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Big Data in operations and supply chain management: a systematic literature review and future research agenda

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  • Shalini Talwar
  • Puneet Kaur
  • Samuel Fosso Wamba
  • Amandeep Dhir

Abstract

In the era of digitalisation, the role of Big Data is proliferating, receiving considerable attention in all sectors and domains. The domain of operations and supply chain management (OSCM) is no different since it offers multiple opportunities to generate a large magnitude of data in real-time. Such extensive opportunities for data generation have attracted academics and practitioners alike who are eager to tap different elements of Big Data application in OSCM. Despite the richness of prior studies, there is limited research that extensively reviews the extant findings to present an overview of the different facets of this area. The current study addresses this gap by conducting a systematic literature review (SLR) to uncover the existing research trends, distil key themes, and identify areas for future research. For this purpose, 116 studies were identified through a stringent search protocol and critically analysed. The key outcome of this SLR is the development of a conceptual framework titled the Dimensions-Avenues-Benefits (DAB) model for BDA adoption as well as potential research questions to support novel investigations in the area, offering actionable implications for managers working in different verticals and sectors.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:11:p:3509-3534
    DOI: 10.1080/00207543.2020.1868599
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    Cited by:

    1. Chaudhary, Sanjay & Dhir, Amandeep & Ferraris, Alberto & Bertoldi, Bernando, 2021. "Trust and reputation in family businesses: A systematic literature review of past achievements and future promises," Journal of Business Research, Elsevier, vol. 137(C), pages 143-161.
    2. Andrew Manikas & Michael Godfrey & Jason Woldt, 2022. "What Drives Higher Beer Ratings? Evidence From Big Data," International Journal of Management and Marketing Research, The Institute for Business and Finance Research, vol. 15(1), pages 1-13.
    3. Ciampi, Francesco & Faraoni, Monica & Ballerini, Jacopo & Meli, Francesco, 2022. "The co-evolutionary relationship between digitalization and organizational agility: Ongoing debates, theoretical developments and future research perspectives," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    4. Terrance Jalbert & Jonathan D. Stewart, 2022. "A Comprehensive Retirement Financial Planning Tool," International Journal of Management and Marketing Research, The Institute for Business and Finance Research, vol. 15(1), pages 47-76.
    5. Pan, Qiaohong & Luo, Wenping & Fu, Yi, 2022. "A csQCA study of value creation in logistics collaboration by big data: A perspective from companies in China," Technology in Society, Elsevier, vol. 71(C).
    6. Viktor Koval & I Wayan Edi Arsawan & Ni Putu Santi Suryantini & Serhii Kovbasenko & Nadiia Fisunenko & Tetiana Aloshyna, 2022. "Circular Economy and Sustainability-Oriented Innovation: Conceptual Framework and Energy Future Avenue," Energies, MDPI, vol. 16(1), pages 1-19, December.
    7. Vaibhav S. Narwane & Rakesh D. Raut & Sachin Kumar Mangla & Manoj Dora & Balkrishna E. Narkhede, 2023. "Risks to Big Data Analytics and Blockchain Technology Adoption in Supply Chains," Annals of Operations Research, Springer, vol. 327(1), pages 339-374, August.
    8. Johannes Hangl & Viktoria Joy Behrens & Simon Krause, 2022. "Barriers, Drivers, and Social Considerations for AI Adoption in Supply Chain Management: A Tertiary Study," Logistics, MDPI, vol. 6(3), pages 1-22, September.
    9. Walter Leal Filho & Peter Yang & João Henrique Paulino Pires Eustachio & Anabela Marisa Azul & Joshua C. Gellers & Agata Gielczyk & Maria Alzira Pimenta Dinis & Valerija Kozlova, 2023. "Deploying digitalisation and artificial intelligence in sustainable development research," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(6), pages 4957-4988, June.
    10. Abuljadail, Mohammad & Khalil, Ashraf & Talwar, Shalini & Kaur, Puneet, 2023. "Big data analytics and e-governance: Actors, opportunities, tensions, and applications," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    11. Hiya Almazroa & Wadha Alotaibi, 2023. "Teaching 21st Century Skills: Understanding the Depth and Width of the Challenges to Shape Proactive Teacher Education Programmes," Sustainability, MDPI, vol. 15(9), pages 1-25, April.
    12. Xu, Jinou & Pero, Margherita & Fabbri, Margherita, 2023. "Unfolding the link between big data analytics and supply chain planning," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    13. Abderahman Rejeb & Andrea Appolloni, 2022. "The Nexus of Industry 4.0 and Circular Procurement: A Systematic Literature Review and Research Agenda," Sustainability, MDPI, vol. 14(23), pages 1-21, November.
    14. Zbysław Dobrowolski, 2021. "Internet of Things and Other E-Solutions in Supply Chain Management May Generate Threats in the Energy Sector—The Quest for Preventive Measures," Energies, MDPI, vol. 14(17), pages 1-11, August.
    15. Kaur, Puneet & Talwar, Shalini & Madanaguli, Arun & Srivastava, Shalini & Dhir, Amandeep, 2022. "Corporate social responsibility (CSR) and hospitality sector: Charting new frontiers for restaurant businesses," Journal of Business Research, Elsevier, vol. 144(C), pages 1234-1248.

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