Knowledge Sharing Process, Innovation Capability and Innovation Performance: An Empirical Study

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Procedia - Social and Behavioral Sciences 75 ( 2013 ) 217 – 225

1877-0428 © 2013 Published by Elsevier Ltd. Open access under CC BY-NC-ND license.

Selection and peer-review under responsibility of The Second International Conference on Leadership, Technology and Innovation Management

doi: 10.1016/j.sbspro.2013.04.025

Corresponding author:

E-mail address: syes66@hotmail.com

2

nd

International Conference on Leadership, Technology and Innovation Management

Knowledge Sharing Process, Innovation Capability and Innovation

Performance: An Empirical Study

a

, Alaeddin Koska

b

,

c

a,bc , , 46100, Turkey

Abstract

The knowledge sharing and innovation have been subject to many studies in the literature. The knowledge sharing and innovation are two important and interrelated subjects that need to be further explored to understand their dynamics and implications. Knowledge sharing has implication for innovation capability and innovation performance of the firms. Innovation capability also affects innovation performance of the firms.

This study focuses on the knowledge sharing process and its impact on innovation capability and innovation performance of the firms. The research model along with hypotheses are developed from the literature and tested based on the data collected through a survey on companies in Kahramanmaras. The obtained data from the questionnaires are analyzed through Smart PLS 2.0 program. The results from the study partially confirm hypothesized the influence of knowledge sharing process on innovation capability of the firms. The effect of innovation capability on innovation performance constitutes another finding of this study. However, the hypothesized the influence of knowledge sharing process on innovation performance was not realized. Theoretical and practical implications of the study were discussed in the conclusion part of the study.

Keywords: Knowledge Sharing, Knowledge Management, Innovation, Innovation Capability, Innovation Performance

2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of 2nd International Conference on Leadership, Technology and Innovation Management

1.Introduction

Intense global competition, rapid change of technology and higher consumers demands have prompted organizations to look for competitive advantage for survival (Black and Synan, 1997). Today innovation is regarded as

an important mechanism to be more competitive and to survive in global business world ; Salaman and

Storey, 2002:147). Eren (1982) argues that innovation provided companies with several strategic advantages such as eliminating costs, differentiation through new product and services development and increased quality. Scholl (2005) stated that if there is no innovation then no one can speak of growth and competitiveness.

Because innovation is regarded as essential for the firms, it has become imperative to clearly identify the underlying factors that enable innovation capabilities and innovation performance. Knowledge sharing is at the center of this argument and is explored in this study to investigate its role on innovation capability and innovation © 2013 Published by Elsevier Ltd. Open access under CC BY-NC-ND license.

Selection and peer-review under responsibility of The Second International Conference on Leadership, Technology and Innovation Management

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performance. Knowledge created, transferred and shared in the firms are the main sources for the innnovation. Barquin (2001:127) noted that any attempt to imrpove company performance need to include knowledge management initiatives. Because of this, managing knowledge has become very important function of any organization and is valued and discussed in any type of organisation over the last few years. Knowledge that the organizations possess are considered to be one of the most important sources of competitive advantages. Many argued that creating,

Fang et al., 2010; Ng, 2008; Syed-ikhsan and Rowland, 2004).

Both knowledge sharing and innovation capabilities help the companies to produce innovative product and services. Drawing from the related literatures, this study proposes a research model and creates several hypotheses regarding main construct of the model and conduct a field study to test the hypotheses. This study argues that knowledge sharing processs affect innovation capability and innovation performance. The link between innovation capability and innovation performance is also examined. This study is expected to contribute to the literatures of knowledge sharing and innovation by bringing new insights from a developing country perspective.

2.Literature Review

2.1.Knowledge Sharing Process

We are living in a knowledge based society in which knowledge available to the firms is becoming strategically important resource (Van Den Hoof and De Ridder, 2004:117), some even consider it as core competence and performance driver of the firms (Barquin, 2001; Lin, 2007). Knowledge sharing is considered to be one of most important aspect of knowledge management (Gupta et al., 2000) and the success of knowledge management initiatives depends on knowledge sharing (Wang and Noe, 2010).

