scholarly journals Coping with Loss Aversion in the Newsvendor Model

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jianwu Sun ◽  
Xinsheng Xu
Keyword(s):  
Expected Utility ◽  
Loss Aversion ◽  
Confidence Level ◽  
Profit Maximization ◽  
Optimal Order ◽  
Market Demand ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Decision Bias ◽  
Optimal Order Quantity

We introduce loss aversion into the decision framework of the newsvendor model. By introducing the loss aversion coefficientλ, we propose a novel utility function for the loss-averse newsvendor. First, we obtain the optimal order quantity to maximize the expected utility for the loss-averse newsvendor who is risk-neutral. It is found that this optimal order quantity is smaller than the expected profit maximization order quantity in the classical newsvendor model, which may help to explain the decision bias in the classical newsvendor model. Then, to reduce the risk which originates from the fluctuation in the market demand, we achieve the optimal order quantity to maximize CVaR about utility for the loss-averse newsvendor who is risk-averse. We find that this optimal order quantity is smaller than the optimal order quantity to maximize the expected utility above and is decreasing in the confidence levelα. Further, it is proved that the expected utility under this optimal order quantity is decreasing in the confidence levelα, which verifies that low risk implies low return. Finally, a numerical example is given to illustrate the obtained results and some management insights are suggested for the loss-averse newsvendor model.

scholarly journals The Loss-Averse Retailer’s Order Decisions Under Risk Management

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 595 ◽  
Author(s):  
Felix T. S. Chan ◽  
Xinsheng Xu
Keyword(s):  
Loss Aversion ◽  
Value At Risk ◽  
Conditional Value At Risk ◽  
Optimal Order ◽  
Market Demand ◽  
Newsvendor Model ◽  
Expected Loss ◽  
Order Quantity ◽  
Decision Bias ◽  
Optimal Order Quantity

This paper characterizes the retailer’s loss aversion by introducing a loss aversion coefficient and proposes a new loss aversion utility function for the retailer. To hedge against the risk arising from the uncertain market demand, we use the Conditional Value-at-Risk (CVaR) measure to quantify the potential risks and obtain the optimal order quantity for the retailer to maximize the CVaR objective of loss aversion utility. It is shown that that the optimal order quantity for a retailer to maximize the expected loss aversion utility is smaller than expected profit maximizing (EPM) order quantity in the classical newsvendor model, which can help to explain decision bias in the newsvendor model. This study shows that the optimal order quantity with the CVaR objective can decrease in retail price under certain conditions, which has never occurred in the newsvendor literature. With the optimal order quantity under the CVaR objective, it is proved that the retailer’s expected loss aversion utility is decreasing in the confidence level. This confirms the fact that high return means high risk, while low risk comes with low return. Based on the results, several management insights are suggested for the loss-averse newsvendor model.

scholarly journals Hedging Risks in the Loss-Averse Newsvendor Problem with Backlogging

Mathematics ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 429 ◽  
Author(s):  
Xiaoqing Liu ◽  
Felix T. S. Chan ◽  
Xinsheng Xu
Keyword(s):  
Value At Risk ◽  
Profit Maximization ◽  
Newsvendor Problem ◽  
Sensitivity Analyses ◽  
Conditional Value At Risk ◽  
Optimal Order ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Decision Bias ◽  
Optimal Order Quantity

This paper studies the optimal order decisions for the loss-averse newsvendor problem with backordering and contributes to the risk hedging issue in the newsvendor model. The Conditional Value-at-Risk (CVaR) measure is applied to quantify the potential risks for the loss-averse newsvendor in a backordering setting, and we obtain the optimal order quantity for a loss-averse newsvendor to maximize the CVaR of utility. It is found that the optimal order quantity to maximize the CVaR objective could be bigger or smaller than the expected profit maximization (EPM) order quantity, which provides an alternative explanation on decision bias in the newsvendor model. This study also reveals that the optimal order quantity for a loss-averse newsvendor to maximize expected utility with backordering is smaller than the EPM order quantity, which implies that backordering encourages the loss-averse newsvendor to order fewer items. Sensitivity analyses are performed to investigate the properties of the optimal order quantities and managerial insights are suggested. This paper provides a novel method for the risk management of the loss-averse newsvendor model and presents several new ordering policies for the retailers in practice.

