Elsevier

Computers in Human Behavior

Volume 91, February 2019, Pages 42-51
Computers in Human Behavior

Full length article
Characterizing the relationship between conscientiousness and knowledge sharing behavior in virtual teams: An interactionist approach

https://doi.org/10.1016/j.chb.2018.09.035Get rights and content

Highlights

  • Conscientiousness positively affects knowledge sharing behavior.

  • Job demands of skill variety positively affects knowledge sharing behavior.

  • Knowledge sharing self-efficacy positively affects knowledge sharing behavior.

  • Personality, job design, self-efficacy jointly affect knowledge sharing behavior.

Abstract

Extensive previous work has studied individuals' knowledge sharing behavior (KSB) in a virtual environment, revealing several key factors. However, prior work focused solely on simple correlations between these factors and KSB. And relatively little attention has been assigned to the complex relationships between them. This study argued that better understanding of the complex relationships may be more important because the nature and wide scope of the determinants of KSB may yield different interaction effects. Thus, to better understand the interaction effects of contextual factors and personal factors on KSB, this study adopted a person-situation interactionist approach which proposes that conscientiousness (C), job demands of skill variety (JDSV), and knowledge sharing self-efficacy (KSSE) have joint effects on virtual team (VT) members' KSB. We empirically validated the main effects and the two-way and three-way interaction effects using data collected from 219 VT members from an information technology company. Our results showed that (1) C, JDSV, and KSSE are all positively related to KSB; (2) KSSE positively moderates the relationship between C and KSB; and (3) JDSV and KSSE jointly moderate the relationship between C and KSB. This study offers a new research perspective on knowledge sharing and integrates personality traits theories, Job Characteristics Model, Job Demands-Resources Model, and social cognitive theory into a single research model to examine the underlying mechanisms and boundary conditions of KSB in a virtual environment. The results of the study might direct VT mangers how to recruit members and when to redesign members' job and foster their KSSE.

Introduction

In the current knowledge economy era, knowledge is considered a valuable but intangible asset for the survival, prosperity, and success of an organization (Pangil & Chan, 2014). Thus, it is essential that organizational knowledge is diligently managed. A common method for managing knowledge within an organization is the encouragement of knowledge sharing among employees. Knowledge sharing refers to an individual converting his or her own knowledge into a form that can be readily understood, absorbed, and employed by others (Ipe, 2003). Knowledge sharing behavior (KSB) allows organizations leverage and capitalize on knowledge-based resources, build on prior experience. In addition, it also enables organizations to make rapid reaction to problems encountered previously, generate creative ideas and insights, and avoid repeating prior mistakes. These, in turn, cut costs, promote innovation, and improve performance (Marouf and Alrikabi, 2015, Pee and Lee, 2015, Wang and Noe, 2010). Hence, some scholars claim that KSB “is an important part of building knowledge-based competitive advantage” in today's dynamic business environment (Foss, Minbaeva, Pedersen, & Reinholt, 2009, p. 872).

With rapid advancements in online interactive technology and the proliferation of online communication tools, many organizations have shifted to online knowledge sharing (OKS). This is because OKS enables employees to efficiently and widely exchange ideas and views throughout an organization, thereby enhancing the benefits of knowledge sharing (Pee and Lee, 2015, Pi et al., 2013). This phenomenon, coupled with the rapid expansion of organizational scales, has led to the emergence of new organizational forms of knowledge sharing (Ardichvili, 2008). One new form that has rapidly gained popularity is the virtual team (VT; Cohen & Bailey, 1997). The VT has revolutionized the way employees work (Powell, Piccoli, & Ives, 2004): not only does VT enable communication without the limitations of time and location, but it also equips companies with greater flexibility and responsiveness (Pangil and Chan, 2014, Powell et al., 2004). However, despite these advantages and its increasing popularity, successfully encouraging employees to spontaneously share their knowledge via VTs remains a challenge (Fang & Chiu, 2010).

Previous studies indicate that people resist sharing their exclusive knowledge “even when an organization makes a concerted effort to facilitate knowledge exchange” (Ardichvili, 2008, p. 543). In fact, people do not exhibit KSB under all circumstances, and when they do, they may not “share as much [knowledge] as their organizations would like them to” (Yu, Lu, & Liu, 2010, p. 32). Many researchers so far have argued that a VT's effectiveness and success depend, to a great extent, on the frequency and intensity of its members' participation in KSB (Ardichvili, 2008, Fang and Chiu, 2010, Hsu et al., 2007, Lin et al., 2009, Pangil and Chan, 2014). Thus, better understanding the factors that lead to effective and successful knowledge sharing in VTs becomes a crucial task for knowledge management theoreticians and practitioners alike.

