Organizational culture, structure, technology ...

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Organizational culture, structure, technology infrastructure and knowledge sharing Empirical evidence from MNCs based in Malaysia Md Zahidul Islam

MNCs based in Malaysia

67 Received 19 May 2014 Revised 8 September 2014 Accepted 25 October 2014

Faculty of Business, Economics and Policy Studies, Universiti Brunei Darussalam, Brunei, Brunei Darussalam

Sajjid M. Jasimuddin Euromed Management, Marseille, France, and

Ikramul Hasan Faculty of Business, Economics and Policy Studies, Universiti Brunei Darussalam, Brunei, Brunei Darussalam

Abstract Purpose – This paper aims to examine how organizational culture, structure and technology infrastructure influence knowledge sharing. Design/methodology/approach – This study is based on quantitative research, administered on 90 managerial staff in multinational corporations (MNCs) based in Malaysia. Findings – The paper explains the role of organizational cultural and structure on knowledge-sharing processes in MNCs, with the moderating effect of technology infrastructure. Learning and development, top management support and centralization are positively related to knowledge sharing, using technology infrastructure as a moderator. Research limitations/implications – The findings will help MNCs to create an appropriate environment of knowledge sharing. However, the research is limited to MNC’s in Penang, Malaysia, only. Furthermore, similar research can be extended to MNCs in other Asian countries with a larger sample which may bring more statistical power and, thereby, increases generalizability. Practical implications – The outcome of this research provides useful indications of how organizations can work to ensure knowledge sharing within their work place. Originality/value – While the links between organizational culture and knowledge sharing and between organizational structure and knowledge sharing have been examined independently, few studies have investigated the association between the three concepts. This paper examines the nature of this relationship and presents empirical evidence, which suggests that the relationship between organizational culture, organizational structure and knowledge sharing is moderated by the technology infrastructure. Keywords Knowledge sharing, Organisational culture, Applied knowledge management, IT architecture Paper type Research paper

VINE Vol. 45 No. 1, 2015 pp. 67-88 © Emerald Group Publishing Limited 0305-5728 DOI 10.1108/VINE-05-2014-0037

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1. Introduction In today’s knowledge-driven economy, organizations acknowledge knowledge as a strategic resource which is shared and created to ensure a sustainable competitive advantage (Zhang and Jasimuddin, 2008; Howell and Annansingh, 2013; Jasimuddin, 2007). Knowledge management is an integrated process that collects, stores and disseminates knowledge in an organization. Although sharing of knowledge among organizational employees is encouraged (Jasimuddin and Zhang, 2011), knowledge sharing is not straightforward. For example, tacit knowledge is more difficult to share than explicit knowledge which can be easily disseminated to a large number of people (Ling et al., 2009; Jasimuddin et al., 2005a, 2005b). In this regard, Gold et al. (2001) identify several key factors (e.g. culture, structure and technology) that enable smooth and efficient sharing of knowledge. The topics surrounding organizational culture and structure have attracted considerable interest among both academics and practitioners within knowledge management field (Zheng et al., 2010; Liao et al., 2011; Wiewiora et al., 2013; Islam et al., 2012; Jasimuddin et al., 2005a, 2005b). Zheng et al.’s (2010) study, for example, examines the mediating role of knowledge management in the relationship between organizational culture, structure, strategy and organizational effectiveness, suggesting that knowledge management fully mediates the impact of organizational culture on organizational effectiveness, and partially mediates the impact of organizational structure and strategy on organizational effectiveness. Similarly, the use of technological infrastructure within an organization impacts upon the design of the business, its economic performance and the working conditions of organizational members (Doherty et al., 2010). However, the notions of organizational culture and structure have been frequently discussed independently in the existing literature. But the previous studies rarely combine them. Liao et al. (2011), for example, examine the relationship between environment and organization culture with the mediating role of knowledge management. We know very little about how organization culture and structure jointly influence knowledge sharing. It is argued that technology can be moderated to test the relationship of organizational culture and structure with knowledge sharing. The present paper intends to fill in the gap in the current literature by adding technological infrastructure as a moderating factor in the relationship between organizational culture, structure and knowledge sharing and quantifying the relationship. Most specifically, the paper will focus on the influence of organizational culture and organizational structure, moderated by technological infrastructure, on knowledge sharing. The primary aim of this paper is to present a theoretical model and empirical analysis of the relationship between organizational culture, organizational structure and knowledge sharing. It also contributes to our understanding about the mediating effect of technological infrastructure in this relationship. Hence, the rest of the paper is organized as follows. In the next section, we review the relevant literature and develop the hypotheses. We then describe the methodology adopted in this research, followed by an analysis of the findings. The subsequent section discusses the empirical results. Finally, we conclude with the directions for future research and theoretical and managerial implications.

2. Literature review This section rigorously reviews the relevant literature to propose a research model which posits that the characteristics of organizational culture and structure influence knowledge sharing in the context of multinational corporations (MNCs) based in Malaysia. In addition, potential causal relationships between them are explored using the moderation effect of technological infrastructure.


