determining the effect of information technology …...information technology (it) innovation on...

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International Journal of Management (IJM) Volume 11, Issue 7, July 2020, pp. 1534-1550, Article ID: IJM_11_07_138

Available online at http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=7

ISSN Print: 0976-6502 and ISSN Online: 0976-6510

DOI: 10.34218/IJM.11.7.2020.138

© IAEME Publication Scopus Indexed

DETERMINING THE EFFECT OF

INFORMATION TECHNOLOGY (IT)

INNOVATION ON TECHNOLOGICAL

CAPABILITIES: A RESEARCH ON

ENTERPRISES MANUFACTURING IRON

STEEL AND BY-PRODUCTS IN TURKEY

Dr. Arif Selim Eren

Assistant Professor, Kahramanmaras Sutcu İmam University, Turkey

ORCID: 0000-0001-7274-1113

Dr. Lec. Huseyin Ciceklioglu

Mersin University, Turkey

ORCID: 0000-0003-3922-6755

ABSTRACT

In production management, the resource based view is evolving according to the

availability of infrastructure in globe ascends and organizational dimensions gain

importance as the need for qualified labor emerges. So, the future of enterprises is

more prone to the capabilities to use technological competences and information

technology (IT) in a more appropriate manner.

There is no valid in any case theory of IT innovation and technology management

as Rush et al., 2007: 221 claims, so regional policies are needed to be deployed.

Moving here, the present study investigates the relationship between IT innovation

and technological capabilities in iron steel by products cluster located in Turkey. A

questionnaire adopted from the literature is applied to 180 employees and analyses

are conducted via the use of descriptive statistics, EFA, CFA and SEM.

The results revealed that perceived feasibility is affecting the technological

capabilities of the sample by half. Whereas propensity to use affects technological

competences by a quarter. Implications for future research and some policy proposals

are also included. It is hoped that this can fulfill partly the empirical result limitation

in the literature.

Arif Selim Eren and Lec. Huseyin Ciceklioglu


Key words: IT innovation, Technological Capabilities, Turkey

Cite this Article: Arif Selim Eren and Lec. Huseyin Ciceklioglu, Determining the

Effect of Information Technology (IT) Innovation on Technological Capabilities: A

Research on Enterprises Manufacturing Iron Steel and By-Products in Turkey,

International Journal of Management, 11(7), 2020, pp. 1534-1550.

http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=7

1. INTRODUCTION

Current business environment urges enterprises to be more effective in international markets

and Information Technology (IT) creates opportunity for being more innovative in business

processes (Moghavvemi and Mohd salleh (2014: 139). According to Archibugi et al. (2009:

917), utilizing IT in business processes makes enterprises to be more effective in the markets,

so the production systems should be supported by innovative IT applications. Many countries

are aware of the innovations place in business of the day and adopt or create infrastructures on

developing the innovative capability of their enterprises (Arnold and Thuriaux, 1997: 1).

Furthermore, the need to react liberalizing markets all over the world coercing the enterprises

to be more benchmarking oriented (Cassiolato and Baptista, 1996: 53). Thus, emerging

economies are more prone to be innovative as they are about to construct the production

infrastructure recently and this creates a challenge to have more sophisticated skills on

technology and innovation management (Banarjee, 2012: 665). Thus, they should make a

decision on what to produce by utilizing their resources in the maximum level. By doing so,

they are told to have more advantages in competition and have a chance to improve their

share in the market while having better productivity ratios (Lall, 1992: 165).

Berger and Diez (2006: 109) came with up the idea of the need to be a more knowledge

based economy while adopting and creating new solutions to the current markets. They claim

that the use of IT innovation in production requires some specific skills to claim more

effective systems. While supporting this idea, Berkhout et al. (2010: 474), mentions the need

to have more effective R&D processes in order to obtain faster production aright.

Correspondingly, the resource based paradigm of production has evolved as a result of the

developments in technology after the II. World War and began to seek ways of more

economic solutions to meet ascending demand. However, Tallon (2008: 21) criticizes this

view and claims that adoption of the technology is not just a matter of purchasing hardware or

software. The focus should be on managing these equipment in the right way. Moreover,

Cimoli and Porcile (2009: 675) support this idea by adding the impact of technology in

development of history and economy. They conclude that industrialization requires more

technological operations in production and this can only be obtained by using IT and being

equipped with certain capabilities.

Thus colleagues such as Bharadwaj et al. (1999: 378) started to focus on the

organizational aspects of production and made many contributions to have more effective

adoption of new technologies to production systems. Also Chen et al. (2015: 643) raises some

discussion on the role of technology adoption in production processes and they claim that the

organization should be ready to learn from the environment while requiring the novel

infrastructure. This makes them to be more competitive and usage of technology created

opportunity and time to obtain more countervailing products as a result of innovative

processes. Also it is claimed that when the firms start to be innovative in IT, they typically

begin to develop more sophisticated capabilities to keep up with the rapid change and

turbulence in technology development (Swanson, 2010: 17).

Moving here, there is a bulk of literature investigating the impact of using IT innovations

on firm performance (Dibrel et al., 2008: 203). Prior research focused on the usage of

Determining the Effect of Information Technology (IT) Innovation on Technological Capabilities: A

Research on Enterprises Manufacturing Iron Steel and By-Products in Turkey


knowledge and information and they made a distinction between the tacit knowledge and

dynamic capabilities (Su et al., 2013: 261; Domínguez and Brown, 2004: 129). In this

context, Dutrénit (2007: 125) claims that development of innovative capabilities as a matter of

organizational learning and firms can benefit from this type of learning more by adopting new

technologies. Moreover, Iammarino et al. (2012: 1283) assert that technological capabilities

of the human resources can make contribution to the interactions that the firm needs to be

more competitive. By this way Kyläheiko et al. (2011: 508) adds the idea that technological

capabilities of the firms can get on well with internalization processes. By this way, the firms

are going to be more innovative and benefit more from product development.

