<p>Cognitive biases resulting from the representativeness heuristic in operations management: an experimental investigation</p>

Abstract

Purpose Operations managers are subjected to various cognitive biases, which may lead them to make less optimal decisions as suggested by the normative models. In their seminal work, Tversky and Kahneman introduced three heuristics based on which people make decisions: representativeness, availability, and anchoring. This paper aims to investigate the six cognitive biases resulting from the use of the representativeness heuristic, namely, insensitivity to prior probability of outcomes, insensitivity to sample size, misconception of chance, insensitivity to predictability, the illusion of validity, and misconception of regression. Specifically, the paper examines how cognitive reflection and training affect these six cognitive biases in the operations management context. Methods For each cognitive bias, a scenario related to operations management was developed. The participants of the experimental study are asked to select among three responses, where one response is correct and the other two are biased. A total of 315 students from the University of North Texas participated in this study and 302 valid responses were used in the analysis. Results The results show that in all six scenarios, >50% of the respondents make biased decisions. However, using simple training, the bias is significantly reduced. Regarding the relationship between cognitive biases and cognitive reflection, the results partially support the hypothesis that people with high cognitive reflection ability tend to make less biased decisions. Regarding the effect of training on making biased decisions, the results show that making people aware of the existence of cognitive biases helps them partially to avoid making biased decisions. Conclusion Overall, our study demonstrates the value of training in helping operations managers make less biased decisions. Our discussion section offers some related guidelines for creating a professional environment where the effect of the representativeness heuristic is minimized.

História das vacinas e história da astronomia

“…autores). Alkhars et al (2019) apresentam em seu estudo seis vieses inconscientes que fazem parte da nossa forma de compreender e agir na realidade. Nosso cérebro cria atalhos que possibilitam lidarmos com diferentes situações do nosso dia a dia.…”

“…Como lidar então com esses vieses? Alkhars et al (2019) trazem para discussão alguns estudos que propuseram três categorias de intervenções que podem ser realizadas: incentivos, otimização de arquitetura das escolhas e treinamento. Segundo os autores, algumas estratégias podem ter um efeito negativo nos nossos vieses inconscientes: "como abordagens e conjuntos de ações que visem reduzir a influência prejudicial dos vises, e como tal, aumentar a racionalidade e a eficácia das decisões" (Alkhars et al, 2019, p. 266, trad.…”

The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario

“…It is clear that representations influence analyst behaviors [55]. One of the goals of analytic provenance research is to prevent the effects of belief perseverance [12], base rate biases [40], misuse of representative heuristics [1], and resolving conflicting insights [35]. As an example, visualization techniques have tried to prevent selection bias by showing an overview of how the data has been filtered, and data type comparisons to help users recognize when they may be examining a subset of data too closely or with too much emphasis [8].…”

Relationship Between Stock Market Conditions and Investors Reactions: Evidence from Nigerian Stock Market

“…Representativeness bias is defined as mental shortcut that has the tendency to irrationally attribute one characteristic to imply another ( [10] as cited in [9]). AlKhars, Evangelopoulos, Pavur and Kulkarni stated that representativeness heuristic is also employed when subjects estimate the probability of a specific parameter of a sample [1].…”