An experimental investigation of newsvendor decisions under ambiguity

ABSTRACT

The literature on decision biases in the newsvendor model assumes classical version of the problem where the distribution of random demand is known. This context is decision-making under risk. In many real-life settings, firms are not able to elicit complete and exact information about the demand distribution. This results in decision-making under ambiguity. We examine the newsvendor ordering preferences under ambiguity. Our study is the first attempt in behavioural operations management research to examine the biases in newsvendor decisions under ambiguity. We design experiments to understand the ordering preferences under ambiguity and risk. The experimental results show that subjects deviate from the normative benchmarks. We observe ‘pull-to-center’ bias in newsvendor decisions under ambiguity. We also observe that subjects exhibit ‘asymmetry in ordering’. Both these biases have significant implications for both theory and practice. Our research is a building block for research in a variety of normative models in operations management literature where ambiguity in demand is a highly relevant context for decision-making.

Keywords:

• Behavioural operations management
• newsvendor
• biases
• ambiguity
• risk

Acknowledgments

The authors thank the anonymous referees, and the editors for their valuable feedback that significantly improved the positioning and presentation of this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 In decision theory, maximising expected payoffs is considered the gold-standard of rational behaviour.

2 Products with critical ratio less than 0.5.

3 Products with critical ratio more than 0.5.

4 Minimum daily wage |439 for a shift of 8 h. Hence, we believe that the incentive amount offered for the approximate 90 min task is an appropriate compensation.

Additional information

Notes on contributors

Abhishek Shinde

Abhishek Jaysing Shinde is currently working at Vedak: Expert Advisory Platform that he founded in 2016. Abhishek obtained his doctoral degree in management from the Indian Institute of Management Calcutta in 2016. He works on problems in Decision Theory.

Peeyush Mehta

Peeyush Mehta is a Professor of Operations Management at Indian Institute of Management Calcutta since 2012. During 2005–2011, he was a faculty in the Department of Industrial & Management Engineering at the Indian Institute of Technology Kanpur. He obtained his doctoral degree from Indian Institute of Management Ahmedabad. He worked as a research fellow at the Nanyang Technological University, Singapore under Singapore-MIT alliance programme during 2004–2005. His research interests are in the areas of operations strategy, supply chain coordination, and manufacturing competitiveness.

R. K. Amit

R. K. Amit is an Associate Professor in the Department of Management Studies, Indian Institute of Technology Madras. He completed his undergraduate studies at Indian Institute of Technology Kanpur, and his doctoral studies at Indian Institute of Science Bangalore. His research and teaching interests are game theory and decision theory, and their applications in operations management.