69 2.1 Knowledge sharing Knowledge sharing among employees in an organization is widely regarded as a crucial component in business (Szulanski, 2000; Jasimuddin et al., 2012). Jasimuddin (2006), for instance, contends that knowledge sharing is important for enhancing the competitive advantage of an organization. Jasimuddin’s (2006) argument is developed by Cohen and Levinthal (1990) who suggest that knowledge transfer is a critical factor for a firm’s ability to respond to changes, innovate and achieve competitive success. Drawing on the social capital theory, it can be argued that knowledge sharing between individuals is contingent upon social interaction which is vital for making any successful decision (Adler and Kwon, 2002; Nahapiet and Ghoshal, 1998; Kostova and Roth, 2003). In line with this, Teh and Sun (2012) argue that knowledge sharing is a process of exchanging knowledge, experiences and skills through social interaction within a department or organization. Parallel to this, Dyer and Nobeoka (2000) define knowledge sharing as the activities of how organizational members exchange their knowledge to improve organizational learning capacity, stimulate the creation of new knowledge and, eventually, enhance its competitiveness. An attempt can be made to provide a working definition of knowledge transfer for the purpose of the present research: knowledge sharing within an organization is an act of transmission of organizational knowledge among employees so that they can take purposeful actions and involve in innovation. However, the motivation of knowledge sharing is not straightforward (Jasimuddin et al., 2006). Wang et al. (2014) investigate how to motivate knowledge sharing in an organization, arguing that knowledge sharing will be greater for employees who are encouraged, evaluated and rewarded. Keong and Al-Hawamdeh (2002) observe that knowledge is power and no one is willing to give it away freely. In this regard, others (Davenport and Prusak, 1998; Liao et al., 2011; Gibbert et al., 2002) contend that leadership, organizational structure and organizational culture are critical success factors for knowledge sharing. These issues will be elaborated in turn. 2.2 Organizational culture A knowledge supporting culture is one of the most important conditions to ensure efficient knowledge flow among organizational members (Kazi, 2005). From a constructivist perspective, organizational culture can be viewed as a continuous process of building/rebuilding identity in and around an organization (Tuan, 2012). This, in turn, facilitates social integration among members which helps the organization sustain as a whole, assimilating different subgroups within its environment (Koot, 2004). Appropriate organizational culture is a prerequisite for knowledge creation and dissemination. Several authors (Wiewiora et al., 2013; Ajmal and Koskinen, 2008; De Long and Fahey, 2000) also comply with these facts that culture establishes an

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organizational context for social interaction and creates norms regarding what is “right” and “wrong”. Culture may also act as a barrier to knowledge sharing (McDermott and O’Dell, 2001). Diverse cultures at the intra-organizational, organizational, trans-organizational and supra-organizational levels may act simultaneously, and thus result in cultural complexity (Sackmann and Friesl, 2007). Most specifically, employees’ resistance to change, their motivation to share knowledge and leadership commitment are also affected by the cultural dimensions (Davenport and Prusak, 1998). Therefore, a pertinent culture should be established to encourage people to share their knowledge within an organization, as well as among business partners (Rivera-Vazquez et al., 2009). Innovative organizations create competitive advantages through fostering learning and development, asking people to collaborate and allowing them to share power by practicing participative decision-making (Hurley and Hult, 1998). Although there are various characteristics of culture that affect knowledge sharing, this study focuses on three characteristics: collaboration, learning and development and top management support. 2.2.1 Collaboration. The role of collaborative tools to support social construction of knowledge is evident in organizations around the world (Ryan et al., 2010), and the inclusion of knowledge management as an organization’s best practice is meant to ensure that collaboration is institutionalized, and that knowledge sharing occurs (Rivera-Vazquez et al., 2009). Collaboration refers to how people in an organization actively assist and support in work-related issues. Several studies (Parker and Price, 1994; Eisenberger et al., 1990; Hurley and Hult, 1998; Krogh, 1998; Nahapiet and Ghoshal, 1998) also find the relationship between collaboration and knowledge sharing. Hence, we hypothesized that: H1. Collaboration has positive relationship with knowledge sharing. 2.2.2 Learning and development. Learning and development orientation refers to the extent to which an organization is willing to encourage its members to learn and develop themselves for long-term success. This is due to the fact that an organization relies largely on its employees’ skills and knowledge to produce breakthrough in its products and services (Tidd et al., 1998). Several authors (Yang, 2007; Jones et al., 2003) contend that there is a relationship between learning process and knowledge sharing. Organizations facilitate learning process through sharing knowledge among organizational member. Therefore, we have formulated the following hypothesis: H2. Learning and development orientation has positive relationship with knowledge sharing. 2.2.3 Top management support. Top management support within an organization through leadership skills acts as a role model in which knowledge sharing occurs without any coercive influence. Several scholars (Kerr and Clegg, 2007; Jasimuddin et al., 2006; Islam et al., 2011) contend that leaders play an important role in organizational knowledge sharing. Others (Bircham-Connolly et al., 2005; Seba et al., 2012) emphasize on the pivotal role of leadership in knowledge sharing. Leaders, first, contribute to employees’ learning from their personal experience; second, persuade employees to transfer their knowledge to generate new knowledge; third, they influence decision-making process based on valuable knowledge shared between members.