There are various definitions of knowledge sharing in the literature. Ryu et al. (2003) defined knowledge sharing as the behavior of an individual dispersing his or her obtained knowledge and information to other colleagues within an organization. Cummings (2003) explained knowledge sharing as a means by which an organization obtains access regarded as a necessary way to obtain knowledge for an individual and to innovate new knowledge for an organization. Hendriks (1999) explained knowledge sharing as a communication process that includes two parts: (1) the knowledge owner externalizes the knowledge; (2) the knowledge demander internalizes the knowledge. There are various factors that influence knowledge sharing behavior such as communication, information systems, rewards, organization structure, job satisfaction, organizational culture, organizational climate, leadership, the norm of Hsu et al., 2007; Ridings et al., 2002; Jiacheng et al., 2010). Knowledge sharing as an important part of the knowledge management results in several benefits at individual and organisational levels. One example is that knowledge sharing increase innovation capability and performance of the firms (Cummings, 2003; Gurteen, 1999; Liebowitz, 2002; Lin, 2007; Yang and Wu, 2008; Zhi-hong et al. 2008).

K

knowledge) Van Den Hooff and De Ridder (2004:118) defines. They base their definition on a nu view on the knowledge sharing. For instance, Weggeman (2000)

Oldenkamp (2001) discusses how knowledge sharing Van Den Hooff and De Ridder (2004:118) combine those two perspectives and name them as knowledge collecting and knowledge donating. While knowledge donating concern with

consulting colleagues in order to get them to share their intellectual capital. These two dimensions have different nature and diynamics to consider. Following Van Den Hooff and De Ridder (2004), these two dimentiosn were accepted and used in various studies (e.g. Gumus, 2007; Lin, 2007).

2.2.Innovation Capability and Innovation Performance

Oslo Manual defines innovation as the implementation of a new and significantly improved product (good or service), or a process, a new marketing method, or a new organizational method in business practice, workplace

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organizations or external relations (European Commission, 2005:46). Although the literature recognizes a wide range of innovation types within the firm (product/process, radical/incremental, technological/managerial, market pull/technology push, or competence-enhancing/competence-destroying), most of the empirical works use the product-process typology (Verde et al., 2011).

Calantone et.al., (2002) argued that Drucker (1954) was the first scholars to address the importance of innovation capability for organization. He suggests that a firm has to be innovative to survive in the volatile environment. Innovation capabilities are seen as critical to achieving a superior innovation performance. Burgelman et al., (2004) innovation s

possibilities through to economic practice. The term covers a range of activities from capability to invent to capability to innovate and to capability to improve existing technology beyond the original design parameters (Kim, 1997:9). Wallin et al., (2011) defined innovation capability as the ability to routinely achieve innovative outcomes. Innovation capability is also important for sustainable competitive advantages.

3.Hypotheses Development

3.1.Knowledge Sharing, Innovation Capability and Innovation Performance

It is argued that knowledge is the most strategically important resource for creating and sustaining competitive advantage (Fang et al., 2007). Aulawi et al. (2009) argued that knowledge can be spread, implemented and developed through development of knowledge sharing. They further argued that knowledge sharing can stimulate individual to think more critically and more creatively, so they finally can produce new knowledge. This knowledge can be used for the advantages of the companies in various ways. Jantunen (2005) argued that knowledge donating and knowledge collecting in organizations may lead to superior firm innovation capability. Lin (2007:326) also argued that knowledge collecting and donating are two closely important concepts to affect the innovation capabilities of the firms. The results of the study conducted by Lin (2007) showed the significant positive impact of knowledge sharing on innovation capability. It can be said that organization with knowledge sharing in place and practice are likely to have a chance of increasing their innovative capability.

Egbetokun et al., (2007) argued that there are various factors that could possibly contribute to the build-up of innovation capability. While innovation is a complex concept, research identifies five key areas of influence on an organisation's ability to innovate. These influences relate to leadership; opportunistic behaviour; culture and change; learning; and networking and relationship building. Factors internal to the firm include first of all, the knowledge and skills brought into the firm by the entrepreneur(s) and workforce, which they obtained through earlier experience (Egbetokun et al., 2007). Yang and Wu (2008) argued that companies create organizational innovation on operation, service and products and also can create barriers to their competitors due to tacit, dynamic, irreducible and extensible properties of knowledge they owned. Knowledge management in the firms can enable organisation to obtain a number of strategic benefits (productivity and efficiency reflected in cost savings, customer relationships, decision making, innovation, corporate agility, rapid development of new product lines, employee learning, satisfaction and retention, and management decision making) (Alavi et al., 2005/2006). In many studies, knowledge sharing is regarded as an important factor in improving innovation capability and performance of the firms (Cummings, 2003; Gurteen, 1999; Liebowitz, 2002; Lin, 2007; Yang and Wu, 2008; Zhi-hong et al. 2008). Based on these arguments, the following hypotheses are formulated.

