Adjustment Heuristics Research Articles

Are Auditors Biased? The Effect of Anchoring and Adjustment Heuristics on Auditors’ Judgment

Objective –The objective of this paper is to illustrate one of the crucial factors that affect auditors in making their judgment which can lead to systematic error. This paper provides background on how heuristics and biases can affect the judgment of auditors to increase the awareness of the anchoring and adjustment heuristic on audit judgment.Methodology –This research is a 2 x 2 experimental study which analyzes the employment of anchoring and adjusting bias of auditor in the process of making their audit judgment. This research employed three (3) experimental questions on 100 auditors in Surabaya, Indonesia, with experiences ranging from 0-8 years.Results –The result indicates that is evident that anchoring and adjustment heuristic exist and affect auditors’ judgment. The findings also indicates that experience influence auditors’ judgment whereas gender does not have such effect on auditors’ judgment. However, experience and gender can moderate the effect of anchoring and adjustment heuristic on auditors’ judgment.Research limitations/implications –The experimental questions used were simplified abstractions compared to the complex analytical reviews auditors typically encounter. Additionally, the sample size, consisting of 100 auditors, may limit the generalizability of the findings. The study exclusively focused on differences in auditor judgment influenced by anchoring and adjusting, without exploring potential contributions from other heuristic factors. Lastly, gender was categorized broadly as male and female, without further differentiation based on specific gender characteristics.Novelty/Originality –Its originality lies in adding moderation variable of gender and experience. While prior research has explored the impact of behavior on audit judgment to enhance decision-making in auditing, none have investigated anchoring and adjustment heuristics while considering the moderating factors of gender and experience.

Does the Investor’s Trading Experience Reduce Susceptibility to Heuristic-Driven Biases? The Moderating Role of Personality Traits

The aim of this study was to evaluate whether trading experience reduces exposure to heuristic-driven biases, namely availability bias, anchoring and adjustments bias, representativeness bias, and confirmation biases of individual investors operating in the Indian stock market, through the moderating role of the Big Five personality traits. To achieve these research objectives, primary data were collected through a structured questionnaire. The sample consisted of 408 individual investors trading on the Indian stock market, who were selected on a convenient basis. Confirmatory factor analysis and Cronbach’s alpha were used to measure the validity and reliability of the data. Further analysis was conducted using Pearson’s correlation and multiple regression. The results of this study prove that increased trading experience does not always reduce the susceptibility to heuristic biases. Increased trading experience reduces the susceptibility to availability, and anchoring and adjustment heuristics of individual investors operating on the Indian stock market. The present study has some relevant implications for investors, portfolio managers, financial advisors, and other interested persons in the stock market.

Buyer behaviour and price expectations: a spatial analysis of the Athens residential market

PurposeThis paper examines the price setting behaviour over time and space in the Athens residential market. In periods of house price inflation asking prices are often based upon the last observed highest selling price achieved for a similar property in the same micro-location. However, in a falling market, prices may be rigid downwards and less sensitive to the most recent transaction prices, weakening spatial effects. Furthermore, the paper considers whether future price expectations affect price setting behaviour.Design/methodology/approachThe paper employs a dataset of approximately 24,500 property values from 2007 until 2014 in Athens incorporating characteristics and locational variables. The authors begin by estimating a baseline hedonic price model using property characteristics, neighbourhood amenities and location effects. Following this, a spatio-temporal autoregressive (STAR) model is estimated. Running separate models, the authors account for spatial dependence from historic valuations, contemporaneous peer effects and expectations effects.FindingsThe initial STAR model shows significant spatial and temporal effects, the former remaining important in a falling market contrasting with previous literature findings. In the second STAR model, whilst past sales effects remain significant although smaller, contemporaneous and price expectations effects are also found to be significant, the latter capturing anchoring and slow adjustment heuristics in price setting behaviour.Research limitations/implicationsAs valuations used in the database are based upon comparable sales, then in the recessionary periods covered in the dataset, finding comparables may have become more difficult, and hence this, in turn, may have impacted on valuation accuracy.Practical implicationsIn addition to past effects, contemporaneous transactions and expected future values need to be taken in consideration in analysing spatial interactions in housing markets. These factors will influence housing markets in different cities and countries.Social implicationsThe information content of property valuations should more carefully consider the relative importance of different components of asking prices.Originality/valueThis is the first paper to use transactions data over a period of falling house prices in Athens and to consider current and future values in addition to past values in a spatio-temporal context.

