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This research article aims to systematically explore the association between digitalisation and individual investors’ behavioural biases. Through an extensive exploration of digitalisation modes and their various serviceable avenues in the investment arena, the study aims to elucidate the impact of behavioural biases on individual investors’ investment decision-making processes.

The study employs Interpretative Phenomenological Analysis (IPA) to gain insights into behavioural finance and the associated behavioural biases of investors in digitalisation. IPA, a qualitative method grounded in heuristic, phenomenological, and idiographic elements, facilitates the exploration of individual investor experiences and the role of digitalisation and behavioural biases within.

Investors are categorised into two groups – decision seekers and decision makers – based on their digital inclination and the purpose behind using digital tools. The attributes of these segments are detailed under the sub-themes of Digital Inclination, Market Cognizance, Sophistication and Maturity, Sophomorism and Perception of Digitalisation. The study also identifies the specific behavioural biases pertinent to each segment. Additionally, it introduces a novel section on the insights related to human emotions, behaviour and sentiment within financial markets.

The essence of the current article is the application of the IPA method to the field of behavioural finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive understanding of both, digitalisation and behavioural biases that affect the individual investor’s decision-making. It offers valuable insights for researchers, academicians and scholars in behavioural finance, enhancing the understanding of how behavioural biases influence investment decisions.

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

The cognitive biases exhibited by investors could hinder their capacity for logical reasoning and impact their perception and reaction to information when making financial choices. So, this study was done to identify the behavioral biases that hinder investors' sound decision-making at the Pakistan Stock Exchange (PSX).

A cross-sectional study was undertaken employing a causal research design approach. Questionnaires were administered to individual investors of the PSX as the data collection methodology. The data were subsequently analyzed through the utilization of the Smart PLS Structural Equation Modeling (SEM) technique.

The results suggest that information factors and cognitive biases, namely home bias, geographical bias, investor sentiment, salience, and over/under reaction have a positive association with the investors' choices at PSX.

The study’s emphasis is on the impact of behavioral biases on individual investors only, even though such biases also influence the investment decisions of institutional investors.

The study holds implications for scholars engaged in the field of behavioral finance as well as professionals involved in the stock market, particularly those interacting with individual investors and personal finance. Additionally, the current study will take into account investors, financial advisors, practitioners, policymakers, investment experts, stakeholders or target groups, etc. to support various groups in their professional activity and to help them overcome such biases that influence their sound decision-making power.

The innovative aspect of this research is its ability to advance the understanding of the conceptual underpinnings and social structure of behavioral biases by critically analyzing the body of prior research and adding value to the existing body of literature on behavioral finance in Pakistan by investigating the combined impact of never-studied variables, i.e. geographical bias and information variables, understudied behavioral variables, i.e. home bias and salience and studied variables, i.e. investor sentiment and over/under reaction on individual investor investment decisions at PSX.

The purpose of this study is to investigate the impact of behavioral biases on investment decisions through a serial mediation of overconfidence and disposition effects.

The authors assess the behavioral biases affecting the investment decisions of life insurance policyholders through the serial mediation of overconfidence and disposition effects using a structured questionnaire. The study included 501 life insurance policyholders who were selected using a snowball sampling technique.

The results of this study revealed that behavioral biases influence the investment decisions of life insurance policyholders. The results also support the serial mediation model, where behavioral biases influence the investment decisions of life insurance policyholders via overconfidence and disposition effects.

This study makes a theoretical contribution to the field of behavioral finance by exploring the influences of behavioral biases on investment decisions. It also introduces overconfidence and disposition effects as serial mediators between behavioral biases and investment decisions. The study will be helpful for researchers, academicians and policymakers in the development of a more comprehensive model in the area of behavioral finance and in raising awareness regarding those biases among policyholders in order to improve their investment strategy.

This study has extended the ongoing simple mediation model by integrating overconfidence and disposition effects in a serial mediation model between behavioral biases and investment decisions. The study will contribute to the area of behavioral finance, as it is the first time this particular study has been conducted according to the authors’ knowledge.

This study aims to conduct a bibliometric analysis to provide a comprehensive picture and identify future research directions to enrich the existing literature on behavioral biases.

The data set comprises 518 articles from the Web of Science database. Performance analysis is used to highlight the significant contributors (authors, institutions, countries and journals) and contributions (highly influential articles) in the field of behavioral biases. In addition, network analysis is used to delve into the conceptual and social structure of the research domain.

The current review has identified four major themes: “Influence of behavioral biases on investment decisions,” “Determinants of home bias,” “Impact of biases on stock market variables” and “Investors’ decision-making under uncertainty.” These themes reveal that a majority of studies have focused on equity markets, and research on other asset classes remains underexplored.

