Scientometric analysis of artificial intelligence in sales and the position of Iran

Abstract

Purpose This study aims to investigate the intellectual structure of research on artificial intelligence (AI) within the sales domain through a co-word analysis approach. By examining patterns of keyword co-occurrence in scholarly publications, the study seeks to uncover the major research themes, trends and knowledge clusters shaping the field. Furthermore, the study evaluates Iran’s contribution and positioning within this global research landscape. In addition, this research explicitly highlights its academic contribution by systematically mapping the intellectual structure of AI-sales studies and situation of Iran’s position within the global landscape. Design/methodology/approach A total of 5,399 scientific articles published between 1984 and 2024 were retrieved from the Scopus database. VOSviewer software was used to analyze the titles and abstracts of these publications, enabling the visualization of co-occurring terms and the identification of thematic clusters within the literature. Findings The results reveal that “sales” and “artificial intelligence” are the most prominent and frequently co-occurring terms, indicating their central role in the field. The co-word analysis identified six major research clusters: sales forecasting and data analytics; personalization and recommendation systems; natural language processing and chatbots; intelligent order and inventory management; market analysis and dynamic pricing; and smart sales security and regulatory compliance. Originality/value This study provides a structured framework that can guide future research on AI applications in sales. It also offers practical insights for developing intelligent sales strategies and aligning marketing practices with technological advancements. The long-term significance and methodological novelty of this scientometric approach further strengthen the study’s contribution to both academic research and practice.

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