is assumed
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 103
to be stable, as the system shows emergent patterns. It is called unstable at the
same time, as the system’s future state is unpredictable- the system is far from
equilibrium condition (Anderson, 1999). Burgelman and Grove (2007) also
observe that there is order in chaos and chaos in order. The new order consists
of agents’ attributes that impose tension which causes emergent of the new
order. Agents creates the ordered region through self-organising processes
(Morel & Ramanujam, 1999). Cramer (1993) refers to the region as critical
complexity. Systems on the edge of chaos tend to change, adapt and self-
organise constantly to create new configurations with the ever changing
business environment (Goodwin, 1997). The edge of chaos is considered as a
sweet-spot between order and chaos as the system can self-organise
spontaneously to keep itself in an ordered state, though it changes frequently.
4. Emergence only takes place through self-organisation: The ‘self-organisation’
folklore is very similar to folklore ‘order for free’. However, order for free as
discussed in point 2 to the situation in which emergent order from the
interactions of components is thought of as free, it’s an outcome (Weiss, 1987).
Self-organisation is the process that creates emergence out of the order (De
Wolf & Holvoet, 2004). The close association of the concepts of emergence
and self-organisation in CAS come from the physical and life sciences (Allen,
Maguire, & McKelvey, 2011). Prigogine’s work on dissipative structures in
molecules (Nicolis, et al., 1989), Haken’s articulation of synergistic (Haken,
1977), and Maturana and Varela’s concept of autopiesis (Varela, et al., 1973);
- all of these scholars are agreed upon the fact that self-organisation is not a
part of priori design, rather it emerges as an outcome of interactions among a
system’s components. Self-organisation is thus a part of the emergent process
that connotes properties of CAS such as, unplanned and spontaneous situations
(Goldstein, 2011). Accordingly, Goldstein argues that whether emergence
always takes place through self-organisation process or any other
constructional operations are related to it, which he later on describes through
self-transcending constructions (Goldstein, 2000).
Given that Goldstein (2000) makes clear that complex emergence phenomena do
not happen spontaneously, it is necessary to understand what enables complex
emergence to take place. Goldstein (2005) proposes an alternative conceptual
104 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
explanation self-transcending construction, that allows us to understand how emergent
order arises out of yet transcends the lower level antecedent substrate (Goldstein,
2011), other scholars in organisational studies propose the concept of ‘semi-structure’
(such as, Brown and Eisenhardt (1997)) and Eisenhardt and Sull (2001) discuss the
notion of ‘simple rules’ that may also help to explain how complex emergence takes
place. The folklores help to reduce confusions around the emergence concept and also
provide a way to establish the fact that self-organisation is one of the enabling
conditions of complex emergence.
4.3.3 Enabling Conditions of Self-organised Complex Emergence
This section discusses the ideas of ‘semi-structures’ (Brown & Eisenhardt,
1997) and ‘simple rules’ (Eisenhardt & Sull, 2001) and how they can enable self-
organised based complex emergence. The proposed enabling conditions semi-
structures and simple rules together resolve the ambiguities in theorising complex
emergence.
Semi-structures
The first folklore discussed above debatable idea is that complexity arises
spontaneously and suddenly out of simple or random dynamics, which is similar to the
idea that emergent patterns arise from simple mathematical operations, referred to as
chaos (Young, 1991). An outcome via emergence that suddenly arises distinctively
from the constituent components does not necessarily mean that there are no
intermediary rules or operations or stages related to it. Complexity thought leaders
frequently mention intermediary operations, such as, bifurcation point, criticalisation,
iterative and recursive operations, and feedback processes. (Chiles, et al., 2004;
Goldstein, 1999; MacIntosh & MacLean, 1999; Prigogine, 1984). In a very similar
way, the second folklore is concerned that a focus on ‘order for free’ tends to neglect
the indispensable role of the ‘containers’ and other ‘constraining and constructional
operations’ involved in emergence, like the distance separating two neighbouring
currents is on the order of the vertical height of the container in a Bénard cell (Bergé,
Pomeau, & Vidal, 1986). The fourth folklore highlights the existence of self-
organisation in creating emergent order. In fact, the majority of the emergence
literature that talks about self-organisation, agrees that self-organisation and
emergence occur together (De Wolf & Holvoet, 2004).
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 105
From the above discussion it is clear that the emergence phenomenon involves
intermediary phases that gives rise to the emergent patterns or structures or behaviours,
which are acknowledged in complexity science related research (Holland & Mallot,
1998; Kauffman, 1993; Lissack, 1999; MacIntosh & MacLean, 1999). Moreover,
Kauffman (1993) view on emergence entails that emergence causes the patterns along
with self-organisation. Combining the above two ideas ensures that the emergence and
self-organisation are complement each other (De Wolf & Holvoet, 2004; Goldstein,
2011).
Based on the literature of emergence related to self-organisation, this study
acknowledges that the emergent phenomena involve at least four stages (Goldstein,
2011; Lichtenstein & Plowman, 2009),
1. Disequilibrium state- a period of disequilibrium that triggers the seeds of new
order (McKelvey, 2001) and pushes the system in to a highly dynamic state
(Anderson, 1999).
2. Positive feedback- in the disequilibrium state, small actions or events amplify
(Maruyama, 1963) similar events i.e. the emergence of one order amplifies the
likelihood of similar emergent order via positive feedback loop (Morel &
Ramanujam, 1999).
3. Recombination- in this stage, new correlation between existing components
arises; the systems comes into being in this stage (Lichtenstein, et al., 2006).
4. Stabilising feedback- coordinating mechanisms that stabilises the new
emergent order in this stage for maximum period of sustainability until next
emergence takes place (Chiles, et al., 2004).
This study adopts the view that to be able to change from one emergent order to
another one, the emergent orders must have a level of flexibility that ensures that they
can change from the existing order to the another one with relatively low chaos. To
emphasise this particular condition, this study adopts the idea of semi-structures by
(Brown & Eisenhardt, 1997) in relation to continuous change in complex system.
Semi-structures are defined as some prescribed or determined features such as
responsibilities, organisational goals, project deadlines, etc. of adaptive organizations
(Brown & Eisenhardt, 1997). The semi-structures support non-deterministic features
106 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
that arise from dynamic interactions between components of complex adaptive
systems (Brown & Eisenhardt, 1997; Goldstein, 1999).
The semi-structures facilitate the continuous emergence of orders by supporting
the level of flexibility required for continuous/frequent change. This ensures that the
design of a complex system is flexible so that it can accommodate the complex
emergence by avoiding any types of rigidity that hinders the emergence of IT-enabled
capabilities following the intermediary phases mentioned above. The semi-structures
contain some features, such as, time intervals, rules for coordinating sustainability of
emergent orders (discussed in the next paragraph) and recombination logic so that the
emergent orders can stay at the edge of chaos region (Goldstein, 1999). The concept
supports the intermediary stages of emergence so that it can exhibit frequently
changing patterns.
Simple rules
The above discussion argues that emergent order requires flexibility and semi-
structures are required to provide some predefined features that ensure the emergent
orders shift continuously from one existing state to another emergent state. However,
here I argue that the interim phases as acknowledged above follow to some extent
some rules that give rise to the emergent patterns, specifically complex emergence. In
this study, I propose that complex emergence follows simple rules (Eisenhardt & Sull,
2001; Kauffman, 1995a) that guide the emergent patterns in a direction without
confining complex emergence. The simple rules can be thought of as some non-rigid
(flexible) guidelines or schemas that direct complex emergent phenomena towards the
edge of chaos, between stable and non-stable regions meaning the emergent patterns
will be in a such state that a small change can trigger unintended changes. The simple
rules can be compared to heuristics (Cohen et al., 1996) that self-organised
management uses as guidelines and decision rules (Levy, 2000) along with the
predefined features (semi-structures) to facilitate the unpredictable complex
emergence of IT-enabled capabilities consistent with the organisational goals. Davis,
Eisenhardt, and Bingham (2009) use simulation to show that a simple rules strategy is
essential in unpredictable environments. Eisenhardt and Sull (2001) conjecture that
simple rules enable flexible, yet coherent capture of opportunities related to
organisational processes, such as, product development and internationalisation. Their
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 107
discussion of different simple rules (heuristics) includes boundary rules, how-to rules,
priority rules, timing rules and exit rules.
Kauffman (1995a) explains that the emergent pattern caused by the sensitivity
of small changes follows some rules, which might involve redundancies. Stacey (1996)
also conceives the similar ideas that the balance between canalisation and redundancy
in complex systems makes emergent patterns more robust in the face of turbulent
changes and guides them to operate at the edge of chaos. The use of simple rules in
directing organisational strategies to capture fleeting opportunities has been popular in
the strategic management literature (Brown & Eisenhardt, 1997; Eisenhardt & Sull,
2001; March, 1991). The simple rules work as implicit guidelines (Senge, 1990) or
coordinating mechanisms (Lichtenstein, 2004) so that the spontaneous fluctuations
towards new emergent order in complex emergence stays at the point of the edge of
chaos region (Waldrop, 1992). Combining the above views, for this study, simple rules
are defined as, organisational heuristics that work as guidelines and decision rules to
facilitate complex emergence of IT-enabled capabilities.
The following section discusses the complex emergence perspective in the
context of IT-enabled capabilities.
4.4 A COMPLEX EMERGENCE FRAMEWORK OF IT-ENABLED CAPABILITIES
This section adopts the complex emergence perspective to understand the
emergence of IT-enabled capabilities in contemporary organisations. Based on the
ideas of Nevo and Wade (2010), this study proposes that IT assets and organisational
resources interact together and their interactions give rise to IT-enabled capabilities
(Chapter 1). These interaction are dynamic, meaning that the components of IT assets
and organisational resources can be changed while they are interacting (Weisbuch &
Ryckebusch, 1991). As mentioned in section 4.2.3, in this study I have only focused
on the complex type of emergence. The simple emergence is not disregarded here, but
due to the research focus, the simple type of emergence is not included in the
framework. If a simple emergence becomes complex, decision makes intervene (self-
organised management), investigate while making necessary adjustments similar as
suggested by (Mitleton-Kelly, 2003b) in complexity study and in cynefin framework
(Snowden, 2002).
108 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
For example-an organisational resource such as a customer service department
(CSD) provides answers to the customer inquiries currently at a slow rate. However,
with the use of a customer retention management anaytics tool, e.g. saleforces.com (an
IT asset, SFC), resulting in a new relationship (SFC enabled CSD, IT-enabled
capability ), CSD can answer the inquiries at a high rate. Now, if any module, for
instance a Twitter channel is added to the saleforces.com SFC then that customers who
use Twitter can now inquire through salesforce.com (SFC) to the CSD. Due to this
added option, CSD needs to adapt to the new features of SFC which might trigger new
emergent capabilities, such as, Twitter focused advertising. In a similar way, any
requirement changes on the CSD side may influence SFC to change its options
accordingly, which also can cause new issues such as, system failure, low response
rate, etc. (Orlikowski, 1996). The proposed model refers to these type of instances as
emergent occurences as contemporary organisations are always changing which
provokes different dynamic events in the system .C onsequently the relationships
between IT assets and organisational resources are affected, which trigger further
changes in IT-enabled capabilities.
Figure 4.4 A complex emergence framework of IT-enabled capabilities
Figure 4.4 presents a complex emergence framework of IT-enabled capabilities,
where it emerges from the interactions between IT assets and organisational resources.
The intersected spheres indicate that IT assets and organisational resources are mostly
indistinguishable and it is difficult to separate them from each other (Bharadwaj, et al.,
2013; El Sawy, 2003; El Sawy, et al., 2010). The upward directed arrow from the
IT Assets OrganisationalResources
Complex Emergence
IT-enabled Capabilities
Semi-structures
Simple Rules
Self-organised Management
Compatibility
Enabling Conditions
Complex Causality
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 109
common zone of the sphere represents that the two entities involve in a relationship
that gives rise to IT-enabled capabilities. The figure also includes the enabling
conditions (in short phrases)- semi structures, simple rules, self-organised
management, complex causality and compatibility. The enabling conditions are highly
interrelated to each other and they enable the relationships between IT assets and
organisational resources, which in turn cause the rise of IT-enabled capabilities. In this
conceptual model, I have proposed that the emergence of IT-enabled capabilities is
actually complex in nature as the components of IT assets and organisational resources
are continuously changing and and these changes make the relationships between them
dynamic and non-linear. Therefore, complex emergence concept can be better suited
to describe this dynamic complex emergence of IT-enabled capabilities.
4.4.1 Enabling Conditions of Complex Emergent IT-enabled Capabilities
In the section 4.3.1, it was discussed that IT-enabled capabilities might not be
realised without the presence of enabling conditions. From the Nevo and Wade (2010)
study, I have adopted the compatibility condition - that the components of IT assets
must be compatible with organisational resources to give rise emergent IT-enabled
capabilities. However, I have proposed replacing the integration effort, as it is planned
driven and controlled by managerial hierarchy with a new enabling condition, self-
organised management, which refers to relaxed and flexible management practices
facilitating the dynamic changes in IT assets and organisational resources while they
are interacting. Combined with the enabling conditions of complex emergence from
section 4.3.3, I have proposed a complex emergence framework of IT-enabled
capabilities (Figure 1.3). The following sections build the theoretical case for the
framework, linking the enabling conditions with the complex emergence of IT-enabled
capabilities and a set of propositions is developed.
IT assets and Organizational Resources Compatibility
The complex emergence of IT-enabled capabilities depends on the mutual
compatibility between the components of IT assets and organisational resources
(Singh, 1997). The notion of compatibility can be seen in different forms across
various organisational studies. An early study for example by Markus and Robey
(1983) provided examples of compatibility between IT assets and organisational
processes. They deemed an inquiry system with a decentralised architecture to be
compatible with a department such as research and development characterised by non-
110 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
routine work. In a similar way, a centralised MIS with optimisation models was seen
as compatible with departments characterised by routine work processes. The
compatibility notion is inherent in alignment literature (Peppard & Breu, 2003), and
has been recognised as an essential factor in building synergistic relationships in
different circumstances (Sarkar, et al., 2001). However, Moore and Benbasat (1991)
has argued that the use of compatibility in terms of need is a source of confusion with
another concept (e.g. relative advantage) and hence they have suggested to
conceptualise compatibility as a ‘need free’ variable. I have also taken a similar view
to Moore and Benbasat (1991) on compatibility notion for this study.
The compatibility notion can be seen in digital platform technology. When a new
software module or extension is introduced to an existing digital platform architecture,
such as, Amazon Elastic cloud, this particular module needs to interoperate with the
core functionality of the structure (Tiwana, et al., 2010). If the underlying program is
developed using Unix code, then the newly added module must also be developed by
Unix code so that they interact to form a mutually compatible relationship. However,
because of the connectedness and interdependence between IT assets and
organisational resources in contemporary complex adaptive business systems
(Tanriverdi, et al., 2010), the change in the platform module also needs to be
compatible with business routines; for instance, if a CRM system that manages
customer retention information is built on the digital platform. Now suppose a block
of code is added to the digital platform to enhance its customer retention process. This
particular change in the platform must be made in such a way that it still can continue
the relationship with the CRM system that controls the customer related information.
In other words, any change in the customer retention process needs to be compatible
with the CRM system so that CRM enabled customer retention capability can be same
as before the change. This example is particularly at technical level.
An example of compatibility in relation to complex emergence in organisational
context is as follows. For instance, a financial organisation has an ERP system (IT
assets) that facilitates sales and marketing, payment processing and supply chain
processes (organisational resources). Suppose, the institution has added a new HRM
module to automate the existing HRM processes, e.g. employee application
lodgement, application assessment and application decision processes. Therefore, the
company now has obtained new ERP enabled HRM capabilities that automate the
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 111
mentioned processes. However, after the integration of the new HRM module in the
ERP system, the company identifies that even though the HRM module automates the
HRM processes and is compatible with the ERP system as well as with the HRM
routines and the above mentioned other processes still, this upgrade causes issues in
the employee payroll system. This is because of an incompatibility between the new
ERP-enabled HRM and the existing payroll process (since the HRM processes are
linked with the payroll process). Therefore, the compatibility condition addresses the
feasibility of the relationship between IT assets and organisational resources, though
the emergent IT-enabled capabilities might not result in desirable outcomes (causal
complexity) (Pentland, Feldman, Becker, & Liu, 2012). MacIntosh and MacLean
(1999) discuss how, in the complex emergence state, components constantly adapt to
each other to create configurations that ensure their compatibility as well as with the
ever changing environment that triggers further emergence. Moreover, (Churchman,
1968) highlights that though IT systems enable different capabilities, such as rapid
data analysis for decision making, if the users are unable to interpret the meaning of
the data, it can cause more harm than good. Hence,
Proposition 1: Greater compatibility between IT assets and organisational
resources can positively influence the complex emergence of IT-enabled capabilities.
Self-organised Management influencing IT-enabled Capabilities Complex Emergence
Self-organised management is defined in this study as flexible and spontaneous
managerial practices that support and guide the dynamic relationships between IT
assets and organisational resources following Stacey (2003). In the context of the
complex emergence of IT-enabled capabilities, self-organised management is needed
because it addresses that the notion that, as the components of IT assets and
organisational resources change continuously, the emergent IT-enabled capabilities
also change, and that these changes and self-organised management serve as a catalyst
providing necessary support for the interactions to happen in a manner that is
congruent with organisational goals (Anderson, 1999).
The self-organised management constantly monitors the status of IT assets and
organisational resources and facilitates the emergence of IT-enabled capabilities by
monitoring changes or failures or any emergent contingencies and ensuring that
emergent IT-enabled capabilities are consistent with organisational goals, otherwise
112 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
the new IT-enabled capabilities may cause massive unpredictable consequences
(Perrow, 1984), such as the failure in the overall business processes (Avison, Wilson,
& Hunt, 2003). In the ERP-enabled HRM example provided in the above discussion
of compatibility condition, the payroll process suffers from some inconsistencies due
to incompatible relations between the new ERP-enabled HRM processes and existing
payroll processes. In this case, self-organised management carries out actions in such
a way that the unpredictable inconsistency could be adjusted instantly so that both
ERP-enabled HRM processes and payroll process are consistent with organisational
goals.
Another example of the self-organised management can be seen in agile software
development (Vidgen & Wang, 2009). For instance, any failure in one of the
components in ERP system during development can cause unbound effects on the
organisational processes associated with it. In such a case, an agile driven team
spontaneously forms into small groups, defines local rules (described in the next
section) for each group with lists of possible tasks and then initiates the failure
mitigation process (Vidgen & Wang, 2006b). However, researchers admitted that it is
difficult to accurately predict the effects of interactions in contemporary business
environments (Bharadwaj, et al., 2013; Grant, 2003). Thus, self-organised
management follow simple rules (Eisenhardt & Sull, 2001) (described in the next
section), which are some pre-defined routines, e.g. organisational goal, process
objectives etc., and defined local rules (Vidgen & Wang, 2009), so that IT-enabled
capabilities can be directed to the local and global optima (Dooley, 1997). Self-
organised management therefore, both sets up the context, defines and controls certain
relationships and facilitates overall interactions (Markus & Robey, 1983) so that the
interaction outcomes (i.e. IT-enabled capabilities) do not go beyond control, otherwise
organisational operations would be severely influenced (Perrow, 1984).
Building on the above, I propose that self-organised management acts as an
enabler of the complex emergence of IT-enabled capabilities by facilitating the
relationships between IT assets and organisational resources and providing
organisational context of those interactions. Hence:
Proposition 2: Self-organised management to ensure the relationship between
IT assets and organisational resource can positively impact the complex emergence
of IT-enabled capabilities.
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 113
The preceding discussion also suggests that self-organised management by
ensuring the facilitation of the relationships between IT assets and organisational
resources can have a positive effect on the compatibility between the two components.
Self-organised management provides spontaneous consultation, brainstorming and
arranges flip through sessions with organisational resources such as department,
groups, and individuals (Markus & Robey, 1983) to ensure that they follow simple
rules (Eisenhardt & Sull, 2001) and they maintain the IT assets according to
organisational goals and routines (Pentland, et al., 2012) even though components of
both of the entities are continuously changing. Accordingly, it can be argued that self-
organised management ultimately provides support and organisational context to make
IT assets and organisational resources compatible. Hence:
Proposition 3: Self-organised management to ensure the relationship between
IT and business can positively impact their compatibility.
Semi-structures facilitating Complex Emergence of IT-enabled Capabilities
In section 4.3.3, I have discussed that for complex emergence to take place, it is
required to have semi-structures in the complex system. Semi-structures are defined
as some prescribed or determined features such as, responsibilities, organisational
goals, project deadlines, etc. of adaptive organizations (Brown & Eisenhardt, 1997).
The semi-structures support non-deterministic features that arise from dynamic
interactions between components of complex adaptive systems (Brown & Eisenhardt,
1997; Goldstein, 1999). Semi-structures exhibit partial order and are flexible and lie
between the extremes of very rigid and highly chaotic organisation. Brown and
Eisenhardt (1997) identified that managers with successful product market portfolios
exhibit opportunistic, proactive and agile characteristics and exhibit semi-structures so
that they can direct firms towards effective competition.
Semi-structures support the intermediary phases (section 4.3.3) of the complex
emergence of IT-enabled capabilities. In the hypothetical example of ERP-enabled
HRM process, the intermediary phases related to it will be following-
1. In the disequilibrium period, the new ERP-enabled HRM capabilities, such as,
automated application lodgement, assessment and approval trigger the
unpredictable emergence of new order, i.e. the inconsistencies in payroll
processes,
114 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
2. In the positive feedback stage, the emergent ERP-enabled HRM capabilities
(assuming that they are consistent with organisational goals, can be changed if
the goals change) amplify the fluctuations of inconsistencies in payroll
processes if they are not corrected.
3. If the payroll related inconsistencies are identified, they start making
correlations with the ERP-enabled HRM capabilities until any further changes
occur in both of the components.
4. Coordinating mechanisms (self-organised management) will try to continue
this order of relationships between ERP-enabled HRM and payroll processes
for maximum period of sustainability until the next emergence takes place
(Chiles, et al., 2004).
From the above discussion, it is evident that the complex emergence of IT-
enabled capabilities requires to be aligned with the predefined organisational goals so
that any unpredictable disruptions can be kept to a minimum level (Terry, 2012).
Accordingly, the predefined features in organisation, such as, organisational goals,
routines, policies, are provided by semi-structure (Brown & Eisenhardt, 1997). When
any complex emergence of IT-enabled capabilities arises, self-organised management
matches the emergent capabilities with the semi-structure to facilitate the IT-enabled
capabilities. Self-organised management defines experimental routines and strategic
initiatives, which are neither rigidly planned nor chaotically react, when new IT-
enabled capabilities emerge (Brown & Eisenhardt, 1997). Thus, semi-structures
support the intermediary phases of the complex emergence of IT–enabled capabilities.
The underlying argument is that change readily occurs in IT assets and
organisational resources that trigger complex emergence of IT-enabled capabilities,
such as, incorrect approval of an employee application in the HRM example mentioned
above. Semi-structures are sufficiently rigid features so that emergent IT-enabled
capabilities can be directed towards organisational goals. Too little structure makes it
difficult to coordinate emergent order and too much structure makes it hard to facilitate
the emergent order towards organisation goals. Flexible semi-structures accommodate
the emergence order following simple rules (discussed in next section). Garud (1997)
identifies that semi-structures can accommodate high rates of successful innovation
while maintaining industry standards. However, sustaining the semi-structured state
can be challenging as it is dissipative equilibrium (Brown & Eisenhardt, 1997) and
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 115
thus self organised management ensures constant managerial vigilance of semi-
structures to avoid slipping into pure chaos or pure structure (Morel & Ramanujam,
1999).
Another argument entails that the expected IT-enabled capabilities might not
always be emerged because of the continual changes in the components. Without a
grasp of the future, change becomes inefficient, unpredictable and problematic
(Holland, 1995). Semi-structures provide the features that help to accommodate the
emergent IT-enabled capabilities as well as support them to be consistent with
organisational goals. Hence,
Proposition 4: Semi-structures to ensure the match between predefined goals
with emergent IT-enabled capabilities can positively influence the complex
emergence of IT-enabled capabilities.
Simple Rules supporting Complex Emergence of IT-enabled Capabilities
Simple rules are organisational heuristics (Cohen, et al., 1996) that self-
organised management uses as guidelines and decision rules (Levy, 2000) along with
the predefined features (semi-structures) to facilitate the unpredictable complex
emergence of IT-enabled capabilities consistent with the organisational goals. In
organisations, managers craft simple rules as heuristics to guide a few strategically
important processes, such as product innovation, partnering, alliances, or new market
entry so that organisations can obtain fleeting opportunities (Eisenhardt & Sull, 2001)
in the competitive business environment. In the context of IT-enabled capabilities
(internal to organisation), self-organised management defines simple rules in the case
of unpredictable emergent IT-enabled capabilities to facilitate them to be consistent
with organisational goals. The simple rules can be remarkably effective in guiding the
IT-enabled capabilities adaptation to changing organisational goals (Jarzabkowski,
2004).
