Business, Management and Economics Engineering | 2026
Authors: Badre E.M.; Sidouna S.; Chahbar H.; Mrabti A.; Lahrech A.
DOI: 10.3846/bmee.2026.24087
Journal: Business, Management and Economics Engineering
Year: 2026
Publisher: Vilnius Gediminas Technical University
Document Type: Article
Open Access: All Open Access; Gold Open Access; Green Open Access
Cited by: 1
Purpose – this study was undertaken through a systematic literature review to identify the central role of Artificial Intelligence (AI) in improving supply chain performance across all service sectors. Research methodology – a dual methodological approach was used involving both quantitative and qualitative analysis. The former is largely based on a bibliometric analysis of 61 peer-reviewed articles published between 2019 and 2024. In this respect, two software tools, RStudio and VOSviewer, were used to provide a comprehensive bibliometric landscape. The second concerns a thematic content analysis of 25 full-text studies, focusing on AI techniques, performance results and industry-specific implementation challenges. Findings – the overall result of this systematic review indicates that AI contributes to service supply chain performance by improving forecasting, resilience, operational efficiency and real-time decision-making. Research limitations – however, limitations such as data availability, system interoperability, ethical risks and organizational resistance remain important. Practical implications – the results of this study help practitioners to select AI solutions suitable for their sector and to anticipate obstacles to integration. Originality/Value – this study provides a better understanding of how AI is reshaping supply chains in service industries, while identifying key avenues for both future research and practical adoption. © 2026 The Author(s). Published by Vilnius Gediminas Technical University.
artificial intelligence; bibliometric analysis; performance; service supply chains; systematic literature review