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Knowledge sharing behaviour and its predictors

Zahra Tohidinia (Department of Business Management, Faculty of Management, University of Tehran, Tehran, Iran)
Mohammad Mosakhani (Department of Information Technology Management, Faculty of Management, University of Tehran, Tehran, Iran)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 27 April 2010

11891

Abstract

Purpose

This paper aims to evaluate the influence of different factors on knowledge donation and collection. The examined factors are among those determinants which comprise different aspects of knowledge sharing behaviour in an organisational context.

Design/methodology/approach

Based on the widely accepted theory of planned behaviour (TPB), we tried to develop a comprehensive model. The model covered different individual and organisational factors. Responses to a total of 502 questionnaires were considered. Structural equation modelling was then used to test the research model and hypotheses.

Findings

This research evaluated the influence of a series of potential factors on knowledge sharing behaviour. While perceived self‐efficacy and anticipated reciprocal relationships had a positive impact on attitude toward knowledge sharing, expected extrinsic rewards did not show a significant relationship with this variable. Organisational climate had a positive impact on subjective norms about knowledge sharing. In addition, the level of information and communication technology usage reflected a positive effect on knowledge sharing behaviour. Finally, significant relationships were found between the TPB elements.

Originality/value

This paper has tried to provide a comprehensive understanding about knowledge sharing facilitators in the oil industry. Since there was a lack of such research in an Iranian context, this paper can provide theoretical basis for future researches as well as practical implications for managers and practitioners.

Keywords

Citation

Tohidinia, Z. and Mosakhani, M. (2010), "Knowledge sharing behaviour and its predictors", Industrial Management & Data Systems, Vol. 110 No. 4, pp. 611-631. https://doi.org/10.1108/02635571011039052

Publisher

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Emerald Group Publishing Limited

Copyright © 2010, Emerald Group Publishing Limited

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