While using technology in production processes, firms can take the advantage of shorter

time to market and the mass of production without defects. They also benefit from quality

issues while having the knowledge of the history of the product. With this perspective Yörük

(2011: 330) asserts the idea of creating more international clusters while making intra-country

links of innovation to be competitive globally. However, the ability to create the required

technology is limited especially for those having a developing or under developed economies

(Lynskey, 1999: 317). Then, the developed ones can make a choice by providing the

necessary equipment to others or not. Competition is brutal as the nations with limited

technology development skills are being addicted to technology transfer. This means that the

under-developed and developing ones are limited to produce what developed ones ask them

while paying more than the equipment can produce. Moving here it is obvious that the

emerging economies should be transformed into an innovative culture and this requires skilled

labor under the management of capable leaders (Lyver and Lu, 2018: 442). In this point,

Mishra and Agarwal (2010: 249) claim that firms can adopt or assimilate their production

systems or be innovative and develop more sophisticated technology. Furthermore Morrison

et al. (2008: 39) adds the idea of making clusters to react the developments in the market and

deploy a more comprehensive way of rivalry. By doing so, it is depicted that the country can

make use of direct foreign investments by having a more reliable economy and in the long run

the host will be able to develop their own technology by interacting with the funding one

(Song and Shin, 2008: 291).

Taking the advantage of the knowledge above, the current study investigates the effect of

information technology innovation on technological capabilities in a cluster producing iron

steel and by-products in Turkey. The study is conducted in Kahramanmaraş, as the cluster

makes the %80 of the production. A survey is adopted from literature and applied to 180

employees in the cluster. Analyses are performed via SPSS and AMOS.

The results indicate that there are some significant differences in terms of demographic

features of the sample. Also perceived feasibility and propensity to use are reported to have an

effect on technological capabilities by half and by quarter respectively.

2. LITERATURE REVIEW

Former literature in technological capabilities and IT innovation is rich in studies revealing

conceptual framework. However, the empirical results appeared to be weak in numbers. For

conceptual framework it is ideal to read Lall (1992: 165) but the empirical link is missing to

our regret. In a glance to these studies, it is noticed that Moghavvemi and Mohd salleh (2014:

139) has investigated the relationship between IT innovations and intention to use technology

by using the data obtained from 420 entrepreneurs. This study is used in order to adopt the

questionnaire to be used in the current one. Similarly, Berkhout et al. (2010: 474) searched for

the relationship between innovation and technological capabilities. On the contrary, Chen et

al. (2015: 643) investigated the relationship between IT capabilities and product innovation.

While Dutrénit (2007: 125) searched for the gate from innovation to leadership, Lynskey



(1999: 317) transfers the experience of Fujitsu. On the other hand, Lyver and Lu (2018: 442)

investigated the link from strategic entrepreneurship to IT innovation aiming to keep

sustainability. Whereas, Mishra and Agarwal (2010: 249) focused on the IT capabilities as an

organizational dynamic ability in a technological frame. In a different context, Swanson

(2010: 17) explains the relationship between consultancies and capabilities in terms of IT

innovation. Contrary to these quantitative studies, a qualitative study made by Yörük (2011:

330) deals with the technological capabilities and knowledge network components in Turkish

context.

Besides these works, Archibugi et al. (2009: 917) benchmarks the technological

capabilities of the nations. This work is crucial to depict the state of art in emerging

economies. Moreover, Arnold and Thuriaux (1997: 1) studies technological capabilities of

developing firms and this is useful to depict the technology adoption processes of SMEs as

the present work focuses on a cluster consists of many developing firms. At the same time

Khayyat and Lee (2015: 210) tried to develop a scale to be used in developing countries in

order to see the technological skills. Correlatively, Dibrel et al. (2008: 203) depicts the

policies to be adopted by SMEs in information based innovation processes. Supporting this,

Banarjee (2012: 665) reveals the technology adoption policy of India while giving

information on technological capabilities of emerging countries. Another regional study

conducted by Berger and Diez (2006: 109) catches up the state of art in Southeast Asia.

Similarly, Cassiolato and Baptista (1996: 53) has a focus of effects of liberalization on

developing countries and they report the experience of Brazil. In like manner, Domínguez and

Brown (2004: 129) depicts the technological capabilities of Mexican firms. A similar research

is done in the United Kingdom by Iammarino et al. (2012: 1283) and they looked for the basic

core competences that are to be developed in technology management. Besides these, Su et al.

(2013: 261) searched for the beneficiaries of product innovation in Chinese context. Within

this perspective, Song and Shin (2008: 291) investigated the relationships between the host

and funding country in terms of technology transfer.

There is also literature focusing on the internalization of firms in the context of innovation

such as Kyläheiko et al. (2011: 508) has done. Also Morrison et al. (2008: 39) researched on

how to develop value chains via technological capabilities. On this point, Rush et al. (2007:

221) has more to say about policy development about innovation and technological skills.

Moreover, Tallon (2008: 21) adopts an information technology capability model in business

process agility perspective.