Parallel to this, Kennedy and Mansor (2000) also find that top management support has an impact on knowledge-sharing activities. We, therefore, hypothesize that:


H3. Top management support has positive relationship with knowledge sharing. 2.3 Organizational structure Organizational structure is defined as the ways in which tasks are formally segregated, classified and coordinated (Robbins, 1996). Ghani et al. (2000), as cited in Liao et al. (2011), define organizational structure as the formal allocation of work roles and administrative mechanism to control and integrate work activities. As organizations are perceived as knowledge integrating institutions, high importance should be placed on designing the internal structure of a company, especially the hierarchical design to empower decision-making, standardize rules and procedures and integrate members and work (Chen et al., 2010). The nature of coordination among employees, which is largely decided by the control mechanism, influences knowledge sharing. The control mechanisms are also closely related to other structural dimensions like centralization, formalization and specialization (Willema and Buelensa, 2009). The real benefit of knowledge may not be realized if organizational design does not correspond to the established rules of knowledge sharing. Knowledge, like other resources, may not be used in its full potential if an appropriate structure is not in place (Claver-Cortés et al., 2007). An organizational structure can be classified using various taxonomies, namely, simple, team structure, bureaucratic, mechanistic, organic and matrix. Mechanistic (centralized) and organic (flexible) structures are at the two extremes. Mechanistic organization has relatively low decentralization and complexity in which it operates under specific norms and regulations with predefined functional roles, whereas organic structures are characterized by informal control mechanisms, adaptability and open communication (Burns and Stalker, 1961). The underlying characteristics that differentiate these two extremes are degrees of formalization and centralization. A flexible structure (i.e. horizontal organization) with fewer levels, instead of a bureaucratic one (traditional and hierarchical), is more preferred to make knowledge transfer (Lie and Slocum, 1992; Kanter, 1994). An informal environment, where decision-making is decentralized, hierarchies are minimized and instructions are carried out with few rules, induces employees to work as cohesive groups facilitating interpersonal communication and, thus, helps the transfer of knowledge (Morand, 1995). Indicating the relationship between organizational structure and knowledge-sharing activity, Abouzeedan and Hedner (2012) argue that vertically integrated organizations are less focused to generate innovation than horizontally integrated ones, which are more open and fluid. The social aspect of organizations has been viewed as a social network which is assumed to be composed of hierarchy, density and connectivity that establishes contact and ease of accessibility between employees in exchanging knowledge (Inkpen and Tsang, 2005). Organizational structure also governs communication patterns and interaction, which are based on the social networking theory. Several authors (Chen et al., 2010) argue that both formalization and centralization affect knowledge flow. Accordingly, a combination of formal organizational structure and a non-hierarchical, self-organizing organizational structure would improve knowledge creation and sharing capabilities (Nonaka and Takeuchi, 1995).

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2.3.1 Formalization. Formalization is defined as the extent of job codification and rule observation that exists in an organization (Sciulli, 1998; Andrews and Kacmar, 2001). Chen et al. (2010) claim that the obedience of the rules and procedures may constrain the employees in combining various sources of knowledge for developing new product or service. Formalization measures the degree to which an organization uses its rules and procedures to prescribe behavior (Liao et al., 2011). Less formal structure in an organizational boundary exposes fewer formal rules and regulations. As a result, employees can communicate with each other by sharing their knowledge which creates greater flexibility and creativity. Previous studies (Islam et al., 2010; Chen et al., 2010; Willema and Buelensa, 2009; Islam et al., 2008) also observe that less formal structure allows more transfer of organizational knowledge. Thus, we propose the following hypothesis: H4. Formalization has negative relationship with knowledge sharing. 2.3.2 Centralization. Centralization refers to the hierarchical level of authority and the extent that individuals may participate in the decision-making process within an organization (Andrews and Kacmar, 2001). Liao et al. (2011) describe the extent to which the right to make decisions and evaluate activities is concentrated. Centralization generates a non-participatory environment that lessens communication, commitment and involvement among participants (Damanpour, 1991). Parallel to this, several scholars (Chen et al., 2010; Janz and Prasarnphanich, 2003) argue that centralization leads to inefficiency in creating and sharing knowledge, as employees have no discretion in their working environment. A well-defined centralized hierarchical coordination does not motivate people enough to share their valuable thoughts and suggestions. In contrast, intrafirm networks with a lower degree of centralization foster interdependence and encourage cooperation, as partners share control over outcomes (Chen et al., 2010). It is argued that the degree of centralization within the organization explains the extent to which knowledge sharing will be hindered (Willema and Buelensa, 2009; Tsai, 2002). Thus, we hypothesize that: H5. Centralization has negative relationship with knowledge sharing. 2.4 Technology infrastructure Technology infrastructure is considered as an essential enabler in the knowledge-based economy. Such infrastructure plays a vital role in the knowledge management system of an organization. To create and use new knowledge, the sharing of the existing knowledge needs to be facilitated by incorporating various technological platforms. Several scholars (Ho et al., 2012; Abouzeedan and Hedner, 2012; Harrison and Daly, 2009; Ryan et al., 2010; Nishimoto and Matsuda, 2007; Sridharan and Kinshuk, 2002; Zhang and Jasimuddin, 2012) emphasize on technology infrastructure as an element crucial to the knowledge sharing in organizations. Recently, there has been a trend toward the application of advanced technology (e.g. the Internet, intranets, Web browsers, data warehouses, data mining and software agents) to facilitate knowledge-sharing activities. Technology infrastructure is an important variable in the proposed framework. While hardware, networking and bandwidth are important, they are assumed to be part of any modern organization landscape. In contrast, knowledge-sharing tools such as social media (FB, Twitter, Wikis, GoogleDocs, etc.), content repositories, dynamic Web sites, space for project

