Demand forecasts with judgement bias in a newsvendor problem

AbstractWe explore the impact of judgement bias on demand forecast accuracy and profit to identify the driving force of decision-makers to be biased. We study the accuracy-maximising forecasts and the profit-maximising forecasts, which results in the least error of demand forecasts and minimum deviation from the optimal order decision, respectively. Under the assumption that period-to-period demand is independent over time, we find that both types of forecasts are biased. It implies that a newsvendor has the motivation to be biased to obtain either a more accurate demand forecast or a higher profit. Moreover, the decision error under the accuracy-maximising forecasts can be lower than that under unbiased demand forecasts and be bounded by twice of the error under profit-maximising forecasts. It suggests that the biased accuracy-maximising forecasts can perform satisfactorily in both forecasts and decisions. We further relax the assumption of independent demand by considering correlated and trended demand processes, and show the robustness of the positive impact of judgement bias. We then propose a method to solve pure data-driven newsvendor problem and examine its performance with empirical evidence. Our paper contributes to the literature on behavioural operations management by investigating the rationality of judgement bias and its implications.KEYWORDS: Judgement biasdemand forecastsnewsvendor problemforecast accuracydecision error AcknowledgmentsThe authors are grateful to the associate editor and two anonymous referees for their constructive comments and suggestions that have led to significantly improvements on the presentation and content of the paper.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article or its supplementary materials.Additional informationFundingThe research of Qi Fu is supported in part by the University of Macau [grant number MYRG2020-00256-FBA]. The research of Juan Li is supported in part by the National Natural Science Foundation of China under [grant number #72171113]. The research of Lianmin Zhang is supported in part by the National Natural Science Foundation of China under [grant number #72171156].Notes on contributorsYini ZhengYini Zheng is a PhD student in School of Management and Engineering, Nanjing University. She holds a bachelor degree from Northwest University and a master degree from Nanjing University. Her research interests are supply china management, behaviour operations management, and the interface between Marketing and OM.Qi FuQi Fu is an associate professor in Faculty of Business Administration, University of Macau. She received her PhD from Hong Kong University of Science and Technology. Her research interests include operations and supply chain management, robust inventory planning, marketing-operations interface. Her work has been published in journals such as Operations Research, Production and Operations Management, European Journal of Operational Research, International Journal of Production Economics.Juan LiJuan Li is a professor in the School of Management and Engineering, Nanjing University. She holds a Ph.D. from Shanghai Jiaotong University of China. Her primary areas of research interest include 2021 Cohen, M C, G Perakis, and R S Pindyck. 2021. "A simple rule for pricing with limited knowledge of demand." Management Science 67 (3): 1608–1621.[Crossref], [Web of Science ®] , [Google Scholar] supply china management, behaviour operations management, and the interface between Marketing and OM. She has published in European Journal of Operational Research, International Journal of Production Economics, Annals of Operations Research, and other journals.Lianmin ZhangLianmin Zhang is a Senior Research Scientist in Shenzhen Research Institute of Big Data. He received his PhD in System Engineering and Engineering Management Science from The Chinese University of Hong Kong. His current research interests include supply chain management and operations research. He has published more than 30 papers in leading journals, such as Production and Operations Management, Transportation Research Part B, Naval Research Logistic, Decision Science and European Journal of Operations Research, and other journals.