Call for papers special issue Crossed Perspectvies: Artificial Intelligence and Supply Chain
Logistique & Management + Systèmes d’Information & Management: Double special issue on the theme "Crossed Perspectives: Artificial Intelligence and Supply Chain"
Guest Editors : Laurence SAGLIETTO, Jennifer LAZZERI GRACIA-CAMPO et Federico PIGNI
Following the AIM 2024 annual conference (Association Information et Management) on the theme "Working with AI or despite AI?", the Digitalization of Supply Chain Thematic Group (GTAIM) invites you to contribute to a special double issue dedicated to the intersection of Artificial Intelligence (AI) and Supply Chain Management (SCM) titled:
Crossed Perspectives: Artificial Intelligence and Supply Chain
This issue seeks to showcase the most advanced and significant interdisciplinary research exploring how AI is reshaping supply chain management. We encourage scholars from diverse fields to tackle the challenge of examining the convergence of AI and supply chain, a critical area that is transforming operations management. We invite you to take up the challenge by contributing to this special double issue.
AI is widely recognized as one of the most disruptive technologies for contemporary supply chains (Fosso Wamba et al., 2022). Advanced algorithms and intuitive interfaces enable the extraction of relevant, intelligent data from Big Data, transforming it into actionable insights to enhance decision-making and operational efficiency. Similarly, Smart Data facilitates the categorization and classification of useful resources, making them more readily accessible to various company functions. For instance, in the transportation sector, the management of carbon quotas, the implementation of new extra-financial reporting standards, and the increasing obligations surrounding social and environmental impacts require precise, comprehensive data—mobilized through AI to drive improved performance.
AI thus contributes, with the prerequisite of very high-quality data, to modernizing and making supply chains more efficient by reducing costs, improving forecasting accuracy, and offering a better customer experience. Current research on AI and the supply chain focuses on how AI can enhance business performance and create value when combined with other advanced Industry 4.0 technologies (Fosso Wamba et al., 2022; Abbad et al., 2022; Acquatella et al., 2022, Karaa, 2022, De Corbière et al., 2023) or when it provides support during crises. Recent health and geopolitical events have revealed significant tensions in supply chains and the urgent need to reduce their vulnerability (Zaouari et al., 2021). In these situations, real-time data processing and predictive analytics enabled by AI help to be more agile, anticipate and manage disruptions (Toorajipour et al., 2021) and ensure the continuous and adaptive resilience of the supply chain (Modgil et al., 2022).
Recent research highlights the growing opportunities that artificial intelligence presents for supply chain management, which are increasingly promising (Richey et al., 2023). However, the field of study remains vast. Many challenges remain to be addressed, numerous avenues to explore, and many unanswered questions that deserve to be shared:
• What are the underlying information systems that make data smarter and immediately usable?
• What are the advantages and disadvantages for logisticians? Should companies necessarily adopt AI in their new logistics strategy to eliminate risks (competitive, financial, geopolitical, cyberattacks...), optimize their planning and decision-making processes, diversify their networks, and seize new opportunities?
• How can AI support logistics strategies in mitigating risks (e.g., competitive, financial, geopolitical, or cybersecurity risks)?
• What is the role of AI in balancing competitiveness with social and environmental responsibilities, such as reducing carbon footprints ?
• What major changes will the integration of AI impose on companies?
• What are the limitations of using AI for SCM?
• How do different AI applications (deep Learning, machine Learning) enhance the performance of SCM?
• What ethical, technological, and human factors are crucial for the successful integration of AI into supply chains?
• What are the implications for intellectual property, data privacy, and ethics in AI-driven supply chains?
We invite submissions that explore these and related topics, addressing the profound changes AI is bringing to supply chain management. We welcome both theoretical and empirical papers that provide new insights into the role of AI in supply chain management, especially those that highlight innovative uses of AI and its impact on business performance, crisis management, and sustainability. Contributions that bring together researchers from supply chain management and information systems will be particularly appreciated, as interdisciplinary approaches are essential to fully understanding this complex and evolving field.
Bibliography
Abbad, H., Bentahar, O., & Benzidia, S. (2022). Transformation digitale de la supply chain: caractéristiques, enjeux et voies de recherche futures. Logistique & Management, 30(4), 119-124.
Acquatella, F., Fernandez, V., & Houy, T. (2022). Une mise en perspective technico-économique du rôle central de l’intelligence artificielle sur les marchés. Systèmes d’information et management, 27(4), 51-73.
De Corbière, F., Elie-Dit-Cosaque, C., Leclercq-Vandelannoitte, A. (2023), Intelligence artificielle et recherche en management des systèmes d’information : menace ou opportunités ?, Systèmes d’information et management,(espace)Editorial, 28(1).
Fosso Wamba, S., Queiroz, M. M., Guthrie, C., & Braganza, A. (2022). Industry experiences of artificial intelligence (AI): benefits and challenges in operations and supply chain management. Production planning & control, 33(16), 1493-1497.
Karaa, M. (2022). La blockchain au service de la traçabilité de l’huile d’olive : cas d’une entreprise tunisienne. Logistique & Management, 30(4), 142-155.
Modgil, S., Gupta, S., Stekelorum, R., & Laguir, I. (2022). AI technologies and their impact on supply chain resilience during COVID-19. International Journal of Physical Distribution & Logistics Management, 52(2), 130-149.
Richey Jr, R. G., Chowdhury, S., Davis‐Sramek, B., Giannakis, M., & Dwivedi, Y. K. (2023). Artificial intelligence in logistics and supply chain management: A primer and roadmap for research. Journal of Business Logistics, 44(4), 532-549.
Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 122, 502-517.
Zouari, D., Ruel, S. and Viale, L. (2020), “Does digitalising the supply chain contribute to its resilience?”, International Journal of Physical Distribution and Logistics Management, Vol. 51 No. 2, pp. 149-180, doi: 10.1108/IJPDLM-01-2020-0038.
Calendar
Full article proposals in french and following the Logistique & Management guidelines (https://www.tandfonline.com/journals/tlam20), must be submitted no later than June 30, 2025, via the Taylor & Francis platform
(https://rp.tandfonline.com/submission/create?journalCode=TLAM).
They will undergo the usual double-blind peer review process. This thematic issue, published by the Taylor & Francis Group, will be released in 2026 (V34-n°3- 2026).
The call covers several categories: scientific article, case study, expert opinion, and book presentation. For each category, please comply with the editorial requirements of Taylor & Francis.
Full article proposals in english, and following the journal Systèmes d’Information & Management guidelines (https://revuesim.org/index.php/sim/about/submissions), must be submitted no later than June 30, 2025, via the website (https://revuesim.org/index.php/sim/about).
They will undergo the usual double-blind peer review process. This special issue will be released in 2026 (V31-n°3-2026). The call covers several categories: scientific article, case study, expert opinion, etc.. For each category, please comply with the editorial requirements of Taylor & Francis.
"It is possible to present the project at the AIM Lyon 2025 conference - (GTAIM) Digitalization of the supply chain." (https://aim.asso.fr/fr/conferences/conference-annuelle)
The coordination of this special issue is managed by:
Laurence Saglietto, University Professor, Université Côte d'Azur, IAE Nice, GREDEG CNRS. Laurence.saglietto@univ-cotedazur.fr
Jennifer Lazzeri Gracia-Campo, Associate Professor, Aix-Marseille University, CRET-LOG. jennifer.lazzeri@univ-amu.fr
Federico Pigni, Professor, Grenoble Ecole de Management.
federico.pigni@grenoble-em.com
