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The purpose of this research is to analyze the influence of heuristics on Brazilian investors' behavior in the decision-making process.

The authors apply the partial least squares structural equation modeling methodology. This sample is composed of 220 investors.

The heuristics of overconfidence and anchoring positively influence investors' decision-making, while loss aversion negatively influences it. The herd effect exhibits no influence. The results also support the idea that decision-making positively influences investors' performance. Investors feel secure in their attitudes regarding financial decision-making, even if their decisions are not always rational as they are affected by biases.

This article explains the influence of heuristics on investors' decision-making and performance in the Brazilian context during the COVID-19 pandemic.

The advocates of behavioural finance have denounced the existing literature on investors’ rationality in the decision-making process and questioned the existence of efficient markets and rational investors. Although diversified research has been conducted in the area of behavioural finance, yet there is a need of further explorations into the field as the available knowledge base is confined to one or a few behavioural biases confronted by investors while making investment decisions. Hence, this study aims to develop a comprehensive, reliable and valid scale to measure the behavioural biases affecting investors’ decision-making process.

To develop a comprehensive, reliable and valid scale for measuring the behavioural biases affecting investors’ decision-making process, rigorous multi-stage scale development methodology has been followed. Stage one started with an extensive review of the literature followed by interviews from experienced stockbrokers to clarify construct and getting novel insights about dimensions of behavioural biases. In stage two, 52 items measuring the dimensions of behavioural biases were generated and got evaluated from panel of judges. Pilot testing was done in the third stage which gave a set of 39 items. Finally, in fourth stage, data were collected from 332 individual equity investors on a 7-point Likert scale using the snowball sampling technique.

The results of the study highlighted that behavioural biases is a multidimensional phenomenon that significantly affects investors’ decisions and has different dimensions, namely, Availability Bias, Representativeness Bias, Overconfidence Bias, Market Factors, Herding, Anchoring, Mental Accounting, Regret Aversion, Gamblers’ Fallacy and Loss Aversion. The present research has developed a comprehensive, reliable and valid scale for measuring behavioural biases affecting equity investors’ decision-making process.

Behavioural finance is an emerging area in the field of research particularly in the Indian context which needs further exploration. The present research concentrates on rendering an empirically tested scale to the researchers for measuring the behavioural biases and its impact on investor’s decision-making. Such an instrument can contribute to making progress in the area of behavioural finance and other research studies may also find it useful to achieve their goals.

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.

The biggest challenge in the Indian life insurance industry is mis-selling and unfair business practices. The purpose of this paper is to explore the effect of relational selling behaviour on investor decision making in life insurance market in India. This study also aims to elucidate the mediating role of trust in predicting the purchase of life insurance policies by investors.

A cross-sectional survey was carried out to collect quantitative data using a validated structured questionnaire. A total of 813 policyholders of life insurance companies operating in Karnataka, South India, were chosen. The data were analysed using the partial least square method of structural equation modeling.

The process of investors’ life insurance buying decision is directly influenced by interaction intensity, co-operative intentions of agents, sharing of overt and covert policy information, and indirectly through the partial mediation of trust. Also, trust fully mediates the effect of agent disclosure and personal rapport on decision making by investors. The importance‒performance map analysis highlights the pivotal role of overt policy information in investors’ decision making.

The financial mis-selling in India can be curtailed significantly if the insurance companies insist on responsible and relational selling by their sales agents. The companies would also strategically gain by investing in trust-building programs that enhance quality interactions and honest disclosure of overt and covert policy information, unpretentious intention to co-operate in the policy selection, and emphasize emotional connection and personal rapport with customers. These genuine actions and behavioural manifestations would certainly facilitate appropriate decision making by the investors.

There is a paucity of research in India which explicates the role of relational selling behaviour in insurers’ decision making. As such, this article expands the scope of relational marketing research in insurance by assessing the relational determinants of investor decisions as well as the role of trust as the mediator in influencing insurance decision making.

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 purpose of this paper is to understand both the facts and the values associated with the breadth of issues, and the principles related to sustainable real estate for institutional investors. Sustainable real estate is a growing sector within the commercial real estate industry, and yet, the decision-making practices of institutional investors related to sustainability are still not well understood. In an effort to fill that gap, this research investigates the post-global financial crisis (GFC) motivations driving the implementation of sustainability initiatives, the implementation strategies used, and the predominant eco-indicators and measures used by institutional investors.

This paper presents the results of a three-round modified Delphi study conducted in the USA in 2011-2012 investigating the nature of performance measurements and reporting requirements in sustainable commercial real estate and their impact on the real estate decision-making process used by institutional investors. Two rounds of in-depth interviews were conducted with 14 expert panelists. An e-questionnaire was used in the third round to verify qualitative findings.

The key industry drivers and performance indicators influencing institutional investor decision making were associated with risk management of assets and whether initiatives can improve competitive market advantage. Industry leaders advocate for simple key performance indicators, which is in contrast to the literature which argues for the need to adopt common criteria and metrics. Key barriers to the adoption of sustainability initiatives are discussed and a decision framework is presented.

This research aims to help industry partners understand the drivers motivating institutional investors to uptake sustainability initiatives with the aim of improving decision making, assessment, and management of sustainable commercial office buildings.

Building on the four generations of the sustainability framework presented by Simons et al. (2001), this research argues that the US real estate market has yet again adjusted its relationship with sustainability and revises their framework to include a new, post-GFC generation for decision making, assessment, and management of sustainable real estate.