In the presence of semi-structures, such as, plans, standards, responsibilities for
certain activities, self-organised management define and use simple rules to guide the
complex emergent IT-enabled capabilities while establishing bounds that can prevent
organisations falling off at the edge of chaos (Brown & Eisenhardt, 1997; Eisenhardt
& Sull, 2001). In the dynamic business environment, where, IT assets and
organisational resources are always on the move, which trigger unpredictable IT-
116 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
enabled capabilities, the formulation of simple rules is strategically important.
Organisations utilise simple rules as a means of grasping opportunities from dynamic
markets (Eisenhardt & Sull, 2001). It can be said that the simple rules guide the
emergent IT-enabled capabilities towards organisational goals and that helps
organisation to deal with other competitors in dynamic and high velocity markets
(Jarzabkowski, 2004).
The above discussion entails that complex emergence requires simple rules as
enablers to guide the complex emergent IT-enabled capabilities towards organisational
goals. As the complex emergence is characterised as unpredictable, so formulating
simple rules requires rapid response from self-organised management, but the simple
rules must be well defined because random rules with no clues about organisational
routines can bring negative consequences (Jarzabkowski, 2004). Well defined simple
rules can direct the complex emergent IT-enabled capabilities consistent with
organisational goals.
Proposition 5: Well-defined simple rules can positively impact the complex
emergence of IT-enabled business capabilities.
Complex Causality Logic acknowledging Unpredictability
Complex causality refers to the state, when the outcomes of specific actions are
unpredictable (Stacey, 1996). For the purpose of the study, complex causality is
defined as, the causality concerning the emergence of unpredictable outcomes from
the results of interactions between components following Lippman and Rumelt (1982).
The complex causality aspect of the complex emergence concept in the context of IT-
enabled capabilities is vital because it helps to consider the non-linear and surprising
nature of capabilities. It acknowledges the idea that even the expected IT-enabled
capabilities emerge from the interactions between IT assets and organisational
resources, it might not be beneficial for overall organisational functions. In the HRM
example above, the discussion of IT assets and organisational resources reveals that
although the ERP-enabled HRM capabilities are thought be beneficial for the overall
organisation, they trigger issues in payroll processes. IT-enabled capabilities viewed
via the lens of complex emergence may produce unpredictable outcomes as they arise
from the interactions between IT assets and organisational resources, which are
difficult to know about ahead of the time. The complex causality can be thought as a
part of the complex emergence of the IT-enabled capabilities that enforces self-
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 117
organised management to consider about any unforeseeable orders in the emergence
of the IT-enabled capabilities as shown in Figure 4.4.
The preceding section describes a process starting from two individual entities,
in this case, IT assets and organisational resources; both of them interact together and
their interactions give rise to emergent IT-enabled capabilities. The proposed
relationships are considered as non-linear, because components of both of the entities
always change in organisations and that influences the emergent IT-enabled
capabilities. Because of this non-linear nature, I have used the complex emergence
lens which helps to theorise non-linear and unpredictable emergent patterns from
components’ interactions. When IT assets and organisational resources become
compatible, they are eligible for interactions. However, due to the existence of non-
linearity, I have proposed that self-organised management works as an enabler and
facilitates the emergent IT-enabled capabilities by defining simple rules (enabler)
following semi-structures (enabler) congruent with the organisational goals. The
complex causality characterises any unpredictable outcomes of specific actions related
to the emergence of IT-enabled capabilities.
4.4.2 A Narrative Exemplary Case to Explain the Complex Emergence of IT-enabled Capabilities Framework and Internal Validation
In this section, ERP system has been considered as a case narrative to briefly
show how the framework actually provides a narrative explanation on complex
emergence phenomena in practical organisational context. Moreover, the case study
also helps to provide a first step internal validation of the proposed propositions and
framework.
In recent years, due to the technological innovation, the nature of ERP systems
has experienced considerable change by becoming more open, modular, cloud-based,
collaborative, complex and networked and ecosystem based structure (Cusumano,
2010; Nambisan, 2013; Tiwana, et al., 2010). IT firms (e.g. SAP, Microsoft, Epicor)
has been increasingly taking leverage of service platforms and providing ERP
solutions as software as a service (SaaS) to co-create business value. Platform structure
serves an operant source to allocate a wide variety of software applications and
modules on a remarkable scale (Tiwana, et al., 2010). ERP system is now connected
to robotic systems and mobile applications specially manufacturing and production
118 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
industries to streamline between design and manufacturing and contributes to the
business value creation. The business value creation process has dramatically changed
over the years due to the such ERP integration in contemporary organisations (Teo,
2017). Below, I have adopted empirical qualitative studies from a published thesis to
explain how my proposed framework can help to better explain the dynamic
emergence of IT-enabled capabilities.
Lokuge (2015) conducted nine case studies in various of organisations in two
phases to understand how organisations innovate through enterprise systems (ES) and
digital technologies and to investigate the role of ES in supporting innovation. The
first phase involved four case organisations- logistics, multinational, energy and
farming, where SAP enterprise systems modules- Materials Management, Sales and
Distribution, Financials and Controlling modules were implemented in between 1997-
2008. She tested two propositions; proposition 1- ES facilitates innovation and
proposition 2- digital technologies facilitates innovation. I am using her test case
description as narrative to show how my proposed framework can help better
explaining the complex emergence of IT-enabled capabilities. I have made few
interpretations because the test cases were conducted with researchers aims and foci,
whereas my thesis has different focus.
According to my proposed framework, the IT assets in her case studies are SAP
system and digital technologies- such as, analytics, intelligence software, cloud
computing and mobile technologies. In addition, the organisational resources are
human resources, their skills, organisational strategies, business processes etc. The
study identified that radical innovation and incremental innovation were attained
through ES. The radical innovation is relevant to my framework it is characterised as
discontinuous and leads to greater uncertainty and paradigm shift (Latzer, 2009),
which is very close to the nature of complex emergence. It was found that due to radical
innovation in the SAP (IT assets) from the legacy systems, the interrelated core
business processes, employee responsibilities and organisational structure
(organisational resources) were improved in the multinational organisation.
The scenario was same for the logistics, farming and energy organisations. The
IT and technical inexperience, high cost, high risk, unpredictability and technological
uncertainty were evident in all case organisations, which refers that radical innovation
was evident. The radical innovation further triggers innovation in the mobile and
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 119
analytic technologies, such as, cloud computing (energy organisation) and mobile
application (farming organisation), which further trigger changes in the roles and
responsibilities of organisations.
The analysis of the case data illustrates that-
• Due to the implementation of the SAP system, the roles and
responsibilities of the employees were dramatically improved and they
had to learn how to use the new system to do their tasks. The associated
digital technologies also affected employees’ job tasks and they adjusted
themselves with it over time. The both paradigms refer to compatibility
in between IT assets and organisational resources. They also help to
validate the proposition 1, which refers that greater compatibility
between IT assets and organisational resources can improve the complex
emergence of IT-enabled capabilities.
• The case data provide evidences on the continual support, trainings and
assistance from the SAP implementation team to ensure the SAP
products rightly match with the core business processes and
organisational strategies. This scenario refers to self-organised
management. The case data also reveal the decision makers support
during and after ES implementation, especially in the radical innovation
help to improve better process performance in logistics, multi and energy
organisations. This validates both proposition 2 and 3.
• Complex causality was evident in the case studies. Complex causality is
defined as the causality concerning the emergence of unpredictable
outcomes from the results of interactions between components of the IT
assets and organisational resource. In the farm case study, the case data
shows that even though the ES is expected to improve the business
efficiency, it was so marginal that the company intends to acquire (self-
organised management) new solution- mobile technologies, analytics
and big data. Moreover, the logistics and multi organisations also show
similar outcomes- the respondents share that stand alone digital
application can solve their internal business related issues, which were
expected to be solved by ES, but the ES did not. Therefore, the
120 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
organisations had to proceed with digital technologies. Both of the
scenario present the fact the the ES was expected to improve the certain
capabilities (IT-enabled capabilities), however, the ES failed to do so,
which refer to the complex causality in relation to the IT-enabled
capabilities.
• Because of the SAP implementation, organisations thought they would
get substantial operational efficiency and business benefits; the case data
shows that they had got process efficiencies. However, the business
benefits were marginal, all the four organisations had to further invest in
the mobile and digital technologies for better customer reach (logistics),
to improve productivity (multinational) and productivity improvement
and new business opportunities (energy). The case data reveals that
managers needed to rethink about SAP enabled capabilities and their
effect in the business value as the SAP integration in the business was
creating little to less value. All the case organisations had to adopt new
technologies- cloud based mobile app (logistics), BI (multinational),
third party IT applications (energy) and analytics and big data (farming)
to enhance the SAP enabled capabilities that actually contributed largely
in the organisational and business benefits. The case scenario actually
represents that the organisations had identified the complex causal nature
of emergence of SAP enabled capabilities as the capabilities were not
sufficiently contributing in the organisational benefits. In addition, the
scenario also helps to understand that organisations had to react
proactively (simple rules and semi-structures) and invested in the
integrations of digital technologies which ultimately contributed to the
business value and that also validate the proposition 4 and 5.
The above narrative helps to understand how emergence of IT-enabled
capabilities can be complex and also it helps to validate the framework of the complex
emergence of IT-enabled capabilities in a limited way by explaining it through case
description. Verifying relationships in theory development research is crucial and
important because researchers are unable to conduct any statistical test. The narrative
has established an internal validity of the proposed complex emergence framework
because it helps to provide a good understanding of the dynamics of underlying
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 121
relationships that is ‘why’ this phenomenon is happening (Eisenhardt, 1989). It is
important to note that, the internal validation using the case study is a first step of the
validation process. An in-depth empirical case study can be conducted to further
validate the propositions and the framework.
4.5 CHAPTER SUMMARY
Based on the ideas of Nevo and Wade (2010), this chapter argues that IT-enabled
capabilities emerge as result of interactions between IT assets and organisational
resources. The underlying assumption behind phenomena entails that the components
of the IT assets and organisational resources are always changing in contemporary
organisations, due to changes in business requirements, organisational goals,
innovation, and strategic formulation. Therefore, the emergence of IT-enabled
capabilities becomes non-linear and dynamic in nature. Consequently, I have proposed
that a dynamic lens, the complex emergence concept of CAS theory can provide new
insights into this particular dynamic phenomenon.
Section 4.2 presents an overview of the emergence concept and its use in IS and
broader organisational research. It also presents different emergence typologies from
which the complex emergence concept has been chosen as an overarching lens to
explore IT-enabled capabilities.
Section 4.3.1 recaps the Nevo and Wade (2010) study on strategic IT-enabled
resources and their influence on competitive advantage. Using a complex emergence
perspective two enabling conditions compatibility and self-organised management are
discussed here along with complex causality logic that supports unpredictability
related to complex emergence phenomena. In addition, some ‘folklores’, the
misconceptions around the emergence concept suggested by Goldstein (2000)are
discussed. The section ends with proposing two enabling conditions, semi-structures
and simple rules, that help us to understand how complex emergence takes place based
on self-organising logic.
Section 4.4 presents a complex emergence framework of IT-enabled
capabilities. The complex emergence framework reveals new insights as propositions
from the enabling conditions. Section 4.4.2 includes a case narrative to briefly show
how the framework actually provides a narrative explanation on complex emergence
phenomena in practical organisational context. Moreover, the case study also helps to
122 Chapter 4: An Emergence Perspective on IT-enabled Capabilities
provide a first step internal validation of the proposed propositions and framework.
The framework and the associated propositions are presented in Table 4.3.
Complex Emergence Framework of IT-enabled Capabilities
Propositions
Proposition 1: Greater compatibility between IT assets and organisational resources, can
positively influence the complex emergence of IT-enabled capabilities.
Proposition 2: Self-organised management to ensure the relationship between IT assets and
organisational resources, can positively impact the complex emergence of IT-enabled capabilities.
Proposition 3: Self-organised management to ensure the relationship between IT and business,
can positively impact their compatibility.
Proposition 4: Semi-structures to ensure the match between predefined goals with emergent IT-
enabled capabilities, can positively influence the complex emergence of IT-enabled capabilities.
Proposition 5: Well-defined simple rules can positively impact the complex emergence of IT
enabled business capabilities.
Table 4.3: Complex Emergence of IT-enabled Capabilities
The next chapter argues that once IT-enabled capabilities emerge they start
coevolving with other IT-enabled capabilities and that this influences competitive
advantage. I have applied a coevolutionary CAS perspective to explore the coevolving
IT Assets OrganisationalResources
Complex Emergence
IT-enabled Capabilities
Semi-structures
Simple Rules
Self-organised Management
Compatibility
Enabling Conditions
Complex Causality
Chapter 4: An Emergence Perspective on IT-enabled Capabilities 123
nature of IT-enabled capabilities and I discuss how they influence competitive
advantage.
124 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
Chapter 5 Summary
What was done in the previous chapter: The previous chapter presents a
complex emergence perspective of IT-enabled capabilities. It also discusses few
enabling conditions related to the emergence of the IT-enabled capabilities.
What this chapter does: This chapter presents a coevolution perspective on
IT-enabled capabilities. It addresses how IT-enabled capabilities coevolve in two
levels- micro and macro levels of organisations.
What is still outstanding in later chapters:
Chapter 6: An operational (NKC) coevolutionary framework of IT-enabled
capabilities.
Chapter 7: A CAS based framework on competitive advantage and a
discussion on the overall insights that I have developed in relation to BVIT.
5.1 INTRODUCTION
This chapter presents a micro and macro co-evolutionary perspective on IT-
enabled capabilities and will focus on the second subset of BVIT framework (Figure
5.1) presented in Figure 1.2 in Chapter 1. Based on the RBV view of organisations,
(Melville, et al., 2004) develop an integrated model of BVIT, in which authors argue
that the locus of value generation in organisations is the focal firm where IT resources
are deployed (micro level). Moreover, external factors such as the competitive
environment, including industry characteristics and trading partners, as well as the
macro7 environment denoting country and meta country factors, such as, social and
7 McKelvey (1997c, p. 360) argues that coevolution takes place at multiple levels and makes a distinction between coevolution within the firm as microcoevolution and coevolution between firms and their niche as macrocoevolution. In this study, coevolution of IT-enabled capabilities within firm is
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 125
cultural contexts are pertinent to the value BVIT generation (macro level). Also,
although Melville, et al. (2004) acknowledge that BVIT creation in the micro and
macro levels of organisations has become dynamic and complex, their approach to
understanding the creation of BVIT is static (Schryen, 2012) and they do not describe
the dynamic mechanisms related to the BVIT creation. Accordingly, I propose an
approach to understanding BVIT that accounts for the dynamic mechanisms related to
the value generation.
In contemporary organisations, the adoption of digital technologies in business
gives rise to a step change in the dynamism and unpredictability of the elements in
business systems (Tanriverdi, et al., 2010). A stream of prominent IS scholars (El
Sawy, et al., 2010; Nevo & Wade, 2010; Oh & Pinsonneault, 2007; Tanriverdi, et al.,
2010) has suggested that the dominant approaches to dealing with the unpredictable
dynamics are inadequate and have called for new methodological and conceptual
perspectives for dealing with such dynamic context. These scholars agree that a
holistic system perspective needs to be adopted; e.g. (Nevo & Wade, 2010) uses
systems thinking, (Oh & Pinsonneault, 2007), (Tanriverdi, et al., 2010) and (El Sawy,
et al., 2010) adopts complexity thinking, that is better suited to explore the dynamic
relationships among different components of organisations and environment (Merali,
et al., 2012). Consequently, in this study, I have adopted a CAS perspective,
specifically a CAS coevolution (Figure 5.1) perspective (Koza & Lewin, 2001; Lewin,
et al., 1999; Volberda & Lewin, 2003) to explore how IT-enabled capabilities change
each other at micro (internal to organisation) and macro (external to organisation)
levels and how they influence performance and competitive advantage8 or
organisations. In particular, I have proposed that IT-enabled capabilities change with
other internal and external IT-enabled capabilities in contemporary organisations and
their interplay influences efficiency (micro) and competitive advantage (macro) of
organisations following the idea of Melville, et al. (2004). The research subquestion
for this study is:
considered micro level coevolution of the IT-enabled capabilities and coevolution of IT-enabled capabilities between two or more firms is considered as macro level coevolution.
126 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
Research subquestion 1.2: How do IT-enabled capabilities coevolve and
influence competitive advantage?
Figure 5.1 A Subset of the BVIT framework
Based on the ideas of Shepherd and Suddaby (2017) related to theory
development, I have developed my research method for this study. A broad overview
of the research method is discussed in Figure 1.4 in the Chapter 1. For this chapter, a
subset of the research method is applied as shown in Error! Reference source not
found..
In brief, the research method includes- In brief, the research method includes-
1. The narrative conflict: As described in section 1.4.1 in the Chapter 1, the
overarching narrative conflict of this study is the tension between the existing
literature on BVIT and the conceptualisation of BVIT. Drawing the same ERP
example from Chapter 4, section 4.1, in this chapter, I have described the
narrative conflict in relation to the coevolution concept. Suppose, the ERP
system provides organisation with these mutually related capabilities- logistic
management, production management, purchase management, and sales order
management. If the logistic management capability changes because of an
update in the ERP, it will affect the other capabilities mentioned above because
of the mutual causal relationships, which is a micro coevolution in
organisational setting (Mckelvey, 1999). In a similar way, if the changes in the
logistic capability triggers a change in the competitors’ capability, it is called
macro coevolution (Mckelvey, 1999). However, existing BVIT literature in IS
considers these mutual causal changes within firm and with the competitors as
a linear process. So, the narrative conflict becomes the tension between the
IT-enabled Capabilities
• IT Assets
• OrganisationalResources
Competitive Advantage
Coevolution
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 127
existing literature on coevolution, whether the internal and external
coevolution are linear or non-linear (dynamic) and the conceptualisation of
such coevolution.
2. Building stories- It involves four stages-
o Identifying core constructs: Two major constructs are relevant to this
chapter- IT-enabled capabilities and competitive advantage. They are
broadly discussed in section 2.3 in Chapter 2.
o Determine the narrative settings: For this study a shifting ontology
strategy is adopted to determine the narrative settings. In this chapter,
shifting ontology highlights the change from a static, linear view to a
dynamic, non-linear view on the coevolution of the IT-enabled
capabilities, which is briefly discussed in the first paragraph of this
section.
o Draw boundary conditions- The story’s event sequence: The event
sequence here is- first, IT-enabled capabilities coevolve each other
within organisation, which is denoted as micro coevolution. Moreover,
IT-enabled capabilities from two or more organisations mutually
influence each other, which is termed as macro coevolution. Second,
the micro and macro level coevolution of the IT-enabled capabilities
influence competitive advantage. It is important to note that, though IT-
enabled capabilities can mutually change with other organisational
elements, such as, routines, capabilities, strategies, resources (Koza &
Lewin, 2001; Lewin, et al., 1999), I have considered the mutual changes
between IT-enabled capabilities only. This is broadly discussed in
section 5.4 and 5.5.
o Apply disciplined imagination- theorising via metaphors (analogical
reasoning): In this chapter, coevolution metaphor of CAS theory is
applied to describe how IT-enabled capabilities coevolve in micro and
macro levels of organisations and how they influence BVIT, in
particular competitive advantage. The theorising of the coevolution of
IT-enabled capabilities and their influence on competitive advantage is
discussed in section 5.4, 5.5 and 5.6.
128 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
3. New insights: The application of coevolutionary perspective gives new
insights in relation to the coevolution of IT-enabled capabilities, explains the
way they affect competitive advantage and advances some new strategies,
which are discussed in section 5.4, 5.5 and 5.6. Moreover, an exemplary case
study is used to validate the framework in section 5.6.2. The theories developed
in this chapter using CAS coevolution concept are explanatory type theories
(Gregor, 2006) as they help to provide greater explanation on how IT-enabled
capabilities coevolve in micro and macro levels and their impact on
competitive advantage.
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 129
Figure 5.2 A Subset of Research Method for Coevolution of IT-enabled Capabilities
Melv
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130 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
Based on the RBV view of organisations, Melville, et al. (2004) review past
empirical research related to BVIT. Their BVIT model integrates research assessing
both the implications of IT at the operational level internal to the organisation (referred
to as efficiency) as well as at the strategic level (that addresses how IT helps
organisations to achieve competitive advantage). In brief, their model contains three
domains: focal firm, competitive environment and macro environment.
1. The focal firm is the core organisation that acquires and deploys IT resources
within the organisation. BVIT is generated by the deployment of IT and
complementary organizational resources within business processes. The
applications of IT resources, such as, business applications, database, IT
skills, etc. and complementary resources, such as, non-IT human resources,
production, sales processes, etc. may improve business processes, which in
turn may impact overall organisational performance (Brynjolfsson & Hitt,
2000).
2. The competitive environment refers to the environment in which the focal
firm operates and comprises industry characteristics and trading partners
(Mukhopadhyay, Kekre, & Kalathur, 1995). The industry characteristics,
such as business policy, regulation, and technological change influence the
way in which IT is applied in the focal firm to generate business value (Kohli
& Devaraj, 2003). In addition, trading partners play a role in the BVIT
generation when IT spans focal firm boundaries and includes IT and non-IT
resources from trading partners (Mukhopadhyay, et al., 1995).
3. The macro environment refers to the macro factors, such as, government
initiative related to technological development for the improvement of
organisational performance and broader social, political and cultural
contexts that may influence organisational performance (Dewan & Kraemer,
2000).
This study takes the Melville, et al. (2004) BVIT model and the three domains
as a starting point. However, my study argues that BVIT is generated at two major
levels of contemporary organisations - the micro and macro levels, where, micro
signifies the focal firm (as in the Melville, et al. (2004) model) that acquires and
deploys IT resources that may improve its operational performance, . The macro level
defines the industry within which focal firm is operating and competing with other
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 131
firms via investing and deploying IT resources to achieve superior advantage over its
rivals (Porter & Millar, 1985). For the purpose of the study, I have considered two
domains- the competitive environment and macro environment together as macro
level.
The rest of the chapter is structured as follows; the next section Error!
Reference source not found. presents an overall overview of the coevolution concept
and how it has been used in IS and organisational research. Section 5.3 presents a
preliminary coevolution framework of IT-enabled capabilities. After then, micro and
macro coevolution in relation to IT-enabled capabilities are discussed (section 5.4 and
5.5). A coevolution based framework of IT-enabled capabilities with the focus on how
IT-enabled capabilities influence BVIT in micro and macro levels is proposed in
section 5.6. The chapter concludes with a summary.
5.2 OVERVIEW OF COEVOLUTION 5.2 OVERVIEW OF COEVOLUTION
The previous section briefly presents the research motivation, research question and
research method of the chapter. This section first addresses the basics on
coevolutionary CAS concept. Then it presents a review of the IS and organisational
research that adopt the coevolution CAS concept.
5.2.1 The Basics of Coevolution
Evolution in general is often thought of as progress or improvement. It is
defined as “cumulative and transmissible change” in the components of a system
(Murmann, 2003). The concept of ‘coevolution’ is related to the evolution concept.
Coevolution is the evolution of one domain or entity that is partially dependent on the
evolution of other related domains or entities (Ehrlich & Raven, 1964; Kauffman,
1995a; Kauffman, 1993; Mitleton-Kelly, 2003b).
The term ‘coevolution’ was first coined by Ehrlich and Raven (1964) in
reference to biological evolution when looking at the relationship between the patterns
of evolution of plants and butterflies, and describing the simultaneous, reciprocal
evolution of interacting populations. Coevolution is characterised as the reciprocal
evolutionary process of natural selection (Kauffman, 1993). Coevolution is closely
related to the notion of ecosystem. An ecosystem in biology means, “each kind of
organism has, as parts of its environment, other organisms of the same and of different
kinds ... adaptation by one kind of organism alters both the fitness and the fitness
132 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
landscape of the other organisms” (Kauffman, 1993, p. 242). The way each element
influences and is in turn influenced by all other related elements in an ecosystem is
part of the process of coevolution.
Basic notions of coevolution are homogeneous across natural and social science
literature, reflecting that the evolution of one domain or entity is partially dependent
on the evolution of other related domains or entities (Kauffman, 1995a; McKelvey,
1999). However, coevolution can happen within the entities of a system (Mitleton-
Kelly, 2003b). Therefore, the interpretations of the concept of co-evolution vary
depending on the applications. Coevolution is a dynamic concept that has been used
mostly in natural science and evolutionary biology but the concept has been extended
into diverse fields in social sciences as an applied metaphor or interpretive lens to
understand the dynamic mechanisms of complex evolving phenomena. Though the
concept has been widely used to understand evolving relationships among biological
entities, it is now used also in reference to analogically similar dynamics between
entities within system (endogenous) or systems that coevolve (exogenous) (Mitleton-
Kelly, 2003b).
5.2.2 Types of Coevolution
McKelvey (2002) mentioned total six types of coevolution from evolutionary
biology and organisational studies literature in his seminal paper on coevolutionary
dynamics. Each type of coevolution defines distinctive mutual-reactive relationships
between multiple entities. They are briefly discussed below-
1. Coevolution between mutation (change) rate and environment- This particular type
of coevolution defines reciprocal relationships between two different entities and
with the environment. For instance, the more the ERP develops, the more
organisations develop services; the more they develop their services the faster the
ERP develops, and so on.
