Does online–offline channel integration matter for supply chain resilience? The moderating role of environmental uncertainty
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 21 March 2023
Issue publication date: 27 April 2023
Abstract
Purpose
Drawing on dynamic capability theory, this study investigates how online–offline channel integration (OOCI) affects a firm's supply chain resilience and how such an effect is moderated by market turbulence and regulatory uncertainty.
Design/methodology/approach
A sample of 273 Chinese firms that conduct online and offline business and hierarchical regression analysis were used to examine the research model.
Findings
The results suggest that the effect of OOCI on supply chain resilience differs in terms of its dimensions (i.e. information integration, transaction integration and service integration). While information integration and service integration were positively associated with supply chain resilience, transaction integration had a non-significant relationship with supply chain resilience. Moreover, market turbulence negatively moderated the effect of transaction integration and positively moderated the effect of service integration. Regulatory uncertainty positively moderated the effect of transaction integration and negatively moderated the effect of service integration. Implications and suggestions for future research are discussed.
Originality/value
This study examines the effect of OOCI on supply chain resilience. It further explores the influence of market turbulence and regulatory uncertainty on the relationship between OOCI and supply chain resilience.
Keywords
Acknowledgements
This work was supported by the National Key R&D Program of China under Grant No. 2020AAA0103804 and National Natural Science Foundation of China under Grant No. 72002062.
Citation
Wu, X., Li, Y. and Zhu, Z. (2023), "Does online–offline channel integration matter for supply chain resilience? The moderating role of environmental uncertainty", Industrial Management & Data Systems, Vol. 123 No. 5, pp. 1496-1522. https://doi.org/10.1108/IMDS-06-2022-0361
Publisher
:Emerald Publishing Limited
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