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This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management activities and market efficiency. It also includes some of the research work on the origins and foundations of behavioral finance, and how this has grown substantially to become an established and particular subject of study in its own right. The study also aims to provide future direction to the researchers working in this field.

For doing research synthesis, a systematic literature review (SLR) approach was applied considering research studies published within the time period, i.e. 1970–2021. This study attempted to accomplish a critical review of 176 studies out of 256 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioral finance domain-related explicitly to cognitive heuristic-driven biases and their effect on investment management activities and market efficiency as well as on the origins and foundations of behavioral finance.

This review reveals that investors often use cognitive heuristics to reduce the risk of losses in uncertain situations, but that leads to errors in judgment; as a result, investors make irrational decisions, which may cause the market to overreact or underreact – in both situations, the market becomes inefficient. Overall, the literature demonstrates that there is currently no consensus on the usefulness of cognitive heuristics in the context of investment management activities and market efficiency. Therefore, a lack of consensus about this topic suggests that further studies may bring relevant contributions to the literature. Based on the gaps analysis, three major categories of gaps, namely theoretical and methodological gaps, and contextual gaps, are found, where research is needed.

The skillful understanding and knowledge of the cognitive heuristic-driven biases will help the investors, financial institutions and policymakers to overcome the adverse effect of these behavioral biases in the stock market. This article provides a detailed explanation of cognitive heuristic-driven biases and their influence on investment management activities and market efficiency, which could be very useful for finance practitioners, such as an 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 their financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on cognitive heuristic-driven biases displayed by investors. The current study is original in discussing the role of cognitive heuristic-driven biases in investment management activities and market efficiency as well as the history and foundations of behavioral finance by means of research synthesis. This paper is useful to researchers, academicians, policymakers and those working in the area of behavioral finance in understanding the role that cognitive heuristic plays in investment management activities and market efficiency.

Conventional theories of financial management are notably inconspicuous when considering the influence of heuristic-driven biases and fundamental and technical anomalies on institutional investors' investment decision-making performance and market efficiency, particularly, in emerging Asian economies. This study aims to explore the mechanism by which heuristic driven biases (i.e. cognitive heuristic biases and recognition-based heuristic biases) influence institutional investors' investment decision-making, investment performance and perceived market efficiency, with a mediating role of fundamental and technical anomalies and the moderating role of financial knowledge in Pakistan.

Data were collected through a survey completed by 180 institutional investors trading on the Pakistan Stock Exchange. Structural equation modeling was used to analyze the data and test the hypotheses.

The results suggest that heuristic-driven biases have a significant negative influence on perceived market efficiency and investment performance and a significant positive effect on investment decisions of institutional investors. Fundamental and technical anomalies appeared to mediate these relationships. The results also revealed that financial knowledge moderates these relationships.

This study pioneers research on the links among heuristic-driven biases, financial knowledge, fundamental and technical anomalies and institutional investors' decisions and performance. This adds to the understanding of the role that heuristic-driven bias plays in investment management activities and enhances the appreciation of various behavioral aspects and their influence on investment decision-making and performance in an emerging market. It also contributes to the literature on behavioral finance, specifically the role of heuristics in investment strategies, which is still in its initial stage in developed countries, let alone in developing countries. The current research contributes to the literature by defining heuristic-driven biases as antecedents and fundamental and technical anomalies as intervening variables for irrational investment decision-making and poor investment performance. In addition, this study underlines the significance of utilizing financial knowledge to manage the antecedents and repercussions of fundamental and technical anomalies.

This study aims to use a qualitative approach to explore and clarify the mechanism by which heuristic-driven biases influence the decisions and performance of individual investors actively trading on the Pakistan Stock Exchange (PSX). It also aims to identify how to overcome the negative effect of heuristic-driven biases, so that finance practitioners can avoid the expensive errors which they cause.

This study adopts an interpretative approach. Qualitative data was collected in semistructured interviews, in which the target population was asked open-ended questions. The sample consists of five brokers and/or investment strategists/advisors who maintain investors’ accounts or provide investment advice to investors on the PSX, who were selected on a convenient basis. The researchers analyzed the interview data thematically.

The results confirm that investors often use heuristics, causing several heuristic-driven biases when trading on the stock market, specifically, reliance on recognition-based heuristics, namely, alphabetical ordering of firm names, name memorability and name fluency, as well as cognitive heuristics, such as herding behavior, disposition effect, anchoring and adjustment, repetitiveness, overconfidence and availability biases. These lead investors to make suboptimal decisions relating to their investment management activities. Due to these heuristic-driven biases, investors trade excessively in the stock market, and their investment performance is adversely affected.