On the other hand, Bharadwaj et al. (1999: 378) gives information about the innovation

concept while providing knowledge about IT innovation. Furthermore, this knowledge shed

light on the organizational learning theory and Cimoli and Porcile (2009: 675) made a

contribution to the literature by mentioning some development strategies. Similarly,

Çetindamar et al. (2009: 237) focused on the technological capabilities as dynamic process

and the paradigm of technology management evolved to be more innovation oriented rather

than resource based view.

To sum up, former studies are rich in conceptual knowledge but as they all propose there

is much need to empirical studies. It is interesting to see that one of the main components of

being competitive in the recent business climate is technological capabilities and the other is

innovativeness, but the scarcity of research on this topic means there is more to be done. For

technology adoption studies it is quite normal to have bad acquisition results if the

organizational infrastructure is not ready to adopt new knowledge. The literature provides us

this valuable finding and the recent study is going to test it. Beforehand, the theory and the

hypotheses are going to be presented.




3. THEORY AND HYPOTHESES

The current business environment urges enterprises to be more innovative rather than do

conduct business in a resource based view (Arnold and Thuriaux, 1997: 1). So, in search of

the right product, the need to have higher volumes has become a subsidiary objective when

compared to product innovation. If the firm has sufficient dynamic abilities to adopt

technology and innovation in product development, it becomes more prone to achieve in the

market as the product has superior features to meet the customer requirements. Thus, firms

should deploy technological capabilities besides IT innovation in order to be more effective.

Accordingly, Berger and Diez (2006: 109) stress the importance of knowledge management

and it is crucial for the whole business processes. Therefore the firm should make use of the

knowledge by the use of IT innovation and gather the advantages of being more adoptive.

In order to achieve a working model on innovation, there is no good for every

circumstance way of doing it. So, firms should make a decision on what to improve in their

processes and this creates a unique innovation circle (Berkhout et al., 2010: 474). In other

words, they need to adopt IT innovation in their processes to be more effective (Bharadwaj et

al., 1999: 378). As the sequential development of technology is an ongoing process, the

enterprise should adopt a strategic way of developing technological capabilities as it is

impossible for all to adopt new equipment (Cimoli and Porcile, 2009: 675). Within this

context Lynskey (1999: 317) offers managers to consider short, medium and long-term aims

in a manner that doesn’t inhibit each other. Lastly, Tallon (2008: 21) recommends a structure

that is constructed inside-out in order to adopt technology and innovation in production

systems.

To this point it is obvious that firms need technology in order to cope with the challenges

related to the technological developments. Also they should make use of the knowledge

effectively in order to obtain the right products. So it is assumed to be a relationship between

IT innovation and technological capabilities. Hence H1 is uttered as follows;

“H1- There is a significant positive effect between IT innovation and technological

capabilities.”

The theory related to IT innovation based on a trivet while technological capabilities are

going to be observed in a single dimension. The following part is going to cover the

discussion about these items and some more hypotheses are going to be derived.

3.1. IT Innovation

It is crucial for firms to gather knowledge in a knowledge-based economy to make necessary

changes according to the needs of the market. So firms are about to utilize IT and in order to

maximize the advantages from bulk of information they are supposed to make innovation in

knowledge processing stages (Archibugi et al., 2009: 917). However the definition of

innovation is evolving as exploiting change in operations is also a dynamic process (Khayyat

and Lee, 2015: 210). Thus tacit knowledge is going to be limited in terms of handiness and

firms need to know the reality behind it. This requires much intention to analyze and

synthesize the information and as there is dynamic ways of gathering, the processing should

deploy innovation. Besides these the ongoing innovation process should be sustained or the

benefits of being innovative is not stationary (Lyver and Lu, 2018: 442). For decades,

colleagues searched for filling the gap between information and transformation (Arnold and

Thuriaux, 1997: 1). As a result they concluded that innovation is a new idea, object or practice

for the adopting firm. So, it naturally creates new ways of thinking (Swanson, 2010: 17).

They are supposed to develop ways of using information in a more accurate way and this shed

light to motivate on R&D and innovation processes (Berger and Diez, 2006: 109).



The quest for better innovation has redounded better forms in products, processes and

services. Then managers had to make some decisions on allocation of resources efficiently so

that subdivides of IT can be sustained (Tallon, 2008: 21). Consequently this brought a broader

paradigm of innovation based on level of uncertainty, rapidity and resistance (Berkhout et al.,

2010: 474). Hereat, researches started to deploy more IT practice such as Delphi. Thus we are

now able to discuss IT partnerships, linkages, strategic thinking and management, process

integration and lastly infrastructure related to innovation (Bharadwaj et al., 1999: 378). By

doing so we are also able to assert that innovation in IT can create some advantages on

product innovation and in turn these advantages can accelerate sales volumes and revenue

(Chen et al., 2015: 643).

Taking the above mentioned knowledge into account, we can say that IT innovation is not

just a matter of organizational climate, but it is also beneficial to R&D management, new

product development, commercialization, technological capability and operations research

(Çetindamar et al., 2009: 237). It is also obvious that any change in business processes can

result complexity and this can be a real problem if the radicalness of innovation is high

(Dibrel et al., 2008: 203).

Succinctly, IT innovation is a matter that managers should face and has some advantages

if done in a good manner. Moghavvemi and Mohd salleh (2014: 139) observed IT innovation

by means of perceived desirability, perceived feasibility and propensity to use. This research

is going to deal with this factor in three dimensions.

