Effects of interpersonal trust, team leader support, rewards, and knowledge sharing mechanisms on knowledge sharing in project teams

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Abstract

Purpose

The purpose of this paper is to investigate the effect of interpersonal trust, team leader support, rewards, and knowledge sharing mechanisms on voluntary knowledge sharing in software development project teams in Sri Lanka.

Design/methodology/approach

Survey methodology was used and 150 software developers who were directly involved in developing and maintaining a software product from project teams responded. Regression analysis was used for data analysis.

Findings

Interpersonal trust and rewards have significant positive effects on knowledge sharing. Although it was anticipated that the team leader support would be a significant predictor of knowledge sharing, the results did not provide evidence for a positive and significant relationship. “Work‐group communications” and “Personal interactions” had significant positive effects on knowledge sharing.

Originality/value

It is expected that the findings of this study will provide useful information to better understand the predictors of the extent of knowledge sharing at the individual level in the context of project teams. By doing so, this exploratory study will be able to establish baseline data and would be a source of general guidance in stimulating future research in this area.

Related collections

Most cited references 73

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Common method biases in behavioral research: A critical review of the literature and recommended remedies.

Philip M Podsakoff, Scott MacKenzie, Jeong-Yeon Lee … (2003)

Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.