2. Predator/ prey coevolution: This coevolutionary type is mainly used in the study
of species within ecosystems. The increase in number of rabbits influences the rise
of foxes in that particular ecosystem. The faster the development of IT within
firms, the faster the value obtained through IT is diminished by the development
of new IT in organisations.
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 133
3. Supernormal coevolution: This refers to the coevolutionary phenomena in which,
the cause of coevolution accelerates the coevolutionary process itself. For instance,
the more Engineering graduates are hired, causes the tendency of the firm to hire
more Engineering graduates and so on.
4. Inbreeding and population size: The more breeding within a species of small
population, the more the species become isolated from others;. For instance, the
more research collaboration within a small group of researchers, the more the
narrowly restricted the types of research, - the more intellectually inbred it
becomes, the more collaboration with other research groups becomes restricted and
the more new researchers are excluded from the group and so on.
5. Symbiotic coevolution: This is where a species causes coevolution with other
species with which it is connected. For instance, the more that a large firm hires
surrounding suppliers, the more they survive and grow; the more that the suppliers
survive and grow, the easier it is for the large firm to survive and grow in its
competitive context, and so on.
6. Micro-macro coevolution refers to coevolution between a population and its
environment (Ehrlich & Raven, 1964). For example- Kauffman (1993) discusses
how a species emerges from micro level to macro level that involves RNA to DNA,
to protein sequences, to molecules, to cells, to organisms and species.
Pagie (1999) proposes three types of coevolution in the context of biology,
namely competitive, mutualistic and exploitative. Competitive coevolution occurs
between species which are limited by the same resources. In this case the organisms
are forced to change in such a way that they can either take advantage of or acquire
that resource more efficiently. Mutualistic coevolution, on the other hand, comprises
reciprocal relations where all the participants benefit from the interaction and change
in the direction of better compatibility. Exploitative coevolution comprises relations
where all the participants do not benefit from the interaction.
Based on the above discussion on the types of coevolution it is evident that the
concept of coevolution has different typologies across different disciplines. However,
in the context of organisational studies, two major types of coevolution, micro and
macro coevolution that are addressed across different studies (Chae, et al., 2014; Koza
& Lewin, 2001; Lewin, et al., 1999; Lewin & Volberda, 1999; Melville, et al., 2004;
134 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
Volberda & Lewin, 2003). Therefore, in this study, I have discussed micro and macro
level coevolution in the context of IT-enabled capabilities.
5.2.3 Applications of Coevolution in Strategic Management and IS Discipline
The preceding section addresses different types of coevolution. This section
highlights the use of CAS coevolution concept across Management and IS studies. As
discussed in Chapter 3, the use of CAS theory is very recent, and it has been used in
strategic management and organisational studies since 1960s and then has been applied
into IS research in the last two decades. Therefore, I have presented firstly an overview
of the use of coevolution in organisational studies and then in IS research.
Coevolution in Management Research
The concept of coevolution has been used to analyse the competitive advantage
of nations (Porter, 1990), strategic management (Barnett & Hansen, 1996), strategic
alliances (Koza & Lewin, 2001), new organisational forms (Lewin, et al., 1999), rent
appropriation and capability development (Coff, 2010), entrepreneurship (Pacheco, et
al., 2010), and the management of collaboration among business units in a firm
(Eisenhardt, 2000). Error! Reference source not found. briefly summarises the use
of coevolution concept in management studies.
Based on the observation of the management studies that have applied Based on the observation of the management studies that have applied
coevolution, the studies mainly focus on Type 1 and Type 6 coevolution in section
Error! Reference source not found., where an aspect of firm studied in relation to its
environment and with other competing firms. Majority of the studies explored here has
considered multiple levels and dynamic nature of coevolutionary process. The nature
of relationship has been considered important to some extent in these studies.
Moreover, other researchers have identified and classified different types of
relationships in their research. For instance, Baum and McKelvey (1999c) have used
Heylighen and Campbell (1995) competitive configuration to derive different types of
interactions such as- zero-sum, super competitive and hypercompetitive.
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 135
Authors Summary
(Lewin, et al.,
1999)
Analyse the effect of the environment on the organizational form
with emphasis on the dynamic and multi-level nature of coevolution.
They contend that the coevolution concept in the domain of management
is the inherent integration of an external (selection oriented) focus with an
internal (adaptation oriented) focus.
(Lewin &
Volberda, 1999)
Explore the relationship between firms and their environment with the
interaction between industry selection pressures and firm level adaptation
resulting in new organizational forms. Micro and macro level coevolution
are discussed, where micro characterises change involving inter-
organisational elements and macro signifies relationships between a firm
and one or more components of the external environment.
(McKelvey,
1999)
Explores strategic moves by the firm in response to changes in its
environment, such as, competitors, technology, market and government
policies and how they relate to competitive advantage. He also proposes
ideas on micro and macro levels of competencies in organisations.
(Eisenhardt,
2000)
Uses the coevolution concept to analyse collaboration management
between business units within a firm and how this maximises benefits
from cross-business synergies. The business units are termed as
coevolving species in this research, though the nature of the relationships
is not well explored.
(Coff, 2010) Explores how capabilities and bargaining power coevolve in the context
of rent appropriation.
Table 5.1 Application of Coevolution in Management
The above analysis on the application of coevolution in management studies
helps me to understand and define multiple levels- micro and macro levels in this
study. Moreover, following Lewin, et al. (1999), I have identified six properties of
coevolutionary models used in the management research: multilevel effects,
multidirectional causalities, nonlinearity, positive feedback, path- and history-
dependencies, and adaptation principles. The identification of these properties helps
136 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
me to propose my coevolution framework of IT-enabled capabilities and I have defined
the relevant properties in my proposed framework (see section 5.3).
Coevolution in IS Research
In IS research, coevolution has been used to study IT and business alignment
(Benbya & McKelvey, 2006b; Peppard & Breu, 2003; Vessey & Ward, 2013), IS
engagement (Kim & Kaplan, 2006), information systems development (Hovorka,
2013), business process management (Vidgen & Wang, 2006a), the co-design of
organizations and information systems (Nissen & Jin, 2007) and offshore outsourcing
(Lahiri & Kedia, 2011). Section 1.5 in Chapter 3 broadly discusses the concept of
coevolution, the contributions pertaining to the use of the concept and also the contexts
in which the concept is applied within IS research. Error! Reference source not
found. briefly summarises the use of coevolution concept in IS studies.
Authors Authors Summary
(Peppard &
Breu, 2003)
Both of these studies explore the strategic alignment of IS and
business using the coevolution concept. Benbya and McKelvey
(2006b) consider three major levels, individual, operational and
strategic, involved in the strategic alignment and (Peppard &
Breu, 2003) address key factors related to the strategic alignment
process of IS and business. Both of the studies draw heavily on
complexity thinking (Mitleton-Kelly, 2003a).
(Benbya &
McKelvey,
2006b)
(Vidgen &
Wang, 2006a)
The authors have applied coevolutionary framework in
BPM area to explore whether the conceptual boundary between
IT and business can be divided. The conceptual study has
considered four species that may exhibit coevolutionary
relationships- business processes, software components, IT
developers and business users. They have provided some
guidelines for facilitating coevolutionary development.
(Tanriverdi, et
al., 2010)
Use coevolution concept to address how a firm dynamically
repositions itself, and identifies profitable product-market
positions in the competitive landscape.
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 137
(Chae, 2014) Defines the IT enabled service innovation process as
coevolutionary process involving three stages, variation,
selection and retention following Aldrich (2006) evolutionary
model.
Table 5.2 Application of Coevolution in BVIT related IS research
In IS research, the dynamic nature of coevolutionary process is addressed as
well. Like management research discussed multiple levels are often explored and
reciprocal relationships among multiple levels and environment are considered in the
studies. One important observation is, the use of the coevolution concept is limited in
IS research and majority of the studies adopt the conceptualisation of coevolution from
the key management studies, such as- Lewin and his colleagues (Koza & Lewin, 2001;
Lewin, et al., 1999; Volberda & Lewin, 2003) and Mckelvey and his colleague (Baum
& McKelvey, 1999c; McKelvey, 1997c, 1999, 2002).
An analysis of both of the management and IS literature related to the
coevolution concept reveals that majority of the application of coevolution in BVIT
related studies are in management research (e.g. Baum & McKelvey, 1999c; Coff,
2010; McKelvey, 1999), in particular on competitive advantage and a few number in
IS research (e.g. Chae, 2014; Tanriverdi, et al., 2010). The overall analysis on the
coevolution concept based management and IS studies addresses that
conceptualisation of the coevolution is consistent across different fields and the
properties of coevolutionary frameworks are also mostly same. From this review, I
have mainly developed my perception based on McKelvey (1997c) work and defined
micro and macro levels in this study. In addition, Lewin and his colleagues (Koza &
Lewin, 2001; Lewin, et al., 1999; Volberda & Lewin, 2003) works help me to define
the properties of my proposed coevolution framework of IT-enabled capabilities
(section Figure 5.3).
5.3 A PRELIMNARY COEVOLUTION FRAMEWORK FOR IT-ENABLED CAPABILITIES
The previous section reviews literature related to the use of the coevolution
concept across strategic management and the IS discipline. This section presents a high
level overview of a preliminary coevolution based framework of BVIT.
138 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
As discussed in the Introduction, this study has adopted the Melville, et al.
(2004) model as a starting point to explore the coevolution perspective on IT-enabled
capabilities. Melville, et al. (2004) model provides a foundation for the micro and
macro levels of my proposed coevolution based BVIT model, whereas, the coevolution
framework by Lewin, et al. (1999) helps to describe the dynamic relationships
between IT-enabled capabilities across these levels.
Figure 5.3 presents a preliminary version of my coevolution framework of BVIT.
The model has two major parts, micro level and macro level. The micro level presents
the focal organisation, where investment is made on IT assets. As discussed in chapter
3, IT assets and organisational resources together give rise to emergent IT-enabled
capabilities in an organisation. The IT-enabled capabilities according to the proposed
model coevolve with each other when the focal organisation responds to the changing
business environment over time (Wade & Hulland, 2004). The full framework is
discussed in Section 5.6.
Figure 5.3 A Preliminary Coevolution Framework of BVIT (With the focus on the coevolution of IT-enabled Capabilities)
The macro level part of the framework represents the broader industry within
which the focal organisation is operating and competing to obtain a superior
competitive advantage via the potentials provided by IT-enabled capabilities
IT-enabled Capability
IT-enabled Capability
Focal Firm
IT-enabled Capabilities Other Firms
Micro Coevolution
Macro Coevolution
Dashed Line: Micro coevolution; Solid Line: Macro coevolution
Focal Firm'sCompetitive Advantage
Mutual Adaptation
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 139
(Bharadwaj, 2000). From an RBV perspective of organisation (Barney, 1991), when
the IT-enabled capabilities become valuable (value), idiosyncratic to the focal
organisation (rare), difficult to imitate (inimitable) and non-substitutable, then they
have the potential to lead the focal organisation to attain competitive advantage. The
solid line presents the macro level coevolution of IT-enabled capabilities, where IT-
enabled capabilities of the focal firm changes the IT-enabled capabilities of the
competing firms and vice versa. The dashed line presents the micro coevolution of IT-
enabled capabilities, where an IT-enabled capability mutually adjusts with another IT-
enabled capability within the focal firm.
A few important key points related to the proposed coevolution based BVIT
framework are noted here-
• This study has only considered coevolution of IT-enabled capabilities for the
purpose of the research. Non IT-enabled capabilities can coevolve between
themselves or other capabilities, routines, strategies, but they are not the
focus of this study.
• The study has integrated both micro and macro levels together in relation to
the BVIT generation process in organisation. In this study, I have combined
and conceptualised competitive environment and macro environment
domains together as macro level and the focal firm domain as micro level
from Melville, et al. (2004) study. The micro level defines the focal
organisation that invests, acquires and deploys IT resources. The macro level
refers to the broader industry landscape where the focal organisation
competes for superior competitive advantage over its’ competitors using the
potential of IT resources.
• The study follows Melville, et al. (2004) study to acknowledge the ideas of
micro and macro levels in relation to BVIT. The focal organisation attempts
to obtain superior overall organisational performance to its competitors via
investing in IT resources to gain competitive advantage (Porter, 2008).
• Melville, et al. (2004) RBV based model is considered as one of the most
prominent BVIT models in IS research (Kohli & Grover, 2008; Schryen,
2012). The RBV based view provides a robust framework to examine the
140 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
strategic side of organisational performance expressed as competitive
advantage (Bharadwaj, 2000) in this study.
• The coevolution framework based on Lewin, et al. (1999) is used to provide
an approach to define and explore the implications of IT-enabled capabilities
in deriving competitive advantage for a focal organisation. The framework
also helps to represent the dynamic relationships between IT-enabled
capabilities and their reciprocal effects on the overall performance of
organisations.
• It is important to note that non IT-enabled capabilities and other
organisational resources, competencies and capabilities co-evolve (Volberda
& Lewin, 2003), but for the purpose of this work, I focus on the co-evolution
of IT-enabled capabilities only.
My study diverges from the traditional adaptation–selection debates by
developing a more general theory of firm-industry coevolution (e.g. Lewin, et al.,
1999; McKelvey, 1999, 2002). This study argues that IT-enabled capabilities coevolve
within firms with other IT-enabled capabilities and as well as with other firms. The
direction of these changes is not unidirectional. Moreover, the theorising of the
coevolutionary framework is consistent with sufficient conditions suggested by Lewin,
et al. (1999) and McKelvey (2002) for coevolution to occur-
• It has considered IT-enabled capabilities as heterogeneous element (Lewin, et
al., 1999; McKelvey, 2002). The IT-enabled capabilities are characterised as
heterogeneous, e.g. IT-enabled service delivery, IT-enabled customer
management, etc.
• Multidirectional causality between IT-enabled capabilities in micro and macro
level (McKelvey, 1999) and mutual and simultaneous influences to each other
(Lewin, et al., 1999) is considered in this study. IT-enabled capabilities change
with each other internal to the focal organisation as well as with the changes in
the IT-enabled capabilities of the competing firms in the industry. Changes in
the IT-enabled capabilities are multi-directional within firm and across
competing firms.
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 141
• Elements must have adaptive capability (McKelvey, 2002). IT-enabled
capabilities have the adaptive capability to change with overall business
environment (Wade & Hulland, 2004).
• There needs to be an initiating punch or event to start coevolution (Lewin, et
al., 1999; McKelvey, 2002). Any change in organisational goals, or the
business environment or in the IT-enabled capabilities or other resources, will
trigger changes in the related IT-enabled capabilities. For instance, a change in
the supply chain process cause changes in IT-enabled productions (Swafford,
Ghosh, & Murthy, 2008).
The next sections provide a broad discussion of micro and macro coevolution
perspectives in relation to BVIT.
5.4 MICRO COEVOLUTION OF IT-ENABLED CAPABILITIES WITHIN THE FIRM
The preceding section provides a preliminary version of my co-evolution
framework for BVIT. This section specifically discusses micro coevolution
perspectives in the context of IT-enabled capabilities within the firm. As mentioned
in the previous section, I have only focused the coevolution of IT-enabled capabilities
in this study.
Micro (internal) coevolution of firms refers to the coevolution of intrafirm
resources, capabilities and competencies (Lewin & Volberda, 1999). In this study, I
define micro coevolution for BVIT as the mutual changes among different IT-enabled
capabilities internal to focal firm. A change in one of the IT-enabled capabilities will
likely bring reciprocal changes in other IT-enabled capabilities. Several studies
consider the coevolution of intrafirm resources, dynamic capabilities and
competencies in an intrafirm competitive context (Barnett & Hansen, 1996;
Burgelman, 1994; Galunic & Eisenhardt, 1996). Galunic and Eisenhardt (1996) study
selection and adaptation at the intra-corporate (intra firm) level of analysis. The
Burgelman (1994) coevolution based model shifts the locus from the firm as whole to
the strategic action and views managing intra-organisational processes as a means by
which the firm can achieve learning benefits from external and internal selection.
McKelvey (1997c) recognises that coevolution within the firm level i.e. micro
coevolution, involves processes of variation, selection and retention operating within
142 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
the organisation and interacting with similar processes at the population level. Based
on this logic, I have conceptualised the micro coevolution of IT-enabled capabilities
involves three processes, variation, selection and retention (VSR). The IT-enabled
capabilities take co-evolution journeys proceed through a continuous cycle of
variation, selection and retention, and generate evolution of the focal firm in the
direction of better fit to the selection environment (Volberda & Lewin, 2003). In this
study, I have adopted (McKelvey, 1997c) ideas, followed similar approach as Chae
(2014) and discuss a micro coevolution perspective of IT-enabled capabilities within
the firm.
The stages are described below-
Variation
Variation refers to the change of current routines or forms or structures (Aldrich,
2006). Capabilities are often seen as collection of routines (Nelson & Winter, 1982).
They help organisations to perform basic functional activities (Collis, 1994) and IT-
enabled capabilities are a combination of higher level routines that help organisations
to reliably perform and extend their characteristic output options (Salvato & Rerup,
2011). In today’s organisations, Variation of IT-enabled capabilities provides the basic
elements for adaptation of organisations with the continuous changes in a complex
business environment (Axelrod & Cohen, 2000). In organisational settings, managerial
intentionality deliberately causes variations of IT-enabled capabilities through
decision making, reconfiguring, or imitating (Salvato & Rerup, 2011; Wheeler, 2002).
Moreover, informal and less structured improvisational activities may also lead to
variation of IT-enabled capabilities (Axelrod & Cohen, 2000; Volberda & Lewin,
2003).
Variation creates novelty in IT-enabled capabilities (Lewin & Volberda, 1999).
IT-enabled capabilities are improved via variation, though all variations might not be
beneficial for the functionalities of organisations (Salvato & Rerup, 2011).
Nevertheless, variation is essential as it enables organisations to adapt and fit with the
changing business environment. For instance, big data based analytics though
perceived to be recent, in fact evolved from s predecessors such as data mining and
business intelligence driven decision support in the early 2000s (Chen, Chiang, &
Storey, 2012).
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 143
Two broad categories of variation can be seen in the literature; exploitation and
exploration (March, 1991). Exploitation is based on existing IT assets, modifying their
interaction, and pursuing incremental innovation. In the context of IT-enabled
capabilities, exploitation refers to the enhancement of existing IT-enabled capabilities
by modifying or adding new IT-enabled capabilities via incremental innovation. For
instance, cloud computing can be integrated into existing ERP system as a service
delivery ‘platform’, which can enable cloud based data delivery (new IT-enabled
capability) from existing client-server based data delivery. IT professionals can
incrementally introduce new data services, such as SaaS and Internet of Things (IoT)
analytics (Davenport, Barth, & Bean, 2012) into the cloud, which entails new IT-
enabled capabilities.
Exploration of IT entails “importing energy” in organisations (Anderson, 1999),
such as, implementing big data based analytics (Chen, et al., 2012) or cloud computing
(Battleson, West, Kim, Ramesh, & Robinson, 2016) or even a new IT professional for
improvisation (Axelrod & Cohen, 2000). For instance, CRM focuses mainly on
customer data through a configuration of relational databases and other related
technologies, and their impact is limited to interactions between an organization and
its customers. Big data technology, such as Hewlett Packard’s (HP) big data platform
provides an opportunity in terms of scale and impact to manage abundant data and
domain-specific analytics, such as e-commerce and market intelligence and
organisation specific predictive analytics. An organisation may want to import HP’ big
data platform and with existing CRM for analysing consumer market demands or
discovering new customers and new business opportunities (new IT-enabled
capabilities).
Selection
Selection is the filtering mechanism to choose or eliminate technological
configurations based on their fitness or outcomes (Axelrod & Cohen, 2000). In the
context of IT-enabled capabilities, selection refers to the mechanism of choosing or
eliminating IT-enabled capabilities or routines that are part of an IT-enabled capability
(Nelson & Winter, 1982).The least efficient and effective routines are either
abandoned or changed, or a firm is likely to not be able to survive in the long run. The
most efficient and effective routines help firms to obtain competitive advantage
(Nelson & Winter, 1982).
144 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
Selection of IT-enabled capabilities can be driven by favouring certain IT-
enabled capabilities over others (Weeks, 2002). Favouring particular IT-enabled
capability is involved as organisation mainly favours higher performing IT-enabled
capabilities over existing IT-enabled capabilities with the focus on cost reduction
(Neirotti & Raguseo, 2017). The rise of digital technologies, such as a cloud based
CRM platform (e.g. salesforce.com+ replaces traditional ERP systems based CRM
system in managing customer related information in contemporary organisation
(Cusumano, 2010).
The selection mechanism can be internal or external (Aldrich, 2006). Internal
selection involves reconfiguring or choosing IT-enabled capabilities in such a way that
they become useful for the functionalities of organisation (Chae, 2014). For instance,
when Domino’s Pizza first launched its mobile application, customers faced the issue
of checking the real time status of the pizza delivery. Domino’s recognised this issue
and installed a tracker in the delivery person’s car and added an option in the mobile
application that shows the real time location of the pizza delivery driver. So, the
combination of the tracker and the mobile applications enables customers to track real
time delivery of the pizza.
External selection happens when the selection mechanism is determined by
factors external to organisation. In the context of IT-enabled capabilities, external
selection refers to the mechanism that determines particular IT-enabled capabilities
based on the external market. For instance, where the overall business environment
has become more competitive, uncertain and dynamic, and where everything in
business organisations is connected, there is a strong demand for combinable data
technologies, such as data-analytics, Mongo DB, Splunk etc., which can overpower
the previous data driven technologies, such as business intelligence (Yoo, et al., 2010).
The selection of such new IT-enabled digital capabilities, like IoT driven analytics
instead of traditional Excel based analytics helps firms to improve capabilities such as
reporting (Davenport & Harris, 2007).
Retention
Successful selected IT-enabled capabilities might be retained by organisations
for future potential use (Aldrich, 2006). In organisational settings, particular routines,
strategies, organisational memory and technology artifacts are some examples of
retention (Pentland, et al., 2012). In the case of IT-enabled capabilities, some are
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 145
retained for future variations. For instance, when changes in a business environment
will impact the variation of IT-enabled capabilities, and certain retailed IT-enabled
capabilities, such as, data mining and analytic techniques (Bitterer, 2011) will become
a part of the new variation.
Summary of the Micro coevolution of IT-enabled Capabilities
In brief, the three mechanisms, variation, selection and retention together can
help to understand the evolution of a particular IT-enabled capability in organisations
(McKelvey, 1997c). Figure 5.4 represents micro coevolution of IT- enabled
capabilities. The bidirectional dashed arrows represent the micro coevolution of IT-
enabled capabilities. When the evolutionary process of a particular IT-enabled
capability influences the evolutionary process of another IT-enabled capability within
a focal organisation, then it is called as micro coevolution of IT-enabled capabilities.
The micro coevolution of IT-enabled capabilities is simply illustrated in the following
figure-
Figure 5.4 Micro coevolution of IT-enabled capabilities via variation, selection and retention (VSR) processes
For instance, an ERP system may contain three major modules, such as supply
chain, logistics and inventory control that facilitate business processes that are highly
related to each other. , Thus the related capabilities provided by the ERP system are
ERP-enabled supply chain, ERP-enabled logistics and ERP-enabled inventory control.
If the supply chain module is updated to accommodate new features that will automate
warehouse management processes, this means that a variation of the ERP-enabled
supply chain capability has taken place and a new capability has been selected for
supply chain via ERP; an evolutionary process related to the ERP-enabled supply
chain. Now, as the ERP-enabled supply chain capability gets updated, the other ERP
enabled capabilities are required to adjust to it as they are highly associated. That
IT-enabled Capability
IT-enabled Capability
VSR VSR
146 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
means, the evolution of the ERP-enabled supply chain capability triggers changes in
the other associated capabilities. This might require the logistics and inventory control
ERP modules to undergo variation-selection processes so that they can adjust to the
change and help the organisation to operate appropriately. The variation of one IT-
enabled capability provides the raw material for the adaptation of the other IT-enabled
capabilities (Axelrod & Cohen, 2000). This particular example highlights the role of
evolutionary process of one IT-enabled capability in triggering further evolution in
other IT-enabled capabilities and thus it is a coevolution at a micro level.
Variation creates novelty as well as heterogeneity in IT-enabled capabilities
(Chae, 2014). Once an IT-enabled capability evolves through the processes of
variation, selection and retention, it triggers further evolution in other IT-enabled
capabilities with which it is related. Therefore, the IT-enabled capability starts
coevolving with other IT-enabled capabilities in the organisation (micro level). As the
emergence of the IT-enabled capabilities are not entirely predictable and pre-
determined (see Chapter 4), the micro coevolution is likely to be unpredictable. The
variation mechanism provides options to choose certain IT-enabled capabilities via
reconfiguration or importing. Selection facilitates variation internally and externally
by selecting IT-enabled capabilities internal to organisations based on performance
criteria and organisational goals (Weeks, 2002). Finally, retention helps to retain
certain IT-enabled capabilities for future variations with other social and
organisational elements. Thus, these three mechanisms work together to ensure that
IT-enabled capabilities mutually change with other IT-enabled capabilities (micro
coevolution) in a way that is beneficial for the efficiency of organisation. Based on the
above discussion, I propose-
Proposition 1a: The evolutionary processes- variation, selection and retention
can improve IT-enabled capabilities of focal firm.
