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Artificial intelligence in E-commerce fulfillment: A case study of resource orchestration at Alibaba’s Smart Warehouse

Author

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  • Zhang, Dan
  • Pee, L.G.
  • Cui, Lili

Abstract

Despite heightened interest, integrating artificial intelligence (AI) into businesses remains challenging. Recent surveys show that up to 85 % of AI initiatives ultimately fail to deliver on their promises. Studies on successful AI applications that could provide invaluable lessons for organizations embarking on their AI journey are still lacking. Therefore, this study aims to understand how AI technology, people, and processes should be managed to successfully create value. Building on the resource orchestration perspective, this study analyzes the successful applications of AI at Alibaba's e-commerce fulfillment center. The findings indicate that the key AI resources include data, AI algorithms, and robots. These resources must be orchestrated (e.g., coordinated, leveraged, deployed) to work with other related resources, such as warehouse facilities and existing information systems, to generate strong AI capabilities. The key AI capabilities generated include forecasting, planning, and learning. More importantly, AI capabilities are not independent – they interact and coevolve with human capabilities to create business value in terms of efficiency (e.g., space optimization, labor productivity) and effectiveness (e.g., error reduction). The implications of understanding these social informatics of AI for research and practice are discussed.

Suggested Citation

  • Zhang, Dan & Pee, L.G. & Cui, Lili, 2021. "Artificial intelligence in E-commerce fulfillment: A case study of resource orchestration at Alibaba’s Smart Warehouse," International Journal of Information Management, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:ininma:v:57:y:2021:i:c:s0268401220315036
    DOI: 10.1016/j.ijinfomgt.2020.102304
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    Citations

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    Cited by:

    1. Chen, Xiaoying & Cui, Miao, 2022. "Understanding platform transformation from internal to external: A resource orchestration perspective," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    2. Queiroz, Maciel M. & Fosso Wamba, Samuel & Chiappetta Jabbour, Charbel Jose & Machado, Marcio C., 2022. "Supply chain resilience in the UK during the coronavirus pandemic: A resource orchestration perspective," International Journal of Production Economics, Elsevier, vol. 245(C).
    3. Mohammed Charaf Eddine BOUREZIG & Soumya Chahinez TALEB BOUGUERRI, 2024. "The Intersection of AI and Digital Entrepreneurship: Studying the Varied Ways that AI is Changing Digital Enterprises," Management and Economics Review, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 9(1), pages 78-90, February.
    4. Emmanouil Papagiannidis & Ida Merete Enholm & Chirstian Dremel & Patrick Mikalef & John Krogstie, 2023. "Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes," Information Systems Frontiers, Springer, vol. 25(1), pages 123-141, February.
    5. Nazir, Sajjad & Khadim, Sahar & Ali Asadullah, Muhammad & Syed, Nausheen, 2023. "Exploring the influence of artificial intelligence technology on consumer repurchase intention: The mediation and moderation approach," Technology in Society, Elsevier, vol. 72(C).
    6. Mashalah, Heider Al & Hassini, Elkafi & Gunasekaran, Angappa & Bhatt (Mishra), Deepa, 2022. "The impact of digital transformation on supply chains through e-commerce: Literature review and a conceptual framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    7. Battistoni, Elisa & Gitto, Simone & Murgia, Gianluca & Campisi, Domenico, 2023. "Adoption paths of digital transformation in manufacturing SME," International Journal of Production Economics, Elsevier, vol. 255(C).

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