H1: Kowledge sharing process (Knowledge collecting and knowledge donating) positively affects innovation capability.

H2: Kowledge sharing process (Knowledge collecting and knowledge donating) positively affects innovation performance.

3.2.InnovationCapability and Innovation Performance

This study also investigates the link between innovation capability and innovation performance of the firms. This research regards innovation capability as the performance of the enterprise going through various types of innovation to achieve an overall improvement of its innovation capability (Liao et al., 2009). Lawson and Samson (2001: 377)

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argued that excellent companies invest and nurture innovation capability, from which they execute effective innovation processes, leading to innovations in new product, services and processes, and superior business performance results. Calantone et al., (2002) also argued that innovation capability is closely related to organizational performance. The findinds of the study of Richard et al., (2010) indicate that R&D, resource allocation, learning, and strategy planning capabilities can significantly improve the innovation sales. R&D and resource allocation capabilities can also significantly improve new product introduction. Shan and Zhang (2009) noted that sustained competitive advantage can be achieved by enterprises raising independent innovation capability continually. Wallin et al., (2011) argued that innovation capability is crucial for companies to be competitive on the market over time. Yam et al., (2010) argued that innovation capabilities of firms create opportunities for product innnovation and firm success. Lee and Liu (2008) found that organizational innovation capability has a positive impact on organizational innovation performance. These arguments lead us to suggest that innovation capability is likely to have positive effect on innovation performance. Thus, this research proposes the following hypothesis:

H3: Innovation capability positively affects innovation performance.

4.Methodology

4.1.Research Goal

This study focuses on two important research questions; One is to investigate the influence of knowledge sharing process on the innovation capability and innovation performance, second is to explore the link between innovation capability and innovation performance.

4.2.Sample and Data Collection

To answer the research questions, an empirical study is

of this study is the companies operating within the district of this city. A survey was used to collect data and to accomplish research objectives. A questionnaire was designed based on the various related studies. The sample of the study consists of firms operating within district of Kahramanmaras. The database of the Kahramanmaras Chamber of Commerce is utilized for the e-mail and telephone number of the firms. Questionnaire was sent to these business enterprises through e-mail and 51 usable responses returned.

Answering two research questions is likely to contribute the literature by bringing new insight regarding implications of knowledge sharing process for innovation capacity. Testing the relationship between innovation capability and innovation performance is also expected to contribute to the innovation literature. All analysis were performed based on the data collected through survey by using PLS-Graph (build 1126), a Partial Least Squares (PLS) Structural Equation Modelling (SEM) tool (Ringle et al. 2005).

The original items from the study were used in this study with minor modification when required. Because some of the managers do not know English, questionnarie items were translated into Turkish. Knowledge collecting and knowledge donating items were taken and adapted to this study from (Lin, 2007; Van Den Hooff and De Ridder, 2004). Innovation capabilities (six items) were taken from Lin (2007). All the items regarding innovation performance (seven items) were taken and modified to this research from the related literature (e.g. Calantone et al., 2002; Kmieciak et al. 2012). All the items were rated on a seven-point Likert-type scale ranging between degrees of strongly disagree and strongly agree.

4.3.Analyses and Results

Table 1 shows the characteristics of the respondents and the companies participated in this study. The data collected for this study come from 51 firms from Kahramanmaras. The sample is rich in four sectors including mainly from textile (%64.7), metal (%17.6), food (%15.7), and other (%2). The ages of the respondents vary between 20-30

(%29.4), 31-40 (%33.3), and 41- -50

(%64.7), reflecting that people responded our survey tends to be young. % 66.7 of the sample is male and the remaining part (%33.3) is female. Marital status of the respondents, %64.7 is married and the rest (%35.3) are single. The position of the respondents in the firms, senior manager (%15.7), middle level manager (%33.3), lower level

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manager (%11.8), engineer (%7.8), research and development (%2), supervisor (%5.9) and worker (%23.5). Establishment year of the participant firm tend to be more than 16 years (%76.5) and the rest of the firms tend to be less than 16 years. Number of employees of the participant firms vary between 1-249 (%70.6), and this indicates that most of the companies are Small and Medium Enterprises (SMEs). The participant firms are managed by family members (%66.7), out of family members (%13.7) and professional managers (%19.6).