Proposition 1b: Micro coevolution of IT-enabled capability occurs when
evolutionary improvement of one IT-enabled capability causes evolution in the
associated IT-enabled capabilities.
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 147
5.5 MACRO COEVOLUTION OF IT-ENABLED CAPABILITIES BETWEEN THE FIRMS
The preceding section discusses micro coevolution of IT-enabled capabilities.
This section presents the macro coevolutionary process related to IT-enabled
capabilities and the way it influences BVIT, particularly competitive advantage. Macro
coevolution of IT enabled capabilities refers to the process by which firms’ IT-enabled
capabilities coevolve reciprocally with the IT-enabled capabilities of other firms
(McKelvey, 1999). The focus of macro coevolution of is on firms existing in a
coevolutionary competitive context to obtain IT-enabled capabilities that help them to
achieve competitive advantage (Lewin & Volberda, 1999; McKelvey, 1997c).
Scholars have been using the coevolutionary lens to explore different dynamic
coevolutionary phenomena in macro level in organisational context, such as, the Red
Queen effect (Barnett & Sorenson, 2002), evolutionary stability (Lewin, et al., 1999),
competitive exclusion (Kauffman, 1995a), coevolutionary imbalance (Madhok & Liu,
2006) and Niche separation (McKelvey, 2002). There are myriads of such phenomena
that are related to coevolution and separating such coevolutionary dynamic phenomena
from each other is difficult as they are highly intertwined and implicit within
coevolutionary relationships (Maruyama, 1963; McKelvey, 2002).
In this section, I have focused on three particular macro coevolutionary dynamic
phenomena (interrelated processes), the Red Queen Effect, competitive exclusion and
Niche separation dynamics in the context of IT-enabled capabilities, following the
ideas of coevolutionary organisational dynamics by (McKelvey, 2002). In general, the
competitive exclusion, Red Queen competition and niche separation coevolutionary
dynamics temporarily dominate in IT enabled firms and influence firms’ competitive
advantage (McKelvey, 2002). The coevolutionary dynamics can be generalizable
across coevolutionary relationships in an organisational context (Lewin & Volberda,
1999; McKelvey, 2002). In particular, these three dynamics have been chosen as they
reflect competitive dynamic relationships among components over the coevolutionary
landscape which are looking to achieve some fitness value (Kauffman, 1995a), IT-
enabled capabilities in this case are the components. Moreover, these three dynamics
together represent an action based approach to developing strategic capabilities
(Voelpel, Leibold, Tekie, & Von Krogh, 2005), which in turn may contribute to
148 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
competitive advantage (McKelvey, 2002). The macro coevolutionary dynamics are
described below.
Red Queen Effect
Evolutionary theorists portray how entities dynamically interact and coevolve
with one another via Red Queen competition. The term “Red Queen effect” was
originally introduced by Van Valen (1973) based on the conversation between the Red
Queen and Alice in Lewis Carroll's Through the Looking Glass. In that story, Alice
realizes that although she is running as fast as she can, she is not getting anywhere,
relative to her surroundings. The Red Queen responds: “Here, you see, it takes all the
running you can do, to keep in the same place. If you want to get somewhere else, you
must run at least twice as fast as that!”(Carroll, 1960). Van Valen (1973) has used this
analogy to describe interactions between participants in dynamic systems and how
they maintain relative fitness amongst them in coevolutionary relationships. Since
then, the Red Queen effect has been used to explain dynamic and chaotic behaviours
in a variety of setting ranging from biology to organisational studies (Derfus, Maggitti,
Grimm, & Smith, 2008; Kauffman, 1995a).
In the context of IT-enabled capabilities, the Red Queen effect mainly describes
the macro coevolutionary relationships among firms competing for IT-enabled
capabilities in a business landscape (McKelvey, 1997c; Tanriverdi, et al., 2010)
because it is closely related to the notion of competition as firms compete for valuable,
rare, inimitable and non-substitutable IT enabled capabilities (Grant, 1991). In the
complex adaptive business system, each firm’s adaptation moves to achieve particular
IT-enabled capabilities (e.g. other organisational resources and capabilities) can cause
reciprocal movement of the rival firms over the landscape and other institutional and
external factors, such as technological advancement, market demand, etc. together
change the competitive landscape’s topography (Tanriverdi, et al., 2010).
In the context of macro coevolutionary relationships, the Red Queen can be seen
as a challenge in which, a firm contests to match or exceed the performance or fitness
of its rivals by adopting, reconfiguring or innovating new IT-enabled capabilities
(Baum & McKelvey, 1999c; Kauffman, 1995b; McKelvey, 1999). In these contests,
acquiring new IT-enabled capabilities may improve competitive advantage of the focal
firm over the competitors in the landscape. The only way rivals can improve their
strategic advantage relative to the focal firm is by acquiring at least similar or better
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 149
IT enabled capabilities so that the rival firm can exceed the focal firm in the
competition of achieving strategic advantages. For instance, the Commonwealth Bank
of Australia (CBA) has superior competitive advantage over its’ rival banks, Westpac,
NAB and ANZ due to an easy to use and all-in-one mobile banking application,
according to the recent Forrester report (Zhi Ying Ng, 2018). The app-enabled
capabilities such as, money transfer using mobile number, paying bill by taking a photo
of it and setting up future payments make the CBA app better at attracting more
customers and likely to achieve better competitive advantage over the rival banks. If
the rival banks want to be ahead in the competition, then according to Red Queen
analogy they need to come up with better IT-enabled capabilities than the CBA’s.
Once the rival achieves a better advantage than the focal firm, it waits for some
time period, complexity researchers term the waiting period as Nash equilibrium
period (Kauffman, 1993) subsidiary, before it starts to looking for more improvement
in the IT-enabled capabilities driven by selection of new IT-enabled capabilities and
niches as well as by managerial adaptation that determines the scope of the
organisation (Madhok & Liu, 2006). Again, it triggers further search for improving
IT-enabled capabilities. Therefore, in the macro coevolutionary run for achieving
better IT-enabled capabilities, each firm is forced by the rival firms in an industry to
participate in a continuous action and development race such that firms end up racing
as fast as they can to keep ahead in the competition (Barnett & Sorenson, 2002).
Researchers have discussed that firms that are more than active in sensing the
competitive position of the rivals and responding accordingly is likely to improve their
competitive advantage (Banker, Cao, Menon, & Mudambi, 2013; Overby, Bharadwaj,
& Sambamurthy, 2006); also that firms that are slower than their rivals in creating
opportunities via IT enabled capabilities are likely to experience relatively lower
competitive advantage (Overby, et al., 2006; Sambamurthy, et al., 2003). However,
the Red Queen effect can have negative impacts or consequences (Barnett & Hansen,
1996); for example. frequent changes in the IT-enabled capabilities might affect the
sustainability of competitive advantage. Recognising IT-enabled capabilities is a time
consuming task, and selecting and adapting the new IT-enabled capabilities in the
business can be difficult due to different organisational factors, such as, the cognitive
receptiveness of the local managers (Szulanski, 1996). Therefore, (Voelpel, et al.,
2005) suggests that rather than running harder than the competition, it is better to run
150 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
differently and act more smartly than rivals by developing certain organisational
capabilities; technology, consumer, profitability and business system infrastructure
sensing capabilities.
The longer a firm can monopolise a market and enjoy first-mover advantages
based on a new competitive action, the greater the benefits it enjoys (Lieberman &
Montgomery, 1988). Rapid response to the competitive actions of the rivals require
awareness, sense and agile response to the actions (Overby, et al., 2006). More recent
tools, such as, big data and predictive analytics (Fan, Lau, & Zhao, 2015), text and
web mining (Anica-Popa & Cucui, 2009) provide firms with IT-enabled capabilities
and competitive intelligence to predict rivals action accurately.
In sum, the Red Queen effect help organisation to achieve superior IT-enabled
capabilties so that it can obtain better competitive advantage than its rivals (McKelvey,
1999). The coevolution of IT-enabled capabilities via Red Queen competition changes
and gradually improves competitve advantage of firms. Hence-
Proposition 2a: The Red Queen competition can improve IT-enabled
capabilities of firms in a macro coevolutionary relationship.
Proposition 2b: The Red Queen Effect can positively influence the competitive
advantage of firms in coevolutionary relationships
Competitive Exclusion
The competitive exclusion principle implies that if two firms in an industry have
the same resource pool, the firm with a faster internal mutation/ change rate is likely
to evolve faster than their competitors in a new niche market and likely to surpass its
rivals’ fitness (Hardin, 1960). Given this analogy, the faster are coevolutionary
dynamics, the less likely firms will be held hostage to the law of competitive exclusion.
In brief, the law entails that two firms competing for the same IT-enabled capabilities
or competitive market position cannot coexist together. One of them will find a smart
way to survive in the competition (Voelpel, et al., 2005).
In the context of IT enabled capabilities where firms are in coevolutionary
relationships, competitive exclusion entails that competing firms are continuously
evolving their existing IT enabled capabilities so that they do not lock into a law of
competitive exclusion. For instance, among Australia’s pizza retailers, Domino’s has
been continuously ahead, in an unprecedented manner, of its competitors regarding
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 151
innovations, new IT enabled features and marketing (Rice & Martin, 2017). A recent
report (Hatch, 2018) shows that Domino’s profits are up by more than 30% year-on-
year. The other competing pizza retailers are hardly able to compete with Domino’s in
the market in terms of IT-enabled services within Australia, although the Australian
local pizza joints reign supreme over the big chains. Illustrative of this is Domino’s
mobile application discussed above. Pizza Hut is one of Domino’s closest
competitors,, however, the basic pizza ordering iOS for Pizza Hut is rated poorly for
service ( only 1.9 out of 5.0 rating in Apple store (and only 39 users rated), whereas,
Domino’s pizza ordering app scores 4.5 out of 5 (about 4000 customers rated)).
Although the local pizza shops are not offering such innovative services via IT
for their customers, they are avoiding the competitive exclusion (i.e. not locking
themselves into a position where they are unable to coexist with big chains such as
Dominos) by offering other incentives, such as discounted price, local flavour,
weekend or lunch or dinner time deals, etc. Overall in the Australian pizza retailer
industry in terms of IT-enabled capabilities no one has beaten Domino’s. The pizza
retailers who are weaker in the competition migrate into different niche market
(described in next section) (McKelvey, 2002).
The above example illustrates how competitive exclusion of IT-enabled
capabilities coevolve at the macro level and how it controls a firm’s competitive
position in the pizza industry. In the contemporary business environment, competitive
exclusion law forces a firm to engage in rapid and relentless innovations in IT based
products and services that can help the firm to achieve competitive advantage (Lewin
& Volberda, 1999). Successful firms are likely to compete with the rivals by creating
Niche (discussed in the next section) opportunities (Khanna & Venters, 2013) for the
customers to avoid head-to-head competition in the competitive landscape. Depending
on customer demand and product competition in the market, dominant firms mostly
survive in the Red Queen competition via IT-enabled capabilities (Sambamurthy,
2000); the weaker firms may get away from the competition due to competitive
exclusion (McKelvey, 2002). The stronger firms having better IT-enabled capabilities
obtain superior competitive advantage over the weaker firms and a few firms dominate
the competition via IT-enabled capabilities as well as well reputation regarding their
products and services (Roberts & Dowling, 2002; Selnes, 1993). Hence-
152 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
Proposition 3a: Firms with better IT-enabled capabilities in competitive
exclusion can achieve superior competitive advantage than the firms with weaker IT-
enabled capabilities.
Proposition 3b: The competitive exclusion law can influence firms with weaker
IT-enabled capabilities to compete to obtain improved IT-enabled capabilities.
Niche Separation
McKelvey (2002, p. 5) defines Niche in the context of resources as, “…a pool
of relevant resources- coevolves in its elaboration in conjunction with the elaboration
of the characters describing newly forming species”. For instance, Facebook is not just
a social media platform; as people started using it, the features of Facebook have
coevolved with the skills, demands and preferences of its users, and now it has become
one of the most popular platforms for news, marketing and advertisement, and
communication. From a social media platform, Facebook has become a platform for
news and advertisement i.e. Niche.
As mentioned at the beginning of this section, the three coevolutionary dynamics
are highly related to each other. In the Red Queen competition, when competitive
exclusion situation starts to dominate, pressure starts to increase and favours niche
separation and the beginning of coevolution of new niches and species (McKelvey,
2002). The coevolution in the new niche temporarily stops further coevolution, until
any new species enters into the new niche. For instance, in shared economy based
hospitality industry, Airbnb provides a network platform where customers can
collaboratively make use of under-utilized inventory via fee-based sharing. Individuals
can rent their empty rooms or entire house at reasonably lower costs than traditional
hotels and consumers can benefit by renting at a lower cost. This disruptive innovation
has become one of the most popular and demandable in an IT enabled sharing economy
niche in the hospitality industry (Zervas, Proserpio, & Byers, 2017). However, a few
competitors of the Airbnb, such as Homestay, and Flipkey by Tripadvisor are also
booming in the hospitality industry. Suppose that both of these Airbnb competitors are
in a competitive exclusion situation with almost similar IT-enabled capabilities
looking to achieve superior competitive advantage over each other. Let’s further
assume that, Airbnb introduces a new business, providing an option for booking air
tickets along with accommodation booking from the same Airbnb portal (new niche)
as customers travelling overseas might find it very useful and that new IT-enabled
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 153
capability would bring improved competitive advantage that its competitors. It is
important to note that weaker competitors of Airbnb such as WWOOFing (Working
Weekends On Organic Farms) create niche markets; for example the hosts expect
guests to stay a minimum of two weeks and that the guests do work on the farm, and
get a place to stay, and in most cases food as well.
The basic argument of niche separation in the context of IT enabled capabilities
is that, when firms reach a competitive exclusion situation, they create new IT-enabled
capabilities to increase their competitive advantage in a smarter way than their
competitors. Industries such as banking and finance have recently started creating new
IT-enabled capabilities (niches) to outdo their competitors. The banking industry has
been invaded by Fintech companies, that use technology as a catalyst to offer various
financial services to the end users more efficiently (Dapp, Slomka, AG, & Hoffmann,
2014). To survive in the competition, banks have been trying to achieve competitive
advantage over the Fintechs via IT innovation, collaboration, and a wide range of IT
enabled products and services. For instance, The Commonwealth Bank of Australia is
planning to launch private and permissioned block-chain solutions which will enable
banks to process payments more quickly and more accurately while reducing
transaction processing costs and the requirement for exceptions (Eyers, 2017). This
particular new IT-enabled capability will enable the CBA likely to exceed their
competitors in obtaining competitive advantage. Moreover, this IT-enabled capability
will create further IT enabled niche capabilities such as smart contracts or the direct
transfer of money from investor to issuer, etc. using block-chain. These niche
capabilities will likely influence CBA’s competitors such as, ANZ and Westpac to
come up with new IT-enabled initiatives to improve their competitive advantage in
the banking landscape. Hence,
Proposition 4: Firms with IT-enabled niche capabilities will likely to achieve
superior competitive advantage than their competitors.
Summary of the Macro coevolution of IT-enabled Capabilities
In summary, the above discussion on the three coevolution related dynamics,
Red Queen effect, competitive exclusion and niche separation shows that they are
interwoven together, each continuously influencing the other in a circular way
(McKelvey, 2002). In the context of IT-enabled capabilities, the Red Queen effect
stimulates firms in competition to acquire, reconfigure or innovate new IT-enabled
154 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
capabilities to improve existing fitness value (competitive advantage) at the macro
level (Lewin, et al., 1999). However, in a particular period, if competing firms the
point where they have almost the same IT-enabled capabilities and they try to achieve
same level of competitive advantage in the market, these firms face a situation in which
they compete for almost similar competitive advantage and market position; this is
called a competitive exclusion situation. Firms with stronger IT-enabled capabilities
may stay in the competitive exclusion situation, whereas firms with relatively weaker
IT-enabled capabilities attempt to achieve better IT-enabled capabilities via creating
new niche IT-enabled capabilities. However, while the majority of the competitors
look to achieve better competitive advantage, the focal firm with stronger IT-enabled
capabilities may find itself locked in a situation if the firms with relatively weaker IT-
enabled capabilities want to obtain better competitive advantage via niche, which
Kauffman (1993) terms as Evolutionary Stable region, where firm itself is a sole
competitor. Firms in Evolutionary Stable regions compete with the niche firms
creating new IT-enabled capabilities and this spiral of dynamic relationships to achieve
competitive advantage continues. The next section presents a complete coevolution
framework of IT-enabled capabilities.
5.6 A COEVOLUTION BASED FRAMEWORK OF IT-ENABLED CAPABILITIES
This study argues that IT-enabled capabilities coevolve at micro and macro
levels of organisation after they emerge from the interactions between IT assets and
organisational resources. Based on the argument, the preceding section highlights the
micro and macro coevolution in relation to IT-enabled capabilities and how they
influence BVIT. This section presents a coevolution based framework of IT-enabled
capabilities (Figure 5.5). The preliminary framework (Figure 5.3) only described the
position and existence of micro and macro level coevolution of the IT-enabled
capabilities. Figure 5.5 is a complete version that represents micro and macro level
dynamic mechanisms of the coevolutionary process related to the IT-enabled
capabilities.
The coevolution based framework of IT-enabled capabilities represents both
micro and macro coevolution together and shows how the three dynamic
coevolutionary phenomena fit. The two rectangle overlap as firms exist within a
competitive environment of other firms. One rectangle represents a focal firm and the
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 155
other represents other firms in the business landscape. The focus is the coevolutionary
relationships via IT-enabled capabilities with the other firms. The bidirectional dashed
line presents micro coevolution of IT-enabled capabilities internal to the focal firm. In
the micro-coevolution (discussed in section 5.4), the IT-enabled capabilities coevolve
with other IT-enabled capabilities within the focal firm. The bidirectional solid line
represents macro coevolution of IT-enabled capabilities. IT-enabled capabilities of one
firm influence IT-enabled capabilities of another firm via macro coevolution
(discussed in section 5.5).
Figure 5.5 A Coevolution Framework of IT-enabled Capabilities
The micro coevolution of IT-enabled capabilities is driven by variation, selection
and retention evolutionary processes, where evolution of an IT-enabled capability may
cause evolution of the other IT-enabled capabilities with which it is connected. The
mutual adaptation between two or more IT-enabled capabilities in focal firm level is
referred to as micro coevolution (Axelrod & Cohen, 2000). Moreover, the IT-enabled
capabilities also coevolve with the IT-enabled capabilities of other firms. Three related
coevolutionary dynamics can be highly related with the macro coevolution of IT-
enabled capabilities between firms. The Red Queen causes a focal firm to compete to
obtain IT-enabled capabilities superior to its competitors. The Competitive Exclusion
principle ensures that if two firms (for instance a focal firm and a competing firm) aim
to achieving competitive advantage via similar IT-enabled capability, then they can
IT-enabled Capability
IT-enabled Capability
Focal Firm
IT-enabled Capabilities Other Firms
Micro Coevolution
Macro Coevolution
Dashed Line: Micro coevolution; Solid Line: Macro coevolution
Focal Firm'sCompetitive Advantage
VariationSelection Retention
Red QueenCompetitive Exclusion
Niche Separation
Mutual Adaptation
156 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
hardly co-exist together. In this circumstance, if the focal firm for instance achieves
the competitive advantage, the competing firm looks for achieving niche IT-enabled
capabilities so that it can achieve competitive advantage in an alternative way (Kemp,
Schot, & Hoogma, 1998). Both macro and micro coevolution of IT-enabled
capabilities together helps firms to achieve competitive advantage. The relation
between the micro and macro coevolution of IT-enabled capabilities is broadly
discussed in the next section.
5.6.1 Relation between Micro and Macro Coevolution
In summary, the foundation premise is that micro coevolutionary order in IT-
enabled capabilities within firm emerges in the context of macro coevolutionary
selectionist competitive pressure, which is termed as nested coevolutionary effect
(McKelvey, 1997c). The coevolution of IT-enabled capabilities refers to the fact that
firms coevolve with other firms because of the changes in IT-enabled capabilities via
macro coevolutionary process (Baum & McKelvey, 1999c; McKelvey, 1999).
Whereas, in the micro coevolutionary process, IT-enabled capabilities, evolution of an
IT-enabled capability influences other IT-enabled capabilities with which it is related
and vice versa.
In the competitive business environment, environmental selection forces, such
as, market changes, consumer needs, new technologies, competitors’ strategies cause
variations in business product/technology (Madhok & Liu, 2006). Such variations in
the product and technologies trigger changes in the IT-enabled capabilities at micro
level and which happens continually. In contrast, coevolutionary changes in the IT-
enabled capabilities at micro level are infrequent and punctuated because an
organization cannot constantly change its internal structure, routines and strategies
(Hannan & Freeman, 1984). However, micro coevolution can outpace over macro
coevolution as well. For instance, if the focal firm has the tendency to upgrade its
operations more frequently via selecting new IT-enabled capabilities than faster than
the external competition with the other competitors (Madhok & Liu, 2006).
In the contemporary business environment, in particular macro coevolution of
IT-enabled capabilities outpacing micro coevolution is more likely to occur and poses
a significant challenge (Madhok & Liu, 2006). A faster pace of the external macro
level coevolution of IT-enabled capabilities relative the internal micro level
coevolution may cause negative effect on the focal firm’s competitive advantage. For
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 157
instance, if the IT-enabled capabilities of the focal firm do not coevolve with the
coevolution of the competitor’s IT-enabled capabilities, there is a high chance that the
competitive advantage of the focal firm will be negatively influenced (Madhok & Liu,
2006; McKelvey, 1997c; Morel & Ramanujam, 1999). For instance, although CBA
(suppose, it is a focal firm) is one of the top banks in Australian banking industry with
the topmost share in the market ($93B), has not yet adopted leading edge technology
like, Apple Pay to provide payment service to its customers. Whereas, its competitor,
ANZ is the first of the big banks (CBA, ANZ, NAB, Westpac) which has teamed with
Apple and provide a contactless payments so that customers can use their iPhone or a
smartwatch to pay for purchases (ANZ.com) and this it eventually has achieved better
competitive advantage than the focal firm CBA. Recently, CBA has signed agreement
with Samsung to provide payment service via mobile system (Davidson, 2018).
In a word, macro-micro ‘coevolutionary imbalance’ may compromise firm
overall competitive advantage at global level (Madhok & Liu, 2006). In a different
arena, Burgelman (1994) has found in his study on Intel that the internal selection
mechanism by mimicking market mechanisms and allocating the manufacturing
resources according to the sales margins played a key role to make the company as a
successful microprocessor company. For another perspective, it can be said that
selection mechanism related to IT-enabled capabilities at the micro level enables focal
firm to adapt itself with the changing IT-enabled capabilities of the competitors at the
macro level.
In sum, macro and micro coevolution of IT-enabled capabilities occur
simultaneously (McKelvey, 1997b), which constitutes the coevolutionary process. The
process occurs via a dynamic framework consisting of ongoing iteration of three
processes, variation, selection and retention internal to the firm referred as micro level.
The macro level coevolution of the IT-enabled capabilities causes the micro
coevolution (McKelvey, 1997b). The initiating punch for the coevolution can be
internal to the focal firm. For instance, Commonwealth Bank of Australia’s (CBA)
innovation lab has recently partnered with a Fintech company on a project where
natural language processing (NLP) and artificial intelligence (AI) to automate the
process of reviewing regulations and thus saving hundreds of manual processing hours
and cost related to the processing. This might encourage the other competitor banks
such as, NAB, ANZ and Westpac to come up with innovative ideas and engage digital
158 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
technologies such as, BI or machine learning techniques to bring value for
organisations.
In addition, the initiating trigger can come from broader market. For example,
block chain technology can be used for highly secured money transfer and record
keeping and thus it can subsequently reduce the cost of transaction processing. The
secured money transfers and record keeping via block chain technology can be a great
option for banks in competition to adopt to provide innovative and better services to
the customers. In general, to achieve competitive advantage, it is important for the
focal firm to adjust and manage the tensions between micro-macro levels and match
the rates of coevolution constructively (Madhok & Liu, 2006) so that it can obtain
superior competitive advantage over business landscape (Tanriverdi, et al., 2010).
Hence, I propose that,
Proposition 5: Well balanced micro and macro coevolutionary processes of IT-
enabled capabilities can enable focal firm to achieve superior competitive advantage
over rivals.
5.6.2 A Narrative Exemplary Case to Explain the Coevolution of IT-enabled Capabilities Framework and Internal Validation
This section adopts an empirical case study as a narrative to show how my
proposed coevolution framework of the IT-enabled capabilities helps to provide a
narrative explanation on coevolution phenomena in practical organisational context.
In addition, the case study also helps to provide a first step internal validation of the
proposed framework.
