Knowledge Sharing Behaviour of Bosnian Enterprises

Özlen, Muhammed Kürşad Article Knowledge Sharing Behaviour of Bosnian Enterprises Journal of Accounting and Management Information Systems (JAMIS) Provided in Cooperation with: The Bucharest University of Economic Studies Suggested Citation: Özlen, Muhammed Kürşad (2015) : Knowledge Sharing Behaviour of Bosnian Enterprises, Journal of Accounting and Management Information Systems (JAMIS), ISSN 2559-6004, Bucharest University of Economic Studies, Bucharest, Vol. 14, Iss. 3, pp. 575-590 This Version is available at: https://hdl.handle.net/10419/310602 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Accounting and Management Information Systems Vol. 14, No. 3, pp. 575-590, 2015 Knowledge sharing behaviour of Bosnian enterprises Muhammed Kürşad Özlen a, 1 aPamukkale University, Denizli, Turkey Abstract: Knowledge Management has emerged as a useful tool for sustainability of organizational competitiveness. Beside the importance of achieving knowledge, sharing the existing knowledge is accepted as a key element for organizational success. The main purpose of this research is to investigate the influence of Knowledge sharing behaviour of Bosnian enterprises, supported by a socio-technical knowledge sharing environment, on the individual and organizational performance. In order to test the proposed model, a 7-point Likert scale survey is conducted within various Bosnian private and public enterprises. Finally, the collected data is used to test the model by structural equation modelling. The results provide that knowledge sharing practices improve organizational and individual performance by developing a socio-technical knowledge sharing environment. Moreover, this study is expected to enrich knowledge management literature in Bosnian marketplace and neighbourhood countries which have similar characteristics. Keywords: knowledge management, knowledge sharing, socio-technical environment, individual performance, organizational performance, structural equation modelling JEL codes: D83 1. Introduction Knowledge, its management and its products have never been important as they are in this age. We call this age as knowledge age, its economy as knowledge economy, its society as knowledge society, the ones who creates knowledge as 1 Corresponding author: College of Applied Sciences, International Trade and Logistics Department, Pamukkale University, Denizli/Turkey. E-mail: [email protected] Accounting and Management Information Systems 576 Vol. 14, No. 3 knowledge worker, etc. Beside the importance of knowledge itself, its production, management and dissemination (sharing) are important. Therefore, the organizational ability to identify, capture, create, share or accumulate knowledge become important (Nonaka & Takeuchi, 1995). The flow of knowledge through individuals and organizations, and organizational practices are strongly dependent upon individuals’ knowledge sharing (KS) behaviour (Bock et al., 2005) as one of the fundamental objectives of Knowledge Management in maximizing the flow of existing knowledge. Successful Knowledge sharing is supposed to enhance organizational performance (Argote et al., 2000; Alavi & Leidner, 2001). This study targets Bosnian companies as the subject population. Individual knowledge workers, especially decision makers, in Bosnian public and private enterprises are targeted for the survey. It is observed that Knowledge Management/sharing literature for Bosnian organizations is weak. It may be interesting to see the knowledge sharing behaviour of Bosnian enterprises after the problems they faced within last two decades (the war, political and economic instabilities). Few Knowledge Management studies about Bosnia and Herzegovina in the literature mostly focus on the implementation level of Knowledge Management and its adoption. They report weak levels of knowledge management understandings in Bosnian organizations (Handzic et al., 2007; Biloslavo & Kljajic-Dervic, 2011; Bartlett et al., 2012; Ozlen et al., 2012) and suggest more in order to enhance Knowledge Management success in terms of measurement and technology (Handzic et al., 2007) and Knowledge Management strategies (Ozlen et al., 2012). This research proposes and empirically tests a knowledge sharing model with the dimensions of Knowledge Sharing (KS), Socio-Technical Knowledge Sharing Environment (KSE) and Organizational and Individual Performances by employing a structural equation modelling (SEM). The results may guide Bosnia and Herzegovina and neighbourhood countries which have similar characteristics in developing successful KM and KS behaviour. Further sections of the paper introduce the relevant literature, the research model and hypothesized relationships among the research variables, the research methodology, and the findings. Finally, the last section is used to discuss the results and to conclude the paper with the implications for the research and practice. 2. Literature Review 2.1. Supportive socio-technical environment The factors such as culture, structures, and technology are suggested by the scholars as the environmental antecedents for knowledge sharing (Alavi et al., 2006). Knowledge sharing behaviour of Bosnian enterprises Vol. 14, No. 3 577 KM is concerned with social (Ribiere and Sitar, 2003) and/or technical (Tsui, 2003) factors in enhancing knowledge processes and therefore increases working knowledge and finally affects performance. Handzic (2011) suggests networked structures with modern technologies for open communication and knowledge acquisition. Therefore, she proposes an integrated socio-technical knowledge management (KM) model in order to determine the relative importance of social and technical initiatives in organizational KM. She identifies that social factors have greater importance than technical factors in increasing organizational knowledge and recommends developing a knowledge sharing conducive culture through a variety of measures such as rewards and incentives, and ensuring management commitment. Hansen et al. (1999) recommend considering KM technologies and organizational culture as a knowledge sharing