Cognitive biases resulting from the representativeness heuristic in operations management: an experimental investigation

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This article investigates 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 authors examine how cognitive reflection and training affect these six cognitive biases in the operations management context.

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14 p.

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AlKhars, Mohammed; Evangelopoulos, Nicholas; Pavur, Robert J. & Kulkarni, Shailesh S. April 10, 2019.

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This article is part of the collection entitled: UNT Scholarly Works and was provided by the UNT College of Business to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 52 times, with 11 in the last month. More information about this article can be viewed below.

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This article investigates 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 authors examine how cognitive reflection and training affect these six cognitive biases in the operations management context.

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14 p.

Notes

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.

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  • Psychology Research and Behavior Management, 12, Dove Medical Press Ltd, April 2019

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  • Publication Title: Psychology Research and Behavior Management
  • Volume: 12
  • Page Start: 263
  • Page End: 276
  • Peer Reviewed: Yes

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UNT Scholarly Works

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  • April 10, 2019

Added to The UNT Digital Library

  • March 3, 2020, 10:24 p.m.

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  • March 25, 2020, 4:39 p.m.

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AlKhars, Mohammed; Evangelopoulos, Nicholas; Pavur, Robert J. & Kulkarni, Shailesh S. Cognitive biases resulting from the representativeness heuristic in operations management: an experimental investigation, article, April 10, 2019; (https://digital.library.unt.edu/ark:/67531/metadc1616597/: accessed June 12, 2021), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Business.

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