I have adopted Montealegre, et al. (2014) case study on U.S. National Oceanic
and Atmospheric Administration (NOAA) as a narrative to represent how my proposed
coevolutionary view on the IT-enabled capabilities can generate in-depth insights and
the case data also is used for internal validation. The authors adopted a coevolutionary
view to understand information systems (IS) development process. They investigated
dynamic processes of changes in IS development and how the processes change
(coevolve influencing each other) over time. In the first step, I have adopted their study
for validating my developed explanatory theories on the micro coevolution of IT-
enabled capabilities. However, this study does not provide a wider view of the macro
environment, therefore, I have made some assumptions to discuss how my proposed
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 159
macro coevolutionary view of IT-enabled capabilities work. In fact, majority of the
empirical study on coevolution mainly focuses on one of the coevolutionary
persepectives- micro and macro. Because, coevolutionary studies are longitudinal
(Lewin, et al., 1999) and based on the emphasis on myriad of events among various
components, it is significantly difficult and requires substantiative effort to conduct a
micro and macro coevolutionary study of a phenomenon.
Montealegre, et al. (2014) identified three distinct theoretical domains- 1)
Organization information services choreography (OISC), service interactions and
collaborations are managed via this domain, 2) Organization information services
orchestration (OISO), service processes are selected and interact though this domain
and 3) Organization information services instrumentation (OISI), via which services
are developed and architected. These three domains together form the coevolutionary
core of the Information services and changes in one of the domains trigger changes in
other.
I have particularly focused on the OISO domain as it is relevant with the context
of the IT-enabled capabilities. The OISO domain focuses on how business and
information service interact together and how information service capabilities9 (IT-
enabled capabilities) dynamically adapt to meet the changing needs of organisation.
The case study reveals that the IT-enabled capabilities in the information services can
be easily influenced by the users based on the strategic and tactical business
requirements of the business. The IT-enabled capabilities are selected based on three
fundamental aspects of the business- business goals, business context and business
dynamics. If a capability does not meet the requirements or any unplanned situation
occurs, then a different IT-enabled capability is chosen. Apparently, when an IT-
enabled capability is changed, the relative IT-enabled capability in the information
services also bears the effect and if it does not meet the three aspects mentioned above,
it is also changed by organisations. In brief, the IT-enabled capabilities are constantly
changing to meet business requirements and continuous information service
improvement via variation, selection and retention process. It also proves that micro
coevolution of the IT-enabled capabilities occurs when unplanned exception happens
9 Information Service are assumed as service provided via the means of IT systems. In other words, IT systems enable the business organisation with capabilities, which are IT-enabled capabilities to provide services in different levels in organisations.
160 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
in one of IT-enabled capabilities or IT-enabled capabilities do not align with the
broader business aspects (Benbya & McKelvey, 2006a), which is in alignment with
my proposed propositions related to the micro coevolution of IT-enabled capabilities.
To describe macro coevolution, suppose, there is another government
department X which is competing with the NOAA in developing IS. Further assume
that, both NOAA and X are in the process of implementing the same information
system, A. As both of the departments are different in operations and business needs,
it is quite normal that the system solution A will be different in both organisations
accordingly. However, the competitive advantage of the organisation will be how well
the system A adaptive with the changing business requirements and provides all the
needs for the end users and meets broader business goals. It is evident that, macro
coevolution is also affected by several key factors such as, political, economic,
cultural, demographic and technological etc. (Derfus, et al., 2008; Lewin, et al., 1999;
Montealegre, et al., 2014). In NOAA, the system A provides a special user engagement
capability which enables users to personalise dashboards and share the dashboard via
online service which ensure seamless operational efficiency within internal department
communication. However, the same system in organisation X, does not provide the
same feature and it may cause less user flexibility and hinder operational efficiency.
In this situation, the organisation X will try to provide the dashboard sharing option by
allowing customers to deploy dashboard via online, providing option to customise
them or even with the option to design their own dashboard in the cloud and deploy it
in the core information system. In brief, the dashboard sharing and conjuring capability
in NOAA may trigger further improvement in organisation X dashboard or even
inspire them to come up with unique solution such as, integrating power BI to input
customer data in the dashboard.
Therefore, organisations in competition are always in the run to improve their
IT-enabled capabilities which in terms improve their internal efficiency and
competitive advantage in the competitive business landscape. This is in alignment with
the red queen competition, which helps to improve IT-enabled capabilities as well as
competitive advantage. The above example also indicates that firms with relatively
weaker capabilities tend to provide added feature such as power BI integration option
for better CRM experience and thus create niche capabilities (IT-enabled), which
focuses on improving advantage in the market and internal efficiency. Though both
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 161
organisations possess the same IS, because of their different type of operations, the
competitive exclusion hardly applies here. However, if one of the organisations locks
into competitive exclusion situation, firms with relatively weaker IT-enabled
capability definitely acquires or innovates new IT-enabled capability such as power BI
integration to improve its business value and thus the hypothetical example helps to
internally validate my proposed propositions on the macro coevolution of IT-enabled
capabilities.
The above narrative helps to understand how ceovolution of IT-enabled
capabilities can be complex and also it helps to limitedly validate the framework of the
coevolution of IT-enabled capabilities by explaining it through the empirical case
description. The narrative has helped to establish an internal validity of the proposed
coevolution framework as it helps to provide a good understanding of the dynamics of
underlying relationships that is ‘why’ this phenomenon is happening (Eisenhardt,
1989). It is important to note that, the internal validation using the case study is a first
step of the validation process. An in-depth empirical case study can be conducted to
further validate the propositions and the framework.
5.7 CHAPTER SUMMARY
This chapter presents a coevolution perspective of IT-enabled capabilities and
how it influences competitive advantage. It argues that IT-enabled capabilities
coevolve internal to the firm with other IT-enabled capabilities (micro level) and
coevolve externally with the competitor’s IT-enabled capabilities (macro level).
Section Error! Reference source not found. presents an overall overview of
coevolution concept and its use in IS and strategic management research. It also
presents different coevolution typologies from which micro and macro coevolution
concepts have been chosen as an overarching lens to explore IT-enabled capabilities.
Section 5.3 presents a preliminary coevolution framework of IT-enabled Section 5.3 presents a preliminary coevolution framework of IT-enabled
capabilities, where the loci of micro and macro level coevolution of IT-enabled
capabilities are discussed. The micro coevolution focuses on the mutual changes in
two IT-enabled capabilities within the firm, whereas, macro coevolution signifies how
a firm’s IT-enabled capability changes the IT-enabled capability/es of other firms and
vice versa.
162 Chapter 5: A Coevolution Perspective on IT-enabled Capabilities
Coevolution Framework of IT-enabled Capabilities
Proposition
Proposition 1a: The evolutionary processes- variation, selection and retention can improve IT-
enabled capabilities of focal firm.
Proposition 1b: Micro coevolution of IT-enabled capability occurs when evolutionary
improvement of one IT-enabled capability causes evolution in the associated IT-enabled capabilities.
Proposition 2a: The Red Queen competition can improve IT-enabled capabilities of firms in macro
coevolutionary relationship
Proposition 2b: The Red Queen Effect can positively influence competitive advantage of firms in
coevolutionary relationships
Proposition 3a: Firms with better IT-enabled capabilities in competitive exclusion can achieve
superior competitive advantage than the firms with weaker IT-enabled capabilities.
Proposition 3b: The competitive exclusion law can influence firms with weaker IT-enabled
capabilities to compete for obtaining improved IT-enabled capabilities.
Proposition 4: Firms with IT-enabled niche capabilities will likely to achieve superior competitive
advantage than their competitors.
Proposition 5: Well balanced micro and macro coevolutionary processes of IT-enabled
capabilities can enable focal firm to achieve superior competitive advantage over rivals.
Table 5.3 The complete coevolution Framework of IT-enabled capabilities and strategies
IT-enabled Capability
IT-enabled Capability
Focal Firm
IT-enabled Capabilities Other Firms
Micro Coevolution
Macro Coevolution
Dashed Line: Micro coevolution; Solid Line: Macro coevolution
Focal Firm'sCompetitive Advantage
VariationSelection Retention
Red QueenCompetitive Exclusion
Niche Separation
Mutual Adaptation
Chapter 5: A Coevolution Perspective on IT-enabled Capabilities 163
Section 5.4 presents three processes, variation, selection and retention related to
the micro coevolution of the IT-enabled capabilities and section 5.5 presents three
macro coevolutionary dyanmics, Red Queen effect, competitive exclusion and niche
separation related to the macro coevolution of the IT-enabled capabilities and how the
macro coevolution influences a firm’s competitive advantage.
Section 5.6 presents a complete coevolution based framework of IT-enabled
capabilities. The section also discusses how micro and macro levels coevolution
together influence a firm’s competitive advantage. In addition, section 5.6.2 includes
an empirical case study to show how the proposed coevolution framework provides a
narrative explanation on the coevolution of IT-enabled capabilities organisational
context. This section also provides an internal validation of the proposed framework
and propositions. The complete coevolution framework of the IT-enabled capabilities
and firms’ competitive advantage and propositions in the chapter are presented in
Figure 5.5.
164 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
Chapter 6 Summary
What was done in the previous chapter: The previous chapter proposes a
co-evolution perspective of the IT-enabled capabilities and how it influences
competitive advantage.
What this chapter does: This chapter presents an operational approach
related to the co-evolution of the IT-enabled capabilities. In particular, it shows how
a co-evolutionary operational model, NKC model can be used to formalise strategies
in managing co-evolutionary competition in organisations.
What is still outstanding in later chapters:
Chapter 7: A CAS based framework on competitive advantage and a
discussion on the overall insights that I have developed in relation to BVIT.
6.1 INTRODUCTION
In this chapter, I have mainly focused on an operational approach related to the
co-evolution of the IT-enabled capabilities discussed in the preceding chapter. The
main goal specifically is to show that the co-evolution perspective of the IT-enabled
capabilities can result in more concrete strategies that can be tested by researchers
empirically to and used as guidelines for managers. In order to do so, I have used
Kauffman (1993) coupled fitness landscape model, NKC model to formalise strategic
aspects of co-evolutionary competition in organisations. I have translated the NKC
model of co-evolutionary complexity into an organisation context via IT-enabled
capabilities as “parts” or elements of firms similar as McKelvey (1999), where the
author has conceptualised firms in competitions that are related to each other via value
chain competencies. The approach taken here substitutes linear deterministic history
model by non-linear numerical simulation models (Baum & Singh, 1994) with
particular focus on co-evolutionary competition relationships among competing firms.
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 165
It is important to note that in the macro co-evolutionary interaction, a move by one of
the firms over landscape changes fitness value of relative firms with which it is
connected (McKelvey, 1999).
Specifically, my formulation of strategies are based on the Kauffman’s NKC
model to further explore co-evolutionary competition with these questions- 1) How to
manage co-evolution of the IT-enabled capabilities? 2) What levels (micro and macro)
of complexity might affect the overall adaptive success of firms comprising a co-
evolving system via IT-enabled capabilities? The analysis is completely based on the
simulation results obtained by Kauffman (1993, chapter 6). Kauffman’s theory allows
an interweaving between Porter’s co-evolutionary pocket discussion (Porter & Millar,
1985) and the RBV and competence based views (Teece, Pisano, & Shuen, 1997;
Wernerfelt, 1984)and multi-coevolutionary views of organisations (Baum &
McKelvey, 1999c; McKelvey, 1999). The key aim is to further unfold the potential of
CAS theory by extending the NKC model in the coevolutionary context of IT-enabled
capabilities and develop strategies similar to (McKelvey, 1999) and (Baum &
McKelvey, 1999c). The theories as form of strategies developed in this chapter are
exploratory in nature as it provides a way to explore greater in-depth of the theoretical
insights from the coevolutionary perspective of IT-enabled capabilities using NKC
model.
The next section 6.2 first introduces the NKC model- its’ key the variables and
parameters, assumptions and how the NKC model operates in computational
environment. This section also briefly discusses the research conducted using this
model in IS and referral disciplines. The following section 6.3 contains the
operationalisation of the NKC model components and strategies developed based on
the NKC simulation outcomes following Baum and McKelvey (1999c). The chapter
concludes with a summary (section 6.4). The next section presents a brief overview of
the NKC model and then it shows the applications of NKC model in management and
IS research.
6.2 APPLICATIONS OF NKC MODEL IN RESEARCH
This particular section presents NKC model and NKC model based research.
First, section 6.2.1 briefly introduces the key components, variables, assumptions of
the NKC model and highlights how the NKC model operates in computational
166 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
environment, which is the core of this chapter. The subsequent section 6.2.2 briefly
discusses how the model is used in IS and referral management disciplines for theory
development. The theory development approach that I have adopted in this chapter
based on the study of Baum and McKelvey (1999c) on whole-part coevolutionary
relationships and McKelvey (1999) research on rugged landscape, which are also
included in section 6.2.2.
6.2.1 The NKC Model
Kauffman (1993) introduced NK model as a theoretical tool to model complex
adaptive systems (e.g. species, organisations), where N is the number of genes that
represent an agent and K is the number of couplings between these genes in the species.
Each configuration of a set of genes can take A possible states and is associated with a
fitness value, which can be interpreted as performance if that particular configuration
is implemented. The species uses different types of search strategies like long jump,
hill climbing or trial-error search to find better position (better fitness) over the
landscape. The two parameters (N and K) of the NK model allow a modeller to create
tuneable fitness landscapes of varying degrees of complexity on which to test the
performance or fitness value of various search strategies. When there is little
interaction among the agents (i.e., low K), the resulting fitness landscape is “smooth”;
for instance, when K=0, the landscape has a single peak and thus smooth sides.
Conversely, when the agents are highly interdependent (i.e., high K), for K=N-1 the
resulting fitness landscape is “rugged”.
NKC (Kauffman, 1993) is an extension of the original NK model introduced to
study the coevolution among different species over the landscape. In Kauffman’s NKC
model, each individual gene is also considered to depend on the genes in the other
agents through C coupling with which it interacts. Hence, the adaptive move by one
agent may deform the fitness landscapes of its partners S; altering C, with respect to
N changes the landscape of the interacting agent species. Here, C refers to the
connection between the set of genes from two species S1 and S2. Co-evolution among
two species is modelled in NKC by signing to each gene in the genotype of species 1
“external” inputs from C genes in species 2, and vice versa, in addition to the K
“internal” inputs, which is only the difference between NK and NKC model
(Kauffman, 1993; Kauffman & Johnsen, 1991). If C > 0then a move by one species on
its landscape. It will influence the landscapes of its co-evolutionary partners.
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 167
The model assumes all external (C) and internal (K) interactions among agents
are so complex that it is only appropriate to assign random values from a uniform
random distribution to calculate their effects on the total fitness of landscape.
Therefore, for each of the possible K+C interactions, assuming that the number of
states an agent can take is A = 2, a table of 2(K+1+CxS) fitness contributions is created,
with all entries in the range [0.0, 1.0], such that there is one fitness for each possible
combination of K and C interactions for a specific agent. The fitness contribution of
each agent within an experiment is found from its individual table. These contributions
are then summed and normalized by N to give the actual fitness of the agent. The sum
of all the fitness contributions of all agents reflects the total fitness of the landscape.
Kauffman (1993) used random hill-climbing search to evolve each agent in turn,
i.e. each agent uses the current context of the other neighbour agents to determine
whether a random alteration to its configuration represents progress. From a given
configuration, an agent can alter one agent’s state randomly and can calculate the
resulting fitness. If the resulting fitness value is greater than the agent’s current fitness,
in the current environment, the agent adopts a new configuration and it causes a co-
evolutionary change in other agents’ configurations, which are connected to the current
agent; this is repeated for number of generations. They show how both inter
connections (C) and intra connections (K) epitasis affect a co-evolving system,
particularly in the attainment of Nash equilibria: “a combination of actions by a set of
agents such that, for each agent, granted that the other agents do not alter their own
actions, its action is optimal” (Kauffman, 1993).
6.2.2 Applications of the NKC Model in Management and IS Research
This section presents applications of NKC model in management and IS studies.
As discussed in Chapter 3, the use of CAS theory is very recent in IS discipline and
thus the NKC model has been used in few occasions within IS field, which will be
discussed briefly in this section.
Table 6.1 summarises the applications of the NKC model in various management
and IS studies. Kauffman (1993) NKC model has been used by a number of studies to
explore aspects of organisations and their adaptation in the business environment (e.g.
Levinthal, 1997; Rivkin & Siggelkow, 2007). Researchers have used the NKC model
as a theoretical lens to conceptually describe specific co-evolutionary relationships
among different components over fitness landscape (Ahouse et al., 1991; Levitan,
168 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
Lobo, Schuler, & Kauffman, 2002). Although there is a limited exploitation of NKC
model in social studies (Vidgen & Bull, 2011), a review of the related studies reveals
important insights on how and why NKC model has been used by researchers. Majority
of the studies have applied NKC model as a conceptual lens to management research
(e.g. Baum & McKelvey, 1999c; McKelvey, 1999). Other studies extend the NKC to
capture aspects of social systems and establish that management are not blindly
roaming over the fitness landscape, rather the landscape can be tuned to add different
parameters and explore their effect on the overall fitness value of the landscape (e.g.
Hordijk & Kauffman, 2005), while others go beyond extending the model,
implementing and testing the model in simulation environment (e.g. Levitan, et al.,
2002). Marion (1999) reconceptualises a case study of the microcomputer industry
using the NKC lens. Only one study uses the NKC in a qualitative manner to analyse
case study data of inter-firm networks in Japan (Colovic & Cartier, 2007b).
In IS discipline, a very few studies have been identified that are used NKC
model, specifically to the research on competitive advantage. For instance, Curşeu
(2006) used NKC model to interpret virtual team behavior and the dimensions of
cognition, trust, cohesion, and conflict. Moreover, Vidgen and Wang (2006a) have
used NKC model concepts to discuss how different elements of business process
management co-evolve each other. There are other instances in IS which indirectly use
theoretical interpretation of NKC model, like Tanriverdi, et al. (2010) who actually
have not used NKC directly rather they applied fitness landscape thinking to develop
strategies in managing IS alignment.
Author Application Research Method; Implications
(Ahouse, et al., 1991)
Co-evolution of firm strategies and co-evolution of belief systems have been proposed using NKC. In belief systems, species represent individuals who have N beliefs where each belief is evolved by K other beliefs. Each individual’s beliefs are also affected by C beliefs of other individuals (species). Fitness is measured as cognitive consistency. The model is also applied for firm strategies.
Conceptual; guidance on how to apply NKC in competitive strategy and belief systems.
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 169
(Kauffman, 1995a)
Technological co-evolution, where new technologies enter and influence others and vice versa which create opportunity for further technologies.
Conceptual; examples of coevolution.
(Caminati, 1999)
NKC is used to describe technological co-evolution, and how complementarity of technologies increases over time and how technology from one sector can influence technology in another sector.
Conceptual; in the early stage of innovation technologies were considered as chaotic as they compete for dominance. Calminati hypothesises that the technologies co-evolve over time by tuning K and C in the complex region.
(Baum & McKelvey, 1999b)
Kauffman (1993) co-evolutionary findings are used to interpret strategies for managing co-evolving competition in organisations so that the organisation can achieve maximum fitness.
Conceptual; by tuning K and C vale four co-evolutionary strategies are identified.
(McKelvey, 1999)
Porter and Millar (1985) value chain competency has been conceptualised using NKC lens to speculate how co-evolutionary value chain competency of one firm influence another competing firm.
Conceptual; Firm should match internal complexity K with environment and focus on moderate external competency C for maximum performance.
(Marion, 1999)
Apply NKC to reconceptualise an empirical case study on microcomputer industry to understand how an industry moves toward a stable regime.
Conceptual with reinterpretation of an empirical case study; Microcomputer industry fitness is a function of two interrelated activities: interdependence among actors in the network and the agreement on standards. Any changes in technology have less effect on the fitness function as industry focuses on incremental fitness increases.
(Chang & Harrington, 2000; Chang & Harrington Jr, 2003; Harrington
Co-evolution of the stores competing in the retail chains serving customers in different markets. Each store has N store practices, where K represents relationships between practices and C represents interactions among competing practices of other stores.
Theoretical development with computer simulation; centralisation of the stores is best in low market heterogeneity and decentralisation of the stores is best in high heterogeneity.
170 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
& Chang, 2005)
Fitness value is the customers who make purchases proportional to their ideal practices offered by the store. A headquarter species control the behaviours of competing stores characterised by centralised and decentralised form.
(Levitan, et al., 2002)
NKC is used to model the web of interactions within and between groups.
Theoretical development with computer simulation; For short search periods, larger organizations perform better as larger interconnected groups can test with a larger number of alternative strategies. For longer periods, smaller groups with a small number of external connections perform best as they can exploit random opportunities.
(Colovic & Cartier, 2007a)
NKC is used as an alternative lens to re-conceive qualitative case study of exploration and exploitation in nine inter-firm networks in Japan.
Case study; Different patterns of network, like colony, herd, pack and migratory are identified as a result of NKC reconceptualisation.
(Ganco & Agarwal, 2009)
Investigate the relationship between firms’ entry characteristics and their subsequent performances as contingent on environmental turbulence and stage of industry life cycle by simulating industry as an NKC landscape.
Theoretical development with computer simulation; Diversifying entrants outperforms entrepreneurial start-ups when turbulence is high.
(Curşeu, 2006)
CAS is used to conceptualise virtual team effectiveness. NKC model is considered to interpret virtual team behavior and the dimensions of cognition, trust, cohesion, and conflict.
Conceptual; neural network models are better alternative to NKC model and it is more suitable to model diverse agents and capture relationships among them.
(Vidgen & Wang, 2006a)
Co-evolution of business processes and Web services technology.
Conceptual; A business process infrastructure may become chaotic if processes and Web services are simple (low K) but interconnected (high C) and freeze if they are internally complex (high K) but loosely coupled (low C).
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 171
Table 6.1 NKC Applications in Management and IS Studies (Summarised from Vidgen and Bull (2011))
Among the NKC models described above, two of the models Baum and
McKelvey (1999a) study on whole-part co-evolutionary relationships and McKelvey
(1999) study on value chain competencies and how they can be managed to foster
competitive advantage are particularly relevant to this study for developing strategies
to manage IT-enabled capabilities. McKelvey’s model (McKelvey, 1999) provides as
a theoretical base to relate the co-evolutionary relationships among IT-enabled
capabilities with the competitive advantage of organisations. Baum’s model (Baum &
McKelvey, 1999a) serves as a guideline to formalise and propose strategies for
managing co-evolutionary competition of organisations (see 6.3).
The models are briefly summarised below-
McKelvey’s co-evolutionary lens on firm’s competitive advantage
One of the earliest models based on the core notion of complexity science is
McKelvey (1999) co-evolutionary based conceptual model on competitive advantage.
Built on the notion of NKC model developed by biologist Kauffman (1993) offering
universal principles explaining Darwinian natural selection theory, McKelvey
proposes that multi-co-evolutionary complexity in firms is defined by moving natural
selection processes in side firms and down to the parts level using examples of Porter’s
value chain level. The model focuses on the microstate activities by agents and the
assumptions of stochastic idiosyncratic microstates and how they co-evolve are
analysed. Competitive advantage is defined as a dependent variable and described
through Nash equilibrium conditions in NKC models. He translates the Kauffman’s
model into value chain level description, by taking particular attention on how value
chain landscape can be modelled, the underlying assumptions on NKC models to value
chain perspective and how the NKC models can better explain different aspects of the
competitive advantages with respect to different conditions.
Various computational models from the Kauffman (1993) book are directly
translated into value chain competencies and a range of strategic approaches which
most likely to foster competitive advantages that are derived from the outcomes of the
NKC models. Mckelvey has suggested a number of expected and surprising strategies,
like- “moderate complexity fares best and external co-evolutionary complexity sets an
172 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
upper bound to advantages likely to be gained from internal complexity” (McKelvey,
1999, p. 294).
Baum’s whole-part co-evolutionary competition lens in organisations Baum’s model has some relevance with the McKelvey (1999) model. First,
both of the studies have used Kauffman (1993) NKC model outcomes. Second, both
studies have formalised some strategies to manage co-evolutionary relationships in
organisational level, while Mckelvey’s strategies are particularly related to
competitive advantage, Baum’s strategies are related to managing whole-part co-
evolutionary competition.
Baum and McKelvey (1999a) review some unsuccessful attempts to
understand whole-part relationships in the management literature and use Kauffman
(1993) NKC coupled fitness landscape model to formalise some aspects of co-
evolutionary whole-part competition in organisations. The central argument is that
units of organizational evolution are nested and overlapping, such as individuals and
groups in organisation are integral parts and when they take part in evolution it’s hard
to demarcate any cleavage among them. The structure and patterns of relationships
among them arise from the interactions among various units responding to a series of
organisational goals, shift in the environment and different internal-external dynamics.
The features, such as, some individuals compete or co-operate, or individuals interact
with multiple groups for completing some specific tasks, and thus lower level units
typically out evolve and influence higher levels complicating co-evolution
considerably.
Drawing evolutionary theories, Baum and McKelvey proposed that the
inherently faster pace of evolution at individual and face-to-face-group levels
undermines the emergence of integrated, cooperative organization-level systems and
explains the inefficiency of organisational alignment strategies due to the faster pace
lower level co-evolution among organisational units. They proposed four alternative
“structure-tuning” strategies for managing whole-part co-evolutionary competition in
organizations by employing the Kauffman (1993) NKC model.
