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Performance effects of analytics capability, disruption orientation, and resilience in the supply chain under environmental uncertainty

Author

Listed:
  • Issam Laguir

    (Montpellier Business School)

  • Sachin Modgil

    (International Management Institute Kolkata)

  • Indranil Bose

    (NEOMA Business School)

  • Shivam Gupta

    (NEOMA Business School)

  • Rebecca Stekelorum

    (CEREFIGE)

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.

Suggested Citation

  • Issam Laguir & Sachin Modgil & Indranil Bose & Shivam Gupta & Rebecca Stekelorum, 2023. "Performance effects of analytics capability, disruption orientation, and resilience in the supply chain under environmental uncertainty," Annals of Operations Research, Springer, vol. 324(1), pages 1269-1293, May.
    • Handle: RePEc:spr:annopr:v:324:y:2023:i:1:d:10.1007_s10479-021-04484-4
    DOI: 10.1007/s10479-021-04484-4
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    as
    1. Lee, Craig & Hallak, Rob, 2018. "Investigating the moderating role of education on a structural model of restaurant performance using multi-group PLS-SEM analysis," Journal of Business Research, Elsevier, vol. 88(C), pages 298-305.
    2. Min, Hokey, 2019. "Blockchain technology for enhancing supply chain resilience," Business Horizons, Elsevier, vol. 62(1), pages 35-45.
    3. Baghersad, Milad & Zobel, Christopher W., 2021. "Assessing the extended impacts of supply chain disruptions on firms: An empirical study," International Journal of Production Economics, Elsevier, vol. 231(C).
    4. Jonathan J.J.M. Seddon & Wendy L. Currie, 2017. "A model for unpacking big data analytics in high-frequency trading," Post-Print hal-01404316, HAL.
    5. Sreedevi, R. & Saranga, Haritha, 2017. "Uncertainty and supply chain risk: The moderating role of supply chain flexibility in risk mitigation," International Journal of Production Economics, Elsevier, vol. 193(C), pages 332-342.
    6. Wamba, Samuel Fosso & Dubey, Rameshwar & Gunasekaran, Angappa & Akter, Shahriar, 2020. "The performance effects of big data analytics and supply chain ambidexterity: The moderating effect of environmental dynamism," International Journal of Production Economics, Elsevier, vol. 222(C).
    7. Thompson S H Teo & Yujun Pian, 2003. "A contingency perspective on Internet adoption and competitive advantage," European Journal of Information Systems, Taylor & Francis Journals, vol. 12(2), pages 78-92, June.
    8. Eduardo Ortas & José Moneva & Roger Burritt & Joanne Tingey-Holyoak, 2014. "Does Sustainability Investment Provide Adaptive Resilience to Ethical Investors? Evidence from Spain," Journal of Business Ethics, Springer, vol. 124(2), pages 297-309, October.
    9. Wang, Na & Hua, Ying & Wu, Guoying & Zhao, Chunxia & Wang, Yonggui, 2019. "Reverse transfer of innovation and subsidiary power: A moderated mediation model," Journal of Business Research, Elsevier, vol. 103(C), pages 328-337.
    10. Kwon, Ohbyung & Lee, Namyeon & Shin, Bongsik, 2014. "Data quality management, data usage experience and acquisition intention of big data analytics," International Journal of Information Management, Elsevier, vol. 34(3), pages 387-394.
    11. Scott DuHadway & Steven Carnovale & Benjamin Hazen, 2019. "Understanding risk management for intentional supply chain disruptions: risk detection, risk mitigation, and risk recovery," Annals of Operations Research, Springer, vol. 283(1), pages 179-198, December.
    12. Jie Xu & Jun Zhuang & Zigeng Liu, 2016. "Modeling and mitigating the effects of supply chain disruption in a defender–attacker game," Annals of Operations Research, Springer, vol. 236(1), pages 255-270, January.
    13. Brian Tomlin, 2006. "On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks," Management Science, INFORMS, vol. 52(5), pages 639-657, May.
    14. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov, 2019. "The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics," International Journal of Production Research, Taylor & Francis Journals, vol. 57(3), pages 829-846, February.
    15. Sande, Jon Bingen & Ghosh, Mrinal, 2018. "Endogeneity in survey research," International Journal of Research in Marketing, Elsevier, vol. 35(2), pages 185-204.
    16. Yu, Wantao & Jacobs, Mark A. & Chavez, Roberto & Yang, Jiehui, 2019. "Dynamism, disruption orientation, and resilience in the supply chain and the impacts on financial performance: A dynamic capabilities perspective," International Journal of Production Economics, Elsevier, vol. 218(C), pages 352-362.
    17. Ravi Srinivasan & Morgan Swink, 2018. "An Investigation of Visibility and Flexibility as Complements to Supply Chain Analytics: An Organizational Information Processing Theory Perspective," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1849-1867, October.