management, etc. are critically important in knowledge sharing, storing, dissemination and maintenance. The use of technology in supporting knowledge management opens new capabilities (Standing and Benson, 2000) in business processes. Therefore, information technology (IT) is considered as an indispensable tool that supports discovery of useful knowledge (Ho et al., 2012). Collaborative tools such as intranet-based systems allow people to work together and collaborate interactively. Individual knowledge is thus converted into organizational knowledge through knowledge sharing with the help of IT (Ryan et al., 2010; Zhao and Luo, 2005). Mentzas et al. (2001) shed some light on detailed specific topics of IT-support for knowledge management such as learning and development. The effective use of IT ensures timely access and exchange of knowledge so as to facilitate the decision-making process (Harrison and Daly, 2009; Ho et al., 2012). The fact is that it works as a powerful mechanism for knowledge creation and distribution within and across organizations through encouraging social interactions among people from different organizational hierarchies (Ryan et al., 2010). Along with the infrastructure itself, there is also the need to have IT leaders, as they play important role in creating vision, attitude and behavior which are critical for employee perceptions of innovation, and thus, its adoption outcomes (Ke and Wei, 2008). Top management empowers the content owners and knowledge bearers the responsibility to manage and share their knowledge. An intranet may be classified as a knowledge management application, as a part of the technology infrastructure, as it is capable of distributing knowledge. For example, Doherty et al. (2010) critically reappraise the impact of IT on organizational structure. In an organizational structure, intranets are often used to support knowledge access and exchange within organizations (Ruggles, 1998). Most specifically, such intranets-based information and communications technologies play a crucial role in managing knowledge by allowing efficient distribution and access of knowledge (Ho et al., 2012; Nishimoto and Matsuda, 2007). The technology enactment framework also emphasizes the influence of organizational structure on the design, development, implementation and use of technology. To build knowledge-sharing capabilities, an organization must develop a comprehensive IT infrastructure. Knowledge is transmitted and created within an organization with the use of technological infrastructure (Ryan et al., 2010). Technology refers to the infrastructure of tools, systems, platforms and automated solutions that enhances the development, application and distribution of knowledge (Chong et al., 2010). Technology platforms can only assist in stimulating knowledge flow, but their effect on knowledge sharing is perhaps less visible without a proper cultural and organizational context in which people are encouraged to develop and share their knowledge (Clarke and Rollo, 2001). Based on these arguments, the following hypotheses can be proposed: H6. Technology infrastructure moderates the relationship between collaboration and knowledge sharing. H7. Technology infrastructure moderates the relationship between learning and development orientation and knowledge sharing. H8. Technology infrastructure moderates the management support and knowledge sharing.

relationship

between

top


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H9. Technology infrastructure moderates the relationship between formalization and knowledge sharing. H10. Technology infrastructure moderates the relationship between centralization and knowledge sharing.

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Based on the literature review, this study examines the relationship between organizational culture, structure and knowledge sharing with the use of technology infrastructure as a moderator. A modest attempt is made to design a model by considering five independent variables (i.e. collaboration, learning and development, top management support, formalization and centralization) and a dependent variable (i.e. knowledge sharing). Figure 1 presents the model with the proposed ten hypotheses showing the directions of influence. The research model guides the execution of the study. Overall, the study offers an empirical test for ten hypotheses, which are developed in the previous paragraphs. From the existing studies on the determinants of knowledge flows from the MNCs, we infer that organizational culture and structure are preconditions for knowledge transfer. The theoretical framework suggested in this study draws the organizational culture, structure and technology infrastructure, and their relationship to knowledge transfer. The paper develops ten hypotheses regarding these concepts. 3. Research methodology A hierarchical multiple regression analysis is used to test the hypotheses, using statistical software SPSS version 15. The hierarchical procedure allows us to examine whether adding predicator variables and interaction terms increased the statistical power of the model (Kotabe et al., 2011). The source of data collection was MNC which is an effective vehicle for knowledge transfer (Inkpen, 2008; Hong et al., 2009). A questionnaire survey was developed using the previous work and utilized for data collection. The questionnaire consisted of seven sections having measurement scale for collaboration, learning and development, top management support, formalization, centralization, technological infrastructure and knowledge sharing (Appendix). A draft questionnaire was pilot tested on few academics and professionals to validate these measures prior to finalizing it. The primary means of distributing the survey questionnaire was via e-mail with a cover letter explaining the objectives of the study.

