Cognitive biases resulting from the representativeness heuristic in operations management: an experimental investigation
Received 5 November 2018
Accepted for publication 4 February 2019
Published 10 April 2019 Volume 2019:12 Pages 263—276
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 2
Editor who approved publication: Professor Mei-chun Cheung
Mohammed AlKhars,1 Nicholas Evangelopoulos,2 Robert Pavur,2 Shailesh Kulkarni2,†
1Department of Management & Marketing, College of Industrial Management, King Fahd University of Petroleum and Minerals, Dhahran, Kingdom of Saudi Arabia; 2Department of Information Technology and Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, TX, USA
†Shailesh Kulkarni passed away on July 6, 2018
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.
Keywords: behavioral operations management, cognitive reflection, training, logistic regression
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