3.1.1. Perceived Desirability

In Theory of Reasoned Action (TRA) Ajzen and Fishbein (1980) pursued a paradigm that

offers the individual to react consciously and Moghavvemi and Mohd salleh (2014: 139)

define the perceived desirability accordingly. They assert that the concept is defined as the

degree of attraction that the individual perceives to a specific behavior. Then if the person or

the organization doesn’t want to react to a specific point, they will not be voluntarily

involving activities.

On the other hand the voluntary action plays a significant role in technology adoption and

Arnold and Thuriaux (1997: 1) claims that the whole process is bound to the perception of the

organization. In this respect Banarjee (2012: 665) offers a model derived from the work of

Lewontin and they assert that the behavior is a result of phenotype and genotypes changing in

a variation according to the environmental conditions. Moreover, Berger and Diez (2006:

109) puts emphasis on the importance of organizational learning in order to achieve a more

innovative culture. So, the learning organization should adopt searching, training, interacting

and performing.

By the way, the market should have the same perception for desirability for products as

they have the right to criticize them (Berkhout et al., 2010: 474). Moving here, the firm needs

to deploy a more strategic point of view in perceived desirability. The use of advanced IT in

business can make contribution on the performance of the product in terms of desirability,

while it can kill the life cycle due to the reactions in the market (Chen et al., 2015: 643). Then

the firms should deploy IT in order to obtain better production processes (Çetindamar et al.,

2009: 237). In this manner Swanson (2010: 17) warns that the firms can be technologically

highly developed in time, but sustaining this ability requires more attempts to R&D and

innovation.

At the same time the firm should gather some abilities to adopt technology into their

product development and all of these things are bound to the desirability of the adoption

(Dibrel et al., 2008: 203). In this respect Dutrénit (2007: 125) discusses the role of knowledge

management’s intensity. If the firm has positive climate on knowledge sharing with efficient




speed of diffusion, then the employees will be more willing to use new technology. While

emphasizing the economic limitations of IT adoption, Khayyat and Lee (2015: 210) argues

that the firms can benefit from interacting with others. Thereby they will be aware of the latest

technology and their intention to use it will ascend due to the intensity of the interaction.

Thus, the firms should be organized in networks that will help them to the challenges of the

future. In this manner Lynskey (1999: 317) focuses on the receptivity capability of the

workforce. He claims that the interaction with others will boost the employees’ and firms’

desire to adopt IT technology. Then our new paradigm is going to follow Morrison et al.

(2008: 39)’s view of adopting new technologies has prerequisites such as developing new

skills and upgrading labor competences.

Then we come up to a decision that the firms will be more willing to adopt new

technology as they interact with the business partners in the market. The desirability of the

new technology depends on the final outcomes of the new processes and the more the

organization is innovative, the more they can benefit from the adoption. From this point of

view H2a is derived;

“H2a- The technological capabilities of the firm have significant positive effect on

perceived desirability of IT innovation.”

3.1.2. Perceived Feasibility

Enterprises are constituted in order to meet the needs of people. Doing so, they must be aware

of the final outcomes of the new processes. If the investment is feasible, the financier will be

able to benchmark it with other alternatives. Otherwise founding new business is not a

rational decision. Thus, the degree to which the individual perceives the adoption of IT

innovation is a hard challenge and this is called perceived feasibility. According to

Moghavvemi and Mohd salleh (2014: 139) if the individual feels capable of performing tasks

and starting new processes, they are accepted to have high perceived feasibility.

Moreover technology diffusion is not just a matter of hardware and software. The

employees’ perception on being capable of doing things make significant difference in

adoption of new technologies (Arnold and Thuriaux, 1997: 1). In this manner, Banarjee

(2012: 665) defines some exaptive technological capabilities that the labor should develop to

have more acceptable results in innovation. Namely these capabilities are having non-adaptive

origins, using complementary means and improving particular functions of the products.

Then, the firm will gather more realistic products to meet the customer requirements. Also

Chen et al. (2015: 643) and Berkhout et al. (2010: 474) argue the need of effective team

building in order to boost the results of innovation. So, the labor should be organized in a

manner that supports the IT innovation. By this way they are supposed to have higher

business performance.

For being more feasible, Çetindamar et al. (2009: 237) suggests some acts that can ascend

and accelerate the IT innovation processes. If we are to sequence these acts initially the firm

should develop a set of core competencies on innovation. Secondly they are supposed to

reduce the complexity of adoption and avoid limitations. Lastly the top management must

support the idea of IT innovation. This is going to create a complementary set of policies and

Dibrel et al. (2008: 203) argues that in such a situation the productivity and growth of the firm

is assumed to increase.

To sum all up, as Dutrénit (2007: 125) argues the firms’ labor efficiencies are playing the

most important role in perceived feasibility on IT innovation. In this respect the firm should

act strategically by deploying and allocating suitable resources (Kyläheiko et al., 2011: 508).

By doing so, as Lynskey (1999: 317) states, they will be able to shorten product development



processes and this can make contribution on time to market. Moreover, obtaining such an

efficient labor can upgrade the firms’ abilities while assessing new mechanisms to build more

skilled competencies (Morrison et al., 2008: 39). Within this respect Swanson (2010: 17)

offers professional support on IT innovation processes.

Having a glance on the knowledge above, it is clear that the IT innovation is the job of

those who feels capable of doing new things. Then the human resources should be constituted

according to the needs of the market. Moving here the following hypothesis is derived;

“H2b- The technological capabilities of the firm have significant positive effect on

perceived feasibility of IT innovation.”

3.1.3. Propensity to Use

According to TRA, individuals and organizations should have a propensity to use new things

or have well-formed intentions to IT innovation (Moghavvemi and Mohd salleh, 2014: 139).

