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Examining collaborative buyer–supplier relationships and social sustainability in the “new normal” era: the moderating effects of justice and big data analytical intelligence

Author

Listed:
  • Surajit Bag

    (Institute of Management Technology)

  • Tsan-Ming Choi

    (University of Liverpool Management School)

  • Muhammad Sabbir Rahman

    (North South University)

  • Gautam Srivastava

    (IILM University)

  • Rajesh Kumar Singh

    (Management Development Institute)

Abstract

The COVID-19 pandemic has resulted in a slew of new business practices that have put the society and environment under strain. This has drawn the attention of supply chain researchers working to address the COVID-19 pandemic's looming social sustainability issues. Prior literature has indicated that collaborative relationships improve organizational performance. Over the past years, problems related to justice are reported (e.g., between Walmart Canada and the Lego group), which might negatively affect the buyer–supplier relationship. In the new normal, the effect of justice on collaborative buyer–supplier relationships on social sustainability in the COVID-19 context is obviously essential but under-explored. The current study examines buyer–supplier collaborative relationships' influence on social sustainability under the moderating effect of justice and big data analytical intelligence. In this paper, we employ the stakeholder resource-based view, loose coupling theory, and resource dependency theory as the theoretical lens to establish the research hypotheses. Using primary survey data collected from supply chain practitioners in South Africa, hypothesis testing is done using a covariance-based structural equation modelling technique. To enhance research rigor, we have checked the dyadic perspectives of both buyers and suppliers. Our empirical results reveal that collaborative buyer–supplier relationships positively influence supplier social sustainability in the new normal era. However, it is relatively stronger from the suppliers’ perspective when compared with the buyers’ perspective. Secondly, the moderating effect of perceptions of organizational justice and big data analytical intelligence on the relationship between collaborative buyer–supplier relationships and supplier social sustainability is also statistically significant. However, it is relatively stronger from the buyers’ perspective when compared with the suppliers’ perspective. These are major findings of this study. Theoretical and managerial implications are further discussed.

