Exploring the Intersection of Generative AI and eWOM: A Bibliometric Perspective on Emerging Research Directions

Abstract

The purpose of this study is to explore the evolving research landscape on the role of Generative Artificial Intelligence (GAI) in enhancing the effectiveness of electronic word of mouth (eWOM), focusing on key trends, influential studies, and emerging themes. This study employs a bibliometric analysis using data from the Web of Science (WoS) and Scopus databases. A total of 625 articles published between 2010 and 2024 were analyzed. Various bibliometric techniques were used to identify key research themes, influential journals, and the geographic distribution of research on GAI and eWOM. The findings reveal a rapid growth in research on GAI and eWOM, with significant contributions from China and the United States. Key themes include customer satisfaction, AI-driven decision-making, and sentiment analysis, highlighting GAI’s role in enhancing eWOM effectiveness. This study offers a unique bibliometric analysis of GAI and eWOM, providing new insights into the research landscape and highlighting emerging trends, key contributors, and critical areas for future exploration.

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