AI for Business Analytics in Logistics and Supply Chain Management: Current Streams and Future Trends of Research

Laabidi Mokhtar () and Gattoufi Said
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Laabidi Mokhtar: Université de Tunis, Institut Supérieur de Gestion de Tunis, Laboratoire SMART LR11ES03
Gattoufi Said: Université de Tunis, Institut Supérieur de Gestion de Tunis, Laboratoire SMART LR11ES03

A chapter in Advanced Data Analytics, Machine Learning and AI in Business, 2026, pp 36-53 from Springer

Abstract: Abstract The ongoing mutations in different business sectors generated by the spectacular developments in digital-enabled businesses relying on data analytics and artificial intelligence (AI) are transforming the global economy toward intelligent data-enabled analytics for decision making. The adoption of these intelligent methods and processes gives considerable competitive advantages and generates wealth at unprecedented rates. Logistics and supply chain management, particularly globally, are deeply affected by these trends, particularly following the global economic instability following recent tax issues that are impacting global supply chains. This calls to review and criticize the recent publications, particularly those related to business analytics to understand the existing body of knowledge and identify future trends in research and empirical data-enabled studies. This paper identifies the relevant literature, analyzes it, and through a bibliometric analysis identifies promising paths for developing intelligent tools and processes of empirical and applied research that can enlighten the way of decision makers in the logistics and Supply chain business sectors locally and globally.

Keywords: AI; Business Analytics; Logistics; Supply Chain; Efficiency; Bibliometric analysis (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-032-23493-3_3

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DOI: 10.1007/978-3-032-23493-3_3

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