Heuristic Bias Research Articles

Heuristic of Representativeness and Anchoring-Adjustment in Budgeting

This study aims to examine and analyze the inaccuracy in determining the Local Revenue (PAD) budget estimation in the public sector for the upcoming period. When the budget compilers faced complex problems in arrangement the estimates of PAD, they will perform a decisions unit’s budget estimates quickly and efficiently, just depend on the analyze information of PAD past and present. The method of analyzing this experimental research uses Two Way Analysis of Variance (ANOVA), one of the multivariate analysis techniques which serve to distinguish the average of the two groups of data by comparing the variance. The results of this study indicate that representativeness heuristic approach affects the bias that occurs or inaccuracy of PAD budget estimates, while anchoring-adjustment heuristic does not affect the bias or inaccuracy of the PAD budget estimates. Based on this, the budget compilers of PAD used a representativeness heuristic approach (existence of overreaction behavior) in predicting the amount of the PAD budget for the upcoming period. The heuristic approach is useful in determining the predictions of PAD budget in the public sector if the budget compilers have the knowledge competencies and adequate experiences in order to reduce the heuristic bias that occurs.

Impact of Heuristic Biases on Investment Decision Locus of Control Playing a Moderating Role

Purpose: The main purpose of this paper is to examine the relationship between heuristic biases and investment decision. The authors focus on the key variable that was moderating role of locus of control . Design/Methodology/Approach: The data collect for this research paper is used structure questioner and filled 250 questioner from different types of people i.e. (educated, employees, unemployed, social, etc ) Findings: This paper provide that heuristic biases such as mantel accounting and price anchoring paly importance role in investor decision making. That means this mantel accounting and price anchoring biases effect the individual investor investment decision making process Research Limitation/Implication: The primary limitation of the paper is tiny size of the sample and large sample would have more trustworthy result and could have empowered a more extensive scope of investigation. Practical Implication: This paper encourage the manager to do such types of activities in business environment with the help of which individual as will as household can avoid these biases and do best investment decision. Originality/Value: The current study is first of its kind, focusing on the link between heuristic biases and investment decision locus of control playing a moderating role in the paper.

The Knobe Effect with Probable Outcomes and Availability Heuristic Triggers

This paper contributes to the existing philosophical literature on the Knobe Effect (KE) in two main ways: first, this paper disconfirms the KE by showing that the latter does not hold in contexts with probable outcomes; second, this paper shows that KE is strongly sensitive to the availability heuristic bias. In particular, this paper presents two main findings from three empirical tests carried out between 2016 and 2018: the first finding concerns the fact that if the issuer of a decision with consequences on third parties is unlikely to be perceived as unfriendly, then KE is reduced or absent; the second finding regards instead the fact that if an action has two possible outcomes (one likely to obtain with strong intensity and one likely to obtain with less intensity), then KE does not obtain for decisions whose side-effects have limited consequences on third parties.

Insider trading, representativeness heuristic insider, and market regulation

This article develops an insider-trading model with the presence of rational and representativeness heuristic insiders in the market with and without market regulation. We find that, regardless of whether the market regulation exist or not, the heuristic insider trades more aggressively on his information, than the rational insider does, with the result that there is a higher probability for him to earn greater profits. Further, a higher heuristic bias of the heuristic insider leads to lower expected profit for rational insider, but higher expected profits for the heuristic insider. Moreover, the heuristic insider and rational insider prefer to trade less aggressively on their information when there is market regulation, but, they are likely to get more ex-ante expected profit. Furthermore, we find that the price efficiency and market stability may all be sacrificed if insider trading is regulated.

Overqualified: How Does a Recruiter’s Perception Affect a Hiring Decision of Job Applicants?

This paper contributes to growing overqualification literature by exploring a recruiter evaluation of overqualified job applicants at the initial stage of a selection process. Drawing from information processing and social cognition literature, the paper argues that in the condition of ambiguity about an overqualified job applicant’s motivation in applying for a prospective job, a recruiter is more likely to fall on his or her heuristic bias in decision making. As such, a recruiter inference about an overqualified job applicant mobility and occupational identity is likely to play a major role in whether a recruiter processes an overqualified job applicant to the next stage of a selection process. The paper argues that limited information from bio data of an overqualified applicant is likely to be instrumental in a recruiter drawing inference about mobility and occupational identity of an overqualified job applicant.