Table 1: Characteristics of Respondents and Firms

Age Frequency Percent Valid Position Frequency Valid Percent

20-30 15 29,4 Senior Manager 8 15,7

31-40 17 33,3 Middle Level Manager 17 33,3

41-50 16 31,4 Lower Level Manager 6 11,8

51+ 3 5,9 Engineer 4 7,8

Total 51 100 Research and Development 1 2

Gender Frequency Percent Valid Foreman 3 5,9

Male 34 66,7 Worker 12 23,5

Female 17 33,3 Total 51 100

Total 51 100 Sector Frequency Valid Percent

Establishment Frequency Percent Valid Textile 33 64,7

1-5 years 0 0 Metal 9 17,6

6-10 years 4 7,8 Food 8 15,7

11-15 years 8 15,7 Other 1 2

16-20 years 14 27,5 Total 51 100

21 years and up 25 49 Number of Employees Frequency Valid Percent

Total 51 100 1-49 4 7,8

Management Type Frequency Percent Valid 50-99 10 19,6

Family Members 34 66,7 100-149 6 11,8

Out of Family 7 13,7 150-249 16 31,4

Professional Managers 10 19,6 250-499 9 17,6

Total 51 100 500 and up 6 11,8

Marital Status Frequency Percent Valid Total 51 100

Married 33 64,7

Single 18 35,3

Total 51 100

The research model reflecting the research hypotheses H1 through H3 depicted in Figure 1. The model was analyzed using Smart PLS 2.0, a Partial Least Squares (PL) Structural Equation Modeling (SEM) tool. Smart PLS simultaneously assesses the psychometric properties of the measurement model and estimates the parameters of the structural model. Reliability results of testing measurement model are shown in Table 2. The results indicate that the measures are robust in terms of their internal consistency reliabilities as indexed by their composite reliabilities. The

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composite reliabilities of different measures in the model range from 0.88 to 0.98, which exceeds the recommended threshold value of 0.70 (Nunnally, 1978). The average variance extracted (AVE) for each measure exceeds 0.50, consistent with recommendation of Fornell and Larcker (1981). Table 2 also shows the test results regarding discriminant validity of the measure scales. The bolded elements in the matrix diagonals, representing the square roots of the AVEs, are greater in all cases than the off-diagonal elements in their corresponding row and column. This result supports the discriminant validity of the scales.

Table 2: Reliability Assessment of the Measurement Model

AVE Composite

Reliability R Square Cronbachs Alpha Knowco Knowdo Innoca Innope

Knowco 0,7967 0,9399 0,0000 0,9149 0,892

Knowdo 0,9529 0,9759 0,0000 0,9512 0,6419 0,976

Innoca 0,6682 0,8890 0,3499 0,8320 0,4243 0,5884 0,817

Innope 0,6712 0,9244 0,4744 0,9016 0,4254 0,5154 0,6888 0,819

Note: (Knowco: Knowledge Collecting, Knowdo: Knowledge Donating, Innoca: Innovation Capability, Innope: Innovation Performance) Convergent validity is tested with Smart PLS by extracting the factor loadings and cross loadings of all indicator items to their respective latent construct. The results are shown in Table 3. According to the respective table, all the items loaded (the bolded factor loadings) on their respective construct from lower bound of 0.72 to an upper bound of 0.98 and more highly on their respective construct than on any other construct (the non-bolded factor loadings in any one row). A common rule of thumb to indicate convergent validity is that all items should load greater than 0.70 on their own construct (Yoo and Alavi, 2001) and should load more highly on their respective construct than the other P< 0.01). The loadings presented in Table 3 confirm the convergent validity of measures for the latent constructs. Please note that some of the items were deleted from the model due to their low factor loading or reflect high loading on the more than one factor.

