Abstract:

This study examines the development of Explainable Artificial Intelligence (XAI) in the management and business domains using bibliometric techniques. The analysis includes keyword co-occurrence and thematic mapping to trace the intellectual roots of XAI research and identify research avenues across management research domains. The study covers 40 references for co-citation analysis and 990 articles for bibliographic coupling analysis, employing publications between 2014 and 2023. The co-citation analysis identifies four distinct yet overlapping research streams in the XAI field. Through bibliometric coupling analysis, we show four management-related XAI research themes and highlights promising future research directions. The study contributes to the conceptual and empirical advancement of the field by proposing integrative ways to advance XAI research by exploring its origins, processes, applications, and development. We offer a comprehensive overview of the development of XAI research in the management and business domains and provide valuable insights for both academics and practitioners.

Please choose your submission type: Full Paper

Primary Track: eBusiness and Government

Keywords: Technological solutions (e.g. utilising artificial intelligence, augmented reality and virtual reality) and sustainability

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Prof Michael Shayne Gary