The Impact of Perceived Threat of Infectious Disease on the Framing Effect

The framing effect is a heuristic bias, where the way a question is presented affects people’s response to it. This study (n = 924) investigated the influence of the behavioral immune system on the framing effect. We tested the changes in people’s responses towards two frames (i.e., losses and gains) when presented with a threat of disease and as a function of their perceived vulnerability to disease (PVD) level. After being randomly assigned to one of three priming conditions—disease threat, negative threat, and no-threat—participants were presented with one of the two-frame versions (gain or loss) of the damaged painting problem where they chose between a safe and a risky option. Finally, participants responded to the PVD scale and to demographic questions. Results revealed that when people were primed with disease threat, those with lower PVD had a higher likelihood to take risks in the gain frame and a lower likelihood in the loss frame. This effect was not observed when participants were primed with negative threat or no-threat, nor for those participants with high levels of PVD. This finding suggests a specific effect of disease threat on the framing effect.

Heuristic biases in investment decision-making and perceived market efficiency

PurposeThis paper aims to clarify the mechanism by which heuristics influences the investment decisions of individual investors, actively trading on the Pakistan Stock Exchange (PSX), and the perceived efficiency of the market. Most studies focus on well-developed financial markets and very little is known about investors’ behaviour in less developed financial markets or emerging markets. The present study contributes to filling this gap in the literature.Design/methodology/approachInvestors’ heuristic biases have been measured using a questionnaire, containing numerous items, including indicators of speculators, investment decisions and perceived market efficiency variables. The sample consists of 143 investors trading on the PSX. A convenient, purposively sampling technique was used for data collection. To examine the relationship between heuristic biases, investment decisions and perceived market efficiency, hypotheses were tested by using correlation and regression analysis.FindingsThe paper provides empirical insights into the relationship of heuristic biases, investment decisions and perceived market efficiency. The results suggest that heuristic biases (overconfidence, representativeness, availability and anchoring) have a markedly negative impact on investment decisions made by individual investors actively trading on the PSX and on perceived market efficiency.Research limitations/implicationsThe primary limitation of the empirical review is the tiny size of the sample. A larger sample would have given more trustworthy results and could have empowered a more extensive scope of investigation.Practical implicationsThe paper encourages investors to avoid relying on heuristics or their feelings when making investments. It provides awareness and understanding of heuristic biases in investment management, 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 expensive errors, which occur due to heuristic biases. They can improve their performance by recognizing their biases and errors of judgment, to which we are all prone, resulting in a more efficient market. So, it is necessary to focus on a specific investment strategy to control “mental mistakes” by investors, due to heuristic biases.Originality/valueThe current study is the first of its kind, focusing on the link between heuristics, individual investment decisions and perceived market efficiency within the specific context of Pakistan.

Opioïdes et risques addictifs, comment les prévenir ? Questions posées aux Dr S. Robinet, Dr C. Lucas, Dr J. Bernard et Pr N. Franchitto

Decision trees are highly favoured classifiers because of the resemblance of their understandable nature to the branched process of human thinking. But the comprehensible rationality of these trees can be severely affected by the bias in the selection of the split attribute, and the traditional heuristic methods appear to be multi-value. The present paper proposes an attribute selection method for nodes on the basis of the concept model of decision trees in purpose of avoiding the heuristic bias of attribute measurement and improving the performance of decision trees. The probabilistic statistics form is used to define and express the concept model extracted from the given data of things and created by associated certainty of classes distribution and branches distribution to fulfil certainty description of tree. And class constraint uncertainty (CCE) is used as a heuristic measure in the induction of tree to select the split attribute while the processing of the missing branch as an auxiliary leaf measure to construct a novel algorithm of decision tree learning. Experimental findings show that CCE is effective as a heuristic measure to avoid the bias in the selection of the multi-value attribute to all datasets and improve the performance and stability of the decision trees.

