Performance effects of analytics capability, disruption orientation, and resilience in the supply chain under environmental uncertainty
Issam Laguir (),
Sachin Modgil (),
Indranil Bose (),
Shivam Gupta () and
Rebecca Stekelorum ()
Additional contact information
Issam Laguir: Montpellier Business School
Sachin Modgil: International Management Institute Kolkata
Indranil Bose: NEOMA Business School
Shivam Gupta: NEOMA Business School
Rebecca Stekelorum: CEREFIGE
Annals of Operations Research, 2023, vol. 324, issue 1, No 41, 1269-1293
Abstract:
Abstract The relationship between Analytics Capability of an Organization (ACO) and both Supply Chain Disruption Orientation (SCDO) and Supply Chain Resilience (SCR) in order to achieve adequate operational performance in an era of environmental uncertainty is carried out in this study. Total three hypotheses (seven sub-hypotheses) using a survey of 405 respondents are collected via a pre-tested instrument and tested further. Results indicated the influence of ACO on both SCDO and SCR to achieve the desired degree of operational performance. However, under the moderation of environmental uncertainty, the link between ACO and SCDO was not supported, although the link between ACO and SCR was supported and this further enhanced operational performance. Further investigation of unsupported hypotheses using statistical analysis was conducted to gain deeper insights. It is explained how ACO impacted dynamic capabilities to influence operational performance. The contribution to theory of this study lies in explaining the role of dynamic capabilities that emerge from analytics as compared to the traditional view of supply chain classification. Further, the influence of environmental uncertainty on positioning dynamic capabilities strategically to address disruption in supply chains is discussed in the present study.
Keywords: Analytics capability of organization; Dynamic capability view; Environmental uncertainty; Supply chain disruption orientation; Supply chain resilience (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-021-04484-4
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