The locus of control here is on acts devoted to stable personality traits. Then they will be

more prone to adopt new skills via using new processes. Here comes the issue of diffusion of

innovation across the enterprise and this requires much work on depicting the benefits of the

new technology (Arnold and Thuriaux, 1997: 1). In this point Banarjee (2012: 665) offers to

make adaptations and fulfill the necessary skills to be used. However, Su et al. (2013: 261)

points out that every business needs specific capabilities to adopt innovation.

Thus, as Berkhout et al. (2010: 474) suggests, combining new procedures in a sequential

way, construction of work flows due to ideal outcomes and deviating the defects earlier in

production systems might perform well in such circumstances. Then the firm is going to be

able to scan the system and use the information properly by the use of IT innovation (Chen et

al., 2015: 643; Lynskey, 1999: 317). With respect to the all of the arguments before,

Çetindamar et al. (2009: 237) claim that firms should develop dynamic capabilities.

Furthermore, Dutrénit (2007: 125) emphasizes the importance of a good organizational

climate in order to achieve the tasks in IT innovation. By doing so, the firms are going to be

able to create what the market exactly demand and develop their own technologies (Lall,

1992: 165).

As the firm will have more propensity to use, this will create a value chain in perfection of

business processes. Thus, from exploitation to distribution the firm can maximize the

efficiency of IT usage in innovation processes (Morrison et al., 2008: 39). What’s more,

Swanson (2010: 17) claims that this type of organization can make contribution from supply

chain to customer relations management.

It is clear that the propensity to use IT innovation is just not a matter of finance. The

organization should be equipped with necessary skills so that they can devote themselves to

be more effective. So, the following hypothesis can be derived;

“H2c- The technological capabilities of the firm have significant positive effect on

propensity to use of IT innovation.”

3.2. Technological Capabilities

It is vital for enterprises to adopt themselves to technological changes. So management of

technology gained importance. Çetindamar et al. (2009: 237) define these capabilities as

planning, controlling, directing and coordination of technological implementations in a

strategic point of view. The term is used as “skills”, “capabilities”, “competences” and

“abilities” (Lynskey, 1999: 317). These skills contain more of an innovation management and

should cover tangible and intangible assets of technological challenges (Archibugi et al.,

2009: 917). In this manner, Arnold and Thuriaux (1997: 1) draw the paradigm of




technological capabilities in terms of information, rationality, technological choices and

progress besides behavior. They conclude that these competences should be more exogenous.

On the other hand, Banarjee (2012: 665) doesn’t make a distinction between innovation

and technological capabilities and in some extend this type of classification causes dilemma

about the conceptual framework for many studies. He offers a model consists of six “R’s”

(retire, retrench, replicate, recombine, redeploy and renew). Meanwhile Berger and Diez

(2006: 109) perceive technological capabilities as a consequence of organizational learning

and they interpret a set of actions related to production, investment, minor change, strategic

marketing, linkage and major change capabilities. Again, Bharadwaj et al. (1999: 378)

emphasize the role of IT management in technology management processes. Hence the

explanation of Chen et al. (2015: 643) become more affective as they claim that the IT

innovation is vital for technological capabilities. Similarly, Tallon (2008: 21) supports the

idea of IT innovation in order to obtain more desirable outcomes from adoption of

technology.

With a historical point of view, Cimoli and Porcile (2009: 675) explains the development

of advanced technologies boosted from 1950s to 1980s. This period covers the usage of

numerical control and computers in production management. When the enterprises saw the

benefits of advanced manufacturing technology, this shed light to development of many

others up to date and gave another perspective for business administration i.e. technology

management. Lyver and Lu (2018: 442) claims that technology adoption increase the level of

complexity in the production level but it can also increase the capacity by having broader

volumes in production. After adoption of technologies, firms can benefit from them while

using and they start to accumulate knowledge on technological equipment. By this way they

grant patents and eventually they start to make science based knowledge and become more

sustainable (Kyläheiko et al., 2011: 508). Thus they make use of the know-how and gradually

become creative rather than assimilative (Domínguez and Brown, 2004: 129). So, as depicted

in Dutrénit (2007: 125), the ideal way of technology management is to make its R&D

processes indigenously, however the scarcity of resources and infrastructure with the profit

seeking investors makes it difficult than ever especially in developing and under developed

countries. The distinction between nations mainly differ in terms of economic conditions and

the availability of qualified human resources (Morrison et al., 2008: 39; Lall, 1992: 165).

Moreover, this problem can be solved by direct foreign investments, as they bring the latest

technology together to the host country (Song and Shin, 2008: 291).

To this end, technological capabilities are competences should be developed in order to

manage technological needs of the firms. So, they must be dealt in accordance with IT

innovation. As mentioned above, the literature is rich in conceptual studies related to the

topic. However, empirical evidence is missing. To fulfill this gap (partly), the remaining part

of this paper will be presenting the consequences of the field research.

4. METHOD

The current paper focuses on the relationship between IT innovation and technological

capabilities of firms producing iron steel by products in Turkey. Yörük (2011: 330) focuses

on a specific context in Turkey and suggests some research on other sectors. This method is

also used in Chen et al. (2015: 643)’s work and they also gather data from Chinese context

with the same manner. There is a significant cluster in Kahramanmaraş and they meet the

total production by %80. So, the sample is defined across the firms in this cluster and data is

obtained from 180 employees. These firms were more prone to transfer directly the

technology in the past but today they started to make R&D processes for the advanced

equipment to deploy in the facilities. Thus, the research question directly suits with the



context. The more they adopt indigenous technology, the more they become aware of the

advantages of technology development.