    18. Miri Kim & Jaeki Song & Jason Triche, 2015. "Toward an integrated framework for innovation in service: A resource-based view and dynamic capabilities approach," Information Systems Frontiers, Springer, vol. 17(3), pages 533-546, June.
    19. Ali Alper Yayla & Qing Hu, 2012. "The impact of IT-business strategic alignment on firm performance in a developing country setting: exploring moderating roles of environmental uncertainty and strategic orientation," European Journal of Information Systems, Taylor & Francis Journals, vol. 21(4), pages 373-387, July.
    20. Sidney G. Winter, 2003. "Understanding dynamic capabilities," Strategic Management Journal, Wiley Blackwell, vol. 24(10), pages 991-995, October.
    21. Fraj, Elena & Matute, Jorge & Melero, Iguácel, 2015. "Environmental strategies and organizational competitiveness in the hotel industry: The role of learning and innovation as determinants of environmental success," Tourism Management, Elsevier, vol. 46(C), pages 30-42.
    22. William P. Barnett & Elizabeth G. Pontikes, 2008. "The Red Queen, Success Bias, and Organizational Inertia," Management Science, INFORMS, vol. 54(7), pages 1237-1251, July.
    23. Ritu Agarwal & Vasant Dhar, 2014. "Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research," Information Systems Research, INFORMS, vol. 25(3), pages 443-448, September.
    24. Cavalcante, Ian M. & Frazzon, Enzo M. & Forcellini, Fernando A. & Ivanov, Dmitry, 2019. "A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing," International Journal of Information Management, Elsevier, vol. 49(C), pages 86-97.
    25. David J Teece, 2014. "A dynamic capabilities-based entrepreneurial theory of the multinational enterprise," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 45(1), pages 8-37, January.
    26. K. T. Shibin & Rameshwar Dubey & Angappa Gunasekaran & Benjamin Hazen & David Roubaud & Shivam Gupta & Cyril Foropon, 2020. "Examining sustainable supply chain management of SMEs using resource based view and institutional theory," Annals of Operations Research, Springer, vol. 290(1), pages 301-326, July.
    27. O'Reilly, Charles A., III & Tushman, Michael L., 2013. "Organizational Ambidexterity: Past, Present and Future," Research Papers 2130, Stanford University, Graduate School of Business.
    28. David J. Teece, 2007. "Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance," Strategic Management Journal, Wiley Blackwell, vol. 28(13), pages 1319-1350, December.
    29. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    30. Samuel Fosso Wamba & Angappa Gunasekaran & Rameshwar Dubey & Eric W. T. Ngai, 2018. "Big data analytics in operations and supply chain management," Annals of Operations Research, Springer, vol. 270(1), pages 1-4, November.
    31. Naresh K. Malhotra & Sung S. Kim & Ashutosh Patil, 2006. "Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research," Management Science, INFORMS, vol. 52(12), pages 1865-1883, December.
    32. Seddon, Jonathan J.J.M. & Currie, Wendy L., 2017. "A model for unpacking big data analytics in high-frequency trading," Journal of Business Research, Elsevier, vol. 70(C), pages 300-307.
    33. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    34. Rafaela Alfalla-Luque & Carmen Medina-Lopez, 2009. "Supply Chain Management: Unheard of in the 1970s, core to today's company," Business History, Taylor & Francis Journals, vol. 51(2), pages 202-221.
    35. Tönnissen, Stefan & Teuteberg, Frank, 2020. "Analysing the impact of blockchain-technology for operations and supply chain management: An explanatory model drawn from multiple case studies," International Journal of Information Management, Elsevier, vol. 52(C).
    36. Paul M. Swamidass & William T. Newell, 1987. "Manufacturing Strategy, Environmental Uncertainty and Performance: A Path Analytic Model," Management Science, INFORMS, vol. 33(4), pages 509-524, April.
    37. Morteza Lalmazloumian & Kuan Yew Wong & Kannan Govindan & Devika Kannan, 2016. "A robust optimization model for agile and build-to-order supply chain planning under uncertainties," Annals of Operations Research, Springer, vol. 240(2), pages 435-470, May.
    38. Oke, Adegoke & Gopalakrishnan, Mohan, 2009. "Managing disruptions in supply chains: A case study of a retail supply chain," International Journal of Production Economics, Elsevier, vol. 118(1), pages 168-174, March.
    39. Rameshwar Dubey & Angappa Gunasekaran & Stephen J. Childe & Thanos Papadopoulos & Zongwei Luo & David Roubaud, 2020. "Upstream supply chain visibility and complexity effect on focal company’s sustainable performance: Indian manufacturers’ perspective," Annals of Operations Research, Springer, vol. 290(1), pages 343-367, July.
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