This study provides a practical framework to explore and clarify the mechanism by which heuristic-driven biases influence investment management activities. To the best of authors’ knowledge, the current study is the first to focus on links between heuristic-driven biases, investment decisions and performance using a qualitative approach. Furthermore, with the help of a qualitative approach, the investigators also highlight some factors causing an increased use of heuristic variables by investors and discuss practical approaches to overcoming the negative effects of heuristics factors, so that finance practitioners can avoid repeating the expensive errors which they cause, which also differentiates this study from others.

This article aims to clarify the mechanism by which heuristic-driven biases influence the entrepreneurial strategic decision-making in an emerging economy.

Entrepreneurs' heuristic-driven biases have been measured using a questionnaire, comprising numerous items, including indicators of entrepreneurial strategic decision-making. To examine the relationship between heuristic-driven biases and entrepreneurial strategic decision-making process, a 5-point Likert scale questionnaire has been used to collect data from the sample of 169 entrepreneurs who operate in small- and medium-sized enterprises (SMEs). The collected data were analyzed using SPSS and Amos graphics software. Hypotheses were tested using structural equation modeling (SEM) technique.

The article provides empirical insights into the relationship between heuristic-driven biases and entrepreneurial strategic decision-making. The results suggest that heuristic-driven biases (anchoring and adjustment, representativeness, availability and overconfidence) have a markedly negative influence on the strategic decisions made by entrepreneurs in emerging markets. It means that heuristic-driven biases can impair the quality of the entrepreneurial strategic decision-making process.

The article encourages entrepreneurs to avoid relying on cognitive heuristics or their feelings when making strategic decisions. It provides awareness and understanding of heuristic-driven biases in entrepreneurial strategic decisions, which could be very useful for business actors such as entrepreneurs, managers and entire organizations. Understanding regarding the role of heuristic-driven biases in entrepreneurial strategic decisions may help entrepreneurs to improve the quality of their decision-making. They can improve the quality of their decision-making by recognizing their behavioral biases and errors of judgment, to which we are all prone, resulting in a more appropriate selection of entrepreneurial opportunities.

The current study is the first to focus on links between heuristic-driven bias and the entrepreneurial strategic decision-making in Pakistan—an emerging economy. This article enhanced the understanding of the role that heuristic-driven bias plays in the entrepreneurial strategic decisions and more importantly, it went some way toward enhancing understanding of behavioral aspects and their influence on entrepreneurial strategic decision-making in an emerging market. It also adds to the literature in the area of entrepreneurial management specifically the role of heuristics in entrepreneurial strategic decision-making; this field is in its initial stage, even in developed countries, while, in developing countries, little work has been done.

The purpose of this article is to clarify the mechanism by which underconfidence heuristic-driven bias influences the short-term and long-term investment decisions of individual investors, actively trading on the Pakistan Stock Exchange.

Investors' underconfidence has been measured using a questionnaire, comprising numerous items, including indicators of short-term and long-term investment decision. In order to establish the influence of underconfidence on the investment decisions in both the short and long run, a 5-point Likert scale questionnaire has been used to collect data from the sample of 203 investors. The collected data were analyzed using SPSS and AMOS graphics software. Hypotheses were tested using structural equation modeling technique.

This article provides further empirical insights into the relationship between heuristic-driven biases and investment decision-making in the short and long run. The results suggest that underconfidence bias has a markedly negative influence on the short-term and long-term decisions made by investors in developing markets. It means that heuristic-driven biases can impair the quality of both short-term and long-term investment decisions.

This article encourages investors to avoid relying on cognitive heuristics, namely, underconfidence or their feelings when making short-term and long-term investment strategies. It provides awareness and understanding of heuristic-driven biases in investment management, 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. They can improve the quality of their decision-making by recognizing their behavioral biases and errors of judgment, to which we are all prone, resulting in more appropriate investment strategies.

The current study is the first to focus on links between underconfidence bias and short-term and long-term investment decision-making. This article enhanced the understanding of the role that heuristic-driven bias plays in the investment management and more importantly, it went some way toward enhancing understanding of behavioral aspects and their influence on the investment decision-making in an emerging market. It also adds to the literature in the area of behavioral finance specifically the role of heuristics in investment strategies; this field is in its initial stage, even in developed countries, while, in developing countries, little work has been done.

This study aims to explore and clarify the mechanism by which cognitive heuristics influence strategic decision-making during the coronavirus disease 2019 (COVID-19) pandemic in an emerging economy.

Data collection was conducted through a survey completed by 213 top-level managers from firms located in the twin cities of Pakistan. A convenient, purposively sampling technique and snowball method were used for data collection. To examine the relationship between cognitive heuristics and strategic decision-making, hypotheses were tested by using correlation and regression analysis.

The article provides further insights into the relationship between cognitive heuristics and strategic decision-making during the COVID-19 pandemic. The results suggest that cognitive heuristics (under-confidence, self-attribution and disposition effect) have a markedly negative influence on the strategic decision-making during the COVID-19 pandemic in an emerging economy.