Culture Collaboration Learning and Development orientation Top management support

H1-H5 Structure Formalization Centralization

Figure 1. A conceptual model of knowledge sharing

H6-H10 Technology Infrastructure

Knowledge Sharing

The 35 global high-tech MNCs operating in Malaysia were selected randomly. It is widely believed that global MNCs apply more knowledge management tools than local companies. The respondents of this study were managerial staffs who were also selected randomly from the MNC based in Penang, Malaysia. A total of 150 questionnaires were distributed, 90 were returned showing a response rate of 60 per cent. The respondents were appropriate in terms of sharing knowledge, and were associated with mentoring and leading a team which is essential for knowledge sharing. To ensure content validity, the items of the questionnaire were selected from the previous research, adopted particularly from the constructs used by other scholars (Gold et al., 2001; Yang, 2007; Hedlund, 1999; Hurley and Hult, 1998). Cronbach’s alpha was used to evaluate the internal consistency of the items. All questionnaire items were assessed on a 5-point Likert-type scale ranging from (1) to (5) representing (1) as “strongly disagree” to (5) as “strongly agree”.


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4. Results The profile of the respondents include: university educated (91.1 per cent), male (56.7 per cent) and in the above 30-years age group (74.4 per cent). The study particularly targeted the middle- and the top-management personnel. In total, the majority of the companies were in the electronics/electrical sector (83.3 per cent). In term of years of their operation in Malaysia, 63.3 per cent of the MNCs under the study were operating in Malaysia for more than 20 years. Demographic information is demonstrated in Table I. The internal reliability can be tested using Cronbach’s alpha (Fornell and Larcker, 1981). Hence, Cronbach’s alpha (␣) reliability estimates were used to measure the internal consistency of these multivariate scales (Nunnally, 1978). Table II shows the reliability assessments for independent variables, moderating variable and dependent variable to test the internal consistency. The reliability analysis indicates the degree to Demographic variable

Category

Gender

Male Female 21-30 31-40 Above 41 Post-graduate and above Degree Certificate/diploma/secondary ⬍1 1-2 3-5 Above 6 Electronic/electrical Chemical Others ⬍ 100 101-500 501-1,000 Above 1,000

Age (years)

Education level

Current position (years)

Type of industry

Annual revenue, RM (in million)

Frequency

(%)

51 39 23 57 10 13 69 8 19 31 30 10 75 2 13 5 16 14 55

56.7 43.3 25.6 63.3 11.1 14.4 76.7 8.9 21.2 34.4 33.3 11.1 83.3 2.2 14.4 5.5 17.8 15.6 61.1

Table I. Demographic information

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which items in each set correlate with one another. Cronbach’s alpha (␣) was used to establish this inter-item consistency. The Cronbach alpha (␣) should be greater than 0.7 to indicate a strong reliability for a questionnaire content (Nunnally, 1978; Cuieford, 1965). In this study, the Cronbach ␣ of the majority of constructs was greater than 0.7, except top management support. The smallest Cronbach’s alpha was 0.67 which indicates a reliability (may not be stronger reliability) for our questionnaire content. Regression analysis was carried out to test the relationship of the dimensions of organizational culture and structure with knowledge sharing. The first regression models involve organizational culture and organizational structure as independent variables and knowledge sharing as the dependent variable. This regression analysis was conducted to test H1 to H5. The coefficient of determination R2 is 0.578. The R2 indicates the fraction of total variance in the endogenous construct accounted for by those exogenous constructs (Chin, 1998; Mathieson et al., 2001). Overall, a substantial amount of variance is explained in the endogenous variable, knowledge sharing. In Table III, the coefficient of determination R2 (0.578) indicates that organizational culture and structure variables explain 57.8 per cent of the variance of knowledge sharing. The finding of the study rejects H1 and H5, while accept hypotheses H2, H3 and H4. Technology Infrastructure (TECH) was taken into account as a moderating variable. Table IV describes the result of the hierarchical regression when technology infrastructure moderate the relationship. The coefficient of determination of R2 significantly increases to 0.71 when technology infrastructure was considered as a moderating variable. Thus, the bigger the R2, the more predictive power the model implies (Weinfurt, 1995). Overall, a substantial amount of variance is explained in the endogenous variable, knowledge acquisition. Its R2 value of 0.71 indicates that a

Variables

Table II. Summary of reliability analysis

Support and collaboration Learning and development orientation Top management support Formalization Centralization Technology infrastructure Knowledge sharing

Variable Collaboration Learning and development orientation Top management support Formalization Centralization R2 ⫽ 0.578 Significance ⫽ 0.000 Durbin–Watson ⫽ 2.078 Table III. Regression summary F-value ⫽ 22.453