Table 3: Factor Loading and Cross Loadings

Knowco Knowdo Innoca Innope

Q 1 0,8924 0,6122 0,4175 0,3771 Q 2 0,8554 0,5487 0,3004 0,3630 Q 3 0,8679 0,5165 0,3555 0,3586 Q 4 0,9515 0,6062 0,4206 0,4170 Q 5 0,6333 0,9708 0,5035 0,4970 Q 6 0,6219 0,9815 0,6315 0,5086 Q 7 0,5223 0,5641 0,8812 0,5396 Q 8 0,4144 0,4192 0,8063 0,5211 Q 9 0,2421 0,5505 0,8505 0,5650 Q 10 0,2029 0,3733 0,7231 0,6276 Q 11 0,3713 0,4716 0,5757 0,8390 Q 12 0,3795 0,4842 0,6384 0,8527 Q 13 0,4664 0,5144 0,5060 0,7670 Q 14 0,3607 0,3288 0,6205 0,8649 Q 15 0,2533 0,2734 0,5092 0,7603 Q 16 0,2550 0,4677 0,5144 0,8259

Note: (Knowco: knowledge collecting, Knowdo: knowledge donating, Innoca: innovation capability, Innope: Innovation performance

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Figure 1: The Structural Model with Path Coefficients

Figure 1 shows the results of the structural model, where the beta values of path coefficient indicate the direct influences of predictor upon the predicted latent constructs. According to the results, knowdo (knowledge donating) but not knowco (knowledge collecting) showed a positive influence on innovation capability. This result gives partial support for the hypothesis (H1) regarding the link between knowledge sharing processes (knowledge collecting and knowledge donating) and innnovation capability. However, second hypothesis (H2) suggesting a relationship between knowledge sharing process and innovation performance is not supported. Results also indicate that innoca (innovation capability) is positively related to innope (innovation performance) confirming H3.

5.Conclusion

Current study was undertaken to reveal the impact of the knowledge sharing process on innovation capability and innovation performance of the firms operating in Kahramanmaras. The study also investigated the role of innovation capability on the innovation performance of the firms. Understanding the possible implication of knowledge sharing process on innovation may result in insights regarding how to improve organisational climate with respect to innovation capability and innovation performance. Looking at the role of innovation capability on innovation performance is also likely to produce important information toward better understanding innovation.

The results show that knowledge donating but not knowledge collecting positively affects innovation capability. Although it is expected that knowledge sharing influence innovation capability, this is partly supported in this study due to maybe low level of sample size. With a relatively big sample size, this relationship migh have been identified. Previous theoretical and empirical studies argued and showed the positive link between knowledge sharing process and innovation capabilities of the firms (Cummings, 2003; Gurteen, 1999; Egbetokun et al., 2007; Jantunen, 2005; Lin, 2007). This study gives partial support to the previous studies.

Another result from this study is that knowledge sharing process does not have any effect on innovation performance. This result was interesting because literature on the subject suggests the strong link between knowledge sharing process and innovation performance and firm performance (Alavi et al., 2005-2006; Aulawi et al., 2009; Fang et al., 2007;Yang and Wu, 2008). Perhaps, knowledge sharing process affect innovation performance through innovation capability. This study already confirmed the partial effect of knowledge sharing process on innovation

Knowco Knowdo Innoca Innoper 0,538** 0,689** 0,079 R2= 0.47 R2= 0.35 0,116 0,107 Note: Path coefficient: ** Significant at p< 0.01

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capability. In order for the firms to realize the potential benefits of knowledge over innovation performance, they need manage knowledge as well as leveraging the innovation capability.

Another finding of this study is that innovation capability of the firms has a positive significant effect on the innovation performance. This result provides insight into the related theoretical (Calantone et al., 2002;

Lee and Liu., 2008; Shan and Jolly, 2010; Richard et al., 2010). These findings reflect a strong link between innovation capability and innovation performance of the firms. Companies need to create innovation capabilities, continously increase and improve them. Innovation capability is also important because knowledge in organisation may in fact improve innovation performance through innovation capabilities of the firms.

Like every study, this study also has some limitations that need to be considered in evaluating the findings. The firms that participated in this study come from only one city with relatively smal sample size, thus limiting the generalisability of the findings. It is therefore recommended that further researches can be conducted on companies across the country. Future studies may also try to increase sample size that would help to detect the hypothesized relationships. In addition, possible future studies may also include other variables that may affect innovation capabilities and innovation performance.

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Figure

Table 1: Characteristics of Respondents and Firms

Table 1:

Characteristics of Respondents and Firms p.5
Table 3: Factor Loading and Cross Loadings

Table 3:

Factor Loading and Cross Loadings p.6
Table 2: Reliability Assessment of the Measurement Model

Table 2:

Reliability Assessment of the Measurement Model p.6
Figure 1: The Structural Model with Path Coefficients

Figure 1:

The Structural Model with Path Coefficients p.7

References