The article encourages strategic decision-makers to avoid relying on cognitive heuristics or their feelings when making strategic decisions. It provides awareness and understanding of cognitive heuristics in strategic decision-making, which could be very useful for business actors such as managers and entire organizations. The findings of this study will help academicians, researchers and policymakers of emerging countries. Academicians can formulate new behavioural models that can depict the solutions to dealing with an uncertain situation like COVID-19. Policymakers and strategic decision-making teams can develop crisis management strategies based on concepts from behavioral strategy to better deal with similar circumstances in the future, such as COVID-19.

The paper’s novelty is that the authors have explored the mechanism by which cognitive heuristics influence strategic decision-making during the COVID-19 pandemic in an emerging economy. It adds to the literature in strategic management, explicitly probing the impact of cognitive heuristics on strategic decision-making; this field is in its initial stage, even in developed countries, while little work has been done in emerging countries.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-10-2021-0636.

The study explores new aspects of financial investment management with technological involvement, providing detailed knowledge for future research. It identifies gaps in the literature and summarizes key research topics, utilizing a precise data collection framework.

The study is structured using systematic and bibliometric analysis with the antecedents, decisions, outcome-theories, context, and methods (ADO-TCM) framework. Data from Scopus and Web of Science were filtered based on Q1, Q2, social sciences citation index (SSCI) and Australian Business Deans Council (ABDC) criteria, resulting in 128 articles majorly emphasizing the last ten years. The “R” package facilitated bibliometric analysis, starting with data cleaning and import into Biblioshiny for effective results interpretation.

The study found that artificial intelligence detects and mitigates biases in investment decisions through rigorous pattern analysis, including social and ethical biases. The ADO-TCM framework revealed emerging theories, such as robo-advisory theory, offering new directions in behavioral finance for researchers and practitioners. The top authors and articles highlighted existing work in financial management.

The study’s originality is highlighted by its use of unique frameworks for data collection (SPAR-4-SLR) and interpretation (ADO-TCM).

This study aims to explore and clarify the mechanism by which recognition-based heuristic biases influence the investment decision-making and performance of individual investors, with the mediating role of fundamental and technical anomalies.

The deductive approach was used, as the research is based on behavioral finance's theoretical framework. A questionnaire and cross-sectional design were employed for data collection from the sample of 323 individual investors trading on the Pakistan Stock Exchange (PSX). Hypotheses were tested through the structural equation modeling (SEM) technique.

The article provides further insights into the relationship between recognition-based heuristic-driven biases and investment management activities. The results suggest that recognition-based heuristic-driven biases have a markedly positive influence on investment decision-making and negatively influence the investment performance of individual investors. The results also suggest that fundamental and technical anomalies mediate the relationships between the recognition-based heuristic-driven biases on the one hand and investment management activities on the other.

The results of the study suggested that investment management activities that rely on recognition-based heuristics would not result in better returns to investors. The article encourages investors to base decisions on investors' financial capability and experience levels and to avoid relying on recognition-based heuristics when making decisions related to investment management activities. The results provides awareness and understanding of recognition-based heuristic-driven biases in investment management activities, which could be very useful for decision-makers and professionals in financial institutions, such as portfolio managers and traders in commercial banks, investment banks and mutual funds. This paper helps investors to select better investment tools and avoid repeating the expensive errors that occur due to recognition-based heuristic-driven biases.

The current study is the first to focus on links recognition-based heuristic-driven biases, fundamental and technical anomalies, investment decision-making and performance of individual investors. This article enhanced the understanding of the role that recognition-based heuristic-driven biases plays in investment management. More importantly, the study went some way toward enhancing understanding of behavioral aspects and the aspects' influence on investment decision-making and performance in an emerging market.

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 this paper is to determine whether anchoring and adjustment as heuristic-driven bias and herding behaviour influences listed property fund managers in South Africa’s property investment decisions. The study contributes to the understanding of the influence of heuristic-driven bias and herding behaviour on property investment decisions made in a highly volatile environment.

This study is focused on the subject field of behavioural finance and follows a survey-based design. A questionnaire was finalised after completion of the pilot study and was sent via e-mail to fund managers of all South African-based property funds listed on the Johannesburg Securities Exchange. Non-parametric statistical measures were used.

Consistency with other studies suggests that anchoring and adjustment may exist in the decisions made by listed property fund managers. However, fund managers tend to not adjust to new information due to the current socio-political environment in South Africa rather than a lack of understanding of the new information.

It is recommended that investors form developed and emerging economies take notice of the highly volatile circumstances in which property fund managers in an emerging economy such as South Africa have to make investment decisions. The probability of missed gains as a result of conservative investment strategies may have an impact on future returns.

This study enhanced the understanding of the role that heuristic-driven bias plays in the South African property industry and more importantly, it went some way towards enhancing understanding of behavioural aspects and their influence on property investment decision making in an emerging market.