Effects of Human Decision Bias in Supply Chain Performance
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Studies in newsvendor decision-making have shown that human decisions systematically deviate from analytical solutions found in many utility models of the single period problem (SPP). Yet for the most part the impacts of this human decision bias in systems of newsvendor type products have not been investigated. We study bias in human decision-making to determine how different factors affect the performance of systems of newsvendor type products. We extended the state of the arts utility models of SPP to analyze the effects of individuals wealth on individual decision-making. Our theoretical and empirical results proved that individuals wealth significantly affected individual decision-making. Specifically, our analysis concluded that wealthier individual ordered more than poorer individual did when presented with the same investment opportunity. We created a human decision bias (HDB) model to include different newsvendor ordering policies that individuals could use to determine their order quantities. This model is set up to investigate individuals reliance on different ordering policies under different experimental conditions. We designed multi period newsvendor experiments to study effects of factors such as item profit margin, wealth, value of learning, and salvage value on decision-maker's order quantity. We found that wealth and profit margin factors significantly affected individual newsvendor decision-making. Learning, gender, and salvage value factor did not exhibit significant effects in our empirical studies. We designed multi period multi echelon newsvendor experiments to study effects of factors such as the relationship between newsvendors, item profit margin, and newsvendors' wealth on the performance of two-echelon newsvendors system. We found item profit margin, wealth, and relationship between supplier and retailer to significantly affect newsvendor decision-making. Finally, we present a case study of US fresh produce industry to illustrate the impacts of human decision bias on the performance of a supply chain system.