Suggested Citation

  • Surajit Bag & Tsan-Ming Choi & Muhammad Sabbir Rahman & Gautam Srivastava & Rajesh Kumar Singh, 2025. "Examining collaborative buyer–supplier relationships and social sustainability in the “new normal” era: the moderating effects of justice and big data analytical intelligence," Annals of Operations Research, Springer, vol. 348(3), pages 1235-1280, May.
    • Handle: RePEc:spr:annopr:v:348:y:2025:i:3:d:10.1007_s10479-022-04875-1
    DOI: 10.1007/s10479-022-04875-1
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    1. ManMohan S. Sodhi, 2015. "Conceptualizing Social Responsibility in Operations Via Stakeholder Resource-Based View," Production and Operations Management, Production and Operations Management Society, vol. 24(9), pages 1375-1389, September.
    2. Liu, Steven Y.H. & Napier, Elizabeth & Runfola, Andrea & Cavusgil, S. Tamer, 2020. "MNE-NGO partnerships for sustainability and social responsibility in the global fast-fashion industry: A loose-coupling perspective," International Business Review, Elsevier, vol. 29(5).
    3. Rameshwar Dubey & David James Bryde & Cyril Foropon & Manisha Tiwari & Angappa Gunasekaran, 2022. "How frugal innovation shape global sustainable supply chains during the pandemic crisis: Lessons from the COVID-19," Post-Print hal-03539266, HAL.
    4. Shalini Talwar & Puneet Kaur & Samuel Fosso Wamba & Amandeep Dhir, 2021. "Big Data in operations and supply chain management: a systematic literature review and future research agenda," International Journal of Production Research, Taylor & Francis Journals, vol. 59(11), pages 3509-3534, June.
    5. Tsan‐Ming Choi & Subodha Kumar & Xiaohang Yue & Hau‐Ling Chan, 2022. "Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 9-31, January.
    6. Manit Mishra, 2016. "Confirmatory Factor Analysis (CFA) as an Analytical Technique to Assess Measurement Error in Survey Research," Paradigm, , vol. 20(2), pages 97-112, December.
    7. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    8. Elisabetta Raguseo & Claudio Vitari & Federico Pigni, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," Post-Print hal-03032504, HAL.
    9. Pan, Yuqing & Cheng, T.C.E. & He, Yuxuan & Ng, Chi To & Sethi, Suresh P., 2022. "Foresighted medical resources allocation during an epidemic outbreak," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    10. Mani, Venkatesh & Gunasekaran, Angappa & Delgado, Catarina, 2018. "Enhancing supply chain performance through supplier social sustainability: An emerging economy perspective," International Journal of Production Economics, Elsevier, vol. 195(C), pages 259-272.
    11. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Bryde, David J. & Giannakis, Mihalis & Foropon, Cyril & Roubaud, David & Hazen, Benjamin T., 2020. "Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations," International Journal of Production Economics, Elsevier, vol. 226(C).
    12. Elisabetta Raguseo & Claudio Vitari & Federico Pigni, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," Post-Print hal-03511355, HAL.
    13. Maignan, Isabelle & Hillebrand, Bas & McAlister, Debbie, 2002. "Managing Socially-Responsible Buying:: How to Integrate Non-economic Criteria into the Purchasing Process," European Management Journal, Elsevier, vol. 20(6), pages 641-648, December.
    14. Liu, Weihua & Wei, Wanying & Choi, Tsan-Ming & Yan, Xiaoyu, 2022. "Impacts of leadership on corporate social responsibility management in multi-tier supply chains," European Journal of Operational Research, Elsevier, vol. 299(2), pages 483-496.
    15. Cheah, Jun-Hwa & Memon, Mumtaz Ali & Richard, James E & Ting, Hiram & Cham, Tat-Huei, 2020. "CB-SEM latent interaction: Unconstrained and orthogonalized approaches," Australasian marketing journal, Elsevier, vol. 28(4), pages 218-234.
    16. MacKenzie, Scott B. & Podsakoff, Philip M., 2012. "Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies," Journal of Retailing, Elsevier, vol. 88(4), pages 542-555.
    17. Judith M. Whipple & Robert Wiedmer & Kenneth K. Boyer, 2015. "A Dyadic Investigation of Collaborative Competence, Social Capital, and Performance in Buyer–Supplier Relationships," Journal of Supply Chain Management, Institute for Supply Management, vol. 51(2), pages 3-21, April.
    18. Choi, Tsan-Ming & Shi, Xiutian, 2022. "Reducing supply risks by supply guarantee deposit payments in the fashion industry in the “new normal after COVID-19”," Omega, Elsevier, vol. 109(C).
    19. Wu, Ing-Long & Chuang, Cheng-Hung & Hsu, Chien-Hua, 2014. "Information sharing and collaborative behaviors in enabling supply chain performance: A social exchange perspective," International Journal of Production Economics, Elsevier, vol. 148(C), pages 122-132.
    20. Vicky Ching Gu & Bin Zhou & Qing Cao & Jeffery Adams, 2021. "Exploring the relationship between supplier development, big data analytics capability, and firm performance," Annals of Operations Research, Springer, vol. 302(1), pages 151-172, July.
    21. 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.
    22. Erin Anderson & Barton Weitz, 1989. "Determinants of Continuity in Conventional Industrial Channel Dyads," Marketing Science, INFORMS, vol. 8(4), pages 310-323.
    23. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    24. Elisabetta Raguseo & Claudio Vitari & Federico Pigni, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," Post-Print hal-03511381, HAL.
    25. Raguseo, Elisabetta & Vitari, Claudio & Pigni, Federico, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," International Journal of Production Economics, Elsevier, vol. 229(C).
    26. Terrie Walmsley & Adam Rose & Dan Wei, 2021. "The Impacts of the Coronavirus on the Economy of the United States," Economics of Disasters and Climate Change, Springer, vol. 5(1), pages 1-52, April.
    27. Elisabetta Raguseo & Claudio Vitari & Federico Pigni, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," Grenoble Ecole de Management (Post-Print) hal-03032504, HAL.
    28. Reinartz, Werner & Haenlein, Michael & Henseler, Jörg, 2009. "An empirical comparison of the efficacy of covariance-based and variance-based SEM," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 332-344.
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