The conceptual framework prescribes a model on the relationship between technological

capabilities and IT innovation. In order to test this model initially the former literature is

reviewed and searched for adoptable models. The model utilized in Moghavvemi and Mohd

salleh (2014: 139)’s work suits the initial part of the model as it describes the IT innovation in

a trivet. They adopted the model of Krueger (1993: 315) and used their items for measuring

IT innovation. The present paper adopts them respectively. The second part of the model is

adopted from Zhou and Wu (2010: 547)’s work as it covers technological capabilities in a

single factor. So, the scale used in this study is adopted from these two pieces of literature.

The scale contains a five point Likert type items beginning from “completely disagree” to

“completely agree” (Bharadwaj et al., 1999: 378; Su et al., 2013: 261). As it is applied in

Turkey, the items in the scales are translated into Turkish with the help of experts and the

scale is re-translated into English by other experts in order to see whether there is semantic

shift. To test the hypotheses above, a set of the responses acquired from the questionnaire is

analyzed via the use of SPSS and AMOS.

First of all the sample is analyzed in terms of demographic features in order to see

whether it depicts the reality in the sector. This method is also used in many quantitative

studies (Moghavvemi and Mohd salleh, 2014: 139; Berger and Diez, 2006: 109; Bharadwaj et

al., 1999: 378; Chen et al., 2015: 643; Dibrel et al., 2008: 203; Domínguez and Brown, 2004:

129; Iammarino et al., 2012: 1283; Kyläheiko et al., 2011: 508; Song and Shin, 2008: 291; Su

et al., 2013: 261; Tallon, 2008: 21). The sample includes men (%62,8) higher than women

(%37,2). This shows the reality of the imbalance in the participation of women in the

economy just as all other developing countries. Their education is mostly on high school level

(%72,2) and the white collars (%21,1) are more educated than blue collars (%78,9). Ages

differ from 19 to 61 and income varies from 2200 Turkish Liras (TL) to 23000 TL. Seniority

is in a range from one year to 32. In order to deal with the data in ease these three features are

grouped into four parts.

Before starting to make advanced analyses, descriptive statistics for items to be used to the

dimensions are reviewed (Iammarino et al., 2012: 1283; Khayyat and Lee , 2015: 210;

Kyläheiko et al., 2011: 508; Lyver and Lu, 2018: 442; Song and Shin, 2008: 291; Tallon,

2008: 21). According to achieve this arithmetic means are calculated and the highest

perception is measured to be in propensity to use ( =4,37), whereas the lowest is on

perceived feasibility ( =3,68). The standard deviations are lower than one and this means that

the sample shares similar perceptions.

Initially, an Exploratory Factor Analysis (EFA) is deployed in order to see whether the

items of the questionnaire are mapped properly in the corresponding construct. The EFA is

based on principle component method using varimax rotation (Bharadwaj et al., 1999: 378;

Domínguez and Brown, 2004: 129; Khayyat and Lee , 2015: 210). The results of this analysis

depict that the sample size is adequate to make EFA as the KMO and Bartlett score is 0,818.

Total Variance Explained (TVE) is %65,24 for four factors.

Table 1 Rotated Component Matrix

1 2 3 4

Cronbach

Alpha

PerDes1 .747

,842 PerDes2 .749

PerDes3 .717




PerDes4 .672

PerDes5 .711

PerDes6 .721

PerDes7 .699

PerFea1 .802

,863

PerFea2 .767

PerFea3 .695

PerFea4 .725

PerFea5 .690

PerFea6 .739

ProUse1 .731

,817 ProUse2 .782

ProUse3 .812

ProUse4 .839

TechCap1 .914

,955 TechCap2 .902

TechCap3 .889

TechCap4 .876

TechCap5 .808

After having satisfactory results in EFA, the reliability of the factors in the scale are

calculated by the use of Cronbach alphas and all coefficients for dimensions exceeded 0,842

(Bharadwaj et al., 1999: 378; Su et al., 2013: 261; Tallon, 2008: 21). Later on T-tests and

ANOVA are applied in order to see whether there is statistically significant difference among

demographic groups in the sample. This method is used in Tallon (2008: 21) and they also

searched for significant differences. In terms of gender the responses of the sample don’t

statistically differentiate. Whereas the positions of the respondents differ in propensity to use

and technological capabilities. The white collars have statistically significant higher

perceptions. Seniority and age are not decisive in responses. On the other hand there is

statistically significant difference in incomes. The highest income group has higher

perceptions in technological capabilities.

After observing the differences caused by demography, the dimensions are handled. To do

so, the relationships between sub-factors of IT innovation and technological capabilities are

calculated by the use of Pearson correlation (Lyver and Lu, 2018: 442; Su et al., 2013: 261).

The results of the analysis showed that perceived desirability is not correlated to other items.

However, perceived feasibility and propensity to use are highly correlated (r=0,342;

p<0.01**). Also technological capabilities are positively correlated to perceived feasibility

(r=0,515; p<0.01**) and propensity to use (r=0,331; p<0.01**). The theory and hypotheses of

the research can be tested by this results but the perceived desirability seems to be

uncorrelated.

