Heuristic Bias Research Articles

Behavioral Biases and Judicial Decision-Making in Brazil.

We identify and present Brazil's most common behavioral and heuristic biases in judicial decision-making. Through bibliographic and specific cases, we notice the occurrence of the representativeness heuristic, availability heuristic, anchoring heuristic (anchoring effect), confirmation bias, and affect heuristic bias in Brazilian judicial decisions. We also present the current state of Brazilian legislation and its amendments that aim at impartiality in the production, the assessment of evidence, and the judge's conviction. Finally, we present the suggestions and initiatives that aim to mitigate biases and heuristics in judicial decision-making in Brazil, especially with awareness techniques, the replacement of judges by algorithms, and the review of judicial decisions by collegiate bodies.

Heuristic Bias and Herding Behavior for Predicting Investor Decision in Cryptocurrency Trading

Heuristic Bias and Herding Behavior for Predicting Investor Decision in Cryptocurrency Trading

How to Approach Patients with Acute Chest Pain.

Acute coronary syndrome (ACS) is associated with high mortality rates. Although the goal was to achieve a missed diagnosis rate of 1%, the actual data showed a rate of 2%. Chest pain diagnosis has remained unchanged over the years and is based on medical interviews and electrocardiograms (ECG), with biomarkers playing complementary roles. We aimed to summarize the key points of medical interviews, ECG clinics, use of biomarkers, and clinical scores, identify problems, and provide directions for future research. Medical interviews should focus on the character and location of chest pain (is it accompanied by radiating pain?) and the duration, induction, and ameliorating factors. An ECG should be recorded within 10 minutes of the presentation. The serial performance of an ECG is recommended for emergency department (ED) evaluation of suspected ACS. Characteristic ECG traces, such as Wellens syndrome and De Winter T-waves, should be understood. Therefore, troponin levels in all patients with suspected ischemic heart disease should be examined using a highly sensitive assay system. Depending on the ED facility, the patient should be risk stratified by serial measurements of cardiac troponin levels (re-testing at one hour would be preferred) to determine the appropriate time to perform an invasive strategy for a definitive diagnosis. The diagnostics should be based on Bayes' theorem; however, care should be taken to avoid the influence of heuristic bias.

How Investment Behaviour of Young Investors? A Case Study on The Indonesia Stock Exchange

This research aims to dig deeper into the investment behavior of young investors on the Indonesian Stock Exchange. This research was conducted in Bali Province, especially the Denpasar City area. The sample was determined using convenience sampling with a total sample of 180 young investors, namely the millennial generation and generation z in Denpasar City. Data was obtained directly from distributing questionnaires via Google Form. The data analysis technique used is SEM-PLS analysis. The research results show that, 1) herding behavior effect investment decision making, 2) heuristic bias has no effect on investment decision making, 3) anchoring bias effect investment decision making, 4) the level of overconfidence an investor has will improve the investment decision making process , 5) herding behavior does not have a significant effect on the level of overconfidence, 6) heuristic bias can increase the level of overconfidence, 7) anchoring bias can increase the level of overconfidence, 8) overconfidence cannot increase the effect of herding behavior to improve investment decisions, 9) overconfidence can increasing the effect of heuristic bias to improve investment decisions, and 10) overconfidence can increase the effect of anchoring bias to improve investment decisions. Future researchers can further examine overconfidence in mediating the effect of herding behaviours on investment decision making, and the effect of heuristic bias on investment decision making. Young investors in Denpasar City are advised to increase their knowledge and investment skills in the capital market to reduce the risk of bias in making investment decisions.

