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 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 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 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.

Retailer's Optimal Ordering Policy under Conditions of Allowable Shortage and Two-Level Trade Credit Derived without Derivatives

2013 ◽  
Vol 694-697 ◽  
pp. 3428-3433
Author(s):  
Fei Hu
Keyword(s):  
Differential Calculus ◽  
Trade Credit ◽  
Algebraic Method ◽  
Optimal Order ◽  
Order Quantity ◽  
Numerical Examples ◽  
Ordering Policy ◽  
Optimal Order Quantity ◽  
Optimal Ordering Policy ◽  
Optimal Ordering

An inventory model was developed to determine an ordering policy for the retailer under conditions of allowable shortage and two levels of delay permitted. We present a simple algebraic method to replace the use of differential calculus for determining the retailer's optimal ordering policy. A theorem is presented to obtain the optimal order quantity, and numerical examples are given to illustrate the results obtained in this paper.

Optimal Order Quantity and Inventory Classification Using Clustering

2017 ◽  
Vol 4 (2) ◽  
pp. 41-52 ◽  
Author(s):  
Reshu Agarwal
Keyword(s):  
Inventory Management ◽  
Optimal Order ◽  
Order Quantity ◽  
Ordering Policy ◽  
Optimum Order ◽  
Frequent Items ◽  
Clustering Approach ◽  
Optimal Order Quantity ◽  
Data Objects ◽  
Research Studies

Clustering is the process of analyzing data to find clusters of data objects that are similar in some sense to one another. Some research studies have also extended the usage of clustering concept in inventory management. Yet, not many research studies have considered the application of clustering approach on determining both optimal order quantity and loss profit of frequent items. In this paper, ordering policy of frequent items in each cluster is determined and inventory is classified based on loss rule in each cluster. This helps inventory manager to determine optimum order quantity of frequent items together with the most profitable item in each cluster for optimal inventory control. An example is illustrated to validate the results.

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 Coordination of Supply Chain with One Supplier and Two Competing Risk-Averse Retailers under an Option Contract

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Rui Wang ◽  
Shiji Song ◽  
Cheng Wu
Keyword(s):  
Supply Chain ◽  
Conditional Value At Risk ◽  
Optimal Order ◽  
Pareto Optimum ◽  
Risk Averse ◽  
Order Quantity ◽  
Supply Chain System ◽  
Chain System ◽  
Option Contract ◽  
Optimal Order Quantity

This paper studies an option contract for coordinating a supply chain comprising one risk-neutral supplier and two risk-averse retailers engaged in promotion competition in the selling season. For a given option contract, in decentralized case, each risk-averse retailer decides the optimal order quantity and the promotion policy by maximizing the conditional value-at-risk of profit. Based on the retailers’ decision, the supplier derives the optimal production policy by maximizing expected profit. In centralized case, the optimal decision of the supply chain system is obtained. Based on the decentralized and centralized decision, we find the coordination conditions of the supply chain system, which can optimize the supply chain system profit and make the profits of the supply chain members achieve Pareto optimum. As for the subchain, we also find the coordination conditions, which generalize the results of the supply chain with one supplier and one retailer. Our analysis and numerical experiments show that there exists a unique Nash equilibrium between two retailers, and the optimal order quantity of each retailer increases (decreases) with its own (competitor’s) promotion level.

scholarly journals Trade Credit with Barter in a Capital-Constrained Supply Chain

2021 ◽  
Vol 13 (20) ◽  
pp. 11361
Author(s):  
Yangyang Huang ◽  
Zhenyang Pi ◽  
Weiguo Fang
Keyword(s):  
Supply Chain ◽  
Trade Credit ◽  
Wholesale Price ◽  
Uncertain Demand ◽  
Equilibrium Strategy ◽  
Optimal Order ◽  
Order Quantity ◽  
Supply Rate ◽  
Optimal Order Quantity ◽  
And Performance

Barter has emerged to alleviate capital pressure, maximize the circulation of goods, and facilitate the disposal of excess inventory. This study considers a two-level supply chain consisting of a manufacturer and a capital-constrained retailer with trade credit, in which the retailer exchanges unsold products for needed subsidiary products on a barter platform. The retailer’s optimal order quantity and the manufacturer’s wholesale price are derived, and the influences of barter and other factors on the equilibrium strategy and performance of the supply chain are examined; these results are verified and supplemented by numerical simulation. We find that the retailer can increase profit by bartering when facing highly uncertain demand, that the retailer’s optimal order quantity increases with the supply rate and demand for subsidiary products, and that both manufacturer and retailer benefit from the high supply rate of subsidiary products. However, barter induces the manufacturer to raise the wholesale price to prevent its profit from being harmed. In addition, the manufacturer suffers from the retailer’s initial capital.

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