Extensive study has been dedicated to KSB in the context of virtual environments (e.g., VTs, virtual communities) which has revealed several key factors (Zhang, Fang, Wei, & Chen, 2010). A comprehensive review conducted by Ardichvili (2008) described the motivating factors, barriers, and enablers of KSB in a virtual environment. Others then divided these factors into two categories: contextual factors and personal factors (Lin et al., 2009). Despite these efforts, a meticulous review of the literature uncovers that a key approach, the person-situation interactionist perspective (George & Zhou, 2001), has been neglected. Rather, prior research has focused solely on simple correlations between these factors and KSB. For example, Pei-Lee, Chen, Chin, and Siew (2011) studied how big five personality, subjective norm, and intention to share knowledge affect individuals' KSB. They focused on the simple relationship between these factors and KSB, but neglected the complex relationships such as interaction effects between them. The same problem is presented in Ho, Kuo, and Lin's study (2012). They investigated the simple relationships between factors such as social identification, trust, and knowledge management system quality and knowledge sharing. However, they did not consider the interaction effects between these factors either. We argue that this approach may be inadequate due to the nature and wide scope of the determinants of KSB. These factors may interact in various ways with each other, yielding more complex effects than those described using the above approach. To address this shortcoming, the current study investigates the joint effects of personality, job design, and self-efficacy on KSB in VTs. Specifically, we selected the following three constructs as research variables: conscientiousness (C; independent variable), job demands of skill variety (JDSV; moderator), and knowledge sharing self-efficacy (KSSE; moderator).

The current study uses C as independent variable for several reasons. First, based on previous reports, the relationship between C and KSB is unclear: some authors identifying a strongly positive relationship (e.g., Gupta, 2008), others a slightly positive relationship (Anwar, 2017), and still others a null relationship (e.g., Marouf and Alrikabi, 2015, Pei-Lee et al., 2011). This suggests that further examination of moderating variables is necessary. Second, among the Big Five Personality traits (BFP) which include neuroticism, extraversion, openness to experience, agreeableness, and C, C is considered the most salient predictor of job performance (Barrick & Mount, 1991). This suggests that C may be the most important personality trait in the workplace. Third, a previous study stated that C is “most relevant to person-situation interaction theory” in a work context (Shaffer & Postlethwaite, 2013, p. 184).

JDSV, derived from the Job Characteristics Model (JCM; Hackman & Oldham, 1976), refers to “the extent to which an employee can use different skills in carrying out the work” (Chen & Chiu, 2009). The rationale for the selecting JDSV as a contextual moderator is two-fold. First, although job characteristics (e.g., skill variety, job autonomy, task feedback) are valid predictors of job performance, job attitudes, and absenteeism (e.g., Abbott et al., 2006, Chen and Chiu, 2009, Hackman and Oldham, 1976), empirical studies on the relationship between them and KSB are scarce. In addition, people with higher C are described as thorough, dependable, efficient, achievement-oriented, and hardworking (Barrick & Mount, 1991), suggesting that JDSV and C may have significant joint effects on KSB.

Self-efficacy is defined as “a form of self-evaluation that influences decisions about what behaviors to undertake” (Hsu et al., 2007, p. 155). KSSE is the combination of the concepts of self-efficacy and KSB, and refers to an individual's confidence and ability to initiate KSB (Lin et al., 2009). The current study assigns KSSE as a personal moderator for three reasons. First, as previously described by others, lack of confidence and ability are the primary barriers for KSB (Ardichvili, Page, & Wentling, 2003), indicating a need for more research on KSSE and KSB. Second, according to social cognitive theory (SCT; Bandura, 1977), self-efficacy is considered a basic determinant of an individual's response in a social environment. This finding piqued our interest in the interactions between KSSE and factors related to work environment, such as JDSV. Furthermore, the responsible, careful, and conservative nature associated with C may affect an individual's confidence in the context of sharing knowledge (Barrick & Mount, 1991). This suggests that further studies on the joint effects of C and KSSE on KSB are necessary.

By adopting a person-situation interactionist perspective, the present study examines the conditions under which C leads to KSB in the context of VT. In the next section, we will briefly review relevant constructs and theories. Then, we will describe our hypotheses. Next, we will describe our research design and methodology including the sample, measurement, and data collection process. We will test our hypotheses using our data sample and describe our results. Finally, we will conclude by discussing the major findings, as well as their theoretical and practical implications and limitations, and suggested directions for further study.

Section snippets

KSB in VT

In this age of increasing globalization and internationalization, organizations strive to minimize the cost of bringing employees together in a single location (Pangil & Chan, 2014). Hence, supported by advances in information technology, the VT structure has been introduced to solve this problem. VT refers to a group of individuals who “are geographically dispersed, have limited face-to-face contact, and work interdependently” through electronic mediums to achieve a shared objective (Dulebohn

Sample and procedures

We conducted a survey within an information technology (IT) company that has multiple branches throughout China. Because of this widespread geographical distribution, the majority of employees work in virtual functional or project teams. Many researchers have claimed that online surveys not only have advantages including lower costs, faster responses, and higher response rate, but also have the same data quality as paper surveys (e.g., Hsu et al., 2007, Ng and Feldman, 2013). Additionally, in

Discussion and conclusions

The current study sought to examine under what conditions conscientious employees participating in a VT will perform more KSB. To address this problem, we consulted the current literature focusing on personality, job design, self-efficacy, and KSB to develop a person-situation perspective which incorporated both individual factors (e.g., C and KSSE) and contextual factors (e.g., JDSV). This approach combines personality traits theories, JCM, JD-R model, and SCT to study the underlying

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