Literature Review Topic Presentation

Risk

Knowledge intensity

Capability maturity

Information flow along supply chains

Risk

What are the implications of knowledge leakage?

• Risks from intentional knowledge leakage• Risks from not undertaking intentional knowledge leakage• Risks from unintentional knowledge leakage

Risks from intentional knowledge leakage

Increases time to market if not carried out effectively Increased dependency on supplier Loss of centralised information Piracy of confidential knowledge Conflicts between source and entity Loss of market share Knowledge loss as suppliers develop ‘local’ knowledge that never returns

to the source (see table) Increased risk of unintentional knowledge leakage

• Increased imitability (see table)• Through other information• Loss of knowledge value

Autio, Sapienza and Almeida, 1999, Styhre, 2004, Yanow, 2004, Roper and Cronet, 2003, Ndofor and Levitas, 2004Decarolis, 2003)

Yanow, 2004, Autio, Sapienza and Almeida, 1999

Loss of speculative work within in house R&D• EU productivity report showed the EU outperformed the US in

industry groups where innovations rose from in-house R&D• R&D investments linked to increased productivity

Small suppliers are less likely to have the resources to plan for new technologies

Small suppliers are less likely to look sideways at potentially disruptive technologies emerging in other industry sectors

Reed and Walsh, 2002, O’Mahoy and van Ark

Risks from not undertaking intentional knowledge leakage (benefits really!)

Inability to compete in modern production Movement to supply chain production is often cheaper and more

efficient if organised effectively – increasing productivity. Inability to gain from knowledge leakage plus point (predictable order

flow, reduction of stock/inventory, ,efficient product replenishment, etc)

Increased productivity through divestment Possible closing of the productivity gap attributed to the promotion of

two-way knowledge transfer between enterprise, science based and research institutions and supply chain partners

Reduced productivity growth in the EU has been attributed to the slow exchange of knowledge in response to new technology.

(Brynjolfsson and Hitt 2000, O’Mahoy and van Ark, 2003)

Risks from unintentional knowledge leakage

Loss of disembodied or tacit knowledge of production procedure through employee loss leading to disruptions in productivity

Loss of value of ‘weightless good’ Decreased productivity from loss of knowledge within industries

regarding inefficiency of manufacturing processes

Knowledge intensity

Ways of measuring knowledge intensity:

•Through R&D expenditure •No of patents•Through the development of a hierarchy of knowledge type tasks?• Through taking stock of managerial and production techniques•Through an audit of current knowledge and future knowledge possibilities based on current knowledge

(Autio, Sapienza and Almeida, 1999, Smith 2002, Shadbolt and Milton, 1999, Roper and Cronet, 2003, Ndofor and Levitas, 2004)

•Through identification of technological intensity or the degree of sophistication and customisation of the production process.

•By taking a stock of knowledge through a taxonomy of forms of knowledge, and the use of manufacturing techniques as inductive of the strength of the companies knowledge base (see table)

•Problems that authors do not explain these techniques fully!

(Lepak, Tekeuchi and Snell, 2003, Roper and Cronet, 2003))

Management assessment questionnaires (see figure)

Knowledge Audits?

Autio, Sapienza and Almeida, 1999

Capability maturity / Knowledge maturity models

Derived from software optimisation techniques – generic approaches to developing an entity to its ultimate state.

• Levels (4-6) characterised by achievement requirements.• Sequentially ordered from an initial state to a final level,

normally perfection

Employed in businesses trying to establish an effective knowledge management system.

Can also be used to make comparisons between companies, to rank companies and for benchmarking.

Microsoft ‘knowledge landscape’• 8 levels (‘unaware’ to ‘leadership’)• Ranked via 77 criteria using a 4 level scale

KPMG ‘knowledge journey’• 5 levels (‘knowledge chaotic’ to ‘knowledge centric’)

Gallagher and Hazletts KMƒ• 4 levels (‘Aware’ to ‘optimisation’)• Split into separate focus’ of culture, infrastructure and

technology

(Klimko, 2001)

Example of a knowledge maturitymodel

Klimko, 2001

Information flow along supply chains

Highly non linear, dynamic, complex adaptive systems that differ between supply chains and between entities within supply chains.

Types of information flow

Internal flow External flow Pre-product flow Post-product flowExplicit flow Tacit flowEmbodied flow Disembodied flowEpisodic flow Continuous flowMacro-flow Micro-flowPropriety flow Shared flow

Relationship affecting the information flow

Relationship to one anotherComplementary knowledge portfolios – equal flow (Roper and Cronet have an assessment of complementarity,2003)

Relationship between entity and sourceSupply and demand, continuous development etc

Efficient, continuous information flow reduces costs and maintains cycle times. Reduces machine down time.

