Mapping the Intersection of Marketing, Artificial Intelligence, and the Cooperative Sector: A Bibliometric Analysis

Abstract Purpose: This study examines the role of marketing within the cooperative sector, as well as the potential of artificial intelligence (AI) as a strategic tool. The study aims to identify the main challenges and opportunities in cooperative marketing, evaluate the application of AI in these strategies and inform future research. Methods: A bibliometric analysis was conducted using the Web of Science database to classify academic publications and reveal thematic relationships. VOSviewer was then used to map intellectual structures, while a Python-based co-occurrence analysis examined the links between cultural, regional, and thematic factors. Findings: The findings highlight the growing intersection between marketing, AI, and the cooperative sector. Fifteen research questions, grouped into five themes, were identified to guide future interdisciplinary studies. Integrating marketing and AI within the social economy could enhance the sustainability, competitiveness, and equity of cooperative business models. Study limitations: Although exploratory, the study provides a comprehensive overview of the existing literature. However, limitations include reliance on the WoS database and focus on English-language publications, as well as inevitable subjectivity in interpretation. Including other databases in future analyses could enrich the scope of the research. Practical value: Overall, the study provides valuable insights into how technological innovation, particularly AI, can align with the social and ethical values of cooperatives. It also establishes a foundation for further research and the development of frameworks that can strengthen the cooperative sector's sustainable and competitive marketing strategies.