scholarly journals Opportunity Loss Minimization and Newsvendor Behavior

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Xinsheng Xu ◽  
Hong Yan ◽  
Chi Kin Chan
Keyword(s):  
Conditional Value At Risk ◽  
Optimal Order ◽  
Market Demand ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Loss Minimization ◽  
Decision Bias ◽  
Optimal Order Quantity ◽  
Opportunity Loss ◽  
Order Quantities

To study the decision bias in newsvendor behavior, this paper introduces an opportunity loss minimization criterion into the newsvendor model with backordering. We apply the Conditional Value-at-Risk (CVaR) measure to hedge against the potential risks from newsvendor’s order decision. We obtain the optimal order quantities for a newsvendor to minimize the expected opportunity loss and CVaR of opportunity loss. It is proven that the newsvendor’s optimal order quantity is related to the density function of market demand when the newsvendor exhibits risk-averse preference, which is inconsistent with the results in Schweitzer and Cachon (2000). The numerical example shows that the optimal order quantity that minimizes CVaR of opportunity loss is bigger than expected profit maximization (EPM) order quantity for high-profit products and smaller than EPM order quantity for low-profit products, which is different from the experimental results in Schweitzer and Cachon (2000). A sensitivity analysis of changing the operation parameters of the two optimal order quantities is discussed. Our results confirm that high return implies high risk, while low risk comes with low return. Based on the results, some managerial insights are suggested for the risk management of the newsvendor model with backordering.

scholarly journals Coping with Loss Aversion and Risk Management in the Supply Chain Coordination

2021 ◽  
Vol 13 (8) ◽  
pp. 4364
Author(s):  
Wei Liu ◽  
Han Zhao ◽  
Shiji Song ◽  
Wenxuan He ◽  
Xiaochen Li
Keyword(s):  
Supply Chain ◽  
Loss Aversion ◽  
Confidence Level ◽  
Wholesale Price ◽  
Revenue Sharing ◽  
Conditional Value At Risk ◽  
Optimal Order ◽  
Order Quantity ◽  
Buyback Contract ◽  
Optimal Order Quantity

In this paper, we apply a combined revenue sharing and buyback contract to investigate the channel coordination of a two-echelon supply chain with a loss-averse retailer. Since loss-averse decision makers usually take on more risks, the Conditional Value-at-Risk (CVaR) measure is introduced to hedge against it and the retailer’s objective is to maximize the CVaR of utility. We obtain the retailer’s optimal order quantity under the combined contract. It is shown that there is a unique wholesale price coordinating the supply chain if the retailer’s confidence level is less than a threshold that is independent of contract parameters. Moreover, a complete sensitivity analysis of parameters is carried out. In particular, the retailer’s optimal order quantity and coordinating wholesale price decreases as the loss aversion or confidence level increases, while it increase as the buyback price or sharing coefficient increases. Furthermore, there exists the situation where the combined contract can coordinate the chain even though neither the revenue sharing nor buyback contract can when the contract parameters are constrained.

scholarly journals Managing the Newsvendor Modeled Product System with Random Capacity and Capacity-Dependent Price

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Qingying Li ◽  
Ciwei Dong ◽  
Ruixin Zhuang
Keyword(s):  
Numerical Study ◽  
Market Price ◽  
Optimal Order ◽  
Selling Price ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Product System ◽  
Random Capacity ◽  
Optimal Order Quantity ◽  
House Production

We consider a newsvendor modeled product system, where the firm provides products to the market. The supply capacity of the product is random, so the firm receives either the amount of order quantity or the realized capacity, whichever is smaller. The market price is capacity dependent. We consider two types of production cost structures: the procurement case and the in-house production case. The firm pays for the received quantity in the former case and for the ordered quantity in the latter case. We obtain the optimal order quantities for both cases. Comparing with the traditional newsvendor model, we find that the optimal order quantity in both the procurement case and the in-house production case are no greater than that in the traditional newsvendor model with a fixed selling price. We also find that the optimal order quantity for the procurement case is greater than that for the in-house production case. Numerical study is conducted to investigate the sensitivity of the optimal solution versus the distribution of the random capacity/demand.