Risk Perception as a Predictor of Heuristic Biases: The Role of Sex and Age

Risk Perception as a Predictor of Heuristic Biases: The Role of Sex and Age

Exploring collaborative decision-making: A quasi-experimental study of human and Generative AI interaction

This paper explores the effects of integrating Generative Artificial Intelligence (GAI) into decision-making processes within organizations, employing a quasi-experimental pretest-posttest design. The study examines the synergistic interaction between Human Intelligence (HI) and GAI across four group decision-making scenarios within three global organizations renowned for their cutting-edge operational techniques. The research progresses through several phases: identifying research problems, collecting baseline data on decision-making, implementing AI interventions, and evaluating the outcomes post-intervention to identify shifts in performance. The results demonstrate that GAI effectively reduces human cognitive burdens and mitigates heuristic biases by offering data-driven support and predictive analytics, grounded in System 2 reasoning. This is particularly valuable in complex situations characterized by unfamiliarity and information overload, where intuitive, System 1 thinking is less effective. However, the study also uncovers challenges related to GAI integration, such as potential over-reliance on technology, intrinsic biases particularly ‘out-of-the-box’ thinking without contextual creativity. To address these issues, this paper proposes an innovative strategic framework for HI-GAI collaboration that emphasizes transparency, accountability, and inclusiveness.

Beyond market anomalies: How heuristics and perceived efficiency shape investor behavior in developing markets

Cognitive biases often influence investor behavior in developing capital markets, leading to market anomalies and affecting overall market efficiency. With the increasing integration of global financial markets and the growing participation of retail investors, understanding these biases is more critical than ever. While market anomalies have been extensively studied in developed markets, their influence in developing economies remains under-explored. This study aims to examine the impact of heuristic biases on investment decisions, focusing on Nepal’s stock market. Structural Equation Modeling is used to assess how perceived market efficiency mediates the relationship between heuristic biases and investor behavior. Data were collected from purposively selected 403 active individual investors in Nepal Stock Exchange (NEPSE). The findings reveal that representative and overconfidence biases significantly and positively influence investment decisions and market efficiency. Specifically, investors exhibiting these biases are more likely to make confident and bold investment choices, believing in their ability to predict market movements accurately. Furthermore, the study finds that perceived market efficiency mediates the relationship between anchoring and adjustment bias and investment decisions, suggesting that investors who rely heavily on initial information (anchors) adjust their decisions based on their perceptions of market efficiency. The results highlight the critical role of heuristic biases in shaping investor behavior and stress the importance of market efficiency in this process. The study emphasizes the need to enhance investor awareness of these biases and implement policies to improve market transparency and efficiency. Such measures are vital for mitigating risks and fostering a more robust and resilient financial market in developing economies like Nepal.

Heuristic biases influencing individual stock investment decisions: a hybrid fuzzy DELPHI-AHP-DEMATEL approach

PurposeStock investing choices of individual investors are predominantly influenced by heuristic biases, leading to sub-optimal choices. Accordingly, this study aims to identify, categorize, validate, prioritize, and find causality among the heuristic biases shaping stock investment decisions of individual investors.Design/methodology/approachThis research offers original contribution by employing a hybrid approach combining fuzzy DELPHI method (FDM), fuzzy analytical hierarchy process (FAHP), and fuzzy decision-making trial and evaluation laboratory (F-DEMATEL) techniques to validate, prioritize, and find causality among the heuristic biases.FindingsTwenty sub-heuristic biases were identified under five main heuristic bias categories. Out of which, 17 were validated using FDM. Further, availability and representativeness within main heuristic categories, and availability cascade and retrievability within sub-heuristic biases were prioritized using FAHP. Overconfidence and availability were identified as the causes among the five main biases by F-DEMATEL.Practical implicationsThis study offers the stock investors a deeper understanding of heuristic biases and empowers them to make rational investment decisions.Originality/valueThis paper is the inaugural effort to identify, categorize, validate, prioritize and examine the cause-and-effect relationship among the heuristic biases.

