Withholding effort in knowledge contribution: The role of social exchange and social cognitive on project teams

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Abstract

Few investigations have been made to determine what factors influence people in withholding knowledge from their colleagues. We created a construct, knowledge withholding (KW), defined as the likelihood that individuals contribute less knowledge to others in the organization than they could. We have formulated a model, based on social exchange theory and social cognition theory, to analyze the antecedents of KW from both personal and contextual perspectives. The contextual influencers were subdivided into dimensions of rational choice, normative conformity, and affective bonding to help in understanding KW. Results of a survey of 162 MIS alumni of a university, who had experienced software development, trust, distributive justice, and team-related work showed that personal outcome expectations had a substantial influence on KW.

Introduction

Withholding effort (WE) is the likelihood that an individual will give less than full effort to a job-related task. It is the common denominator of shirking, job neglect, social loafing, and free riding, which all involve an individual's WE while performing a task. Shirking focuses on the individual's lack of a full effort in contribution, whereas job neglect involves partial or full withdrawal from job-related duties, and both focus on a context where an individual employee is working alone. Social loafing involves holding back effort, whereas free riding occurs when the individual enjoys the benefits without contributing, and both focus on processes that occur in group contexts. Overall, our study focused on the general WE which encompasses varied tasks, settings, and individual predispositions, whereas shirking, job neglect, social loafing, and free riding describe specific reasons and contexts in which effort is withheld.

A number of papers have stated that individuals are prone to WE when they participate in group tasks, especially in the context of knowledge contribution. Individuals who provide knowledge often feel that this devalues their contribution while benefiting other people in the group [7]. The value of an individual's shared knowledge is often difficult to judge; knowledge with a contextual nature is complicated and hard to express, and, individuals receive an unearned part of every other member's shared knowledge during group discussion, regardless of their own contribution. Therefore, in the absence of coercion or appropriable inducements, individuals will tend to withhold knowledge.

To gain insight into WE in knowledge contribution, we created a theoretical construct, knowledge withholding (KW), defined as the likelihood that an individual will give less than full effort to contributing knowledge; one of the research streams related to KW is in knowledge sharing, which has been studied by probing the issue from a relatively positive perspective, based on theories of trust, social capital, reward expectation, task-technology fit or IS success model [3].

A negative perspective evinces different research models and constructs of knowledge sharing; this often uses primary variables, such as procedural justice, distributive justice, task visibility, punishment, and conflict (see Table 1), which are considered influential to withholding behavior. However, they are rarely used in traditional knowledge sharing research [10]. Positive behavior variables are not the opposite of negative behavior variables; for example, theories and variables of user resistance research (such as perceived uncertainty, perceived inequity, perceived power loss, and perceived distrust) are not the same as theories and variables of user acceptance research (such as perceived ease of use and perceived usefulness).

Following recent taxonomy of research on WE [20], we analyzed the antecedents of KW from personal and contextual perspectives. Furthermore, the contextual influencers were subdivided into dimensions of rational choice, normative conformity, and affective bonding to understand KW through a systematic analysis. Focusing on those WE factors that have centered on behaviors such as product selling [11], we attempted to identify how such relationships are built, extending their application to the field of KM, and determining which factors were the most important.

Section snippets

Antecedents of withholding effort (WE)

Table 1 shows two streams of research. The first, because contextual factors are complex and often lack a systematic view, we used rational choice, normative conformity, and affective bonding incentives to explain the impact of organizational context on group members’ WE; this is consistent with agency theory, which stresses control. It is also, because of a social exchange perspective, stressed interpersonal relationships [9]. The second adopted a holistic view involving personal motivations

Sampling procedure

We used a survey method to test our research model. The unit of analysis was an individual member who has experience of software development representing his or her group. During software development, individuals often meet problems which must be solved through a process of collaborative knowledge sharing between team members. If all members of the team withhold knowledge, the software product is unlikely to satisfy user needs, there will probably be reduced productivity through defects and

Assessment of the measurement model

Data analysis was carried out in two stages—the measurement and the structure model. The first step was to assess the construct validity for the nine measurement elements using PLS analysis. The internal consistency of each dimension was assessed by computing the Cronbach's alpha. As shown in Table 4, its lowest value was 0.93 for task visibility; thus all well exceeded the normal criterion of 0.70.

Thus all of the items had loadings over 0.70 for their respective constructs. In addition, as

Findings

The goal of our study was to construct a theoretical KW-model from a personal and contextual perspectives in which contextual factors are subdivided into dimensions of rational choice, normative conformity, and affective bonding. The results indicated that KW is influenced by trust and distributive justice in the environmental dimensions as well as team-related and personal outcome expectations. However, group size, task visibility, procedural justice in environment dimension, and contribution

Tung-Ching Lin is a Professor of Information Management at National Sun Yat-Sen University in Taiwan. He received his Ph.D. in MIS from University of Wisconsin-Milwaukee. He has published two books (Management Information Systems: The Strategic Core Competence of e-Business, Knowledge Management) and numerous papers in professional journals such as Information & Management, Computers & Education, Journal of Information Science, Electronic Commerce Research and Applications, Expert Systems with

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      Such differences, based on the intention to withhold knowledge whether requested by others or not, conceptually shape the KW literature (Oliveira et al., 2021; Silva de Garcia et al., 2020; Strik, Hamstra, & Segers, 2021). As a result, knowledge hiding as a standalone construct of KW is frequently confusing since KW is often conceptualized as knowledge hiding (Lin & Huang, 2010; Wang, Lin, Li, & Lin, 2014; Wu, 2020). Similar conflicting uses happen concerning knowledge hiding and other KW-related constructs, such as knowledge hoarding, exacerbating inconsistencies in the literature (Issac & Baral, 2018).

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    Tung-Ching Lin is a Professor of Information Management at National Sun Yat-Sen University in Taiwan. He received his Ph.D. in MIS from University of Wisconsin-Milwaukee. He has published two books (Management Information Systems: The Strategic Core Competence of e-Business, Knowledge Management) and numerous papers in professional journals such as Information & Management, Computers & Education, Journal of Information Science, Electronic Commerce Research and Applications, Expert Systems with Applications, International Journal of Innovation and Learning, and others. His current research interests include knowledge management, Web2.0, electronic commerce and management of information systems.

    Chien-Chih Huang received his Ph.D. in the Department of Information Management at National Sun Yat-Sen University in Taiwan. Now, he works in Chunghwa Telecom. His works have been published in journals such as Information & Management, Journal of Information Science, Electronic Commerce Research and Applications, Expert Systems with Applications and presented at conferences such as Pacific Asia Conference on Information Systems, European Conference on Knowledge Management, and others. His current research interests include knowledge management, Web2.0, electronic commerce and management of information systems.

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