A conceptual framework for information-leakage-resilience

Wong, Wai Peng; Tan, Kim Hua; Govindan, Kannan; Li, Di; Kumar, Ajay

Abstract

In today’s dynamic and competitive business environment, it is critical for firms to share information selectively and develop organizational resilience. However, only a few existing studies examine the relationships between information management and supply chain resilience. Aiming to bridge the gaps between both domains, we propose a model encompassing information security culture, information leakage, information sharing effectiveness and supply chain resilience and to derive insights from their inter-relationships in this research. A cross-sectional survey of the multi-national corporations and small and medium enterprises among their senior managers in the United Kingdom was carried out for data collection. The data set was analysed using a structural equation modelling approach. The results obtained validate the proposed model. The findings ascertain that information security culture and information leakage are negatively correlated, which influence the supply chain resilience. Specifically, information security and information leakage affect the effectiveness of information sharing, which in turn positively and negatively influence the supply chain resilience, respectively. This study posits that information security culture is instrumental to mitigate information leakage and foster effective information sharing to strengthen supply chain resilience.

Citation

Wong, W. P., Tan, K. H., Govindan, K., Li, D., & Kumar, A. (2021). A conceptual framework for information-leakage-resilience. Annals of Operations Research, https://doi.org/10.1007/s10479-021-04219-5

• Journal Article Type: Article
• Acceptance Date: Jul 26, 2021
• Online Publication Date: Aug 5, 2021
• Publication Date: Aug 5, 2021
• Deposit Date: Sep 6, 2021
• Publicly Available Date: Aug 6, 2022
• Journal: Annals of Operations Research
• Print ISSN: 0254-5330
• Electronic ISSN: 1572-9338
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1007/s10479-021-04219-5
• Keywords: Management Science and Operations Research; General Decision Sciences
• Public URL: https://nottingham-repository.worktribe.com/output/6184847
• Publisher URL: https://link.springer.com/article/10.1007/s10479-021-04219-5
• Additional Information: Accepted: 26 July 2021; First Online: 5 August 2021