Grounding on relational view and contingent resource-based views, the authors investigate the conditional indirect effect of Supply Chain Relational Practices (SCRPs) on supply chain performance (SCP) through proactive and reactive supply chain resilience (SCRE) capabilities at different levels of network complexity (NC).
The authors adopt an “exploratory sequential mixed methods design” combining the qualitative and quantitative approaches under a positivist paradigm. The qualitative method is primarily used to contextualize and develop better measurements of the factors and variables using content analysis of the field studies. This then informs the quantitative phase which conducts a questionnaire survey among the apparel manufacturing firms in Bangladesh. The authors analyzed the quantitative data using Partial Least Square based Structural Equation Modelling. The authors also used PROCESS integrated regression analysis to test conditional indirect effects.
Our research findings indicate that the indirect effect of SCRPs on SCP through proactive and reactive SCRE is positive and significant. It also finds that the conditional indirect effect is high at higher NC.
The results have immense practical implications as it proposes to enhance relational practices in order to develop SCRE as a contingent resource to mitigate disruptions. This will also help the supply chain (SC) managers to work through smoothly at different levels of supply chain NC and improve SCP.
Extant literature does not provide a deeper understanding of the impact of SCRPs on SCP, while SCRE and NC influence the link. Therefore, investigation of the conditional direct and indirect effect of SCRPs on SCP through proactive and reactive SCRE at different levels of NC is novel in SC management literature.
Chowdhury, M.M.H., Quaddus, M. and Chowdhury, M. (2023), "Managing relational practices for performance improvement in a complex supply chain network: the mediating roles of proactive and reactive resilience in apparel industry of Bangladesh", The International Journal of Logistics Management, Vol. 34 No. 1, pp. 34-59. https://doi.org/10.1108/IJLM-12-2020-0485
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