Improved NSGA-II for energy-efficient distributed no-wait flow-shop with sequence-dependent setup time

This paper addresses a multi-objective energy-efficient scheduling problem of the distributed permutation flowshop with sequence-dependent setup time and no-wait constraints (EEDNWFSP), which have important practical applications. Two objectives minimization of both makespan and total energy consumption (TEC) are considered simultaneously. To address this problem, a new mixed-integer linear programming (MILP) model is formulated. Considering the issues faced in solving large-scale instances, an improved non-dominated sorting genetic algorithm (INSGA-II) is further proposed that uses two variants of the Nawaz-Enscore-Ham heuristic (NEH) to generate high-quality initial population. Moreover, two problem-specific speed adjustment heuristics are presented, which can enhance the qualities of the obtained non-dominated solutions. In addition, four local and two global search operators are designed to improve the exploration and exploitation abilities of the proposed algorithm. The effectiveness of the proposed algorithm was verified using extensive computational tests and comparisons. The experimental results show that the proposed INSGA-II is more effective compared to other efficient multi-objective algorithms.

Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics.

Bao et al. (2017) show that in laboratory subjects have problems with both trading an experimental asset and forecasting its price. In this paper I explore these experimental results, by investigating a model in which financial traders individually learn how to use forecasting and/or trading anchor and adjustment heuristics, by updating them with Genetic Algorithms. The model replicates main outcomes of the Bao et al. (2017) experiment, and shows that both forecasters and traders coordinate on asset price oscillations, albeit the trading markets generate larger cycles. Both forecasters and traders learn to chase market trends, and this behavior is reinforced when agents have to perform both tasks. As a result, the famous positive feedback between financial expectations and price trends becomes enhanced and markets generate prices that oscillate between 10% and 350% of the fundamental value.

Uma aplicação da heurística da ancoragem e ajustamento considerando diferentes estratos socioeconômicos no Município de Fortaleza-CE

A Economia Comportamental avança como alternativa à abordagem mainstream econômica, pressupondo que a racionalidade limitada dos agentes os conduz a regras simplificadoras na tomada de decisão, as heurísticas. O objetivo deste trabalho foi analisar os efeitos da heurística da ancoragem e ajustamento em estimativas numéricas de itens de consumo entre os estratos socioeconômicos de indivíduos fortalezenses. Para tanto, realizou-se uma pesquisa empírica com análise posterior nos moldes estatísticos propostos por Jacowitz e Kahneman. Os resultados indicaram uma grande influência do efeito ancoragem nas decisões desses agentes. O Estrato Baixo foi mais influenciado pelas âncoras que o Médio, que sofreu maior influência que o Alto. Concluiu-se que a estratificação socioeconômica afetou as estimativas numéricas dos indivíduos no ambiente de consumo.

Readmission Risk Assessment Technologies and the Anchoring and Adjustment Heuristic.

Approximately 23% of patients discharged from primary healthcare facilities are readmitted within 30days at an annual cost of roughly $42 billion. To remedy this problem, healthcare providers are attempting to deploy readmission risk estimation tools, but how they might be used in the traditional, human-expert-centered decision process is not well understood. One such tool estimates readmission risk based on 50 patient-specific factors. This paper reports on a study performed in collaboration with Order of St. Francis Healthcare to determine how healthcare workers' own risk estimates are influenced by the tool, specifically testing the hypothesis that they will first anchor towards tool results while making adjustments based on their expertise, and then make further adjustments when additional human expert opinions are presented. Task analysis was performed, fictional patient scenarios were developed, and a survey of 56 subjects in two stratified groups of case managers was conducted. Data from the control and experiment groups were analyzed using ANOVA/GLM and t-tests. Results indicate that the healthcare workers' risk estimates were influenced by the anchor provided by the tool, then adjusted based on their expertise. The workers further adjusted their estimates in response to new expert human inputs. Thus, a reliance on both the predictive model and human expertise was observed.