Anchoring and Overconfidence: The Influence of Culture and Cognitive Abilities

Abstract Anchoring and overconfidence are some of the best-known biases in psychology and behavioral finance literature. While a number of studies have investigated the evidence of these biases and explored the motives and human factors that contribute to the one’s susceptibility to the effects, little is known about the cultural factors behind these heuristic biases. This paper aims to fill the research gap and shows the differences in proneness to the anchoring effect and overconfidence in two samples of students from Poland and India. The purpose of the study is twofold: to analyze susceptibility to behavioral effects relative to cultural background; and to consider the subjects’ cognitive abilities as a potential factor in their exposure to behavioral biases and confirm that subjects with higher cognitive skills, measured by the cognitive reflection test (CRT) display less susceptibility to the above heuristic biases.

Quantifying Heuristic Bias: Anchoring, Availability, and Representativeness

ABSTRACTConstruct: Authors examined whether a new vignette-based instrument could isolate and quantify heuristic bias. Background: Heuristics are cognitive shortcuts that may introduce bias and contribute to error. There is no standardized instrument available to quantify heuristic bias in clinical decision making, limiting future study of educational interventions designed to improve calibration of medical decisions. This study presents validity data to support a vignette-based instrument quantifying bias due to the anchoring, availability, and representativeness heuristics. Approach: Participants completed questionnaires requiring assignment of probabilities to potential outcomes of medical and nonmedical scenarios. The instrument randomly presented scenarios in one of two versions: Version A, encouraging heuristic bias, and Version B, worded neutrally. The primary outcome was the difference in probability judgments for Version A versus Version B scenario options. Results: Of 167 participants recruited, 139 enrolled. Participants assigned significantly higher mean probability values to Version A scenario options (M = 9.56, SD = 3.75) than Version B (M = 8.98, SD = 3.76), t(1801) = 3.27, p = .001. This result remained significant analyzing medical scenarios alone (Version A, M = 9.41, SD = 3.92; Version B, M = 8.86, SD = 4.09), t(1204) = 2.36, p = .02. Analyzing medical scenarios by heuristic revealed a significant difference between Version A and B for availability (Version A, M = 6.52, SD = 3.32; Version B, M = 5.52, SD = 3.05), t(404) = 3.04, p = .003, and representativeness (Version A, M = 11.45, SD = 3.12; Version B, M = 10.67, SD = 3.71), t(396) = 2.28, p = .02, but not anchoring. Stratifying by training level, students maintained a significant difference between Version A and B medical scenarios (Version A, M = 9.83, SD = 3.75; Version B, M = 9.00, SD = 3.98), t(465) = 2.29, p = .02, but not residents or attendings. Stratifying by heuristic and training level, availability maintained significance for students (Version A, M = 7.28, SD = 3.46; Version B, M = 5.82, SD = 3.22), t(153) = 2.67, p = .008, and residents (Version A, M = 7.19, SD = 3.24; Version B, M = 5.56, SD = 2.72), t(77) = 2.32, p = .02, but not attendings. Conclusions: Authors developed an instrument to isolate and quantify bias produced by the availability and representativeness heuristics, and illustrated the utility of their instrument by demonstrating decreased heuristic bias within medical contexts at higher training levels.

Observational Heuristics in a Group of High Level Paddle Sports Coaches

Observation of performance forms a critical part of the complex coaching process. A professional judgment and decision making (PJDM) framework enables optimum decisions to be made under time pressure and with limited information that derive from that observation. Observation and the associated decision making can be particularly affected by heuristic bias. We extend the work on PJDM via a greater focus on its relationship with observation within the coaching process. After revisiting PJDM and observation, we introduce and explore heuristics as a “tool” within the observation process. Specifically, we propose that observation is prone to heuristics built on a coach’s experience and understanding. We report on a small scale preliminary investigation with a group of high-level paddle sport coaches. We identify heuristics that both restrict and enhance the effectiveness of the observation in an effort to promote discussion and further research.

Heuristics and bias in rectal surgery.