No. of items 5 5 6 5 5 7 6

No. of items deleted None None None None None None None

Cronbach’s ␣ 0.86 0.70 0.67 0.73 0.70 0.74 0.74

␤

Significance

0.190 0.373 0.483 0.367 0.141

0.07 0.00 0.00 0.00 0.06

Model 1 2 3

Collaboration (COL) Learning and development (LEARN) Top management support (MGT) Formalization (FOR) Centralization (CEN) Technology infrastructure (TECH) COL ⫻ TECH LEARN ⫻ TECH MGT ⫻ TECH FOR ⫻ TECH CEN ⫻ TECH

Variables 0.19 0.43 0.54 0.31 0.11 0.22 0.96 4.69 7.58 0.15 3.70

␤ 0.07 0.00 0.00 0.00 0.06 0.08 0.63 0.00 0.00 0.86 0.00

Significance

0.57 0.59 0.71

R2

0.57 0.01 0.12

R2 change

22.45 3.73 6.33

F change

0.00 0.08 0.00

Significance F change

2.038

Durbin–Watson


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Table IV. Hierarchical regression summary

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substantial fraction of total variance of successful knowledge sharing was, indeed, predicted by the variables considered. From the hierarchical regression, it was found that moderator TECH was not significant enough to be considered as an independent variable. However, as proposed in the study, TECH plays a role as a moderator. The hypothesized relationship between centralization and knowledge sharing which was rejected in Model 1 is positively moderated by TECH in Model 3. This indicates that TECH moderates the relationship between centralization and knowledge sharing (Significance ⫽ 0.00). Therefore, from the findings of hierarchical regression, we can accept the following hypotheses: • Technology infrastructure moderates the relationship between learning and development and knowledge sharing (H7). • Technology infrastructure moderates the relationship between leadership commitment and knowledge sharing (H8). • Technology infrastructure moderates the relationship between centralization and knowledge sharing (H10). 5. Discussion This study attempts to extend our understanding of the relationship between organizational culture, structure and knowledge sharing by adding technology infrastructure as a moderator in their relationship. We propose and test an integrated framework in which organizational culture and structure are treated as the key factors that influence knowledge sharing, and technology moderates such relationship. The study reveals that collaboration plays an important role in organizational knowledge sharing. Collaboration is found to be positive but insignificant among the factors contributing to knowledge share in this study. This result partially supports the work of Ryan et al. (2010) and Rivera-Vazquez et al. (2009). The outcome regarding the relationship between collaboration and knowledge sharing found in MNCs based in Malaysia could be interpreted from different angle. It is possible that people within an organization believe in the principle of knowledge hoarding, what Hansen (1999) identifies the fear of losing power. The notion explains individuals’ unwillingness to share knowledge with others as they believe their acquired knowledge is valuable and necessary for their personal benefits (e.g. job security, career progression). This is quite a normal tendency of individuals and the opposite may be true when they perceive that their colleagues and managers are supportive what Jasimuddin et al. (2006) term it as “reciprocity”. The insignificant moderating role of technology infrastructure, as evidenced in the relationship between collaboration and knowledge sharing, confirms that employees are reluctant to share information despite the technological orientation their organizations have toward knowledge-sharing process. Learning and development orientation is found to have a significant relationship with knowledge sharing. This result also confirms the previous studies (Islam et al., 2008; Yang, 2007). From the organizational perspective, learning and development orientation is a prerequisite for long-term success in knowledge cultivation. Learning through sharing knowledge among organizational members can bring in benefits for an organization (Yang, 2007; Jones et al., 2003). First, it enables employees to reflect on the consequences of their behaviors and actions. Second, it augments the ability to approach

to organizational problem more accurately by understanding the environment, obtaining insights from the place where they operate. That is why organizations rely largely on its employee skills and knowledge so as to produce a breakthrough in its products and services through continued learning (Tidd et al., 1998). Because learning is vital for knowledge flow, technology helps bridging the gap between knowledge sharing and learning. In addition, technology infrastructure can be explained as an enabler to the knowledge-based organization, especially in the area of learning and development. Moreover, technology infrastructure plays a positive and significant role between learning and development and knowledge sharing. The research also reveals that leaders as role models play an important role in organizational knowledge sharing, arguing positive and significant relationship between top management support and knowledge sharing. The finding of this paper also supports the previous work (Islam et al., 2011; Kerr and Clegg, 2007). In fact, they can influence subordinates to involve in knowledge-sharing activities (Islam et al., 2011). Technology, however, is shown here to play an important positive role in contributing to the relationship between leadership and knowledge sharing, as leaders’ vision, attitude and behavior are critical for the employees’ perceptions (Ke and Wei, 2008). A possible explanation of this finding can be urged that managers of the MNCs operating in Malaysia are committed toward their effort to promote knowledge-sharing activities as knowledge bearers, and connecting themselves with other people within the organization using technological platform. Formalization has been found to have a significant negative relationship with the knowledge-sharing process. This finding fully complies with the prior studies (Islam et al., 2010). The existing literature also supports the notion that formally structured organizations cannot ensure full flow of knowledge, as these organizations are driven by set goals which do not create culture for effective knowledge sharing to take place. In fact, formalization can impede the generation of new ideas. Whereas, informal setting or structure with fewer rules and regulations makes people feel less stressed, thereby creating opportunities to knowledge sharing with each other in respect to their work which creates greater flexibility and creativity. Therefore, for MNC’s based in Malaysia, it is important to develop an informal environment where employees consider their organizational members as family, and share knowledge among themselves. Previous studies (Islam et al., 2010; Chen et al., 2010; Willema and Buelensa, 2009 Islam et al., 2008) support the findings of this study. It is to be noted that technology infrastructure was not shown to have a favorable moderating effect in establishing the relationship between formalization and knowledge sharing in MNC’s operations. This further explains the importance of informal organizational setting for knowledge sharing irrespective of the working environment that is facilitated with or without good technological infrastructure. Thus, organizations with insufficient technical platform cannot escape the need of creating less formal environment, pointing to the idea that it is perhaps more needed for organizations with appropriate technical infrastructure. Rigid hierarchical arrangement within the workplace is thought to hinder knowledge sharing and creation (Tsai, 2002). MNCs operating in Malaysia demonstrate the same trend in relation to the possible relationship between centralization and knowledge sharing. The less hierarchical organization structure enhances greater instances of knowledge sharing (Sharratt and Usoro, 2003). It is possible that people in Asia are more comfortable working under close supervision and well-defined chain of command. Again, this interpretation could