The reason for reviewing the NKC model related literature was to identify how
NKC model has been applied in different management studies, learn about the current
practices and applications of NKC and apply it to the BVIT study. The review of the
NKC model on management and organisational studies give several insights-
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 173
• NKC model has been mostly exploited for conceptually modelling to explore
co-evolutionary management phenomena, such as whole-part relationships in
organisational units (Marion, 1999), in economics (Kauffman & Macready,
1995). The C represents the connections of couple fitness landscapes of agents
in the system, such that adaptive moves by one agent interact (more or less
profoundly) with the fitness landscapes of other agents in the system. C
provides a natural way to couple different agents' landscapes; that is, each trait
of agent1 depends on K other of its own traits and of C other traits of agent2
and thus, C represents the number of agent2's traits that might co-evolve with
a given trait of agent1. Kauffman’s NKC framework thus affords a dynamic
model of couple landscapes whose ruggedness and richness of coupling can be
tuned and different organisational phenomena, which are irregular, and
sensitive to initial conditions, occasionally can cause unpredictable behaviours
can easily be represented using the NKC framework (Kauffman, 1993).
• Kauffman (1993 Chap. 6) carried out a series of co-evolutionary simulation
using the NKC model. In the simulation, Kauffman changes the N, K and C
values to explore how the resulting landscapes behave, analyses the common
patterns or behaviours to identify and understand the best strategies in different
combinations of N, K and C and then apply them to the analysis of
organisational phenomena. Once a basic NKC model is constructed different
patterns, findings and insights that can be achieved. Extensions to the NKC
model allow researchers to add features through tuning model parameters that
capture aspects of systems under study and acknowledge that researchers can
intervene through tuning the model parameters.
• The above review has only dealt with a fraction of research at the intersection
of NKC model and competitive advantage. In particular, the analysis represents
that the management studies have probed in to strategic challenges posed by
interdependencies between practices. Critically taking stock of this body of this
research as well as the field more broadly, it is fair to say that the research up
to now has been fairly fragmented and specifically focused on the strategic
perspectives, such as, what are the best strategies to choose, how to choose a
set of strategies in different situations to achieve better advantages than the
competitors and so on.
174 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
6.3 MANAGING THE COEVOLUTION OF THE IT-ENABLED CAPABILITIES
This section discusses the operationalisation of the NKC model into the context
of IT-enabled capabilities in section 6.3.1. The subsequent section 6.3.2 presents the
strategies developed based on the NKC simulation outcomes following Baum (1999).
Chapter 5 broadly discusses on micro level (internal) and macro level (external)
co-evolution of IT-enabled capabilities and its impact on competitive advantage. That
is, the IT-enabled capabilities do not merely evolve, they co-evolve with other IT-
enabled capabilities internal to organisations and with the competitors’ IT-enabled
capabilities. In a co-evolutionary process, the fitness landscape of one agent is altered
by the adaptive moves made by other agents at the macro level. At the micro level, the
co-evolution mechanism addresses mutual changes among the IT-enabled capabilities,
like, changes in ERP –enabled logistics (e.g., more accurate inventory data) is likely
to bring changes in E-commerce-enabled sales (e.g., showing items in or out of stock).
In contrast, the macro level co-evolution process features non-linear and dynamic
changes that pressurise organisation in competition to continually improve the IT-
enabled capabilities to maintain its fitness relative to the competitors (Baum & Singh,
1994). For example, when a firm can show the inventory levels of their stores on the
website, its direct competitors will likely follow.
McKelvey (1999) used Kauffman’s NKC model that allows to model value
chain competencies and suggest various strategies that may foster competitive
advantage. Based on McKelvey (1999) approach, I have used NKC model to
operationalise the co-evolutionary perspective of the IT-enabled capabilities in this
study. I have first translated the co-evolution of the IT-enabled capabilities using the
parameters of NKC model (Table 6.2). Then, I have followed Baum and McKelvey
(1999c) approach to formalise strategies on whole-part co-evolutionary competition.
Consistent with Kauffman (1993) as well as McKelvey (1999), I have conceived the
macro co-evolution as a process that couples the NK fitness landscapes of different
firms. However, I have made assumption that these landscapes of firms are connected
via one or more IT-enabled capabilities of the firms. In sum, to understand the strategic
relationships between firms in competition via macro co-evolutionary relationship, I
have translated Kauffman (1993) model of co-evolutionary complexity into a firm
context via IT-enabled capabilities as “parts” or elements of firms similar as
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 175
McKelvey (1999), where the author has conceptualised firms in competitions which
are externally connected to each other via value chain competencies. The approach
taken is similar as Kauffman (1993) did in evolutionary biology and McKelvey (1999)
followed Kauffman’s in modelling value chain competencies and I have followed
McKelvey (1999) in the context of IT-enabled capabilities. The proposed model
substitutes linear deterministic history model by non-linear numerical simulation
models (Baum & Singh, 1994) with particular focus on co-evolutionary competition
relationships among competing firms.
The section first translates Kauffman’s NKC model to firms with particular
attention to (1) how IT-enabled capabilities landscapes might be modelled following
McKelvey (1999) (section 6.3.1) and (2) how assumptions underlying Kauffman’s
models can be used to derive basic strategies to increase landscape’s fitness same as
(Baum & McKelvey, 1999c) and how these basic strategies related to the fitness
landscape can be used to develop more concrete level strategies to managing micro
and macro co-evolutionary competition in organisations (section 6.3.2).
6.3.1 Translation of NKC Key Assumptions in IT-enabled Capabilities Context
Kauffman (1993, chapter 6) presents a series of simulations and outcomes
generated from the simulations using the NKC model. The simulation in the
Kauffman’s model features a dynamic model of coupled fitness landscapes, whose
ruggedness can be tuned by changing values of N, K and C. McKelvey (1999) has
suggested that these assumptions can be applicable in the context of firms in
competition and thus he has applied the Kauffman’s model landscape into the context
of value chain competencies. As mentioned earlier, in this study, I have followed
McKelvey (1999)’s approach to translate the key assumptions of the NKC model into
the context of IT-enabled capabilities. Table 1.2 summarises the translation of NKC
model parameters into the context of IT-enabled capabilities and key assumptions that
I have made. For the purpose of readily understandable, I have mentioned both
Kauffman (1993) and McKelvey (1999) assumptions of each parameters of the NKC
model and I have presented my assumptions.
NKC Parameters and assumptions
Translation into the the IT-enabled capabilities context
176 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
S • Represents a species in Kauffman’s term, that is treated as a
homogeneous entity. Mckelvey uses it to denote number of firms.
• I have also used it to represent number of firms over the landscape.
N • It is the number of genes that represent an agent (section 1.2.1). In NKC
model, it represents an independent “part”. Mckelvey’s value chain
model denotes the number of subunits, production stations, value chain
units, competencies, and so forth.
• For the simplicity of my model, I have used it to represent number of
(heterogeneous) IT-enabled capabilities or number of agents that
represents the heterogeneous IT-enabled capabilities.
K • In Kauffman’s terms it measures epistatic links that inhibit change.
Mckelvey uses it to represent internal co-evolutionary density among
parts within a firm.
• I have used K to represent the internal co-evolutionary density among
various IT-enabled capabilities within a single firm.
C • Kauffman uses it to represent coevolving pair (gene or species). In
Mckelvey’s model, it is used to represent agents/microagents between a
pair of competing coevolving firms.
• I have used C to represent the number of interdependent IT-enabled
capability that connects between a pair of competing coevolving firms. In
broad sense, it measures external co-evolutionary density among firms in
competition
A • In Kauffman’s model, it is used to denote number of alleles (alternative
states) that a gene may take. Mckevely uses it to assume that any
alternative adaptive walk that agent takes to improve its fitness is limited
within two options- fitness remain unchanged or changed.
• I have used same assumption as Mckelvey did. The fitness value of the
IT-enabled capabilities are limited to two options- either the value will be
same or it will be changed to obtain a better fitness value.
W • Represents the total fitness value of all N agents. It is the average of all
its N agents, W=1/ N*Σwi,j. This parameter is used to denote overall
fitness value of NK landscapes both in Kauffman and Mckelvey.
Adaptive
walk
Evolution can be thought of as an adaptive walk over the fitness
landscape of the IT-enabled capabilities. At each time period during
simulation, a firm improves its IT-enabled capabilities (agents) by
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 177
surveying all the other one-change neighbouring agents and randomly
selects one that offers improved fitness. The agent stays same, if none
offers better fitness.
Table 6.2 Translation of NKC model into the context of IT-enabled capabilities
6.3.2 Strategies to Managing Micro and Macro Co-evolutionary Competition in Organisations
In this section, I have first discussed four basic strategies based on Kauffman
(1993) NKC model simulation results proposed by (Baum & McKelvey, 1999c).
(Baum & McKelvey, 1999c) suggest four basic strategies that represents how co-
evolutionary relationship can be tuned so that organisations can achieve increased
effectiveness (fitness value). The authors also discuss the underlying rationale behind
the strategies observed from Kauffman’s simulation and they have proposed some
specific operationalisations of these propositions in the context of firms.
In this study, I have followed Baum’s approach (Baum & McKelvey, 1999c)
and propose four concrete strategies to managing micro and macro co-evolutionary
competition of IT-enabled capabilities in organisations. The strategies are proposed in
relation to the Strategy A and Strategy B of Baum and McKelvey (1999c) in Table 6.3.
The rightmost column of Table 6.3 contains the mapping between C and K with my
proposed coevolution framework of IT-enabled capabilities, the middle column
contains the rationale behind the NKC model and leftmost column contains Baum’s
strategies.
Strategies proposed by Baum and McKelvey (1999c) following Kauffman’s NKC model
Rationale behind the model
Proposed concrete strategies to manage co-evolutionary competition
Strategy A: Raise organisation’s K when C is high
When C is high- the likelihood of reaching Nash equilibria is low. High K agents get higher mean pre nash equilibria
Strategy 1: When macro co-evolution is High, Increase micro co-evolution of IT-enabled capabilities. • Strategy 1.1: Increase Variation
by continual incremental
178 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
if paired with low K agents
reorganising and reconfiguring of IT-enabled capabilities.
• Strategy 1.2: Aid selection mechanism by employing multiple, inconsistent and changing performance measures of IT-enabled capabilities.
Strategy B: Lower organisation K when C is low
When C is low- the likelihood of reaching Nash equilibria is high. Lowering K increases access to local optima with high fitness peaks at Nash equilibria
Strategy 2: When Macro Coevolution is Low, Lower Micro Coevolution of the IT-enabled Capabilities. • Strategy 2.1: Aid selection
mechanism by adopting comparable performance measures of the IT-enabled capabilities.
• Strategy 2.2: Adopt Modular IT-enabled capabilities.
Strategy C: Balance organisation K and C
Already implied via strategy A and B
Match between C and K is discussed via the proposed strategies 1 and 2.
Strategy D: Lower C
When C is low, K can be lowered, which can increase access to local optima with high fitness peaks at Nash equilibria
Placed as future work.
Table 6.3 Strategies for managing Micro and Macro Coevolutionary
Competition in Organisations
Strategy 1: When macro co-evolution is High, Increase micro co-evolution of IT-enabled capabilities
When the external complexity (macro co-evolution) of the IT-enabled
capabilities is high, then one way of balancing the macro co-evolution is to increase
the internal complexity (micro coevolution) of the IT-enabled capabilities. The
strategy is proposed based on the ‘nested coevolutionary effect’ by McKelvey (1997c),
where the author argues that micro co-evolutionary mechanisms appear within the
context of macro co-evolution with the underlying principle to attain external fitness
value. In the context of this study, this means that macro level and micro level co-
evolution of the IT-enabled capabilities jointly influence competitive advantage.
Madhok and Liu (2006) in the context of multi-national companies have argued that
macro co-evolution outpacing micro co-evolution may negatively impact on the
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 179
overall competitive advantage. They further suggest that internal micro level co-
evolution is in fact a part of managerial adaptation efforts at the external macro level
changes. There are two ways in which organisations can increase micro level co-
evolution of the IT-enabled capabilities (internal to organisation) to balance with the
macro level co-evolution between two or more organisations, which relate to variation
and selection and are described in the following sections.
Strategy 1.1: Increase Variation by continual incremental reorganising and reconfiguring of IT-enabled capabilities
The first proposed strategy to increase micro co-evolution is to increase
variations in the internal IT-enabled capabilities. As discussed in the previous chapter,
variation is to create novelty in the internal IT-enabled capabilities (Volberda &
Lewin, 2003). In the context of IT-enabled capabilities in organisational settings,
organisation can increase internal micro co-evolution via variation mechanism by
continual incremental reorganisation and reconfiguration of exiting IT-enabled
capabilities (Chae, 2014). The terms continual refers to the fact that the business
environment is continually changing, which requires the organisation to adjust its
internal sets of resources, capabilities and competencies (Levinthal, 1997). In addition,
incremental implies that the continual changes take place in the IT-enabled capabilities
does not pose significant threat to any existing elements of the business (Wolfe, 1994).
The incremental reorganising of the IT-enabled capabilities involve minor
modification of the interactions of IT-enabled capabilities or pursuing incremental
innovation (Chae, 2012). In the service science literature, incremental formulation
results in many successful services. For instance, United Parcel Service (UPS) is very
well known to adopt incremental reorganising variations into logistic management.
UPS preliminarily focuses on improving package delivery service, but later on they
emphasise on delivering specialised service offerings, such as inbound logistic
management, outbound logistic management and reverse logistic management via
incrementally modifying existing capabilities (Sawhney, Balasubramanian, &
Krishnan, 2004). Organisations today for instance can modify ERP-enabled service
delivery capability with the emphasis on enterprise wide data management, reporting
and visualisation by incrementally adding predictive analytics. Such reorganising can
actually increase connections with the existing IT-enabled capabilities, such as, ERP-
enabled customer data management, which is a way to increase internal connections
180 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
among IT-enabled capabilities. In Kauffman’s term Kauffman (1995a), variations via
incremental reorganising is a safer strategy as agent (climber) keeps moving to high
peaks.
According to Kauffman (1995a) simulation, variations via reconfiguration can
be compared as combinations of many short walks and occasional long jumps over
fitness landscape that provides an optimised strategy for finding solutions. The
incremental reconfiguration of the IT-enabled capabilities involves finding alternative
solutions than what organisations currently have. The nature of this particular
variations can be demanding as it deals with the existing uncertainties present in
business (Birkinshaw, Bessant, & Delbridge, 2007). Incremental reconfiguration
involves bringing new resources, such as, big data or cloud computing and combine
and reconfigure the existing architectures to improve existing set of capabilities (Chen,
et al., 2012). For instance, IBM in its early days in the 1990s was suffering from
immense market and financial losses due to its reliance on mutation for service
innovation (O'Reilly III, Harreld, & Tushman, 2009). However, IBM realised this
particular issue and in response, it introduced variations via reconfiguring emerging
business opportunities with the existing service innovation strategies that gave IBM
long term business growth with innovative services (O'Reilly III, et al., 2009).
Strategy 1.2: Aid selection mechanism by employing multiple, inconsistent and changing performance measures of IT-enabled capabilities
The second strategy to increase the micro co-evolution of the IT-enabled
capabilities is to guide the selection mechanism by adopting multiple, inconsistent and
changing performance measures of various IT-enabled capabilities based on similar
idea proposed by Baum and McKelvey (1999c). In the context of IT-enabled
capabilities, multiple, inconsistent and changing performance measures of the IT-
enabled capabilities can be initiated locally, i.e., it is an ‘exploitative’ search, in which
locally (within firm boundary) best known good IT-enabled capabilities are identified,
routinized, extended and evaluated that may lead to positive outcomes. However, if
the time is limited, then ‘exploratory’ search, experimenting new IT-enabled
capabilities outside from organisations likely dominates, which may lead to globally
best results (March, 1994). Meyer (1994) argues that if the overall performance of an
organisation is considered to be uncertain, then multiple, inconsistent and differential
performance measures can facilitate organisational adaptation because the
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 181
measurement approach sets up an upper limit of performance on a given dimension,
the dimension loses prominence and performance in other domain increases
accordingly (Baum & McKelvey, 1999c). Moreover, he suggests that if the
performance is a fixed target, then multiple, inconsistent and differential performance
measures can facilitate organisational adaptation (Baum & McKelvey, 1999c). When
multiple, inconsistent and changing performance measures are initiated in the context
of the IT-enabled capabilities it slows down the speed of evolution by increasing
reconfigurations of the IT-enabled capabilities locally or bring over new IT-enabled
capabilities that ultimately increase internal connections (Baum & McKelvey, 1999c).
Strategy 2: When Macro Coevolution is Low, Lower Micro Coevolution of the IT-enabled Capabilities
In contrast with the proposed Strategy 1, when the macro co-evolution of the
IT-enabled capabilities is low (low C), then the way to fit between macro and micro
co-evolution is to reduce the micro co-evolution of the IT-enabled capabilities
(decrease K). Basically, macro co-evolution is characterised as market-driven and
constantly changing, in contrast, micro co-evolution internal selection pressurise, for
instance on the routines or organisational structure are not intense always (Cyert &
March, 1963). However, micro co-evolution can outpace macro co-evolution in some
cases. For instance, in an automobile industry, Toyota and Honda exhibit superior
capabilities in new product offering than the other competitors (Fujimoto & Clark,
1991). The Japanese firms have a short product development life cycle. Usually the
Japanese car manufacturers offer new features in the vehicle or newly designed vehicle
in every five years, where US competitors redesign their cars every seven years. Such
internal variation and retention speed by the Japanese car manufacturers enables them
to offer new features or new cars in the US market faster than the local US
manufacturers, which means macro co-evolution is slower than the micro co-
evolution. In such case, faster micro co-evolution can shape the landscape faster than
the external macro co-evolution (Madhok & Liu, 2006).
There are two ways in which organisations can lower micro level co-evolution
of the IT-enabled capabilities (internal to organisation) to balance with the macro level
co-evolution between two or more organisations, which relate to variation and
selection and are described in the following sections.
182 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
Strategy 2.1: Aid selection mechanism by adopting comparable performance measures of the IT-enabled capabilities This proposed strategy is almost opposite to the strategy 1.2. Baum and
McKelvey (1999c) argues that adopting comparable performance measures can bring
benefit in organisational level from an evolutionary view point as it simplifies the
range of possible configurations for evolution to occur in particular multi divisional
organisations where the performance of each division is represented by same metric,
such as, sales and the performances are comparable. In fact, the adoption of
comparable performance enhances evolution of capabilities at the organisational level
by improving coexisting processes as organisations inquire or reconfigure new
capabilities (exploration) and improve capabilities that are effective (exploitation)
(March, 1994).
In the context of the IT-enabled capabilities, the selection of the IT-enabled
capabilities can be aided by comparable performance measures so that the chosen set
of the IT-enabled capabilities can be beneficial for organisations. The comparison
between similar capabilities has been popular in measuring process performance in
particular in manufacturing industry (Chen & Chen, 2004). It helps practitioners to
determine whether or not two similar processes are equally capable. In a similar way,
during the selection process, the two or more IT-enabled capabilities can be compared
to determine whether both generate similar level of performance for organisations.
Suppose, organisation may have two different implementing options- traditional ERP
system and salesforce CRM to improve customer service delivery process i.e. ERP-
enabled and salesforce CRM enabled customer service. The organisation can adopt a
performance measure of the two chosen capabilities such as, rate of service to
determine the one is capable of improving customer service process. Such comparable
performance measures can be considered to simplify the optimisation problem for
complex organisations (Baum & McKelvey, 1999c). In terms of the NKC model,
adoption of comparable performance measures lowers internal complexity K
(Kauffman, 1993), which helps organisations to lower K when C is low.
Strategy 2.2: Adopt Modular IT-enabled capabilities Organisations can adopt modular IT-enabled capabilities (Rai, Venkatesh,
Bala, & Lewis, 2010) to decrease micro co-evolution, when the macro co-evolution is
high. Modular systems are composed of elements, which can independently perform
distinctive functions (Simon, 1962). As modular elements can evolve autonomously
Chapter 6: Towards Strategies for Managing IT-enabled Capabilities 183
without hampering overall structure of the system, they are often robust in the case of
any changes than tightly coupled systems (Pil & Cohen, 2006). In a modular system,
like an ERP system consisting of different modules- sales, customer management,
service delivery and so forth; each of the module provides some capabilities to support
particular business functions. These capabilities are called modular capabilities (Pil &
Cohen, 2006). In a similar way, if the above definition is matched with the concept of
IT-enabled capabilities, then, it can be said that, each of the ERP modules (i.e. IT
assets) interact with some organisational resources, such as, business units, operational
employees, processes, etc. and their interactions give rise some IT-enabled
capabilities, such as, ERP(sales module)-enabled sales, ERP(service delivery module)-
enabled service delivery process etc. In contemporary environment, IT has become
highly modular and continuously changing in nature and that is making the IT-enabled
capabilities evolving faster (Tiwana, et al., 2010).
The modular IT-enabled capabilities can be used to meet with changing
business demands- provide organisations with far more competencies to grow rapidly
and profitably. Rai, et al. (2010) identified that Delivery Corp encapsulated services
from core legacy systems using component based architectures. They further found
that the organisation developed separate subsystems that enable providing various
services- a subsystem that handles brokerage, a subsystem that handles forwarding and
so on. The separation of the services via different application components makes it
easier for the organisations to maintain loose coupling that lower connections (K)
among services so that they can be combined efficiently. Modular IT-enabled
capabilities can be found in digital platform architecture (Tiwana, et al., 2010). By
promoting partitioning of different modular capabilities on the core platform,
organisations can reduce the cost of innovation as the new system does not need to be
changed or innovated from scratch as new modules can be introduced without limiting
effects on the core structure (Gawer, 2009).
Modular capabilities helps to lower down connections that means it maintains
loose coupling among different components and hence different IT-enabled
capabilities. However, developing modular IT-enabled capabilities is a longer process
and it is often hampered by organisational tendency to acquire immediate business
needs rather than long term capabilities. Nonetheless, organisations can adopt
developing modular IT-enabled capabilities to lower down the connections K between
184 Chapter 6: Towards Strategies for Managing IT-enabled Capabilities
various IT-enabled capabilities in organisations and thus balance evolutionary
connection C.
6.4 CHAPTER SUMMARY
This chapter presents how a co-evolutionary operational model, NKC model
(Kauffman, 1993) can be used to formalise strategies in managing micro and macro
co-evolutionary competition in organisations, in particular in the context of IT-enabled
capabilities. Chapter 5 broadly discusses the micro level (internal) and macro level
(external) co-evolution of IT-enabled capabilities and its impact on competitive
advantage. This chapter has extended the discussion on coevolution by translating
NKC model into the context of IT-enabled capabilities (section 6.3.1) and developing
four strategies based on the simulation results obtained by Kauffman (1993, chapter 6)
following Baum and McKelvey (1999c) approach (section 6.3.2). The strategies are
proposed in relation to the Strategy A and Strategy B of Baum and McKelvey (1999c).
The key aim of proposing strategies is to provide guidance for managers so that they
can better manage the micro and macro coevolution of IT-enabled capabilities in
organisations.
Few limitations are related to the use of the outcomes of NKC model. Any
computational model can never represent a real world scenario. Therefore, the
parameters in NKC model represents a very simplified representation of the events in
a firm. So, the validity of the model has little validity. Nevertheless, NKC models can
provide very useful insights about co-evolutionary relationships (McKelvey, 1999). In
addition, the moves in the NKC model is conceived as random and their adaptive value
is randomly determined. However, in real life these events are less random (McKelvey,
1999).
The next chapter presents a CAS-BVIT framework and discusses important
insights from overall dissertation. It also addresses the limitation of the study and
discusses future research opportunities.
Chapter 7: Discussion and Conclusion 185
Chapter 7: Discussion and Conclusion
This chapter explains the dynamic mechanisms of BVIT, in particular
competitive advantage through a CAS based framework. This is followed by a detailed
discussion on the insights that I have obtained from the study. The structure of the
chapter is as follows. The first section presents the study CAS conceptual framework
on BVIT. The subsequent section presents implications of the proposed CAS
framework by comparing it with major extant BVIT models. The chapter concludes
by explaining the theoretical contributions, practical implications, limitations and
potential future research.
7.1 A CAS-BVIT FRAMEWORK
This section presents a CAS-BVIT framework that reflects how I have applied a
CAS theoretical lens to view how BVIT contributes to strategy in contemporary
organisations’, how IT-enabled capabilities emerge from IT assets and organisational
resources, and how these capabilities influence competitive advantage. This CAS view
of the BVIT sees competitive advantage as the outcome of the complex emergence and
coevolution of IT-enabled capabilities (Figure 7.1). It presents a consolidated version
of the whole BVIT creation process from a CAS lens including the complex emergence
and coevolution of IT-enabled capabilities. It includes all the components of proposed
two frameworks together to instantiate a wide view and broader understanding of the
dynamic way of BVIT creation process. The proposed CAS based BVIT framework
contains two key foci,
1. From IT assets and organisational resources to IT-enabled capabilities
via complex emergence, and
2. From the IT-enabled capabilities towards competitive advantage via
micro and macro coevolution.
