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Big data analytics in operations and supply chain management

Author

Listed:
  • Samuel Fosso Wamba

    (Toulouse Business School)

  • Angappa Gunasekaran

    (California State University, Bakersfield)

  • Rameshwar Dubey

    (Montpellier Research in Management)

  • Eric W. T. Ngai

    (The Hong Kong Polytechnic University)

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:270:y:2018:i:1:d:10.1007_s10479-018-3024-7
    DOI: 10.1007/s10479-018-3024-7
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    References listed on IDEAS

    as
    1. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    2. Nada R. Sanders & Ram Ganeshan, 2015. "Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(10), pages 1671-1672, October.
    3. Nada R. Sanders & Ram Ganeshan, 2015. "Call for Papers: Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(6), pages 1028-1029, June.
    4. Nada R. Sanders & Ram Ganeshan, 2015. "Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(9), pages 1509-1510, September.
    5. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    6. Fosso Wamba, Samuel & Akter, Shahriar & Edwards, Andrew & Chopin, Geoffrey & Gnanzou, Denis, 2015. "How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study," International Journal of Production Economics, Elsevier, vol. 165(C), pages 234-246.
    7. Nada R. Sanders & Ram Ganeshan, 2015. "Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(3), pages 519-520, March.
    8. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    9. Nada R. Sanders & Ram Ganeshan, 2015. "Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(8), pages 1371-1372, August.
    10. Nada R. Sanders & Ram Ganeshan, 2015. "Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(12), pages 1984-1985, December.
    11. Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
    12. Nada R. Sanders & Ram Ganeshan, 2015. "Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(11), pages 1835-1836, November.
    13. Nada R. Sanders & Ram Ganeshan, 2015. "Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(5), pages 852-853, May.
    14. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    15. Nada R. Sanders & Ram Ganeshan, 2015. "Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(7), pages 1193-1194, July.
    16. Nada R. Sanders & Ram Ganeshan, 2015. "Special Issue of Production and Operations Management on “Big Data in Supply Chain Management”," Production and Operations Management, Production and Operations Management Society, vol. 24(4), pages 681-682, April.
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    Citations

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    Cited by:

    1. Nguyen Thi Bich Tram, 2022. "Coordinating supply and demand applied Bass diffusion modelling," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ECONOMICS AND BUSINESS ADMINISTRATION, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 12(2), pages 82-95.
    2. 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.
    3. Morshadul Hasan & Ariful Hoque & Thi Le, 2023. "Big Data-Driven Banking Operations: Opportunities, Challenges, and Data Security Perspectives," FinTech, MDPI, vol. 2(3), pages 1-26, July.
    4. Giuseppe Fragapane & Dmitry Ivanov & Mirco Peron & Fabio Sgarbossa & Jan Ola Strandhagen, 2022. "Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics," Annals of Operations Research, Springer, vol. 308(1), pages 125-143, January.
    5. Efpraxia D. Zamani & Conn Smyth & Samrat Gupta & Denis Dennehy, 2023. "Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review," Annals of Operations Research, Springer, vol. 327(2), pages 605-632, August.
    6. Amankwah-Amoah, Joseph, 2019. "Big data analytics and business failures in data-Rich environments: An organizing framework," MPRA Paper 91264, University Library of Munich, Germany.
    7. Mohamed Dia & Pawoumodom M. Takouda & Amirmohsen Golmohammadi, 2022. "Assessing the performance of Canadian credit unions using a three-stage network bootstrap DEA," Annals of Operations Research, Springer, vol. 311(2), pages 641-673, April.
    8. Ferdaws Ezzi & Maher Abida & Anis Jarboui, 2023. "The Mediating Effect of Corporate Governance on the Relationship Between Blockchain Technology and Investment Efficiency," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 718-734, June.
    9. Shivam Gupta & Sachin Modgil & Samadrita Bhattacharyya & Indranil Bose, 2022. "Artificial intelligence for decision support systems in the field of operations research: review and future scope of research," Annals of Operations Research, Springer, vol. 308(1), pages 215-274, January.
    10. Mahmud A. Shareef & Yogesh K. Dwivedi & Vinod Kumar & D. Laurie Hughes & Ramakrishnan Raman, 2022. "Sustainable supply chain for disaster management: structural dynamics and disruptive risks," Annals of Operations Research, Springer, vol. 319(1), pages 1451-1475, December.
    11. Oduro, Stephen & De Nisco, Alessandro & Mainolfi, Giada, 2023. "Do digital technologies pay off? A meta-analytic review of the digital technologies/firm performance nexus," Technovation, Elsevier, vol. 128(C).
    12. Ayman wael AL-Khatib & Ahmed Shuhaiber, 2022. "Green Intellectual Capital and Green Supply Chain Performance: Does Big Data Analytics Capabilities Matter?," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    13. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach," Annals of Operations Research, Springer, vol. 319(1), pages 581-607, December.
    14. Surajit Bag & Shivam Gupta & Lincoln Wood, 2022. "Big data analytics in sustainable humanitarian supply chain: barriers and their interactions," Annals of Operations Research, Springer, vol. 319(1), pages 721-760, December.
    15. Chatterjee, Sheshadri & Chaudhuri, Ranjan & Vrontis, Demetris & Jabeen, Fauzia, 2022. "Digital transformation of organization using AI-CRM: From microfoundational perspective with leadership support," Journal of Business Research, Elsevier, vol. 153(C), pages 46-58.
    16. Gupta, Rakesh & Pandey, Ritesh & Sebastian, V.J., 2021. "International Entrepreneurial Orientation (IEO): A bibliometric overview of scholarly research," Journal of Business Research, Elsevier, vol. 125(C), pages 74-88.
    17. Zengyuan Wu & Caihong Zhou & Fei Xu & Wengao Lou, 2022. "A CS-AdaBoost-BP model for product quality inspection," Annals of Operations Research, Springer, vol. 308(1), pages 685-701, January.
    18. Wilkin, Carla & Ferreira, Aldónio & Rotaru, Kristian & Gaerlan, Luigi Red, 2020. "Big data prioritization in SCM decision-making: Its role and performance implications," International Journal of Accounting Information Systems, Elsevier, vol. 38(C).
    19. Abdurrezzak Sener & Mehmet Barut & Ali Dag & Mehmet Bayram Yildirim, 2021. "Impact of commitment, information sharing, and information usage on supplier performance: a Bayesian belief network approach," Annals of Operations Research, Springer, vol. 303(1), pages 125-158, August.
    20. Ferdaws Ezzi & Anis Jarboui & Khaireddine Mouakhar, 2023. "Exploring the Relationship Between Blockchain Technology and Corporate Social Responsibility Performance: Empirical Evidence from European Firms," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 1227-1248, June.

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