Deciding to defunction after anterior resection can be difficult, requiring cognitive tools or heuristics. From our previous work, increasing age and risk-taking propensity were identified as heuristic biases for surgeons in Australia and New Zealand (CSSANZ), and inversely proportional to the likelihood of creating defunctioning stomas. We aimed to assess these factors for colorectal surgeons in the British Isles, and identify other potential biases. The Association of Coloproctology of Great Britain and Ireland (ACPGBI) was invited to complete an online survey. Questions included demographics, risk-taking propensity, sensitivity to professional criticism, self-perception of anastomotic leak rate and propensity for creating defunctioning stomas. Chi-squared testing was used to assess differences between ACPGBI and CSSANZ respondents. Multiple regression analysis identified independent surgeon predictors of stoma formation. One hundred fifty (19.2%) eligible members of the ACPGBI replied. Demographics between ACPGBI and CSSANZ groups were well-matched. Significantly more ACPGBI surgeons admitted to anastomotic leak in the last year (p<0.001). ACPGBI surgeon age over 50 (p=0.02), higher risk-taking propensity across several domains (p=0.044), self-belief in a lower-than-average anastomotic leak rate (p=0.02) and belief that the average risk of leak after anterior resection is 8% or lower (p=0.007) were all independent predictors of less frequent stoma formation. Sensitivity to criticism from colleagues was not a predictor of stoma formation. Unrecognised surgeon factors including age, everyday risk-taking, self-belief in surgical ability and lower probability bias of anastomotic leak appear to exert an effect on decision-making in rectal surgery.

Attribute selection for decision tree learning with class constraint

Decision trees are highly favoured classifiers because of the resemblance of their understandable nature to the branched process of human thinking. But the comprehensible rationality of these trees can be severely affected by the bias in the selection of the split attribute, and the traditional heuristic methods appear to be multi-value. The present paper proposes an attribute selection method for nodes on the basis of the concept model of decision trees in purpose of avoiding the heuristic bias of attribute measurement and improving the performance of decision trees. The probabilistic statistics form is used to define and express the concept model extracted from the given data of things and created by associated certainty of classes distribution and branches distribution to fulfil certainty description of tree. And class constraint uncertainty (CCE) is used as a heuristic measure in the induction of tree to select the split attribute while the processing of the missing branch as an auxiliary leaf measure to construct a novel algorithm of decision tree learning. Experimental findings show that CCE is effective as a heuristic measure to avoid the bias in the selection of the multi-value attribute to all datasets and improve the performance and stability of the decision trees.

Conflict and bias in heuristic judgment.

Conflict has been hypothesized to play a key role in recruiting deliberative processing in reasoning and judgment tasks. This claim suggests that changing the task so as to add incorrect heuristic responses that conflict with existing heuristic responses can make individuals less likely to respond heuristically and can increase response accuracy. We tested this prediction in experiments involving judgments of argument strength and word frequency, and found that participants are more likely to avoid heuristic bias and respond correctly in settings with 2 incorrect heuristic response options compared with similar settings with only 1 heuristic response option. Our results provide strong evidence for conflict as a mechanism influencing the interaction between heuristic and deliberative thought, and illustrate how accuracy can be increased through simple changes to the response sets offered to participants. (PsycINFO Database Record

Heuristic. Psychological Aspects of Decision-Making on Capital Market

Heuristics are efficient cognitive processes that ignore part of information. In classical view, heuristic decisions save effort, but imply greater errors then “rational” decisions, defined by logic and statistical model. It clearly emerges that in real life people do not always make rational decisions based on established preferences and complete information. In many ways their behavior thus contradicts the homo oeconomicus model. Much of the behaviour observed is caused through people trying to cope with the complexity of the world around them by approximating, because collating and evaluating all the factors of relevance to a decision overtaxes their mental processing capacity. These psychologically driven inadequacies also occur with investment decisions. Heuristics are simply a more effective way of evaluating choices in the rich and changing decision making environment investors must face. The aim of this paper is to review the impact of heuristics bias decision-making on capital market.

Heuristic. Psychological Aspects of Decision-Making on Capital Market - Literature Review

Purpose – the aim of this paper is to review the impact of heuristics bias decision-making on capital market. Heuristics are efficient cognitive processes that ignore part of information. In classical view, heuristic decisions save effort, but imply greater errors then “rational” decisions, defined by logic and statistical model. It clearly emerges that in real life people do not always make rational decisions based on established preferences and complete information. In many ways their behavior thus contradicts the homo oeconomicus model. These psychologically driven inadequacies also occur with investment decisions. Design/methodology/approach – literature review. Findings – much of the behaviour observed is caused through people trying to cope with the complexity of the world around them by approximating, because collating and evaluating all the factors of relevance to a decision overtaxes their mental processing capacity Originality/value – article can be base to formulating new concept of rationality or new concept of homo oeconomicus (Mikolajek-Gocejna, 2017).

