To read this content please select one of the options below:

Leverage risks for supply chain robustness against corruption

Xiaojing Liu (School of Economics and Management, Zhejing Sci-Tech University, Hangzhou, China) (ISOM Department, Business School, The University of Auckland, Auckland, New Zealand)
Tiru Arthanari (ISOM Department, Business School, The University of Auckland, Auckland, New Zealand)
Yangyan Shi (School of Economics and Management, Shanxi University, Taiyuan, China) (Department of Management, Macquarie Business School, Macquarie University, Sydney, Australia)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 29 April 2021

Issue publication date: 5 July 2021

547

Abstract

Purpose

This paper examines the establishment of supply chain robustness against corruption by utilizing risk interactions.

Design/methodology/approach

Based on empirical results from the New Zealand dairy industry, a system dynamics model is established to explore the underlying relationships among variables.

Findings

The results show that although certain supply chain risks seem unrelated to corruption, their mitigation would help mitigate the impact of corruption due to risk interactions; and mitigation of some of the risks is more effective in mitigating the impact of corruption. Leverage risks have been defined and identified in this research, which expands the extant knowledge in reducing the impact of corruption on supply chains.

Originality/value

The research illustrates how the impact of corruption can be studied in an integrated way with dairy supply chain SD analysis. It is a pioneering study to mitigate the impact of corruption on supply chains from supply chain robustness.

Keywords

Acknowledgements

Dr. Xiaojing Liu thanks China Scholarship Council for supporting the doctoral study at the University of Auckland. Dr. Yangyan Shi thanks the key fund programme for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province [2018, RSC1617] and the programme for the Top Young Academic Leaders of Higher Learning Institutions of Shanxi [TYAL, 2019052009].

Citation

Liu, X., Arthanari, T. and Shi, Y. (2021), "Leverage risks for supply chain robustness against corruption", Industrial Management & Data Systems, Vol. 121 No. 7, pp. 1496-1521. https://doi.org/10.1108/IMDS-10-2020-0587

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

Related articles