Financial Literacy's Moderating Effect on Project Selection with Heuristic-Driven Biases: SMEs’ Entrepreneurial Market Development in Pakistan

Certain biases on various project stages influence projects. Based on the moderating influence of financial literacy, the effect of heuristic-driven biases on project selection is evaluated in this research. The study aimed to evaluate how heuristics-driven biases affected the project management environment. A questionnaire with a five-point Likert scale is used to gather quantitative data. The study's target demographic comprises project managers and other senior employees at Small and Medium Enterprises (SMEs) with more than five years of experience. This study involved 200 participants, but only 151 responses were deemed authentic. Convenience sampling is the study's methodology. SPSS and Smart PLS3 are used for data analysis. The findings show that three behavioural biases, availability, representativeness, and under-confidence, have a negligible influence on project selection, but two behavioural biases—overconfidence and anchoring have a favourable impact. The research asserts that individuals do not succumb to these biases in many SMEs. The findings indicate that financial literacy does not moderate the association between heuristic-driven biases and project selection. Entrepreneurs, managers, investors, and businesses will gain immensely. Business owners should detect heuristic-driven biases to make better judgements. Controlling heuristic biases helps entrepreneurs make better decisions and implement productive business strategies. This research will help business owners manage their heuristic biases and grab business opportunities without making costly mistakes. This study offers a unique opportunity and the potential to improve the knowledge of entrepreneurial managers about the impact of heuristic-driven biases in the context of project management.

The Influence of Anchoring and Overconfidence on Investment Decision-Making in the Saudi Stock Market: A Moderated Mediation Model

Abstract This research sheds light on the relationships between heuristic biases and investment decisions as demonstrated by Saudi investors by establishing a mediating role for investor overconfidence in the relationship between anchoring heuristics and investment decision-making. The first to present evidence for this role, the study takes into account specific types of investment decisions – i.e. decisions to buy, sell, and engage in frequent trading. Based on a sample of 598 responses, empirical evidence is presented to show that anchoring directly increases the extent to which investment decisions are irrational and also does so indirectly through its impact on overconfidence. Given that this is the case, investors would be well-advised to critically assess the influence on their investment decision-making of overconfidence, which may, in turn, be rooted in deep-seated biases such as anchoring. Further, the potential moderating effect of trading frequency on overconfidence and investment decisions is examined and a moderated mediation model presented to elucidate the relationship between anchoring bias and investment decisions. The findings underscore the importance of understanding these biases and taking a scientific approach to trading, including by engaging in infrequent trading, to producing more rational investment decisions. Put differently, the study highlights the benefit of infrequent over frequent trading: Compared to those who trade less frequently, investors who trade more frequently are more susceptible to overconfidence and anchoring biases.

Corridor-Level Auto Occupancy in Mobility Monitoring Efforts: A Crash-Based Approach

Vehicle occupancy (the number of persons per vehicle) is fundamental to evaluations of transportation system performance focused on the movement of people rather than solely vehicles. Historically, obtaining detailed estimates of occupancy has required manual (expensive) field data collection. This paper reports on a crash-based approach for estimating occupancy. Because some characteristics, such as the presence of multiple passengers aged 16 to 21, may affect the likelihood of crash involvement, the study examined ways to control possible crash bias using two methods. The first—heuristic bias correction, which entails synthesizing missing samples—is useful for smaller jurisdictions where there is no ground truth value readily available but an area-wide occupancy measure is needed. The second—statistical bias correction, which uses manual observations for calibration followed by the creation of a model—is suitable for obtaining occupancy at the corridor level. The approach is demonstrated with 12 years of fall and spring crash data for the Hampton Roads region of southeastern Virginia, U.S., representing 1.7 million people and 50,000 crashes. Testing showed estimated occupancies were within roughly 0.05 of true occupancy when corridor-specific calibration was performed. Further, the larger number of samples used for an area-wide occupancy means that heuristic bias correction is not always necessary: for cities with more than 200 samples, the difference between uncorrected and corrected occupancies was 0.02. For states that report the number of occupants for crashes with and without injury, this approach holds promise for estimating vehicle occupancy for both corridors and regions.