Employees’ judgment and decision making in the banking industry

PurposeHeuristics are used in the judgment and decision-making process of bank employees; however, discussions and research on the type or range of judgmental heuristics are very difficult to find throughout the world. In light of this, the purpose of this paper is to empirically analyze what types of heuristics are used in bank employees’ judgment and decision-making processes and the extent to which those types of heuristics prevent rational decision making due to the systematic biases they generate. In particular, this study aims to conduct empirical research based on various scenarios related to the banking industry.Design/methodology/approachTo examine the heuristics in decision-making circumstances and the level of subsequent biases, the present study narrowed the scope of research to the three main types of heuristics introduced by Tversky and Kahneman (1974), namely, representativeness heuristics, availability heuristics and anchoring and adjustment heuristics. To analyze the bank employees’ decision making, this study specifically investigated the level of decision-making heuristics and the level of bias by focusing on these three types of heuristics. This study targeted bank employees who either sell financial products or are engaged in customer service work at a real/physical bank.FindingsFor representativeness heuristics, this study found bank employees’ judgment of probability was influenced by biases, such as insensitivity to prior probability, insensitivity to sample size, misconception of chance and insensitivity to predictability. Regarding availability heuristics, it found that bank employees judge the probability of events based on the ease of recalling an event instead of the actual frequency of the event, and so they fall prey to systematic biases. Finally, regarding anchoring and adjustment heuristics, this study found that employees fall prey to judgment biases as they judge the probability of conjunctive events and disjunctive events based on anchoring and insufficient adjustment.Originality/valueAlthough people who are well-trained in statistics can avoid rudimentary errors, they fall prey to biased judgment at a similar level to those who are not properly trained in statistics when it comes to more complicated and ambiguous issues. It clearly indicates that it is risky to determine that financial experts would be more rational than the general public in making various judgments required in the policy-making process. To conclude, it is imperative to recognize the existence of heuristics-based systematic biases in the judgment and decision-making process and, furthermore, to reinforce the education and training system to improve bank employees’ rational choice and judgment ability.

Uso de heurísticos y error diagnóstico en Atención Primaria: revisión panorámica

ObjectiveTo assess the use of representativeness, availability, overconfidence, anchoring and adjustment heuristics in clinical practice, specifically in Primary Care setting. DesignPanoramic review (scope review). Data sourcesOvidMedline, Scopus, PsycoINFO, Cochrane Library and PubMed databases. Each one of the selected studies was reviewed applying TIDIER criteria (Template for Description of the Intervention and Replication) to facilitate their understanding and replicability. Selection of studiesA total of 48 studies were selected that analyzed availability heuristics (26), anchoring and adjustment (9), overconfidence (9) and representativeness (8). ResultsFrom the 48 studies selected, 26 analyzed availability heuristics, 9 anchoring and adjustment, 9 overconfidence; and 8 representativeness. The study population included physicians (35.4%), patients (27%), trainees (20.8%), nurses (14.5%) and students (14.5%). The studies conducted in clinical practice setting were 17 (35.4%). In 33 of the 48 studies (68,7%) it was observed heuristic use in the population studied. Heuristics use on diagnostic process was found in 27 studies (54.1%); 5 of them (18%) were carried out in clinical practice setting. Of the 48 studies, 6 (12,5%) were performed in Primary Care, 3 of which studied diagnostic process: only one of them analyzed the use of heuristics in clinical practice setting, without demonstrating bias as consequence of the use of heuristic. ConclusionThe evidence about heuristic use in diagnostic process on clinical practice setting is limited, especially in Primary Care.

Energy-Efficient Dynamic Lightpath Adjustment in a Decomposed AWGR-Based Passive WDM Fronthaul

To cope with the explosion of mobile traffic demand, cloud radio access networks (C-RAN) have been recently proposed. In C-RANs, the two main elements of traditional base stations (BSs), i.e., the baseband unit (BBU) and the remote radio head (RRH), are separated, and the BBU can be virtualized and located in a remote location together with BBUs of other BSs. High-bandwidth digitized baseband signals must be exchanged between BBUs and RRHs through a large-capacity fronthaul network. Wavelength division multiplexing (WDM) technology is an efficient solution to provide sufficient fronthaul bandwidth with a large number of optical transceivers. With the fixed connections between BBUs and RRHs in the traditional C-RAN, the utilization of optical transceivers as well as BBUs is inefficient. In this paper, we propose a decomposed arrayed waveguide grating router (AWGR)-enabled passive WDM fronthaul, and we formulate the minimal energy consumption problem as integer linear programming, with the objective of minimizing the energy consumption caused by optical transceivers and BBUs, etc. We also design two dynamic lightpath adjustment heuristics by light-path reconfiguration to improve energy efficiency. In addition, we take AWGR decomposition into consideration to reduce the tuning range of tunable transceivers and free spectrum range of AWGR, hence lowering the deployment cost of transport network components. Numerical evaluation shows that our proposed schemes achieve significant energy savings compared to fixed lightpath allocation.

