Artificial Intelligence and Business Analytics Applications in Supply Chain Operations

A special issue of Logistics (ISSN 2305-6290). This special issue belongs to the section "Artificial Intelligence, Logistics Analytics, and Automation".

Deadline for manuscript submissions: 16 October 2026 | Viewed by 616

Special Issue Editors


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Guest Editor
Department of Management, College of Business, Bowling Green State University, Maurer Center 312, Bowling Green, OH 43403, USA
Interests: global supply chain management; supply chain technology; supply chain benchmarking; supply chain model design; operations management
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Operational Sciences, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH 45433, USA
Interests: logistics and supply chain management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Logistics is pleased to announce a call for papers for a Special Issue titled “Artificial Intelligence and Business Analytics Applications in Supply Chain Operations”. It will focus on the relevance and managerial implications of two emerging technological tools, artificial intelligence (AI) and business analytics, for supply chain practices in the era of the fourth and fifth industrial revolutions. This Special Issue aims to encourage contributing scholars to conduct state-of-the-art theoretical and empirical research on the usefulness of AI and business analytics in enhancing supply chain productivity in the 21st century.

This Special Issue aims to gather cutting-edge research and innovative perspectives on various aspects of AI and business analytics. Topics of interest include supply chain analytics; machine learning algorithms for demand planning, inventory planning, logistics planning, and sourcing; smart warehousing and manufacturing; autonomous trucking; drone technology applications to last-mile delivery; delivery service providers for last-mile delivery; AI tools (e.g., ChatGPT and Co-Pilot) for supply chain ecosystem and resilience; and AI (e.g., neural network) applications in healthcare logistics and production scheduling.

Other topics related to generative AI issues or business analytics applications are welcome, provided they focus on the successful applications of AI and business analytics in logistics managerial problem-solving and innovative supply chain practices.

Prof. Dr. Hokey Min
Prof. Dr. Seong-Jong Joo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Logistics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • logistics management
  • operations management
  • purchasing management
  • marketing management
  • applied statistics
  • operations research

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Published Papers (1 paper)

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Research

21 pages, 1222 KB  
Article
Artificial Intelligence-Driven Supply Chain Agility and Resilience: Pathways to Competitive Advantage in the Hotel Industry
by Ibrahim A. Elshaer, Alaa M. S. Azazz, Abdulaziz Aljoghaiman, Mahmoud Mansor, Mahmoud Ahmed Salama and Sameh Fayyad
Logistics 2026, 10(1), 5; https://doi.org/10.3390/logistics10010005 - 26 Dec 2025
Viewed by 455
Abstract
Background: The extraordinary disturbances faced by the hotel industry, ranging from worldwide health problems to political instability and climate change, have highlighted the insistent need for more resilient and agile supply chain (SC) systems. This study explored how artificial intelligence (AI) capabilities [...] Read more.
Background: The extraordinary disturbances faced by the hotel industry, ranging from worldwide health problems to political instability and climate change, have highlighted the insistent need for more resilient and agile supply chain (SC) systems. This study explored how artificial intelligence (AI) capabilities can generate competitive advantage (CA) through supply chain agility (SCA) and supply chain resilience (SCR) as mediators and competitive pressure (CP) as a moderator. Methods: Drawing on the resource-based view (RBV) framework, we suggested and empirically tested the study model. Using data collected from 432 hotel managers and analyzed using Partial Least Squares Structural Equation Modelling (SEM-PLS). Results: the results reveal that AI-driven SC can significantly strengthen SCA and SCR. Furthermore, SCA and SCR can act as powerful mediators, and CP can strengthen the tested relationships (the links from AI adoption and CA) as a moderator. Conclusions: The study made several theoretical and practical contributions by integrating AI capabilities into SCR and SCA frameworks in the hotel and tourism context, and by providing practical evidence for professionals aiming to leverage AI-driven SC tools to navigate uncertainty and create sustainable CA. Full article
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