Heuristic Biases and Investment Decision-making of Stock Market Investors: A Review Paper

This article builds a theoretical and research framework by identifying numerous behavioural biases in investing decision-making through a survey of research publications in the field of behavioural finance. It outlines some of the early research that helped establish behavioural finance as a field of study and shows how it has developed through time. The purpose of the article is to carry a systematic review of the literature on heuristic biases, namely overconfidence, representativeness, anchoring, availability and gambler’s fallacy influencing stock market investment decisions, identifying the major gaps in the existing studies on behavioural biases. It also aims to raise specific questions for future research. In the present study, systematic literature review (SLR) technique has been employed. By looking at the research’s year of publication, the journal of publishing, the country of study, the type of study and the statistical methods employed, one can determine the relevance of the study. On the basis of keyword searches for ‘behavioural finance’ in various published journals, conference proceedings, working papers and some other published publications, the research papers are analysed. For the purpose of creating this article, research papers from the earliest studies (1970) to the most recent publications (2022) have been gathered over a period of years. The study also highlights some of the most recent research carried out in this area. The current study is based on 131 selected research papers that were published in reputable journals between 1970 and 2022. A significant portion of the body of literature on behavioural biases highlights the dearth of this type of study in emerging nations; increase in the number of studies after behavioural finance was applied to investment decision-making, the predominance of empirical research; the widespread use of regression analysis; the prevalence of studies on overconfidence bias and the dearth of studies on availability bias and gamblers fallacy. To the best of the authors’ knowledge, the article is a pioneering work in the field of behavioural finance to employ SLR method for a considerable span of time (1970–2022) and to evaluate all the heuristic biases involved in investment decision-making. The present research study is an integration of SLR and bibliometric analysis. The publications’ patterns have been revealed, and the relationships between different types of literature have shed information on the direction that further research should go in.

Exploring the Mediating Role of Financial Risk Tolerance between Heuristic Biases and Working Women Investors’ Investment Decisions

The increasing financial independence of working women has contributed to their growing interest in investment to enhance their wealth. Working women investors are prone to psychological biases and have a conservative approach to risk, which can affect their investment decisions (ID). The study explores the role of financial risk tolerance (FRT) as a mediator in controlling the link between heuristic biases and working women investors’ investment decisions. Three heuristic biases are investigated: representativeness, availability, and anchoring. A structured questionnaire has been used to procure data from 211 working women investors trading in the Indian stock market. PLS-SEM was used to determine the association between the constructs. According to the findings, representativeness has a positive impact on the women investors’ investment decisions as well as their financial risk tolerance, anchoring has a detrimental impact on working women investors’ investment decisions and their risk tolerance capacity, and availability positively influences women investors' risk tolerance. The ability to tolerate financial risk has a positive impact on the investment decisions of women investors. The results of the mediate study show that the risk tolerance ability of women investors partially mediates the interaction between heuristic biases and their investment decisions. This paper will assist women investors to become more aware of these heuristic biases and lessen their negative effects on their investment choices. Its further results in more precise evaluations of risk tolerance and, ultimately, more successful investment planning.

The Impact of Heuristics Bias on Investment Decision: An Empirical Study

The purpose of the article is to investigate how heuristic bias affects investors’ investment decision. Understanding heuristic biases is essential for predicting and explaining human behaviour in various contexts, from consumer choices to financial decision-making and beyond. By identifying and categorizing different types of biases, researchers can discern patterns in decision-making that might otherwise remain obscure. The study takes into account four different types of heuristic bias, that is, availability bias, representativeness bias, overconfidence bias and adjustment and anchoring bias. It is very important to study heuristics bias because these biases can lead to deviations from the rational decision making. The knowledge of these biases can be used to develop strategies to improve decision making. With the aid of a questionnaire, the data is gathered. The method of convenient sampling is employed to choose 358 respondents. The data are analysed using Structural Equation Modelling and Descriptive Statistics. The study of the data reveals that the investors’ investment decisions are highly impacted by availability and adjustment and anchoring bias. Overconfidence and representativeness bias are insignificant.