In the first part of the CAS-BVIT framework, I argue that IT assets and
organisational resources come together in a relationship that gives rise to IT-enabled
capabilities, as an emergence process following ideas the from the Nevo and Wade
(2010) study on the strategic advantage of IT assets. IT assets are defined as those that
are used to store, process and disseminate information (Wade & Hulland, 2004), and
186 Chapter 7: Discussion and Conclusion
organisational resources are other tangible or intangible factors owned by
organisations (Helfat & Peteraf, 2003).
I argue that the emergence of IT-enabled capabilities from the interactions
between IT assets and organisational resources is non-linear and dynamic in nature. I
propose a complex emergence perspective (Halley & Winkler, 2008) that helps to
explain the dynamic rise of IT-enabled capabilities. Additionally, I suggest that four
enablers (see section 4.3 in Chapter 4): compatibility (Nevo & Wade, 2010) - enables
the interactions between the two entities- IT assets and organisational resources, self-
organised management (Vidgen & Wang, 2009)- spontaneous managerial practices
that support the interactions, semi- structures (Brown & Eisenhardt, 1997)- provide
flexible structures to accommodate unpredictable emergence of the IT-enabled
capabilities, and simple rules (Eisenhardt & Sull, 2001)- provide schemas to guide the
unpredictable emergence in a way that is beneficial for organisational processes. All
of the enablers together help the complex emergence of the IT-enabled capabilities to
occur. Overall, a complex emergence model of IT-enabled capabilities (Figure 7.1)
and several propositions (Table 7.1) are proposed in this study.
Regarding the second part of the CAS-BVIT framework, I argue that the IT-
enabled capabilities start mutually changing with other IT-enabled capabilities at the
micro level (internal) and macro level (external) of organisations10. I argue that a
coevolution perspective (Lewin, et al., 1999) on IT-enabled capabilities can better
explain the reciprocal changes. Based on the coevolution framework by Lewin and his
colleagues (Koza & Lewin, 2001; Lewin, et al., 1999; Lewin & Volberda, 1999), I
propose a coevolution perspective on IT-enabled capabilities that explains how IT-
enabled capabilities coevolve in micro and macro levels of organisations and influence
competitive advantage of organisations. Following Chae (2014), at the micro level,
three mechanisms - variation, selection and retention, explain coevolution of the IT-
enabled capabilities internal to the organisation. Following McKelvey (2002), at the
macro level, three macro coevolutionary dynamics - Red Queen effect, competitive
exclusion and niche separation, explain the competitive actions that organisations
undertake to obtain superior competitive advantage over competitors. This suggests
10 It is important to note that, though IT-enabled capabilities can mutually change with other organisational elements, such as, routines, capabilities, strategies, resources (Koza & Lewin, 2001; Lewin, et al., 1999), I have considered the mutual changes between IT-enabled capabilities only.
Chapter 7: Discussion and Conclusion 187
that coevolution of the IT-enabled capabilities actually follows a ‘nested’ mechanism
(McKelvey, 1997c) in which macro coevolution triggers micro coevolution of the IT-
enabled capabilities.
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188 Chapter 7: Discussion and Conclusion
Figure 7.1: A CAS-BVIT framework
The second part also addresses how the overall coevolution of the IT-enabled
capabilities influence competitive advantage of organisations. It reveals how, due to
the macro level competitive action-reaction, firms are highly prone to stay in the Red
Queen competition and are incentivised to take a variety of actions, such as adoption
of new IT-enabled capabilities or reconfiguration of the new ones that erode their own
and competitors’ advantage (D'Aveni, et al., 2010). The three macro coevolutionary
dynamics together represent an action based approach to developing strategic
capabilities (Voelpel, et al., 2005). Therefore, firms in the competition show rivalrous
behaviour to achieve superior IT-enabled capabilities and thus competitive advantage
over others (Chen, 1996). Such behaviour, aimed at achieving better IT-enabled
capabilities than rivals, erodes firms’ existing advantage as well as affecting the rivals’
advantages; this incessant rivalry resulting in a temporary advantage (D'Aveni, et al.,
2010). The competitive dynamics also increase hyper-competition in the industry (Lee,
2010). Under these circumstances, a firm on a dynamic business landscape can pursue
new, temporary advantages by availing itself of valuable, rare and nearly inimitable
IT-enabled capabilities and striving to concatenate a series of temporary advantages
over time, although consistently achieving new temporary advantages will be highly
challenging (D'Aveni, et al., 2010; Tanriverdi, et al., 2010). Thus, I propose a micro-
macro co-evolution model of IT-enabled capabilities (Figure 7.1) and several
propositions (Table 7.1).
As an extension of the second foci as well as to develop new insights from
analysing the outcomes of simulation model, in particular Kaufman’s NKC model
(Kauffman, 1993), I have followed Mckelvey’s approach (McKelvey, 1999) and
propose four high level operational strategies (section 6.3.2 in Chapter 6). The
strategies (new insights) are proposed based on the underlying rationale of Kaufman’s
NKC model. The proposed strategies focuses on the conceptual understanding of the
coevolution of the IT-enabled capabilities and serve as a way for managing micro and
macro coevolutionary competition in organisations.
Chapter 7: Discussion and Conclusion 189
Propositions related to the emergence perspective of the IT-enabled capabilities
Proposition 1 Greater compatibility between IT assets and organisational resources can positively influence the complex emergence of IT-enabled capabilities.
Proposition 2 Self-organised management to ensure the relationship between IT assets and organisational resources can positively impacts the complex emergence of IT-enabled capabilities.
Proposition 3 Self-organised management to ensure the relationship between IT and business can positively impacts their compatibility.
Proposition 4 Semi-structures to ensure the match between predefined goals with emergent IT-enabled capabilities can positively influence the complex emergence of IT-enabled capabilities.
Proposition 5 Well-defined simple rules can positively impact the complex emergence of IT enabled business capabilities.
Propositions related to the coevolution perspective of the IT-enabled capabilities
Proposition 1a
Focal firm can improve IT-enabled capabilities via variation, selection and retention evolutionary processes.
Proposition 1b
Micro coevolution of IT-enabled capability occurs when evolutionary improvement of one IT-enabled capability causes evolution in the associated IT-enabled capabilities.
Proposition 2a
The Red Queen competition can improve IT-enabled capabilities of firms in macro coevolutionary relationships.
Proposition 2b
The Red Queen Effect can positively influence competitive advantage of firms in coevolutionary relationships.
Proposition 3a
Firms with better IT-enabled capabilities in the macro level competition can achieve superior competitive advantage than firms with weaker IT-enabled capabilities.
Proposition 3b
The competitive exclusion law can influence firms with weaker IT-enabled capabilities to compete in obtaining improved IT-enabled capabilities.
Proposition 4 Firms with IT-enabled niche capabilities will more likely to achieve superior competitive advantage than their competitors.
Proposition 5 Well-balanced micro and macro coevolutionary processes of IT-enabled capabilities can enable the focal firm to achieve superior competitive advantage over rivals.
Table 7.1 Propositions related to the emergence and coevolution perspectives of the IT-enabled capabilities
190 Chapter 7: Discussion and Conclusion
In the next section, I will address how my proposed dynamic, non-linear
perspective is more useful for understanding BVIT in contemporary organisations than
the existing static, linear perspective.
7.2 FROM A STATIC, LINEAR PERSPECTIVE TO A DYNAMIC, NON-LINEAR PERSPECTIVE
One of the underlying arguments of the thesis is that the contemporary business
environment is no longer simple, linear and predictable. The deployment of digital
technologies has given rise to complexities, dynamism and unpredictability in
contemporary organisations (Merali, et al., 2012), which requires methodological and
conceptual alternatives to deal with these changes. Based on this argument, this study
has taken a dynamic and non-linear approach and adopted CAS theory (Dooley, 1996)
to explore the underlying dynamics related to BVIT generation.
One of the most prominent theories used to investigate the business value of IT,
the RBV approach, argues that firms possess IT resources that are valuable and rare
and that can provide firms with long term competitive advantage if the firms are able
to protect against resource imitation, transfer or substitution (Barney, 1991; Grant,
1991). However, the RBV has been criticised for being a static concept, unable to
adequately capture the nature of a dynamic business environment (Eisenhardt &
Martin, 2000; Priem & Butler, 2001). Considerations such as how resources are
developed, how they are integrated in the firm, how they are configured to obtain
competitive advantage in the dynamic business environment, have been under-
explored in the literature (Wade & Hulland, 2004). Therefore, the concept of dynamic
capabilities attempts to bridge this gap by adopting organisational and strategic
processes that help firms to manage resources into productive assets in the changing
business environment (Eisenhardt & Martin, 2000; Teece, et al., 1997). The dynamic
capabilities help a firm to adjust its resources so that it can maintain the sustainability
of the firm’s competitive advantage, which might be eroded in the dynamic
environment (Helfat & Peteraf, 2003).
A few prominent models in the IS literature partially account for the dynamics
related to BVIT generation, such as the Sambamurthy, et al. (2003) strategic model
linking IT competence to a firm’s performance via competitive actions, Tanriverdi, et
al. (2010) complex adaptive business systems based model of a firm’s strategic
competitive advantage, and the dynamic capability theory based models emphasising
Chapter 7: Discussion and Conclusion 191
competitive advantage (e.g. Kim, et al., 2011; Schwarz, Kalika, Kefi, & Schwarz,
2010; Wheeler, 2002). However, the underlying organisational dynamics driving the
relationships among IS and other organisational resources remain unclear, though they
are understood to be complex in nature (Tanriverdi, et al., 2010). How IT resources
and their related capabilities continuously emerge and evolve over time and how they
influence competitive advantage in the dynamic environment is still opaque. The
strategic value of resources lies in their inherent complexity, and attempts to explicate
causal explanations of this complexity are limited in the literature (Colbert, 2004);
neither are RBV and dynamic capabilities theories clear about this. Consequently, this
study has adopted a dynamic theory, CAS theory, that acknowledges such issues and
acknowledges that IT driven capabilities may stem from causal ambiguity, complex
relationships and/ or unpredictable path dependencies to influence competitive
advantage (Colbert, 2004).
Based on the Schumpeterian dynamics of disequilibrium (Schumpeter, 1934),
the CAS theory serves as an approach to explore the dynamics related to the emergence
of IT-enabled capabilities, from non-linear relationships between IT assets and
organisational resources. The CAS theory holds a dynamic opportunistic logic in this
study similar to Sambamurthy, et al. (2003), who suggested in relation to firm
performance, that superior firms achieve competitive advantage through the
continuous creation of valuable and rare IT-enabled capabilities and competitive
actions (D'Aveni, et al., 2010). This logic in the context of this study suggests that
competitive advantage can be eroded if rivals obtain superior IT-enabled capabilities
or uncover new market opportunities that threaten the focal firm’s competitive
advantage (Sambamurthy, et al., 2003). The CAS theory thus first draws attention to
the dynamic and complex emergence of IT-enabled capabilities. It then argues that
firms follow a coevolutionary strategic mechanism at the micro level that reconfigures
and adjusts various IT-enabled capabilities. Moreover, firms also allow coevolutionary
adaptation of the IT-enabled capabilities at the macro level, which helps firms look for
windows of opportunity in achieving unique IT-enabled capabilities (Barney, 1991)
superior to its competitors. The fit between micro and macro level coevolution of the
IT-enabled capabilities helps a firm to achieve greater competitive advantage over its
rivals. It also implies that the adoption of new IT-enabled capabilities may largely
influence and change other related IT-enabled capabilities at the micro level (Lewin,
192 Chapter 7: Discussion and Conclusion
et al., 1999). The dynamics at both micro and macro levels, together provide a firm
with better detection and exploitation opportunities (Mata, et al., 1995), i.e. identifying
and deploying IT-enabled capabilities so that it can acquire superior competitive
advantage over its rivals.
In sum, the complex emergence of the IT-enabled capabilities and the
coevolution between different IT-enabled capabilities inside organisations represent
the non-linear internal dynamics related to the IT-enabled capabilities. In addition, the
macro level coevolution of the IT-enabled capabilities between two or more firms
portrays external competitive dynamics related to the IT-enabled capabilities. The
micro coevolution occurs as a ‘nested’ mechanism within the macro coevolution of the
IT-enabled capabilities (McKelvey, 1997c) that a firm undertakes to outperform its
competitors in the dynamic environment and achieve competitive advantage via
obtaining valuable, rare and nearly inimitable IT-enabled capabilities (Barney, 1991;
Bharadwaj, 2000).
7.3 KEY INSIGHTS COMPARED WITH PROMINENT, TRADITIONAL BVIT MODELS
In this section, I have specifically addressed the limitations of the prominent,
traditional BVIT models, Nevo and Wade (2010), Melville, et al. (2004) and Wheeler
(2002), and discussed what I have added to each model to deal with the limitations.
Moreover, I have also discussed several specific implications that derive from my
proposed CAS-BVIT framework in section 7.3.1.
Nevo and Wade’s Model vs. The CAS-BVIT Framework
The RBV and systems thinking based BVIT model by Nevo and Wade (2010),
maintains that IT-enabled resources emerge from interactions between IT assets and
organisational resources which have strategic potential that can contribute to the firm’s
competitive advantage. However, the systems thinking based emergence concept used
in the Nevo and Wade’s model is static and linear in nature. One of the key reasons is
that the underlying components of the IT assets and organisational resources are
assumed to be stable and unchanged during the time when they are in the relationship.
This also results in the predictability of the outcomes of the relationships, i.e. IT
enabled resources and the emergent capabilities. These assumptions become
questionable in the dynamic business environment, where every element of an
Chapter 7: Discussion and Conclusion 193
organisation is constantly changing (El Sawy, et al., 2010; Tanriverdi, et al., 2010). In
a dynamic and complex environment, at the time any measures or hypothesized
emergent relationships are captured, one or more of the components of an organisation
will exhibit emergent moves, which may change the relationships between the
components, and in the new state previously hypothesised relationships are unlikely
to be valid (Tanriverdi, et al., 2010).
My proposed complex emergence view addresses the limitations of Nevo and
Wade’s model, which are the components of IT assets and organisational resources are
stable and the outcomes of their relationships- the emergent capabilities are
predictable. My proposed view considers the ‘dynamic and non-linear’ changes in the
components of the IT assets and organisational resources, that give rise to the IT-
enabled capabilities, which may not result in expected outcomes. Moreover, my
proposed view also focuses on the ‘unpredictable’ nature of emergent IT-enabled
capabilities via the complex emergence lens. The overall complex emergence view
and the inclusion of additional enabling conditions- self-organised management, semi-
structures and simple rules with the existing compatibility condition, addresses in
dealing with the limitations of the Nevo and Wade model.
Melville’s Model vs. The CAS-BVIT Framework
Melville, et al. (2004) RBV based BVIT model focuses mainly on the locus of
IT business value in three domains: focal firm, competitive environment, and macro
environment. However, the authors are relatively opaque in describing the underlying
dynamic mechanisms, such as, how a focal firm acts or reacts with regard to the
changing competencies of rivals, how resources are reconfigured or developed over
time and their influences on BVIT in their model. Although, the authors acknowledge
that “The macro environment is dynamic and complex” (Melville, et al., 2004, p. 310),
they focus on the macro factors such as, telecommunication structure, which
potentially shape the BVIT of organisation and thus they underexplore the dynamic
mechanisms related to the BVIT generation. Besides, they are silent about the dynamic
mechanisms in relation to the focal firm as well.
My proposed CAS-BVIT framework addresses this limitation by identifying the
latent mechanisms via which organisations obtain competitive advantage in the
dynamic business environment. This involves explicating intra-firm and inter-firm
action based competitive processes (D'Aveni, et al., 2010) related to IT-enabled
194 Chapter 7: Discussion and Conclusion
capabilities, which ultimately help firms to obtain competitive advantage. In particular,
the CAS-BVIT framework includes coevolutionary mechanisms at two levels - the
micro and macro11 levels of organisations. The micro level coevolution explains how
IT-enabled capabilities are improved over time via variation, selection and retention
mechanisms (Aldrich, 2006) and the macro level coevolution explains three key
competitive dynamic mechanisms, Red Queen effect, competitive exclusion and niche
separation towards achieving competitive advantage via acquiring valuable and rare
IT-enabled capabilities. These added mechanisms in the two levels-micro and macro
levels help to deal with the limitation.
Wheeler’s NEBIC Model vs. The CAS-BVIT Framework
Rooted in RBV, the dynamic capability theory focuses on the ability of a firm to
achieve new forms of competitive advantage by renewing its resources in congruence
with the changing business environment (Teece, et al., 1997). One of the major applied
dynamic capability focused BVIT models, the Wheeler (2002) model of Net-Enabled
Business Innovation Cycle (NEBIC) argues that net-enabled organisations reconfigure
their internal and external resources to employ digital networks to exploit business
opportunities. Therefore, the net enabled dynamic capabilities engage processes and
routines that help organisations to turn IT into customer value (Sambamurthy, et al.,
2003). In the NEBIC view, a firm possesses four capabilities that help the firms to
create customer value - choosing emerging information technologies, matching
economic opportunities with emerging technologies, executive business innovation for
growth, and assessing customer value. NEBIC is an applied dynamic capability theory.
The term ‘dynamic’ implies a tautological notion of an organisational capability that
allows for continuous adaptation, otherwise the addition of ‘dynamic’ is either obsolete
or misleading (Burisch & Wohlgemuth, 2016); however, the NEBIC theory does not
include the notion of ‘continuous adaptation’. Although the dynamic capability theory
has the potential to contribute to understanding competitive advantage, it does not
include the concept of ‘complex system interaction effects’ (Colbert, 2004). Moreover,
NEBIC theory is driven by predefined capabilities and routines that help a firm to
create customer value.
11 For the purpose of the study, I have considered two domains- the competitive environment and macro environment together as macro level. It is briefly discussed in section 5.1, chapter 5.
Chapter 7: Discussion and Conclusion 195
My proposed CAS-BVIT framework addresses the above mentioned three
limitations of the NEBIC model. First, the proposed coevolutionary view, in particular
the macro level coevolution of the IT-enabled capabilities suggests that because of the
competition among firms, each firm’s adaptation move changes the adaptation move
of rival firms and thus firms continually adapt to obtain superior advantage over their
rivals. Moreover, the micro coevolution, the variation of the IT-enabled capabilities
provides the raw material for the continuous adaptation of the other IT-enabled
capabilities (Axelrod & Cohen, 2000). Second, both of the proposed views- complex
emergence and coevolution in the context of IT-enabled capabilities deal with complex
interaction effects among components. The complex emergence view suggests that the
dynamic and non-linear interactions between IT assets and organisational resources
give rise to emergent IT-enabled capabilities. The coevolution view deals with the
reciprocal interactions between two or more IT-enabled capabilities between firms in
competition at micro level and inside firm in micro level. Third, the underlying logic
of spontaneous responsiveness of firms in coevolutionary relationships by developing
or reconfiguring particular IT-enabled capabilities makes my CAS-BVIT framework
different from the partially planned12 and predictable opportunistic logic of NEBIC
theory (Pavlou & El Sawy, 2010). In addition, the emergent IT-enabled capabilities
are characterised as unpredictable in nature as discussed in section 7.1.
7.3.1 Implications of the CAS-BVIT Framework
The previous section highlights the limitations of the traditional BVIT models
and how I have dealt with these limitations using a CAS perspective. Following, I
discuss some implications of my proposed CAS-BVIT framework.
Dynamic and unpredictable view of contemporary business environment:
The business environment has become less predictable in nature, which requires
organisations to be super responsive, by understanding the impact and likelihood of
disruptions (Coutu, 2002). A small change in the organisation can cause large-scale
effect, like the butterfly effect (Lorenz, 1963), according to which, a flap of butterfly
wings can change the course of weather. In a similar way, my proposed view
acknowledges that a small change in any component of the IT assets (e.g. software
12 Choosing emergent technologies must be planned and predictable, whereas the value provided by a particular technology might not be as expected and thus I have used ‘partially’
196 Chapter 7: Discussion and Conclusion
applications, or IT skills of a developer) or organisational resources (e.g. management
practices, business functions), can give rise to unexpected IT-enabled capabilities,
which might or might not be beneficial for overall organisational functions (Gleick &
Berry, 1987). So, basically my CAS view supports such notions that a small tweak,
such as a small IT investment can bring greater competitive advantage to an
organisation. Or it can cause negative consequences; for example a small shift in the
downstream of consumer market can become amplified and cause bankruptcy among
equipment manufacturers (Lee, Padmanabhan, & Whang, 1997).
A novel IT management style: Such a point of view actually challenges the
traditional IT management style, such as long term planning, IT strategy formulation,
evaluation and implementation and control (Rosenhead, 1998). So the question
becomes, how should we look at IT management? Stacey (1996) suggests that this type
of creative disorder in organisations needs to be taken to heart by managers. Learning
about the fundamentally unpredictable future of contemporary organisations can be
fostered so that managers not only focus on their success relative to pre-determined
targets; they need to be reflective in the light of unfolding events and use assumptions
(mental models (Senge, 1990)) to set up various actions (Rosenhead, 1998). Rather
than trying to consolidate stable equilibrium, organisations need to seek for a region
of instability and welcome disorder in the system as it will provoke IT management
creativity, which may lead to a better competitive position. Moreover, a combined
adoption of ordinary and extraordinary IT management, in which the former refers to
the day-to-day activities and the latter presents required actions to accommodate open-
ended change, can be adopted to handle such unpredictable situations (Rosenhead,
1998).
Facilitates longitudinal research: The proposed coevolution perspective of the
CAS-BVIT framework provides a basis for longitudinal research on firm adaptation
in general with the emphasis on the emergence and coevolution of the IT-enabled
capabilities. The need for conducting longitudinal studies on organisational adaptation
on is not new (Tushman & Anderson, 1986; Van Valen, 1983). At the organisational
level, longitudinal research requires details of firm specific strategic and evolutionary
events with time series data (Lewin, et al., 1999). The proposed framework includes
both internal and external coevolutionary dynamic mechanisms that together serve as
sources of insights for managers to identify the existence of different dynamic events
Chapter 7: Discussion and Conclusion 197
(such as, VSR and Red Queen, Niche Separation) in relation to IT-enabled capabilities.
As a major barrier for longitudinal studies is the absence of time series data on
adaptation events (Lewin, et al., 1999), managers need to record the dynamic
mechanisms of specific events (e.g. the transition from ERP to salesforce based
customer management- event due to Red Queen competition- dynamics) and allocate
time in the organisational portfolio, which can be used to conduct longitudinal
research.
7.4 CONCLUSION
The dissertation started with an overarching research problem; that is, how BVIT
can be understood in the contemporary, dynamic business environment. The high level
research question is-
RQ 1: How is BVIT created in the dynamic business-IT environment?
To address this research question, the study takes a complex adaptive system
approach, more specifically it adopts emergence and coevolutionary perspectives
together, to explore BVIT in a dynamic environment. Using the emergence concept of
CAS theory, first, the study explores the way IT-enabled capabilities emerge. It then
adopts the coevolution concept of CAS theory to explore how these IT-enabled
capabilities help organisations to achieve competitive advantage.
Consequent research questions are,
RQ 1.1: How do IT-enabled capabilities emerge?
RQ 1.2: How do the IT-enabled capabilities coevolve and influence competitive
advantage?
The resultant frameworks and propositions from the emergence and
coevolutionary perspectives together provide a holistic overview of how BVIT, in
particular, competitive advantage is created in contemporary organization (Figure 1.1).
The proposed perspectives may stimulate analysis and understanding of the role of IT
in organizational strategy by pointing to foundational aspects and suggesting emergent
relationships. The theoretical contributions, suggestions for future research, and
limitations, are presented next.
198 Chapter 7: Discussion and Conclusion
7.4.1 Theoretical Contributions
The study has several theoretical contributions. First, it has provided a deeper
understanding of how BVIT is created in the modern dynamic business environment
and has shown the limitations of existing models of BVIT (as summarised in section
7.3). Second, CAS theory has been elaborated by its application to BVIT; in particular,
the concepts of emergence and coevolution have been rigorously applied to IT enabled
capabilities. Third, The development of the framework can be considered as
contributing to BVIT theory, comprising an ontological shift from a static-linear view
on BVIT to a more dynamic-complex view on BVIT. Fourth, the new insights from
NKC simulation model on coevolution of IT-enabled capabilities contributes to the
foundation of developing BVIT theory based on simulation model. Fifth, using a CAS
lens, my study contributes to the action based competitive advantage literature on
BVIT. Sixth, the structured literature review on CAS theory in IS contributes to the
knowledge body of both CAS theory and IS literature. Last, the dissertation contributes
to theory building in information systems by developing a novel research method
based on the ideas of Shepherd and Suddaby (2017) in theory development. Each of
these are discussed below.
Complex emergence as a way to understand the unpredictable rise of IT-
enabled capabilities: It has been widely agreed that CAS theory can capture dramatic
changes occurring in social institutions (Cohen, 1999; Lewis, 1994). Yet there is a
growing concern that as emergent events are unpredictable (Goldstein, 1996), there is
no assurance that the outcome of interest (which, in this study, is the emergence of the
IT-enabled capabilities) will occur, Indeed unforeseen consequences are a defining
characteristics of CAS (Mitleton-Kelly, 2003b). Therefore, this study proposes that the
use of emergence in prior BVIT studies to understand competitive advantage e.g.