Then, the model to be tested in this study is analyzed via the use of Structural Equation

Modelling (SEM). This method is being widely used as it enables to see multiple regressions

while seeking for interdependency and depict them in a graph (Hair et al., 2006; Moghavvemi

and Mohd salleh, 2014: 139; Bharadwaj et al., 1999: 378; Chen et al., 2015: 643; Cimoli and

Porcile, 2009: 675; Dibrel et al., 2008: 203; Iammarino et al., 2012: 1283; Lyver and Lu,

2018: 442; Tallon, 2008: 21). To do so, a Confirmatory Factor Analysis (CFA) is conducted

via AMOS in order to test the measurement model (Chen et al., 2015: 643; Lyver and Lu,

2018: 442; Tallon, 2008: 21).



Figure 1 CFA measurement model

The measurement model reported good fit indices (CMIN/df= 1,477; GFI=0,872;

AGFI=0,833; NFI=0,896; RFI=0,877; IFI=0,964; TLI=0,957; CFI=0,964; RMSEA=0,052).

However, the coefficients between perceived desirability and other dimensions seem to be

low. Then, reliability and validity tests are conducted by the use of Composite Reliability

(CR) and Average Variance Extracted (AVE) (Bharadwaj et al., 1999: 378; Su et al., 2013:

261; Tallon, 2008: 21). Table 2 Composite Reliability (CR) and Average Variance Extracted (AVE) Measures

CR

AV

E

MS

V

Ma

xR

(H)

Pro

pen

sity to

use

Perceiv

ed

desira

bility

Perceiv

ed

Fea

sibility

Tech

nolo

gica

l

Cap

ab

ilities

Propensity to use 0.828 0.548 0.160 0.838 0.740

Perceived desirability 0.837 0.426 0.004 0.914 -,036 0.653

Perceived Feasibility 0.851 0.502 0.316 0.950 ,400 -,062 0.708

Technological Capabilities 0.956 0.812 0.316 0.978 ,350 ,027 ,562 0.901

CR= Composite Reliability; AVE= Average Variance Extracted; MSV= Maximum Shared Variance;

MaxR(H)= Maximum Reliability

In terms of reliability CR values obtained from CFA results are higher than 0,70 and this

shows that the dimensions are reliable. For discriminant validity there seems to be no

problem, whereas for convergent validity AVE value obtained for perceived desirability is

lower than 0,5 which means that this dimension fails validity. So, items that report low factor

loadings are going to be omitted or the SEM will be constructed on means of these factors. In

,42

Perceived

desirability

PerDes1

,38

e1

1,00

1

PerDes2

,38

e21,05

1

PerDes3

,49

e3,981

PerDes4

,58

e4,84 1

PerDes5

,44

e5

,871

PerDes6

,37

e6

,68

1

PerDes7

,43

e7

,71

1

,94

Perceived

Feasibility

PerFea1

,63

e81,00

1

PerFea2

,42

e91,01

1

PerFea3

,34

e10,991

PerFea4

,61

e11

,881

PerFea5

1,57

e12

,64

1

PerFea6

1,43

e13

,69

1

,40

Propensity to use

ProUse1

,51

e141,00

1

ProUse2

,69

e151,401

ProUse3

,27

e16

,911

ProUse4

,25

e17

1,14

1

1,10

Technological

Capabilities

TechCap1

,14

e181,00

1

TechCap2

,17

e19,941

TechCap3

,20

e20,96 1

TechCap4

,25

e21

,921

TechCap5

,40

e22

,92

1

-,04

-,01

,02

,25

,57

,23

1,14

,23

,14




order to manage the data in ease, the means of the dimensions are used in the measurement

model.

Figure 2 SEM measurement model

The values obtained from the model report that the data suits well to the model

(CMIN/df= 2,864; GFI=0,977; AGFI=0,923; NFI=0,899; RFI=0,797; IFI=0,932; TLI=0,858;

CFI=0,929; RMSEA=0,102). From this model we can say that perceived desirability has

minor or doesn’t make any effect on technological capabilities, whereas perceived feasibility

explains the technological capabilities by half. Moreover propensity to use explains a quarter

of technological capabilities. Then we can depict the test of hypotheses as follows;

Table 3 Hypotheses Testing Results

Code Hypothesis Result

H1 There is a significant positive effect between IT innovation and technological

capabilities.

Rejected

H2a The technological capabilities of the firm have significant positive effect on

perceived desirability of IT innovation.

Rejected

H2b The technological capabilities of the firm have significant positive effect on

perceived feasibility of IT innovation.

Accepted

H2c The technological capabilities of the firm have significant positive effect on

propensity to use of IT innovation.

Accepted

H1 is rejected as perceived desirability reported to have no effect on technological

capabilities. H2a is also rejected for the same result. H2b and H2c are accepted as they

explain the technological capabilities by half and a quarter respectively. These results gives us

to opportunity to make some recommendation to researchers and policy makers. Initially the

items used to measure perceived desirability didn’t work well in terms of validity. So,

researchers should adopt or create another scale to measure this dimension. Secondly, policy

makers and managers should perform better in convincing the labor to use technology. As

many researches put forth, technology adoption causes complexity in work flows and

employees resist change as a result of the fear of losing their jobs or having inadequate

support from the top management in developing their capabilities. Thus the last part of the

research will be on discussing these results according to the findings of former researches.

5. CONCLUSIONS, LIMITATIONS AND IDEAS FOR FUTURE

RESEARCH

The resource based view in production management is evolving to the organizational needs as

the labor’s competence in adopting technological change can result the competitive advantage

(Tallon, 2008: 21). Yörük (2011: 330) emphasizes that these capabilities should be beyond

PerDes

PerFea

ProUse

TechCap

,40

e11

,68

e21

1,03

e31

,55

e41

,02

,49

,26



the national borders as the economy of today requires the use of technology and especially IT

in a more comprehensive way. So, there is need for researches depicting the relationship

between infrastructure and organizational aspects of production.