Risk Perception as a Mediator Between Heuristic Biases and Investment Decision Making: Case Study of Pakistan Stock Exchange

Risk Perception as a Mediator Between Heuristic Biases and Investment Decision Making: Case Study of Pakistan Stock Exchange

Research on the Heuristic Bias in Behavioral Economics

Behavioral economics is a branch of economics. It studies people's decision-making patterns and behavioral principles when making decisions. Behavioral economics has penetrated into people's lives, and heuristics are everywhere. This paper shows several classifications and experimental investigations of heuristic bias in behavioral economics. It is widely believed that heuristic bias means that when people want to judge a complex, fuzzy, and uncertain event, they often take some shortcut in thinking due to the lack of effective methods, such as relying on past experience, analyzing and processing past experience, getting inspiration, and then making judgments using the inspiration. However, through literature reading and analysis, it can be found that people don't always make such choices when faced with problems, or they stay rational.

Sunk Cost Fallacy in Blind Box Consumption Among High School Students

Blind box consumption attracts young consumers with its novelty and mystery, and high school students are essential consumers in the blind box economy. With the increasing popularity of blind boxes among senior high school students, a rising number of high school students consume irrationally, and the sunk cost fallacy influences consumers’ decisions. The research entails a laboratory experiment, exploring the existence and extent of sunk cost fallacy in blind box purchase behavior of senior high school students in China, and uses SPSS to analyze data. Research results have shown that the majority of high school students are affected by sunk cost fallacy in blind box consumption. They are more heavily influenced by this heuristic bias when the sunk costs are high. Also, females are more likely to be affected by this bias than male students, as they consider more about the money and time they already spent.

Impact of Behavioural Biases on Investment Performance: A Comparative Analysis of Investors from India, USA and UK

This study presents evidence towards the existence of behavioural biases while analysing the impact of such biases on the investors’ investment performance in India, the USA, and the UK. Further, the study aims to investigate the moderating role of financial literacy on the relationship between behavioural biases and investment performance. It reveals that behavioural biases like affect heuristic, herding and status quo positively impact the investors’ investment performance amongst Indian investors whereas loss aversion, overconfidence, availability, and representativeness biases positively impact the investors’ investment performance amongst UK investors; and affect heuristic bias amongst USA investors. The findings divulge the negative impact of anchoring bias and mental accounting amongst Indian investors; availability bias, disposition effect, and overconfidence bias amongst USA investors; and affect heuristic and herding amongst UK investors. The study finds that a few of the behavioural biases impact investment performance positively, though less often. Hence investors should be cautious as these biases generally lead to irrational decision-making and might adversely influence the investors’ investment performance in the long run. The study further concludes that financial literacy significantly moderates the relationship between anchoring bias and individuals’ investment performance in India and affect heuristic in the USA. Interestingly, in the UK scenario, no significant moderating impact of financial literacy was found between any of the behavioral biases and investment performance.

Determinan Keuangan Keperilakuan Heuristic dan Herding Analysis terhadap Keputusan Investasi Berbasis Syariah

Increasing investor interest in investing will certainly increase transaction activity in capital market, so that it will have an impact on the smooth running of company's operations. Business activities that run well and safely will increase the rate of economic growth. Relatively affordable investment capital as launched by Indonesia Stock Exchange since 2015 by holding the "Yuk Nabung Saham" campaign aimed at inviting investors to invest by buying stocks or other instruments on a regular basis at Capital Market. Throughout 2021, the growth in the number of investors has increased very significantly, especially for novice investors from millennial generation to invest in several sharia instruments. This study aims to examine heuristic bias (representativeness, overconvidence) and herding financial behavior models of sharia-based investment decisions for millennials in the West Java region. Quantitative research with a causal design was applied using a purposive sampling technique by collecting a questionnaire of 180 respondents. Meanwhile, the data analysis method uses the PLS software application. The results showed that financial variable representativeness behavior had a significant negative effect on investment decisions of millennial generation in West Java, while financial variables of overconfidence and herding behavior had a significant positive effect on investment decisions of millennial generation in the West Java region.

Effects of behavioral biases on life insurance demand decisions in Uganda

PurposeThis paper examines the relationship between behavioral biases, and demand decisions for life insurance products in Uganda.Design/methodology/approachData 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.FindingsResults 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.Practical implicationsThese 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.Originality/valueThis 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.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0201