Anchoring-Adjusted Capital Asset Pricing Model

ABSTRACTWhat happens when the capital asset pricing model is adjusted for the anchoring and adjustment heuristic of Tversky and Kahneman [1974]? The surprising finding is that adjusting the capital asset pricing model for anchoring provides a plausible unified framework for understanding almost all of the key asset pricing anomalies. The anomalies captured in the theoretical framework include the well-known size and value effects, high alpha of low beta stocks, accruals, low volatility anomaly, momentum effect, stock splits, and reverse stock splits. The market equity premium is also larger with anchoring. This suggests that the anchoring-adjusted capital asset pricing model may provide the needed unifying structure to behavioral finance.

English

This article discusses the decision-making process of Wine Producers Association of Altos Montes, at Serra Gaucha/Rio Grande do Sul/Brazil (APROMONTES) winegrowers and winemakers, in their process of adopting innovations to increase their competitiveness. To do that, we used the Prospect Theory. Data collection was conducted through interviews with 12 wineries, 25 winegrowers of APROMONTES wineries, and, as witnesses, seven winegrowers, members of the Rural Labor Union (STR), from Flores da Cunha, Rio Grande do Sul/Brazil. The results point to the fact that both the wineries and winegrowers support their decisions on heuristics of judgment, and, wine producers use mainly the affect, representative, anchoring and adjustment heuristics, while the wineries used representative and affect heuristics. In this perspective, we identified winegrowers as affective decision whose decisions are based primarily on emotional aspects. On the other hand, the wine makers as copier decision whose decisions are supported primarily by observing the decisions of other wine producers: The practice of overflow. Key words: Decisions, judgment heuristics, wine production sector.

Investigating the Decision Heuristics of Candidate Teachers Who are Different in Their Responsibility Controls

In this study, decision heuristics used by individuals with different responsibility controls were investigated. In the research, 370 final grade university students studying at Erzincan University Faculty of Education were included. In order to collect data, Internally Controlled Responsibility-Externally Controlled Responsibility Scale of Ozen and Gulacti (2011), and Decision Heuristics Scale developed by Ozen (2015) were used. Obtained data were investigated benefiting from Pearson Product-Moment Correlation and t-test. As result of the analyses, it was determined that the students generally had internally controlled responsibility, and they mostly used representative heuristic. When the correlation of decision heuristics with Internally Controlled Responsibility-Externally Controlled Responsibility was investigated, a low level negative relationship was found between representative heuristic and Internally Controlled Responsibility-Externally Controlled Responsibility. A low level positive relationship was found between availability and adjustment heuristics and Internally Controlled Responsibility-Externally Controlled Responsibility. In the research, moreover, it was also determined when the students who had internally controlled responsibility were compared with the ones who had externally controlled responsibility that the students with internally controlled responsibility significantly used more logical representative heuristic and less availability heuristic and anchoring heuristic.

Effect of Principal Heuristics on Accuracy of Property Valuation in Nigeria

Valuation inaccuracy has been attributed amongst others to behavioural issues such as the usage of Anchoring and Adjustment Heuristics. There is however a dearth in the research of the other principal heuristics namely availability, representative and positivity. This research is hereby aimed at discovering the effects of these heuristics on the accuracy of property valuation. To accomplish this, the study undertook a cross-sectional questionnaire survey of 159 of the 270 Head Offices of Estate Surveying and Valuation firms in Lagos Metropolis, while 29 and 30 questionnaires were distributed to the Head Offices of the entire Estate Surveying and Valuation Firms in Abuja and Port Harcourt respectively. For ease of coverage, Lagos Metropolis was stratified into six zones; thereafter respondents were selected randomly. The respondents were required to carry out simulated valuations using each of the four types of heuristics and also with supplied current market data. The T-test at the 95 per cent confidence interval was employed to test for inaccuracy in heuristically determined values relative to the sale values (values of the ‘control’ properties). The result reveals that heuristic-determined values, particularly that of representative, are not as accurate as those derived from supplied current market data. The authors recommended more focus on research of representative heuristics while consistent usage of heuristics should be dissuaded, to prevent loss of clients’ confidence in valuation reports.

