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A conceptual framework for information-leakage-resilience

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

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Authors

Wai Peng Wong

KIM TAN kim.tan@nottingham.ac.uk
Professor of Operations and Innovation Management

Kannan Govindan

Di Li

Ajay Kumar



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.

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 Science and Business Media LLC
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

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