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<p>This study conducts a comprehensive bibliometric analysis of 1183 peer-reviewed articles on analyst stock recommendations published between 1975 and 2024. While the literature on analyst behavior and forecasting is mature, its role within the knowledge economy remains underexplored. By framing analysts as key knowledge workers who create, diffuse, and apply financial expertise, this study positions their recommendations as critical elements of knowledge-based economic activity. The paper sets four objectives: (i) to identify the most influential contributions; (ii) to map the intellectual and thematic structure of research; (iii) to derive theoretical, managerial, and policy implications; and (iv) to propose a future research agenda. Using data from Scopus and Web of Science and bibliometric tools such as co-citation analysis, keyword co-occurrence, and thematic mapping, the study identifies emerging areas like ESG, AI adoption, and fintech innovation. A novel conflict risk scoring (CRS) framework is proposed to assess bias in analyst reports, reflecting the evolving nature of financial knowledge systems. Overall, the study consolidates fragmented research and contributes to understanding the production and transmission of knowledge in financial markets.</p>

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Mapping the Landscape of Analyst Stock Recommendations: A Bibliometric Analysis

  • 期刊论文

  • 发表日期：

    2025年7月21日

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  • Suresh Kadam,
  • Madhvi Sethi

摘要

This study conducts a comprehensive bibliometric analysis of 1183 peer-reviewed articles on analyst stock recommendations published between 1975 and 2024. While the literature on analyst behavior and forecasting is mature, its role within the knowledge economy remains underexplored. By framing analysts as key knowledge workers who create, diffuse, and apply financial expertise, this study positions their recommendations as critical elements of knowledge-based economic activity. The paper sets four objectives: (i) to identify the most influential contributions; (ii) to map the intellectual and thematic structure of research; (iii) to derive theoretical, managerial, and policy implications; and (iv) to propose a future research agenda. Using data from Scopus and Web of Science and bibliometric tools such as co-citation analysis, keyword co-occurrence, and thematic mapping, the study identifies emerging areas like ESG, AI adoption, and fintech innovation. A novel conflict risk scoring (CRS) framework is proposed to assess bias in analyst reports, reflecting the evolving nature of financial knowledge systems. Overall, the study consolidates fragmented research and contributes to understanding the production and transmission of knowledge in financial markets.