Multicast with cooperative gateways in multi-channel wireless mesh networks

Wireless mesh networks (WMNs) are emerging as a promising solution for pervasive and cost-effective broadband connections. In this paper, we target high-throughput multicast that combats the interference and bandwidth limitation of wireless channels, which are particularly severe with wireless meshes. We suggest that they can be addressed by introducing multiple cooperative mesh gateways and exploiting the diversity of wireless channels. We present a cross-layer design that jointly selects appropriate channels for each mesh node to use at judiciously tuned power, and computes the optimal multicast flows from multiple cooperative gateways. We show that this design can be iteratively optimized through Lagrange relaxation and primal–dual decomposition. A progressive channel assignment and power level adjustment heuristic is introduced in the MAC/PHY layer, together with a smart link capacity allocation for cooperative gateways in the network layer. Through extensive simulations, we demonstrate the effectiveness of the proposed solution framework and the sub-problem heuristics. In particular, a throughput improvement of up to 100% is observed compared to straightforward approaches of utilizing multiple wireless channels for multicast routing.

Electrophysiological correlates of adjustment process in anchoring effects

Anchoring is a judgmental bias that final judgments are assimilated toward the starting point of the judge's deliberations. The anchoring-and-adjustment heuristic holds that anchoring bias is caused by insufficient adjustment. With the manipulation of some subjective factors, previous research found that anchoring is an effortful process. However, there is little evidence supporting that the effortful process is an adjustment process. In the present work, number accuracy was introduced as an objective factor which involves in an adjustment process. An event-related brain potential (ERP) experiment on young normal subjects examined the impact of number accuracy on anchoring processes responding to anchors which were generated by subjects themselves. A dot-image paradigm was firstly employed to explore anchoring effects. Behavioral results found less accurate anchors which determined a coarser mental scale diminished the anchoring biases responding to self-generated anchors. A positive deflection at 250–800 ms after target onset can be taken as a direct electrophysiological evidence of the adjustment process, whose amplitude was more positive on more accurate anchors condition. The present results further support that people adjust upwards or downwards on a mental scale from the self-generated anchor, which is consistent with the adjustment heuristics.

Cognitive Biases in Playing the Lottery: Estimating the Odds and Choosing the Numbers

Three experiments were conducted to examine the operation of the representativeness and anchoring and adjustment heuristics in lottery play. Subjects in Experiments 1 and 2 indicated their chances of winning a lottery with an objective probability of 1 in 10. Consistent with the anchoring and adjustment heuristic, subjects (in both experiments) perceived their chances of winning to be greater when the lottery was based on a single event than when it was based on a disjunctive event. Subjects in these two experiments also selected numbers to play in a pick‐3 (Experiment 1) or pick‐4 (Experiment 2) lottery. Consistent with the representativeness heuristic, subjects in Experiment 2 demonstrated a preference for numbers without repeating digits. This also occurred in Experiment 3 wherein the numbers actually played in the Indiana daily Pick‐3 lottery were examined.

A Lagrangian Relaxation Heuristic for Capacitated Facility Location with Single-Source Constraints

Facility location models are applicable to problems in many diverse areas, such as distribution systems and communication networks. In capacitated facility location problems, a number of facilities with given capacities must be chosen from among a set of possible facility locations and then customers assigned to them. We describe a Lagrangian relaxation heuristic algorithm for capacitated problems in which each customer is served by a single facility. By relaxing the capacity constraints, the uncapacitated facility location problem is obtained as a subproblem and solved by the well-known dual ascent algorithm. The Lagrangian relaxations are complemented by an add heuristic, which is used to obtain an initial feasible solution. Further, a final adjustment heuristic is used to attempt to improve the best solution generated by the relaxations. Computational results are reported on examples generated from the Kuehn and Hamburger test problems.

A Cost Adjustment Heuristic for Dynamic Lot-Sizing with Uncertain Demand Timing

We define a new heuristic, based on the adjustment of set-up costs, for the dynamic lot-sizing problem when demand timing is uncertain. Using a range of simulated problems, we compare the performance of this cost adjustment heuristic with that of a safety lead time heuristic, Zangwill's deterministic algorithm, which ignores uncertainty, and the optimal solution. Results show that the safety lead time heuristic works well for problems with high shortage costs and high probability of early demands, but poorly in other circumstances. The cost adjustment heuristic is quite robust, generally exceeds the performance of the safety lead time approach, and is relatively insensitive to variations in uncertainty.