Nevo and Wade (2010) is not clearly explained. More recent ideas of complex
emergence are concerned about this potential ‘black box’ of unpredictability (Pavlou
& El Sawy, 2011). The notion of complex emergence helps us to understand the
unpredictable nature of the emergence of the IT-enabled capabilities, as well as to
understand the enabling conditions (e.g. simple rules) that can potentially serve as a
countervailing force to take advantage of the unpredictable phenomena (in this study,
the IT-enabled capabilities).
Chapter 7: Discussion and Conclusion 199
Coevolution as a way to understand micro and macro level changes in IT-
enabled capabilities and competitive dynamics between firms in competition: The
coevolutionary perspective of the IT-enabled capabilities offers new ways of managing
the processes of their development in organisations. Recognising the tensions between
various IT-enabled capabilities and their evolutionary adaptations is more likely to be
effective than the traditional approaches that are premised on rationally planned and
controlled processes through which the IT-enabled capabilities adapt in business
systems (Tanriverdi, et al., 2010). This is particularly a very important issue given the
increasingly dynamic business environment in which information systems connect
people, places and organisations. Moreover, the study suggests that IT-enabled
capabilities continually coevolve internally and externally with organisations. Thus the
key is to identify valuable and rare IT-enabled capabilities, as well as to initiate
strategic variations for competitive success in organisations (Volberda & Lewin,
2003). Organisations should invest in dynamic capability, which enables them to
sense, seize and reconfigure different unique IT-enabled capabilities (Eisenhardt &
Martin, 2000). In another way, organisations can initiate strategic variation via
improvisation that can open the door allowing radical innovation of IT-enabled
capabilities to occur, hence, competitive advantage (Chae, 2014).
CAS-BVIT framework as a dynamic way to understand BVIT: The
proposed CAS-BVIT framework (Figure 7.1 in section 7.1) helps to capture the logic
of how IT assets derive business value via creating IT-enabled capabilities towards
competitive advantage. The proposed dynamic and non-linear approach to understand
the dynamics related to BVIT research, contributes to the overall BVIT research in IS.
A majority of existing BVIT studies in the IS literature have considered a static
perspective and thus my proposed dynamic approach will bring further attention to the
IS scholars who are very interested in the BVIT related research.
The framework makes explicit how emergence and coevolution and related
concepts (such as enabling conditions) operate to achieve BVIT for competitive
advantage. The propositions developed via the emergence and coevolution
perspectives can be considered as contributions to the existing knowledge. The
propositions related to the complex emergence might be beneficial for empirical
testing to examine the unpredictable effect of various IT-enabled capabilities on
overall organisational success. The proposed enabling conditions - simple rules, semi-
200 Chapter 7: Discussion and Conclusion
structures, and self-organised management can be used as tools to manage possible
unforeseen outcomes raised from the IT-enabled capabilities in organisations. In a
similar way, the propositions related to the micro and macro level coevolution of the
IT-enabled capabilities reveal important insights on coevolutionary adaptation of IT-
enabled capabilities in dynamic environment. These propositions can also be
empirically tested in contemporary organisations. Moreover, exploring the micro
coevolutionary dynamics- variation, selection and retention of the IT-enabled
capabilities together with macro coevolutionary dynamics- Red Queen effect,
competitive exclusion and niche separation will help managers to practically
investigate the dynamics in organisations.
Conceptual understanding on multilevel CAS view and dynamic fit between
micro-macro levels: The attempt to integrate multiple levels of research in a single
framework is significant in IS as the discipline suffers from fragmentation and some
incoherence (Robey, 2003). In addition, the constructive tension between micro and
macro levels and flow of different resources from outside into inside organisations has
been emphasised in major strategy research (Barney, 2001; Priem & Butler, 2001), and
this is focused on in the proposed framework via IT-enabled capabilities.
The proposed coevolutionary perspective can serve as an important foundation
for understanding dynamic fit between between the micro and macro coevolution of
the IT-enabled capabilities and it also puts managers in the central role to help achieve
this dynamic fit (Madhok & Liu, 2006). Managers in organisations scan for changes
in the business environment that may drive an opportunity or challenge for
organisations. So managers play a role in influencing internal relationships between
different IT-enabled capabilities as well as adjusting external relationships with other
competitors by scanning these companies’ benefits that are driven by IT-enabled
capabilities. From an evolutionary point of view, this particular phenomenon ensures
requisite variety, necessary information to adjust (fit) the micro and macro coevolution
of the IT-enabled capabilities (Ashby, 1968) and a balance between internal and
external selections (Miner, 1994).
A novel way of learning about BVIT theory from simulation model: I have
adopted the simulation outcomes of Kauffman’s coevolutionary NKC model
(Kauffman, 1993) as a way of getting new insights of the coevolution perspective on
IT-enabled capabilities. Based on the underlying rationale of NKC model and
Chapter 7: Discussion and Conclusion 201
following Mckelvey’s approach (McKelvey, 1999), I have proposed some
propositions that can be helpful in managing the coevolution of IT-enabled
capabilities. Based on the observation of the rationale of NKC, I have found that it is
crucial for organisations to balance the coevolution of IT-enabled capabilities in
between the micro and macro levels so that the coevolutionary balance helps
organisations to achieve competitive advantage, which is also acknowledged by
McKelvey (1999) in the context of value chain coevolutionary competencies in
competing firms. This simulation based theorising shows a novel way of learning
about BVIT theory, which is relatively uncommon in IS although it has been popular
in strategic management discipline (e.g. Baum & McKelvey, 1999c; Rivkin, 2000).
Although the derived propositions might be dismissed by some on the basis of being
developed by biologists, the developed propositions can be practised in organisational
settings for further validation and can be used for critical strategic decision making.
A new discussion on action based competitive advantage via the CAS lens:
The study contributes to the research stream related to action based competitive
advantage (D'Aveni, et al., 2010). The deeper insights discussed through the three
coevolutionary dynamic mechanisms, Red Queen, competitive exclusion and niche
separation, help to explain how organisations erode each other’s competitive
advantage and achieve temporary competitive advantage over the dynamic landscape.
The concept of temporary competitive advantage is illuminated via the CAS lens and
it is hopeful to open new discussions in relation to this particular concern.
A new conceptual theory building approach: The research approach for
theory building derived particularly for this study, based on the review by Shepherd
and Suddaby (2017) is unique and can potentially be applied to other IS and
organisational studies. My application of these ideas for exploring the dynamics of
BVIT provides a first illustration of how this approach can be used. Using “thickest
descriptive literature” (Mintzberg, 2005, p. 362), I have attempted to develop theories
of BVIT. The integration of conceptual descriptions as a way of describing complex
dynamics is a particular feature of the approach based on Shepherd and Suddaby
(2017). In particular, the research method can be adopted for theory building studies
in IS research.
Structured literature review on CAS theory in IS research as a future point
of reference: Finally, the structured literature review on CAS theory in the IS
202 Chapter 7: Discussion and Conclusion
discipline contributes to the overall knowledge body on CAS theory and IS theories.
To date, as far as I am aware, this is one of the very first structured literature review
within the IS field that has captured a variety of aspects related to CAS theory, such
as, concepts applied in IS research, related contributions, objectives, different
theoretical perspectives, and methodologies as well as context. The information
gathered on the applications of CAS theory in IS domain will serve as a knowledge
repository of CAS related IS research, hence it is expected to advance the use of CAS
theory in future IS research. For example, in the strategic management field, the
potential benefits of CAS theory such as, conceptual and simulation modelling or
fitness analysis or landscape behaviour analysis can be used in IS research.
7.4.2 Implications for Practice
The dissertation is highly abstract and conceptual, so the direct practical
implication may be more limited, but more concrete and applied follow-up work can
result in interesting, new strategies and guidelines. For example, complexity thinking
can be combined with RBV theory to develop principles for managing strategic human
resource management (Colbert, 2004). These principles, which are dynamic in nature
can be tested in organisational settings. On a high level, this can be helpful to examine
the practical implications of unfolding situations in planning and managing basic
aspects of organisations (Mintzberg, 1989).
The developed strategies based on NKC model in chapter 6 (section 6.3.2)
exhibit relationships with managerial actions to impact the organisation’s competitive
advantage. Anyone can adopt these strategies and apply them in their organisations
because of their intuitive scale-free nature- top strategy level, or mid-level, or at the
level where various IT-enabled capabilities interact. For instance, Benbya &
McKelvey (2006a) applied such dynamic strategies in IS-business alignment.
Admittedly, this example is not related to managing IT-enabled capabilities for better
competitive advantage, per se, it illustrates the real world potential of applying such
dynamic managerial actions similar to what I have proposed. Arguably, it is better to
initiate the proposed strategies by IS managers so that they can help organisations to
achieve better competitive advantage.
Moreover, the emergence and coevolutionary perspectives of IT-enabled
capabilities proposed in the thesis can provide a basis for a constructive and
penetrating dialogue among practitioners about the unfolding events and tensions
Chapter 7: Discussion and Conclusion 203
related to IT-enabled capabilities that develop in organisations. The proposed enabling
conditions in the emergence perspective and the dynamics in the coevolutionary
perspective can serve as guidance for managers for technology alignments and change
management activities. McKelvey (1999) suggests that organisation should
synchronise concurrent exploration and exploitation, a balance between innovation in
IT and process improvements for the improvement in productivity. Further,
Kauffman’s NKC model suggests that organisations should mix long jumps
(exploration) and adaptive walk (exploitation) with the implication of radical
innovation in IT systems for better process improvement. The above suggestions are
in align with my micro coevolutionary view on IT-enabled capabilities (see section
5.4). The case narrative used in Chapter 4 (section 4.4.2) suggests that radical
innovation in Enterprise Systems performs better than incremental innovation in the
case organisations. The above examples, admittedly highly relevant to managerial
actions and complexity leaderships that might guide IS managers to better synchronise
and manage IT-enabled capabilities for continuous improvement in organisational
productivity.
One of the core contributions of the CAS theory is developing mental models
(Senge, 1990) via the application of complex emergence and coevolution concepts.
My proposed emergence and coevolution frameworks can help practitioners visualise
IT-enabled capabilities map in their organisations. For example, firm can categorise
IT-enabled capabilities into operational, strategic and support and then analyse how
direct and indirect ties among these capabilities shape their position in the business
landscape in comparison to their competitors. Moreover, firm can use the emergence
framework to predict any future IT-enabled capabilities. This will also help firm for
better capability management for competitive market positions. In a similar way, the
coevolution framework can help firm to map the capabilities in micro and macro levels
and then manage them accordingly with current organisational goals to obtain better
competitive advantage.
Describing the dynamic mechanisms underlying BVIT is an important
contribution for IS practitioners who seek to understand how BVIT is created in
contemporary organisational contexts via IT-enabled capabilities. The relationships
between IT assets and organisational resources depends on the degree of compatibility
between these two, and it also influences IT enabled capabilities. Thus, it alerts
204 Chapter 7: Discussion and Conclusion
managers to consider not only the IT assets in which they invest, but also the
relationships with the organisational resources with which these assets are fused. They
can also be aware of the importance of simple rules and semi-structures for the
emergence of IT-enabled capabilities which are conducive for overall performance.
Moreover, managers can mind map a portfolio of the dynamics related to IT enabled
capabilities to better realise the state and importance of each capability and how it
brings advantage.
7.4.3 Limitations
My study acknowledges several limitations. The thesis has considered CAS as a
theory following (Stacey, et al., 2000), however, several IS and management
researchers, (Benbya & McKelvey, 2006a; McKelvey, 2001; Merali, 2006) consider
CAS as a concept of complexity theory. There are two major school of thoughts- the
European school led by Prigogine, Allen, Cramer, Haken, and Mainzer (Allen, 2001;
Cramer, 1993; Haken, 1977; Prigogine, 1984) and among many others and North
American school rooted in the work of Kauffman, Lorenz, Anderson, Holland, Arthur
(Anderson, 1972; Arthur, 1989; Holland & Miller, 1991; Kauffman, 1993; Lorenz,
1963) among many others influence the way CAS is defined within complexity
theories. Further, a number of complexity scholars, (Merali, 2004; Stacey, et al., 2000)
warn about using CAS in interpreting engineering type of systems, including IT
systems, as the system components remain unchanged while they are interactions.
Such interpretation can cause intuitive inconsistencies in the ontological and
teleological foundations of CAS theory. Consequently, any literature review on CAS
may become ontologically and teleologically inconsistent, which is a limitation of my
structured review on CAS. An in-depth study by complexity experts gathering
evidences on the evolution of the complexity theories from root into various disciplines
and mapping them in a coherent and consolidated framework may resolve such
inconsistencies.
This study has only emphasised the complex emergence of IT-enabled
capabilities. However, IT-enabled capabilities can rise via simple emergence process
similar as Nevo and Wade (2010) studied. My study is not disregarding them, however,
due to the research focus on understanding the dynamic aspect of BVIT creation, such
simple emergence phenomena are not considered in the thesis, which is a limitation of
thesis.
Chapter 7: Discussion and Conclusion 205
The conceptual line between the emergence and coevolutionary perspectives is
drawn to enable the conceptual understanding of the two foci of the study.
Theoretically, it is difficult to draw such distinctions as CAS concepts are highly
intertwined and such distinction can be ambiguous in the use of complexity theories
(Mitleton-Kelly, 2003b). However, I have made an assumption that the emergence and
coevolution of the IT-enabled capabilities occur separately to better understand the
dynamic mechanisms related to the BVIT, which is a limitation.
In chapter 4 (section 4.4.2) and 5 (5.6.2), I have adopted multiple empirical case
studies to validate my proposed frameworks and propositions, which is known as
internal validity (Eisenhardt, 1989). However, internal validity in this thesis is just a
first step and quite limited. Scholars (McKelvey, 1999; Merali, 2006) followed similar
approaches in their research to validate their proposed theories. A dedicated empirical
case study can be conducted in future to establish concrete validation of the proposed
theories in this research.
Moreover, the use of CAS theory is questioned by scholars, such as not being
applicable in organisational studies where traditional streamlined theories, such as
RBV or dynamic capabilities theory are preferred, to explore BVIT. More broadly,
CAS raises ontological and epistemological issues in relation to research and
knowledge accumulation. Because of the continuous and rapid changing nature of the
CAS components, it is often assumed that at the time when the information is collected,
CAS is in a temporary equilibrium state, which means the gathered knowledge on the
relationships is unlikely to be valid because components might change during that
short window of stability (Tanriverdi, et al., 2010). Therefore, while the attractions of
the CAS theory are apparent, this limitation is particularly implicit in CAS based
research. Another limitation of the research includes the consideration of coevolutionary
relationships only between IT-enabled capabilities at micro and macro levels of
organisations. In organisational settings, IT-enabled capabilities actually coevolve
with other organisational elements, such as, routines, capabilities, strategies, resources
(Koza & Lewin, 2001; Lewin, et al., 1999), but these coevolutionary relationships are
not considered in this study, which can be investigated in future research.
206 Chapter 7: Discussion and Conclusion
In addition, the study is highly conceptual and based on the existing literature.
Further development of theory and empirical testing is required in future research,
which will help to test the proposed framework and related propositions.
Furthermore, I have focussed on the notion of temporary advantage in the
context of contemporary organisations, but there are many organisations who are
actually achieving sustainability of their competitive advantages in these dynamic
environments (Bharadwaj, et al., 2013). This study does not consider the how the
temporary advantage can become sustainable nor indeed what ‘temporary’ means,
time-wise, which can be explored in future research.
7.4.4 Future Research
The study has drawn on many case studies, hypothetical examples and prior
relevant research in information systems to illustrate and explain claims.
Consequently, the dissertation provides many examples that offer preliminary
empirical illustration regarding the viability of the proposed frameworks. While
grounded in relatively new theories in the IS discipline and supported by anecdotal
evidence, the usefulness of the unified model may be further evaluated by
operationalizing the conceptual constructs and empirically testing the propositions as
well as conducting simulation for exploration and testing. As a first step, in Chapter 6,
I have shown how to develop deeper insights based on simulation outcomes Therefore,
the study calls for future empirical research based on the theoretical perspectives
developed in the context of BVIT to get better insights and empirical support for the
arguments, assumptions and models. Further, operationalising CAS perspectives can
be challenging and problematic (Rivkin & Siggelkow, 2007; Siggelkow, 2002). Thus,
I suggest that researchers seeking to test the conceptual models should employ, as a
methodological compromise to operationalise different variables and constructs.
Furthermore, the inconsistent interpretations of CAS and the invalid ontological and
teleological foundations of CAS theory will require to be addressed by an in-depth
engagement of the whole body of work via complexity experts.
I believe that the proposed perspectives in this dissertation can be applied in
different ways. First, an operational model of the emergence perspective on IT enabled
business can give insights into phenomena which are difficult to understand via
theories. Future studies can also extend my integrated CAS framework to large
organisations, where there are multiple levels, highly digitalised and they depend
Chapter 7: Discussion and Conclusion 207
highly on competition in niche markets, to test my model in real life to make sense or
for decision making.
One of the key insights from the proposed CAS theory is that the things we plan
and make decisions about in relation to the organisational context, do not always work
as planned. There is a huge potential for research, particularly in this area of
unpredictability. As this study suggests that the concept of sustainability is being
eroded via unpredictability, research into identifying and reducing unpredictability to
some extent would positively contribute to the research on BVIT. Future research may
be able to shed more light on this important issue by exposing the barriers that prevent
sustainable competitive advantage in contemporary organisations.
The research asserts that there is ongoing Red Queen competition among
contemporary firms for enhancing IT-enabled capabilities over their competitors.
However, there is very little research that has focused on the firms in the competitive
exclusion region or niche separation and this is mainly focused in the strategic
management and marketing literature (Kemp, et al., 1998). There is a possible
opportunity to investigate these dynamics in empirical settings to better understand
these dynamics and how they influence competitive advantage in real life.
In sum, an empirical case study with the emphasis on the conceptual claims in
the study as well as validating the hypotheses in a real life case study would establish
a strong base from this study. A simulation study such as Nan (2011) can also be
conducted as a way of validating the assumptions in the conceptual models as well as
the hypotheses.
This dissertation has explored the dynamics related to the business value of IT
(BVIT)—in particular, competitive advantage—in contemporary organisations. It
adopts CAS theory as a lens to explore the emergence of different IT-enabled
capabilities, their coevolution, and their influence on competitive advantage. The study
highlights the dynamic mechanisms via which IT-enabled capabilities emerge in
organisations. It also provides explanation on the coevolutionary dynamic mechanisms
in relation to the IT-enabled capabilities and discusses the influence of IT-enabled
capabilities in shaping competitive advantage. In the future, these mechanisms will be
challenged and adapted, but until then, they provide plausible guidance to researchers
to consider about taking a complex and dynamic view on contemporary organisations
208 Chapter 7: Discussion and Conclusion
in the quest of obtaining new knowledge and in-depth insights on the generation of
BVIT.
Chapter 7: Discussion and Conclusion 209
Appendices
Appendix A
Abstract of the publications
Publication Details Abstract
Onik, M. F. A., Fielt, E., & Gable, G. G. (2017). Complex Adaptive Systems Theory in Information Systems Research-A Systematic Literature Review. In the Proceedings of 21st Pacific Asia Conference on Information Systems (PACIS), Langkawi, Malaysia.
A special branch of complexity science, complex adaptive systems (CAS), is a way of thinking about systems of interacting agents and how order emerges in systems from the interactions of agents. Though CAS has been widely used in management and organizational studies for decades, it has been employed in the Information Systems (IS) research domain only more recently to investigate complex phenomena like agile software development, bottom-up IT use process, and systems dynamics. The aim of this research is to conduct a review of CAS studies within the IS discipline, particularly focusing on how CAS concepts are used for theorizing complex phenomena and the context of the use. To achieve this, we survey papers published in top outlets between 2002 and 2014, conduct in-depth analysis and categorize the contributions of the papers sampled by mapping them with the relevant CAS concepts. The review suggests that CAS has attracted limited interest within IS due to confusion with its central concepts, inherent complexities and possible ontological and epistemological issues with knowledge accumulation. We identify some promising IS research areas that can be studied using CAS and propose some guidelines for future researchers.
Onik, M. F. A., Fielt, E., & Gable, G. G. (2017). Towards Complex Adaptive Systems Roadmap for Information Systems Research. In the Proceedings of 21st Pacific Asia Conference on Information
Complex adaptive systems (CAS) theory conceptualises a system composed of heterogeneous agents, which interact with each other to adapt to the environment. CAS concepts have been applied in several Information Systems (IS) referent disciplines over the last decade to study complex phenomena in strategic management, social science and organisational research. The application of CAS theory in IS is more recent, wherein researchers have studied complex phenomena including agile
210 Chapter 7: Discussion and Conclusion
Systems (PACIS), Langkawi, Malaysia.
processes, systems dynamics and IS alignment. Though CAS has gained some traction with IS researchers, general understanding of the potential of CAS, and its methodological and theoretical applications in IS research, is yet partial and fragmented. The aim of this study is to develop a roadmap for applying CAS in IS research, to analyse the key research objectives with CAS in extant IS research, and to identify methodological and theoretical approaches that researchers follow in conducting CAS-based IS research. To achieve this, we review IS papers published 2002-2014 inclusive in top IS outlets. We analyse the papers based on a supportive theoretical framework and identify eight main objectives of applying CAS, three methodological approaches, and two theoretical approaches related to CAS-based research in the IS discipline. The study reports several valuable observations, including the relative versatility of computational studies over other studies, the minimal use of CAS in design research, methodological triangulation, and theoretical triangulation in IS research. We propose several guidelines for future researchers.
Onik, M. F. A. & Fielt, E. (2016). Understanding The Dynamics of BVIT Process: A Complex Adaptive Systems Approach. In the Proceedings of 27th Australasian Conference on Information Systems (ACIS), Wollongong, Australia.
There has been a long-running discourse in the information systems literature around the business value of IT (BVIT). Researchers have adopted a myriad of conceptual, theoretical and analytical approaches to evaluating the tangible and intangible measures of BVIT. Little research however, has explored richer theoretical explanations of the dynamic nature of the BVIT processes in contemporary dynamic business environments. To address this gap, this research in progress seeks to explore how BVIT is created as a bottom-up emergent process. In pursuit of such understanding, this research embraces complex adaptive systems (CAS) theory to develop a bottom-up conceptual model of BVIT. The agent-based modelling (ABM) technique is introduced as an analytical tool for computationally representing and examining the CAS model of BVIT. Operationalization of the CAS model and ABM modelling will be demonstrated through a theory building exercise.
Onik, M. F. A., Fielt, E. & Gable, G. G. (2017). Understanding The Dynamics of BVIT Creation:
Dramatic change is occurring in the structure of business, governmental and non-profit organisations due to the advent of complex technologies. These changes are engendering the emergence of business eco-systems as complex adaptive systems linking
Chapter 7: Discussion and Conclusion 211
A Complex Adaptive Systems Approach. ISS Doctoral Consortium, QUT Brisbane.
firms, innovations, processes and services in a network of increasingly interconnected, interdependent and diverse entities; IS has become fused with the business environment in a way that they are indistinguishable. Thus, the competitive organisational context is becoming more complex and less predictable suggesting the need for more dynamic models of BVIT in IS. In this fast changing, dynamic environment, traditional approaches to theorising and conceptualising BVIT have reached their limits. Beyond static or discreet views of BVIT or episodic events that lead to BVIT, there is need for more holistic theoretical logic concerning the bottom-up emergence of BVIT from resource level to organisational level. This research-in-progress paper seeks to contribute to BVIT research by proposing a novel framework especially suited to the examination of the bottom-up dynamic nature of BVIT by extending the analytical elements of complex adaptive systems (CAS) theory. By varying the assumptions of basic properties of CAS components e.g. fitness value, schemata or population dynamics, it is possible to model and theorize emergent, non-deterministic and co-evolutionary behaviours of dynamic systems.
Onik, M. F. A., Fielt, E. & Gable, G. G. (2016). What Are Information Systems- Information Systems as Complex Adaptive Systems. ISS Doctoral Consortium, QUT Brisbane.
The rise of the Internet and advancement in the technologies has given rise myriad of complexities in the current information systems (IS) in organisations. The contemporary IS are open ended, more diverse, internet-based and fast changing according to the demand. Organisations are adopting advanced technologies at the fundamental level and increase their capabilities, like processes, information, and expertise. It also helps organisations to expand their business, maximise performance and increase revenue. However, organizations now-a-days are considered as a globally distributed systems consisting of networks of internet-enabled IS. Thus, the competitive context and structure of IS is progressively becoming more complex and less predictable and it is being questioned whether the traditional approaches to theorising and conceptualising are efficient enough to deal with this new context. To address the issue, this study adopts the connectionist network framework of IS developed by (Merali, 2004) and proposes that the contemporary IS can be conceptualised as complex adaptive systems (CAS) in order to better understand the unpredictable complexities arising from the highly interconnected
212 Chapter 7: Discussion and Conclusion
world of distributed IS. We would like to explore whether the CAS theory can contribute to the discourse on contemporary IS characterised by internet-enabled technologies.
References 213
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