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be further questioned given the fact that, formalization, being as an important aspect of organizational structure, is found to have a significant negative impact in the current study. In general, knowledge sharing through relatively flat hierarchy (horizontal) induces more flow of knowledge than a hierarchy that incorporates too many layers empowering people at the top (vertical). This paper confirms others’ work (Chen et al., 2010; Nonaka and Takeuchi, 1995) who argue that centralization affects knowledge sharing. The introduction of technology infrastructure as a moderator in the relationship, however, sheds some new light. A positive and significant relationship is observed to affect the relationship between centralization and knowledge sharing in the presence of technology infrastructure. In the absence of technology infrastructure, no significant relationship has been found. This prompts us to infer that centralization affects knowledge sharing, and technology plays a vital role in such relationship. Interestingly, the paper confirms the previous work (Zheng et al., 2010; Liao et al., 2011; Wiewiora et al., 2013; Islam et al., 2012) which also shows that organizational culture and organizational structure as a whole play an active role in knowledge sharing. Additionally, the results of this study suggest that technology infrastructure mediates the impact of organizational culture and organizational structure on knowledge sharing, as they extend the scope of research. This paper makes several contributions to the literature. The contribution of this paper is twofold. First, we contribute to the conceptualization of the organizational culture and organizational structure as the important aspects of knowledge sharing. Prior work has typically studied the effect of organizational culture and organizational structure on knowledge sharing, which this study confirms. While many studies have focused isolatedly on the importance of organizational culture (Sackmann and Friesl, 2007; Rivera-Vazquez et al., 2009) and organizational culture and organizational structure (Chen et al., 2010; Willema and Buelensa, 2009) for knowledge transfer, this paper brings them together to explain their linkage and quantify the relationship. Second, we extend these studies by exploring technological infrastructure that moderates the relationship of organizational culture and organizational structure with knowledge sharing. Hence, the paper goes beyond the conventional finding to provide new insights. Although the paper does not develop a new theory, it will motivate scholars and practitioners to engage with the issues in different ways than they have in the past. 6. Limitations and future work The results of this research must be interpreted in the context of its limitations, requiring additional research. First, the data were collected from a sample of organizations within one country (i.e. Malaysia). It is possible that the results could vary in other organizational contexts. Future work would also investigate the differences in antecedents of knowledge sharing in local organizations and in other industry sectors. Further, the findings could vary in different countries because of the influence of national cultural factors. Cross-cultural validation would allow the impact of culture on knowledge-sharing behavior to be revealed. Hence, we believe that the results may be extended to MNCs in other Asian countries with similar economic and infrastructure conditions. Second, based on a sample of 90 respondents, several significant results have been obtained. However, a larger sample that brings more statistical power would have allowed more sophisticated analysis and, thereby, increases generalizability.

