Artificial Intelligence in Logistics Service Quality: A Bibliometric Analysis of Research Trends, Intellectual Structure, and Future Directions

This study aims to analyse the existing literature and identify major research trends in artificial intelligence in logistics service quality research.Data were retrieved from the Scopus database, comprising 281 journal articles and review papers published between 2002 and 2026, after applying predefined inclusion and exclusion criteria to an initial dataset of 533 records.A bibliometric analysis was conducted using R Studio (Bibliometrix/Biblioshiny) and VOSviewer to examine publication trends, citation patterns, influential sources, country productivity, highly cited documents, keyword co-occurrence networks, and thematic structures within the research domain.The findings indicate a rapidly expanding body of research linking artificial intelligence and digital technologies with logistics service quality, customer satisfaction, e-commerce logistics, last-mile delivery, route optimization, and digital supply chain management.The field has experienced particularly strong growth after 2020, reaching its highest publication output in 2025.Customer satisfaction emerges as the most central keyword, suggesting that the literature remains strongly grounded in a service-quality and customer-experience perspective, even as advanced technologies such as artificial intelligence, machine learning, big data analytics, the Internet of Things, blockchain, automation, and optimization techniques become increasingly integrated into logistics service systems.Keyword co-occurrence analysis and thematic mapping are used as two complementary techniques.The keyword co-occurrence analysis identifies four major clusters representing distinct research streams, while thematic mapping reveals five thematic areas, reflecting different analytical logics underlying network-based clustering and centralitydensity-based classification.The study contributes to a clearer understanding of the intellectual structure of AI-driven logistics service quality research and provides future research directions related to customer experience, sustainable last-mile delivery, responsible AI adoption, and intelligent logistics service systems.