The purpose of this paper is to investigate the relationship between rational decision-making and behavioural biases among individual investors in India, as well as to examine the influence of demographic variables on rational decision-making process and how those differences manifest themselves in the form of behavioural biases.

Using a structured questionnaire, a total of 386 valid responses have been collected from May to October 2015. Statistical techniques like t-test, analysis of variance (ANOVA) and Fisher’s least significant difference (LSD) test have been used in this study. Structural equation modelling (SEM) has been used to analyse the relationship between rational decision-making and behavioural biases.

The findings show that the structural path model closely fits the sample data, indicating investors follow a rational decision-making process while investing. However, behavioural biases also arise in different stages of the decision-making process. It further explores that gender and income have a significant difference with respect to rational decision-making process. Male investors are more prone to overconfidence and herding bias in India.

The findings of the study have significant implication for the individual investors. It is recommended that if individuals are aware about the biases, they may become alert before taking irrational investment decisions.

To best of the authors’ knowledge, the present study is a first of its kind to investigate the relationship between rational decision-making and behavioural biases among individual investors in India.

The purpose of this paper is to determine whether individual investor sentiment and its factors influence investment decision-making behavior in the Indian stock market. The study contributes to the novel conceptual framework that integrates the impact of investor sentiment and outlines the role of its factors (herding, media factor, advocate recommendation and social interaction) during the investment decision-making process.

In this paper, data were collected using a structured questionnaire survey from Indian individual investors. It uses self-reported sources of information collected via a survey of individual investors and estimated the linkage via path modeling. The collected data were analyzed using partial least square structural equation modeling to examine the relationship between the construct, namely, herding, media, advocate recommendation and social interaction with investor sentiment and investment decision-making.

The study shows that herding, media factor, advocate recommendation and social interaction significantly and positively influence the investor sentiment. Among all the factors, social interaction has the lowest influence on investor sentiment. The study also reveals that investor sentiment has a positive impact on investment decision-making.

The study provides valuable insights for the individual investors, financial advisors, policymakers and other stakeholders. Knowledge of behavioral finance would enhance the decision-making capabilities of individual investors in the stock market. Thus, the study calls for the need to increase awareness among Indian investors about behavioral finance and its usefulness in investment decision-making. The paper also sheds light upon the influence of investor sentiment and its antecedents on investment decision-making. The study confirms that the investor relies on their sentiment while making investment decisions. Hence, the stakeholders in the stock market should focus on investor sentiment and other psychological aspects of individual investors as well.

There are very few studies that deal with the behavioral aspects of individual investors in an emerging market context. The study mainly focuses on the antecedent of investor sentiment and its influence on investment decision-making in the Indian stock market. To the best of authors’ knowledge, the present study unique nature that examines the impact of the antecedent of investor sentiment which was not explored in the Indian context and investment decision-making of individual investors.

Innovation is the way of life and we see various innovative techniques and methods being introduced in our daily life. This study aims to focus on digital innovation in the wealth management domain. This study examines the effect of usage of robo-advisory services in investment decision-making and behavioural biases, i.e. overconfidence and loss aversion. Such studies are more pronounced in developed countries and little has been studied about investor behaviour in association with advisory services in developing countries such as India.

Overconfidence and loss-aversion biases, investment decision-making and advisory services questions are measured using a five-point Likert scale. The number of respondents was 172 investors. A purposive sampling is used for gathering responses from investors. Structural equation modeling model was run using AMOS 22 version software package.

The authors found that behavioural biases positively and significantly influence the irrationalities of investment decision-making. The findings of this study also provide empirical evidence that the usage of robo-advisory services, by individual investors, is still incapable of mitigating behavioural biases, such as overconfidence bias and loss-aversion bias.

The sample size of this study could be a limiting factor. This study is limited only to two biases, while other behavioural biases affect the investment decision-making of the investors, which can be considered for future research along with the impact of robo-advisory services in different socio-cultural backgrounds.

This study will assist fintech start-ups, banks, architecture of robo advisors, product owners and wealth management service providers improvise their products, platforms and offerings of these automated advisory services. This could help individual investors to mitigate their behavioural biases in investment decision-making.

This study is useful to society as the awareness of robo-advisory services is very less, at present, and there is a need to increase the usage of these services to extend the benefit of this to the lower stratum of society. These services would be useful to all investors who find it difficult to afford financial advisors and help them mitigate their behavioural biases for investment decision-making.

This study is the first of its type that establishes the linkage between behavioural biases, digital innovation in fintech, i.e. robo-advisory services and individual investor’s investment decision-making in individual investor of the Indian stock market.

Current research in the field of behavioural finance has attempted to discover behavioural biases and their characteristics in individual investors’ irrational decision-making. This study aims to find out how biases in information based on knowledge affect decisions about investments.

In step one, through existing research and consultation with specialists, 13 relevant items covering major aspects of bias were determined. In the second step, multiple linear regression and artificial neural network were used to analyse the data of 337 retail investors.

The investment choice was heavily impacted by regret aversion, followed by loss aversion, overconfidence and the Barnum effect. It was observed that the Barnum effect has a statistically significant negative link with investing choices. The research also found that investors’ fear of making mistakes and their tendency to be too sure of themselves were the most significant factors in their decisions about where to put their money.

This research contributes to the expansion of the knowledge base in behavioural finance theory by highlighting the significance of cognitive psychological traits in how leading investors end up making irrational decisions. Portfolio managers, financial institutions and investors in developing markets may all significantly benefit from the information offered.

This research is a one-of-a-kind study, as it analyses the emotional biases along with the cognitive biases of investor decision-making. Investor decisions generally consider the shadowy side of knowledge management.