The aim of this paper has been to investigate the relationship between technological

capabilities and IT innovation of firms producing iron steel by products in Turkey. Former

research showed that technological capabilities and priorities of firms can vary according to

the regional location (Iammarino et al., 2012: 1283). Generalized innovation and technology

management policies are being criticized as the dynamics of all enterprises are not alike (Rush

et al., 2007: 221). Then we see that there is need for categorization and acting in a regional

manner.

Meanwhile, Kyläheiko et al. (2011: 508) classifies firm in four different categories.

Namely these are domestic replicators, domestic innovators, international replicators, and

international innovators. In order to be an international innovator the firms should have the

ability to deal with the needs of qualified labor and this requires higher pay checks besides

recreation facilities. Lall (1992: 165) warns us in reverse effects of technology adoption if the

organization is not ready to adopt it. So, managers should have a focus on holding down the

qualified labor while empowering them for the challenges of the future.

Su et al. (2013: 261) reports that innovation is only accepted to be successful if the

economical results are tangible. This is not true but economy is more of technology

development but a social phenomenon. According to Banarjee (2012: 665) IT innovation can

result many advantages by providing greater production volume and flexibility in product

development. However, he claims that if the organization is not ready to adopt new

technology, this can result drastically. So the organization should be empowered to keep up

with the challenges of the business environment. To do so, Berger and Diez (2006: 109)

propounds a model based on organizational learning and this should be adopted in all

organizations if the locus of control will be on sustainability. Moreover, Berkhout et al.

(2010: 474) claims that linear thinking will not be adequate to meet the everyday changing

customer demands. So, they propose an emphasis on continuous R&D, interaction and

developing technological capabilities of labor. Bharadwaj et al. (1999: 378) define this need

as boosting technological functionality across the whole enterprise so that every individual

can make their best to be more competitive. Furthermore Chen et al. (2015: 643) recommends

improving the level of interaction with other companies can help firms to develop novel

competences.

Archibugi et al. (2009: 917) reports that there is a huge gap between developed countries

and developing ones in terms of innovation and technological capabilities. In their work

Turkey is depicted to be the 40th

country in innovation index whereas it has the 16th

largest

economy of the world. So, as many other emerging markets, Turkey should deploy a more

indigenous innovation based policy in order to be more competitive in the world. In this

respect deploying national R&D policies can result integration of many clusters in innovative

environments (Cimoli and Porcile, 2009: 675). Otherwise, the growth in the economy doesn’t

make any contribution but ascend the debt load. The government applies many support

programs to solve this issue, however they are aborted due to the problems in reaching fund or

qualified labor just as Domínguez and Brown (2004: 129) reports for Mexico. In order to

solve a similar problem, Arnold and Thuriaux (1997: 1) offers proactive mentoring for SMEs

so that they become producers of technology rather than assimilators. Also Dutrénit (2007:

125) proposes a more science-based approach to improve the skills of the labor. Besides this,

Khayyat and Lee (2015: 210) offers a national award system that encourage researchers and

firms to be more innovative. In this respect the ideas of Cassiolato and Baptista (1996: 53) on

foreign direct investments can be adopted to Turkish context as they bring the latest




technology together. Meanwhile Song and Shin (2008: 291) offers establishment of multi-

national companies as they will be able to keep up with the local and global rivalry. In this

point receiving international support is also emphasized by Lynskey (1999: 317). By this way,

as Morrison et al. (2008: 39) proposes, integration in global value chains can make

contribution on developing a more innovative economy. Similarly, Swanson (2010: 17) offers

making engagements across the firms in order to interact more.

The present paper adopted the IT innovation dimensions used by Moghavvemi and Mohd

salleh (2014: 139) and technological capabilities of Zhou and Wu (2010: 547) and conducted

a questionnaire to an iron steel by products cluster operating in Kahramanmaraş, Turkey. The

cluster can meet the national production by %80 and has a great effect on the global demand.

180 responds are collected from various firms and the sample reported good features in

reflecting the universe. The analyses are conducted via the use of SPSS and AMOS. Initially

the descriptive analyses are made and then the hypotheses are tested via the use of SEM. The

results showed that the technological capabilities of the sample is affected by perceived

feasibility by half and propensity to use by a quarter. However no affect is detected in terms

of perceived desirability. The items used to test this dimension seemed to fail in validity. So,

as all firms has their own dynamics, there is need for a study to measure this dimension

regionally. Moghavvemi and Mohd salleh (2014: 139) reports the strongest influence on

propensity to use and the current work reports the highest influence to be on perceived

feasibility. Then we come up to a decision that the context can make significant change in the

theory and every enterprise should develop their own adoption strategy to be successful. With

respect to this finding, the findings of Dibrel et al. (2008: 203) suits well as they pursue a

strategy that is intra-centered and aims to develop firm performance.

As in all other researches, this study has some limitations. Initially the literature is limited

in terms of empirical studies, so benchmarking the results obtained from the current one was a

great challenge. Secondly, the questionnaire is applied to a little sample (although KMO and

Bartlett results show it is adequate), so generalizing these results is not possible. Lastly the

items used to measure perceived desirability failed to meet validity barely. Lyver and Lu

(2018: 442) offers to adopt their research design in different contexts so that their findings

should make greater sense. In this point we also propound the same for our research.

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