facilitator in enhancing the interactions among knowledge workers. O'Dell and Hubert (2011) suggest that supportive social and technical environment, even if geographically dispersed, enhances the collaboration among the people in achieving their goals through exploitation. Liu, Olfman and Ryan (2005) recommend effective collaboration of organizational members for KM success in a virtual enterprise. They also suggest the evaluation of social relationships among individuals for successful collaboration. According to Alavi and Leidner (1999), organizational culture is accepted as an important factor for KM success. Moreover, individualistic cultures are generally found to be supportive for knowledge acquisition, while cooperative cultures support knowledge sharing. According to Davenport et al. (1998), the key factors for successful projects are knowledge friendly culture and top management support. Fink (2000) also suggests effective organizational management as an important factor to generate an enabling environment for knowledge generation and to support collaboration and knowledge sharing. O'Dell and Hubert (2011) suggest developing a knowledge sharing culture as the best strategy for KM program by (1) Leading by example; (2) Branding KM by kind messaging, formal communications, rewards and recognition and (3) Making KM fun. Technology is also recognized as extremely important in facilitating knowledge sharing and has a critical role in creating, storing and distributing explicit knowledge in an accessible and quick manner by the help of knowledge repositories, data mining and decision support systems (Hahn and Subramani, 2000) in order to establish a knowledge sharing platform. Liu et al. (2005) recommend a flexible corporate infrastructure for enterprise-based knowledge management systems to operate and support collaborations. Another dimension as an enabler of knowledge sharing is sharing motivation. Oye et al. (2011) report that knowledge sharing in workplace can be influenced by both Accounting and Management Information Systems 578 Vol. 14, No. 3 motivators and demotivators. Gu and Gu (2011) suggest the role of motivation aspect in successful knowledge sharing. Teh and Yong (2011) observe that Individuals’ knowledge sharing behaviour is influenced by intention to share knowledge. They suggest managers enhancing intrinsic motivation among employees, and developing better joint relationships and interpersonal interactions among employees to facilitate successful knowledge sharing. Teng and Song (2011) suggest voluntary sharing behaviour for increasing performance. Lastly, O'Dell and Hubert (2011) state that that people are the key element of KM, since (1) sharing and learning are social activities among people, (2) technology can hold descriptions involving complex cultural and contextual elements, (3) connecting employees and allowing them to share their deep, rich, tacit knowledge in order to guarantee the effective sharing and transfer of the practices. They suggest mutual obligation, reciprocity and individual motivation as the most powerful social forces through the organizations for successful knowledge sharing. Consequently, this study considers supportive socio-technical knowledge sharing environment as the initial construct including social, technical and motivational dimensions in order to enhance Knowledge Sharing. 2.2. Knowledge sharing Knowledge sharing practices are supposed to be very valuable in possessing and improving intellectual capital and therefore organizational success. Pugna and Boldeanu (2014) suggest exchanging knowledge capital among people in order to enhance itself and increase organizational benefits. Therefore, Knowledge sharing is one of the fundamental concerns of Knowledge Management activities. Heisig (2009) report that knowledge sharing is most frequently used in KM activities (31 of the analysed 117 KM frameworks). By considering Polanyi’s (1966) conceptualization, Nonaka and Takeuchi (1995) propose their SECI model (Socialization, Externalization, Combination, and Internalization) in order to explain tacit and explicit knowledge sharing in the knowledge creation process. Knowledge sharing transforms organizational knowledge into individual or group knowledge through internalization and socialization however transforms individual and group knowledge into organizational knowledge through externalization and combination. Vygotsky’s (1978) socio-cultural theory of learning suggests that knowledge is acquired and represented through knowledge sharing and social interaction by the social/individual and the public/private mechanisms. O'Dell and Hubert (2011) advise that the winners in the marketplace are usually knowledge-sharing cultures that can continuously value from their intellectual assets. They suggest individuals freely create, share, and use information and knowledge in a collaborative Knowledge sharing behaviour of Bosnian enterprises Vol. 14, No. 3 579 environment toward a common goal and therefore, achieve their work objectives, do their jobs quicker and systematically, and be recognized by their peers and mentors as the key contributors and experts. Wang and Noe (2010) suggest knowledge sharing as a fundamental knowledgecentered activity through which employees can mutually exchange their knowledge and contribute to knowledge application and ultimately the competitive advantage of the organization. This research evaluates knowledge sharing behaviour as the central variable of the proposed research model. 