scholarly journals Maximization of container slot booking profits for carriers in the liner shipping industry

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Yu Guo ◽  
Ran Yan ◽  
Hans Wang
Keyword(s):  
Liner Shipping ◽  
Expected Profit ◽  
Optimal Order ◽  
Newsvendor Model ◽  
Shipping Industry ◽  
Order Quantity ◽  
Sensitive Analysis ◽  
Transportation Demand ◽  
Maximum Profit ◽  
Optimal Order Quantity

AbstractIn the liner shipping industry, if a shipper wants to transport its cargo by container ships, it first needs to contact a carrier to book container slots based on the estimated transportation demand. However, one problem in the booking process is that the actual demand is uncertain, resulting in mismatch between the required demand and the booked quantity. To address this issue, this study develops a Newsvendor model to find the optimal order quantity of container slots for the shipper. In addition, uncertainties in the quantity of container slots booking made by the shipper might cause revenue loss to the carrier and low utilization of ship capacity in the daily operations of liner shipping services. Therefore, this study suggests that the shipper should pay reservation fee when booking container slots. This study also aims to find the maximum profit for the carrier under the optimal order quantity of the shipper. In sensitive analysis, how different prices per container slot offered by the carrier would influence the reservation fee, the optimal order quantity of the shipper, and the expected profit of the carrier are explored and discussed. This study can help to manage and promote the online container booking systems in the liner shipping industry.

scholarly journals Loss-Averse Retailer’s Optimal Ordering Policies for Perishable Products with Customer Returns

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Xu Chen ◽  
Qian Zhou
Keyword(s):  
Optimal Order ◽  
Order Quantity ◽  
Policy Model ◽  
Decision Bias ◽  
Perishable Product ◽  
Ordering Policy ◽  
Optimal Order Quantity ◽  
Ordering Policies ◽  
Customer Returns ◽  
Order Quantities

We investigate the loss-averse retailer’s ordering policies for perishable product with customer returns. With the introduction of the segmental loss utility function, we depict the retailer’s loss aversion decision bias and establish the loss-averse retailer’s ordering policy model. We derive that the loss-averse retailer’s optimal order quantity with customer returns exists and is unique. By comparison, we obtain that both the risk-neutral and the loss-averse retailer’s optimal order quantities depend on the inventory holding cost and the marginal shortage cost. Through the sensitivity analysis, we also discuss the effect of loss-averse coefficient and the ratio of return on the loss-averse retailer’s optimal order quantity with customer returns.

scholarly journals Coordination of a Random Yield Supply Chain with a Loss-Averse Supplier

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jiarong Luo ◽  
Xu Chen
Keyword(s):  
Supply Chain ◽  
Loss Aversion ◽  
Optimal Order ◽  
Random Yield ◽  
Order Quantity ◽  
Optimal Production ◽  
Numerical Examples ◽  
Risk Neutral ◽  
Production Quantity ◽  
Optimal Order Quantity

This paper investigates the coordination of a supply chain consisting of a loss-averse supplier and a risk-neutral buyer who orders products from the supplier who suffers from random yield to meet a deterministic demand. We derive the risk-neutral buyer’s optimal order policy and the loss-averse supplier’s optimal production policy under shortage-penalty-surplus-subsidy (SPSS) contracts. We also analyze the impacts of loss aversion on the loss-averse supplier’s production decision making and find that the loss-averse supplier may produce less than, equal to, or more than the risk-neutral supplier. Then, we provide explicit conditions on which the random yield supply chain with a loss-averse supplier can be coordinated under SPSS contracts. Finally, adopting numerical examples, we find that when the shortage penalty is low, the buyer’s optimal order quantity will increase, while the supplier’s optimal production quantity will first decrease and then increase as the loss aversion level increases. When the shortage penalty is high, the buyer’s optimal order quantity will decrease but the supplier’s optimal production quantity will always increase as the loss aversion level increases. Furthermore, the numerical examples provide strong evidence for the view that SPSS contracts can effectively improve the performance of the whole supply chain.

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