An information sharing theory perspective on willingness to share information in supply chains

摘要

Purpose - The quality of information sharing is of the utmost importance for supply chains (SCs). The purpose of this paper is to improve understanding of the human attitude: willingness to share, its antecedents and its role in improving information sharing quality. Design/methodology/approach - Based on information sharing theory, a theoretical model and research hypotheses are developed. Data from 387 respondents were collected to test the hypotheses and model fit using structural equation modelling and mediation analysis. The impact of social-psychological factors and information technology (IT) infrastructure capability on willingness to share information and, consequently, its effect on information sharing quality were analysed using IBM SPSS Statistics, PROCESS and AMOS. Findings - The statistical analysis showed a good model fit. Trust is the most important antecedent for willingness to share;while the impacts of commitment and reciprocity are also significant. Interestingly;power is not a significant antecedent of willingness. Life satisfaction is a significant precursor to willingness to share information;whereas surprisingly overall job satisfaction does not play a significant role. Research limitations/implications - Cross-sectional data were used and the scope was limited to SCs. Practical implications - Managers should be aware that trust;commitment and reciprocity with their SC partners influence the willingness to share information with varying effects. Access to proper IT capabilities increases willingness as does the life satisfaction. SC individuals who are happy with life are more willing. Interestingly;high power might get the sharer to share information albeit unwillingly. Originality/value - The model provides a social-psychological understanding of the antecedents of human willingness to share information;which is crucial to sharing quality information. Overall;the social-psychological and IT factors model based on information sharing theory is statistically valid for the SC context