2.3. Performance variables Knowledge sharing activities in organizations are found to be on organization level or individual level and critical for both levels in order to obtain KM success. Knowledge sharing (KS) has been a common concern of researchers for the organizational dimension of KM including KS effectiveness in knowledge networks (Hansen, 2002), KS impact on individual performance (Teigland & Isko, 2003) and contribution to the organizational performance (Argote et al., 2000). Wang and Wang (2012) assume that knowledge sharing has direct positive impact on performance by increasing innovation and therefore contributing to the firm performance. They identify that both explicit and tacit knowledge sharing practices influence innovation and performance. Explicit knowledge sharing is found to have more significant influence on innovation speed and financial performance. However, tacit knowledge sharing is observed to have more significant effects on innovation quality and operational performance. Furthermore, the use of Knowledge Management Systems (KMS) is considered as the influencing factor of KMS success (Jennex & Olfman, 2004, 2005, 2006; Jennex, 2008). Wang and Wang (2012) reports that there are few studies studied the relationship between knowledge sharing and firm performance directly. This study evaluates success variables (individual performance and organizational performance) as a consequence of knowledge sharing (KMS use). 2.4. Research model and hypotheses This study proposes a knowledge sharing model based on the assumptions of Ozlen and Handzic’s (2014) Knowledge Management Systems Adoption and Effectiveness model which extends Davis’ (1989) Technology Acceptance Model (TAM) by adding antecedents and outcomes of adoption behaviour. They evaluate decision making related components for individuals (Individual’s Self-Efficacy and Task complexity) and socio-technical KMS as the antecedents. Furthermore, they Accounting and Management Information Systems 580 Vol. 14, No. 3 add performance outcomes by including knowledge, individual performance and organizational performance. In this study, social environment, KMS and sharing motivation are included as the possible drivers of Knowledge Sharing. Knowledge sharing dimension is considered as the use of KMS systems for knowledge sharing purpose. Finally, individual performance and organizational performance are proposed for the ultimate outcomes of the model as success (or effectiveness) measurements (DeLone & McLean, 1992, 2003) (Figure 1). Social (supportive organizational culture), technical (KMS) and motivation (sharing motivation) related components are collected under the name “Supportive Socio-Technical Environment”. The second component is knowledge sharing behaviour and finally organizational and individual performances are considered as the outcomes of successful Knowledge Sharing (Figure 1). Figure 1. Research model Therefore, the following hypotheses are proposed for the research model in Figure 2. H1. “Supportive Socio-Technical Environment” has a positive influence on “Knowledge Sharing”. H2. “Knowledge Sharing” will positively affect “Individual Performance”. H3. “Knowledge Sharing” will have a positive impact on “Organizational Performance”. 3. Methodology 3.1. Research design and instrument A survey based method is preferred in order to empirically analyse the proposed research questions and to verify the constructed research model. The questionnaire is developed according to a seven-point Likert scale (1=strongly disagree, Supportive Socio-Technical Environment Knowledge Sharing Individual Performance Organizational Performance Knowledge sharing behaviour of Bosnian enterprises Vol. 14, No. 3 581 2=disagree, 3=slightly disagree, 4=neutral, 5=slightly agree, 6=agree, 7=strongly agree). Furthermore, the survey is distributed both on English and Bosnian language. 3.2. Sample The survey focused on the employers of Bosnian public and private enterprises. Mainly high rank employees such as supervisors, presidents, auditors and CEOs are targeted. On the other hand, the other level employees are also surveyed. Because of the availability of respondents, convenience sampling is preferred while selecting the sample. Totally 207 responses are achieved from distributed surveys. One experienced difficulty is that the awareness of KM in general. Hence, KM and the goal of this research are briefly explained to the respondents in order to increase the number of qualified data. Another challenge is that lack of trust towards this kind of surveys which requires giving certain internal information about company. The sample size is found to be sufficient to test the assumed relationships by structural equation modelling. MacCallum et al. (1999) and Kline (2011) suggest that an increasing sample size is better for the possible problems with factor analysis and the validity of the statistical results. The achieved sample size (207 responses with 26 items) can be accepted as almost satisfactory according to the literature (Nunnally, 1978; Velicer & Fava, 1998; Garson, 2012). Descriptive statistics, factor analysis, correlation analysis and reliability test are performed in SPSS 18 and the structural model is analysed by the help of structural equation modelling (SEM) software AMOS 18. 4. Results 4.1. Demographic information The respondents are mainly from operational (35,3%), administrative (26,6%) and educational (17,4%) departments. Their positions are as follows: clerical workers (42%), managers (28,5%), university lecturers (21,7%), etc. Male and female respondents are nearly equally participated (52,7% vs. 47,3% respectively). Accounting and Management Information Systems 582 Vol. 14, No. 3 Table 1. Respondents’ departments Respondents According to Their Departments Frequency Percent Operations 73 35.3 Administration 55 26.6 Education 36 17.4 Finance 11 5.3 Law 10 4.8 Marketing and Sales 9 4.3 Auditing 7 3.4 Research and Development 5 2.4 Human Resources 1 0.5 Total 207 100 4.2. KM Implementation Level The respondents also evaluated their organizations KM implementation levels. Few respondents (30/207) rated their organizations as having no KM strategy. According to 82 responses, their organizations have at least a KM strategy (82/207). 62 respondents stated that their organizations have an implemented KM strategy. Moreover, 50 respondents rated their organizations as successful in knowledge sharing. 27 respondents assume that KM practices are a part of their organizational culture. 35 considered their organizational internal environment is approvable for emerging of KM. 25 respondents suppose their organizational external environment as approvable for emerging of KM. Figure 3. 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