This study extracted data from a single database (Web of Science) to ensure standardization of results. Consequently, future research could broaden the scope of the bibliometric review by incorporating multiple databases.

The novelty of this research is to provide valuable guidance by evaluating the existing literature and advancing the knowledge base on the conceptual and social structure of behavioral biases.

This paper examines the relationship between behavioral biases, and demand decisions for life insurance products in Uganda.

Data were collected from 351 life insurance policyholders in Uganda. The authors used a cross-sectional survey by applying a structured questionnaire. Descriptive analysis was conducted and hypothesized relationships between the constructs were evaluated through the use of structural equation modeling.

Results indicate that, behavioral biases are significant predictors of life insurance demand among Ugandan policyholders. Also, the two behavioral bias variables (heuristic bias and prospect bias) are significant predictors of demand decisions for life insurance products.

These results are helpful for both insurers and regulators. For insurers, it is now evident that demand decisions for life insurance products are not fully rational. It is imperative for insurers to simplify life insurance product information (heuristics), integrate product education and widen dissemination of product information (prospect bias) to allow policyholders to come up with optimal demand decisions. While for insurance policymakers, the study provides an understanding of behavioral biases. With such insights, policymakers can identify exploitative and deceptive information that target policyholders to better guide life insurance documentation and product designs.

This study is the first to offer insights into behavioral biases' influence on demand decisions for life insurance products in a developing country like Uganda. By integrating prospects and expected utility theory, this study examines rationality and irrationality in demand decisions for life insurance products.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0201

The purpose of this study is to examine the behaviour of retail investors while making an investment decision and how it gets affected by the behavioural biases of the investors using a moderated-mediation framework.

A mixed method approach has been used to fulfil the objectives of the study. In the first study, a qualitative analysis of the interviews with 15 retail investors was conducted. As part of the quantitative study, a total of 201 responses from Indian retail investors were collected using systematic sampling and analysed using structural equation modelling and Process Macro.

The results indicate that anchoring bias, availability bias, herding bias, switching cost, sunk cost, regret avoidance and perceived threat have a significant effect on retail investors’ investing intention. The attitude of the investors towards investing decisions mediates the effects of behavioural bias and the status quo on investment intention. The results of the moderated-mediation analysis indicate that mediating effect of attitude varied at the low and high-risk aversion of investors.

The findings of this study will help regulators and retail investors to understand the critical behavioural biases which affect the investors’ investing intention.

The paper contributes to the literature on investors’ behaviour, status quo bias theory (SQB) and behavioural bias. This study uniquely proposes a moderated-mediation framework to understand the effects of biases on retail investors’ investment intention.

Purpose – This study aims to investigate how behavioural biases affect cryptocurrency investment choices. The study also evaluates how risk tolerance mediates the relationship between behavioural biases and investment decision-making.

Need for the Study – The study is required to refine research methods and to ensure the reliability and validity of findings on behavioural biases in cryptocurrency investment decision-making.

Methodology – This pilot study involved responses from individuals in India’s western and northern regions who either invested in cryptocurrencies or had adequate knowledge of such investments. To assess the normality, validity, and reliability of the questionnaire data, a sample of 51 individuals was analysed using SPSS software.

Findings – The results of this study validate the reliability of the questionnaire in conducting pilot research by attaining high reliability with high coefficients of measures and reasonable normality.

Originality/value – The study confirmed the tool’s efficiency to analyse various specific antecedents influencing investing choices.

The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them.

For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities.

The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan.

The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners’ such as investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/ broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making its financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities.

The purpose of the study is to investigate, synthesize and critically evaluate empirical research findings on the behavioral traits of fund managers from 1994 to 2024. The ultimate goal is to provide a unified body of literature on three broad topics: first, fund managers' demographic and professional characteristics, such as age, gender, level of education and years of industry experience; second, fund managers' social and political connections; and third, fund managers' behavioral biases that lead to irrational investment decisions.

The relevant papers from selected journals were discovered and manually validated using the Scopus database. From 317 retrieved documents, 57 relevant articles were chosen and analyzed after the forward and backward search of the existing articles.

This paper presents a categorized summary of behavioral factors that have gained a foothold in influencing the behavior of fund managers in fund management research, with several studies demonstrating their significance leading to improved prediction and model precision, as this review indicates. In addition, the study summarized the contributions of prior empirical studies within the aforementioned three major categories and illustrated their consequences.

The present study contributes to the understanding of the effects of behavioral finance theories on fund managers by providing meaningful explanations of their behavioral traits based on empirical evidence and existing trends and knowledge gaps, both of which can influence the future direction of research.