Effect of Demographic Factors and Awareness on Investment Behaviour in Stock Market: Evidence from West Bengal

The objective of the study is to know the effect of two independent variables namely Demographic Factors and Awareness on the only dependent variable namely Investment Behaviour of individual investors of stock market. The study has been done analysing primary data that have been collected from 377 randomly selected individual investors of stock market from three districts of West Bengal namely Purulia, Bankura and Paschim Medinipur using a structured questionnaire. The major findings of descriptive statistics, Cronbach Alpha, Factor Analysis, Correlation Coefficient and Probit Regression Model using SPSS and Stata Softwares indicate that people of ages between 28 years to 37 years invest more in the stock market. Most of the investors in the stock market are educated and graduate in academic qualification. In occupational perspective most of the investors are businessperson. In case of annual income most are in the band of Rs. 100000 to Rs. 500000 and most of the individual investors are experienced in this field as they are making investment in stock market for more than five years and the objective of most of the investors is to make short term profit. The awareness levels of the individual investors are on moderate level and they rely more on financial awareness in comparison to social learning. Herding Bias of Investment Behaviour is not so strong in comparison to Heuristics Bias, Prospects Bias and Markets Bias of Investment Behaviour in stock market. The study finally concludes that there exists a significant effect of Demographic Factors and Awareness on Investment Behaviour of individual investors of stock market.

Loss Aversion Bias or Fear of Missing Out: A Behavioural Economics Analysis of Compensation in Investor–State Dispute Settlement

This article considers the application of the behavioural economics theory of loss aversion bias as an explanation for observed approaches to monetary compensation in Investor–State Dispute Settlement (ISDS). Beginning with a critique of the assessment that damages for breach of contract in the common law (both the reliance and expectation measures) embody the ethos of loss aversion bias, this article suggests that the dominant approach to compensation in ISDS is primarily forward-looking and profit-focused. Instances of loss-based compensation may be explained by rational means rather than through the heuristic of loss aversion bias. Compensation tied to loss may more accurately reflect full market value and often denote a lower quantum justified on the basis of lawfulness (as in expropriation). Most notably compensation based on actual losses serves the objective of certainty. The article concludes by suggesting that the dominant tendency of ISDS tribunals to award profit-oriented compensation may itself have a basis in a heuristic bias, namely the human tendency to seek to avoid missing out on future opportunities.

Podejmowanie decyzji a efekt języka obcego: potencjalny wpływ na wyniki badań uzyskiwane na platformach crowdsourcingowych

In this paper, issues connected with conducting research on crowdsourcing platforms which are specific types of research panels are described. The focus lays on advantages and disadvantages of mentioned platforms and revealing how to mitigate the impact of disadvantages on collected data. Moreover, the article depicts the influence of the foreign language effect (reduced presence of heuristic biases in the decision-making process when decision is made in the foreign language compared to the native language) on decision-making, which may be one of the threats connected with conducting experiments on crowdsourcing platforms. The last section is a description of author’s own study in domain of investment decisions. Results reveal that processing in a foreign language influences the decision. Namely, participants in a foreign language condition were not influenced by the status quo effect.

Unravelling the asymmetric volatility puzzle: A novel explanation of volatility through anchoring

This paper discusses a novel explanation for asymmetric volatility based on the anchoring behavioral pattern. Anchoring as a heuristic bias causes investors to focus on recent price changes and price levels, which leads to a belief in continuing trend and mean-reversion, respectively. The empirical results support our theoretical explanation through an analysis of large price fluctuations in the S&P 500 and the resulting effects on implied and realized volatility. These results indicate that asymmetry (a negative relationship) between shocks and volatility in the subsequent period indeed exist. Moreover, contrary to previous research, our empirical tests also suggest that implied volatility is not simply an upward biased predictor of future deviation compensating for the variance of the volatility but rather, due to investors’ systematic anchoring to losses and gains in their volatility forecasts, a co-integrated yet asymmetric over-/under-estimated financial instrument. We also provide results indicating that the medium-term implied volatility (measured by the VIX Index) is an unbiased though inefficient estimation of realized volatility, while in contrast short-term volatility (measured by the recently introduced VXST Index representing the 9-day implied volatility) is also unbiased and yet efficient.