Third, the MNCs under study deploy technology infrastructure without considering different capabilities of ITs. It is possible that differences in the features of ITs would affect the results. It might also be fruitful to consider differences in the features of ITs that may shed further light. Fourth, this study did not consider all determinants that facilitate knowledge sharing. Social dimension of knowledge sharing is an important area that may help understand why employees share what they know and what they are sharing (Widén-Wulff, 2014). Other than those prescribed may also affect knowledge sharing and the use of technology. For instance, other factors associated with the social capital theory (e.g. trust) could be examined in future research. Furthermore, the knowledge characteristics were not taken into account in the research model. For instance, IT is inherently limited in its capability to transfer tacit knowledge (Hildreth and Kimble, 2002). Additional research is warranted to incorporate tacit and explicit knowledge in understanding the notion of knowledge sharing. 7. Conclusion In today’s business world, knowledge is considered as a vital resource in formulating appropriate competitive strategies so as to ensure successful performance of MNCs. As knowledge sharing is thought to be a powerful source of gathering knowledge and creating competitive advantage, it is desirable for companies to adopt an environment where proper knowledge flow can be assured. Generally speaking, knowledge-sharing activities are dependent on organizational culture and structure. The current study explains the role of organizational cultural and structure on knowledge-sharing process in MNCs based in Malaysia, with the moderating effect of technology infrastructure. Given its results, this study provides some useful suggestions for managers. The outcome of this research provides useful indications of how organizations can work to ensure knowledge sharing within their work place. This study helps MNCs to be aware of the issues related to knowledge sharing. Most specifically, the finding will help the MNCs to create appropriate environment within their surrounding knowledge to share. As mentioned earlier, the research framework postulated in this study contributes to the knowledge management practice, particularly knowledge sharing, in several ways. As mentioned earlier, this study has some contributions towards the literature, as it examined the relationship between organizational culture, structure and knowledge-sharing practices in the MNC context. The incorporation of the moderating variable (i.e. technology infrastructure) is an important addition to the literature because the current body of knowledge lacks the empirical evidence on the moderation of technology infrastructure in the knowledge-sharing process within the MNC environment in an emerging economy (i.e. Malaysia). More specifically, this has been reflected and evidenced in the study revealing the relationships between learning and development, top management support, formalization, centralization and knowledge-sharing behavior with the moderating role of technology infrastructure. With a set of guidelines on technological infrastructure, organizations can pick up an appropriate technology to share knowledge more efficiently. Because various organizations require distinct types of approaches to knowledge sharing because of the size, people, financial capability, etc., knowledge sharing requires a major change in organizational culture and commitment at all levels of employees, especially from the top management (Gupta and Govindarajan, 1991). The findings of


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Appendix Please assess each of the following factors in terms of its importance in determining knowledge-sharing process in organizations: I. ORGANIZATION CULTURE A. Items on collaboration In my organization […] 1. Employees are supportive and helpful. 2. Adequate organizational resources are available to the employees. 3. There is willingness to collaborate across organizational unit. 4. Employees are encouraged by their superiors to express and exchange their opinions and ideas regarding work-related matters. 5. Employees are encouraged by their work group to express and exchange their opinions and ideas regarding work. B. Items on learning and development orientation In my organization […] 1. Opportunities are provided for individual development, other than formal training (e.g. work assignments and job rotation). 2. Employee are encouraged to attend formal development activities (e.g. training, professional seminars, symposium). 3. There are people who provide guidance and counsel regarding one’s career. 4. Employees are rewarded for ideas on improvement. 5. Employees are encouraged to analyze mistakes made and learn from them. C. Items on top management support In my organization, management […] 1. Supports the role of knowledge in the firms’ success. 2. Provides adequate budgeting to support knowledge exchange or knowledge management projects. 3. Reformulates any rules (e.g. personnel policies) that obstruct the knowledge sharing. 4. Encourages team members to experiment to improve work processes. 5. Rewards innovative ideas that work. 6. Does not treat new ideas from employees seriously. II. ORGANIZATIONAL STRUCTURE A. Items on formalization In my organization […] 1. The employee feels that “I am my own boss” in most matters. 2. How things are done is left to the person doing the work. 3. Most people make their own rules on the job. 4. The employees are constantly being checked for rule violations. B. Items on centralization Using the scale above, which level of management is usually responsible for APPROVING the following decisions? 1. Commitment of resources into new products. 2. Commitment of resources into new markets. 3. Initiating changes in the strategic direction of the firm. 4. Approving entry into new markets/businesses. 5. Strategic planning. III. TECHNOLOGY INFRASTRUCTURE Items on technology My organization uses technology that allows […] 1. It to monitor its competition and business partners. 2. Employees to collaborate with other persons inside the organization. 3. Employees to collaborate with other persons outside the organization.


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4. People in multiple locations to learn as a group from a single source. 5. People in multiple locations to learn as a group from multiple sources. 6. It to retrieve and use knowledge about its markets and competition. 7. Generate new opportunities in conjunction with its partners. IV. KNOWLEDGE SHARING Items on knowledge-sharing process In my organization […] 1. There are processes for exchanging knowledge between individuals. 2. There are processes for distributing knowledge throughout the organization. 3. There are processes for exchanging knowledge with my business partners. 4. Knowledge is made accessible to all who need it. 5. Interdepartmental knowledge sharing occurs as a matter of course. 6. Employees fear that sharing their knowledge with others might reduce their influence within the firm. Notes: Organization Culture, Structure (Formalization), Technology and Knowledge Sharing scale item: 1 Strongly Disagree, 5 Strongly Agree. Centralization scale item: 1 Top Executive, 2 Senior or corporate management, 3 Division managers or functional managers if there is no divisional structure, 4 Functional managers if there is divisional structure and 5 ⫽ Middle-level manager. Corresponding author Sajjid M. Jasimuddin can be contacted at: [email protected]

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