Unravelling Behavioural Biases in Individual and Institutional Investors Investment Decision- making: Intersection of Bibliometric and Systematic Literature Review

Abstract

Over the past two decades, there has been a remarkable increase in research endeavours in exploring behavioural biases within the context of investment decision-making. This growth can be attributed to the growing interest and publication efforts of academic scholars. The objective of this study is to conduct a systematic literature review (SLR) of the existing academic literature on the influence of behavioural biases on investment decisions (ID), utilizing bibliometric tools. Initially, a corpus of approximately 124 research papers was gathered by conducting a keyword search in the Scopus database. These papers were then subjected to inclusion and exclusion criteria, resulting in a final selection of 82 papers for in-depth analysis. Bibliometric analysis was conducted using VOS-viewer software, which identified the most prolific articles, authors and journals in the field. Moreover, a thematic analysis was performed to identify six clusters of author keywords, which were further grouped into three broader themes. This process shed light on the connections and patterns prevalent in the study of behavioural biases in investment decision-making. Crucially, keywords with the lowest link strength and co-occurrences played a vital role in identifying potential areas for future research. Additionally, the study identified approximately 50 research articles published from 30 top journals with the highest citations and h-index for further investigation. By following this systematic process, the study not only highlights gaps in the existing literature but also provides valuable insights for future endeavours. Ultimately, this study serves as a roadmap for guiding further investigations in the field of behavioural biases and their influence on ID. By delving into the relationships and themes surrounding these biases, the research aims to contribute significantly to the advancement of knowledge in this domain.