Mechanisms for information flow

Phone, fax, internet, post, person to person etcElectronic data interchanges (EDI’s)

Information exchangesStandardised / formalised (Proformas, spreadsheets etc)Less formalised / casual (comments, remarks etc)

Three flows :materialsinformationresources

(Stefersson, 2002, Johnston 1998, Meer-Kooistra, Jud and Jijlttra, Pittaway, Robertson, Munir, Denver and Neeley,2004, Un and Cuero-Cazura, 2004)

Information mechanisms in companies of varying size

(Stefersson, 2002)

Knowledge leakage in relation to the UK productivity GAP – additional comments

Assess knowledge leakage in countries with increased productivity in order to assess if knowledge leakage does effect productivity.

Or within companies with similar productivity growth or decline levels (OECD STAN database

Sector competitiveness analysis of the software and computer service industry by the DTI found the productivity gap in India was due to high levels of staff turnover (KL through employee loss) and due the the high levels of piracy)

Difficulty in assessing effect of KL on productivity as intentional KL (outsourcing) is often linked with other activities

(Reynolds, Howard, Dragon, Rosewell and Ormerod, 2005, van Ark, Inklaar and Mcgucken, 2003))

EU Report on productivity suggests sector specific improvements in technologies within industries with wide applications in other industries and promoting knowledge flows along product supply chains in order to increase productivity

(O’Mahoy and van Ark, 2003)

Bibliography

Autio E, Sapienza HJ, Almeida JG (1999) ‘Effects of Age at Entry, Knowledge Intensity, and imitability on international growth’ revised manuscript for the International Entrepreneurship issue of the Academy of Management Journal, March 31 1999 Brennan N ( ) ‘Reporting intellectual capital in annual reports: evidence from Ireland’ Johnston R (1998) The changing nature and forms of knowledge: A review, Department of employment, education, training and youth affairs, Sept 1998 Lepak D P Takeuchi R A. Snell S A 03 (2003) ‘Employment Flexibility and Firm Performance: Examining the Interaction Effects of Employment Mode, Environmental Dynamism, and Technological Intensity’ Journal of Management 2003 29(5) 681–7 Meer-kooistra Jvd and Zijlsttra S M ( ) ‘Reporting on intellectual capital’ Ndofor H A, Levitas E (2004) ‘Signaling the Strategic Value of Knowledge’ Journal of Management 2004 30(5) 685–702

O’Mahory M and van Ark (2003) EU productivity and competativeness: An industry perspective – Can Europe resume the catching up process? European commission, Enterprise Publications

Pittaway L, Robertson M, Munir K, Denyer D and Neely (2004) ‘Networking and Innovation: a systematic review of the evidence’, IJMR Reed F M and Walsh K (2002) ‘Enhancing Technological Capability Through Supplier Development: A Study of the U.K. Aerospace Industry’ IEEE Transactions on Engineering Management, VOL. 49, NO. 3, August 2002 231 Roper S and Cronet M (2003) ‘Knowledge complimentarity and coordination in the local supply chain: Some empirical evidence’, British Journal of management, Vol 14, 339-355 Shadbolt N and Milton N (1999) ‘From knowledge engineering to knowledge management’, British journal of management, Vol 10, 309-322 Smith K (2002) What is the knowledge economy? Knowledge intensity and distributed knowledge bases, The United Nations University, Discussion paper, June 2002 Stefansson G (2002) ‘Business-to-business data sharing: A source for integration of supply chains’ in International Journal of Production Economics 75 (2002)135 –146 Styhre A (2004) ‘Rethinking Knowledge: A bergsonian critique of the notion of tacit knowledge’, British journal of management, Vol 15, 177-188

Un C A and Cuero-Cazura A (2004) ‘Strategies for knowledge creation in firms’, British Journal of Management, Vol 15, S27 – S41

 

Yanow D (2004) ‘Translating local knowledge at organizational peripheries’, British Journal of Management, Vol 15, S9-S25

 

Klimko G (2001) knowledge management and maturity models: Building common understanding, proceedings of the 2nd European Conference on knowledge, 2001

Reynolds, Howard, Dragon, Rosewell and Ormerod (2005) Assessing the productivity of the UK retail sector, International Review of retail, distribution and consumer research, Vol 15, No 3, 237 – 280

Sector competitiveness analysis of the software and computer service industry by the DTI – www.dti.gov.uk/industries/software/Sector_Competitiveness_Analysis.doc

Van Ark, B, Inklaar R and Mcguckin RH (2003) ICT and productivity in Europe and the United States. Where do the differences come from?, CESifo Economic Studies, Vol 49, No 3 295-318

Brynjolfsson and Hitt (2000) Beyond Computation: Information technology, organizational transformation and business performance, Journal of economic perspectives, Vol 14, No 4, 23-48