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Advancing supply chain management from agility to hyperagility: a dynamic capability view.
Raj, Alok; Sharma, Varun; Shukla, Dhirendra Mani; Sharma, Prateek.
  • Raj A; Department of Production, Operations and Decision Sciences, XLRI Xavier School of Management, Jamshedpur, India.
  • Sharma V; Department of Operations and Decision Science, T A Pai Management Institute, Manipal Academy of Higher Education, Manipal, India.
  • Shukla DM; Strategic Management, Indian Institute of Management Lucknow, Lucknow, India.
  • Sharma P; Finance and Accounting, Indian Institute of Management Udaipur, Udaipur, India.
Ann Oper Res ; : 1-32, 2023 Jan 03.
Article in English | MEDLINE | ID: covidwho-2174473
ABSTRACT
Research and practice emphasize the criticality of supply chain agility in responding to external disruptions. However, many organizations struggled to respond at enhanced speed to the global supply chain shocks caused by the COVID-19 pandemic. Organizations need hyperagile supply chains to survive and remain competitive in an environment characterized by unexpected and sudden disruptions such as the COVID-19 pandemic. We propose that supply chain hyperagility (SCH) is a distinctive organization-specific capability. It enables organizations to effectively manage demand shocks at extreme speeds and under extreme time pressures. We advance the concept of supply chain hyperagility and establish its antecedents, taking the dynamic capability perspective. This study operationalizes the SCH construct for the first time and investigates its antecedents using structural equation modeling. The results highlight the significance of data analytical capabilities, market orientation, entrepreneurial orientation, and supply chain integration in shaping supply chain hyperagility. The study offers practical insights for managers regarding designing supply chains that can navigate hyperagile environments and benefit from the opportunities presented by such environments.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Ann Oper Res Year: 2023 Document Type: Article Affiliation country: S10479-022-05158-5

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Ann Oper Res Year: 2023 Document Type: Article Affiliation country: S10479-022-05158-5