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 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.

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.

The Effects of Demand Randomness in Newsvendor Model

2013 ◽  
Vol 397-400 ◽  
pp. 2595-2600
Author(s):  
Zhi Bing Lin
Keyword(s):  
Concave Function ◽  
Order Conditions ◽  
Retail Price ◽  
Expected Profit ◽  
Optimal Order ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Objective Functions ◽  
First Order ◽  
Decision Variables

In this paper, we consider a newsvendor model while its demand randomness is changeable. We analyze how the demand randomness affects the decision variables and objective functions in two difference situations: (1) the retail price is fixed;(2) the retail price is changeable. In first situation, we characterize the optimal order quantity, expected profit and variance of profit based on the benchmark model. In second situation, we show that the expected profit is joint concave function with respect to order quantity and retail price, also give the first order conditions. Finally, we use number analysis to show the effects of demand randomness on optimal retail price and order quantity

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 Risk Management for the Optimal Order Quantity by Risk-Averse Suppliers of Food Raw Materials

2018 ◽  
Vol 6 (4) ◽  
pp. 96
Author(s):  
Tyrone T. Lin ◽  
Shu-Yen Hsu
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Food Safety ◽  
Utility Function ◽  
Raw Materials ◽  
Expected Profit ◽  
Optimal Order ◽  
Risk Averse ◽  
Order Quantity ◽  
Optimal Order Quantity

In uncertain food safety environments, the suppliers of food raw materials (FRM) are facing crucial food safety issues. Therefore, this article aims to probe the risk-averse attitude of FRM suppliers in the face changing marketing environments, in order to establish a decision-making theory as a standard reference for optimization methods to satisfy the maximum expected profit and utility function for the optimal order quantity of FRM suppliers’ decision-making. We assume that urgent orders are permitted when products are out of stock, and surplus products will be sold at discounted prices, as based on the food safety circumstances and the differences of market acceptance (optimistic/normal/pessimistic), in order to affect the procurement costs and selling prices. The results of sensitivity analysis for the maximum expected profit show that the probability of imported FRM having no food safety problems when the external environment has no food safety problems is the most important parameter, with the importers fulfilling their responsibility for FRM source quality control. Meanwhile, a responsible attitude toward handling a crisis will reduce losses, transform the crisis into an opportunity, and win the trust of consumers, thereby, fostering corporate sustainability. Sensitivity analysis identifies the significant parameters that influence suppliers’ maximum utility function, and provides a reference by which food-related companies may formulate sustainable business policies.

Fuzzy random Newsboy problem with chance distribution

2020 ◽  
Vol 39 (5) ◽  
pp. 6857-6868
Author(s):  
Krishnendu Adhikary ◽  
Jagannath Roy ◽  
Samarjit Kar
Keyword(s):  
Equivalent Form ◽  
Expected Profit ◽  
Chance Constraint ◽  
Optimal Order ◽  
Order Quantity ◽  
Newsboy Problem ◽  
Proposed Model ◽  
Newsboy Model ◽  
Optimal Order Quantity ◽  
Fuzzy Random

Due to increasing difficulty and challenging issues of newsboy problem under uncertainty, managers seek newer and appropriate approaches to apprehend more accurately the demand for perishable products and or the products having a short shelf life. This paper investigates a newsboy problem with fuzzy random demand in a single product business scenario. The classical newsboy model is extended to a fuzzy random newsboy problem to determine the optimal order quantity and expected profit under hybrid uncertainty. To solve the proposed model, a new solution approach based on chance constraint programming is proposed to formulate the crisp equivalent form of the fuzzy random newsboy model. Numerical examples and a real-life case study are presented to show the utility of the projected model. From the outcomes, decision makers can make comprehensive recommendations for the optimal order quantity and expected profit obtained by our proposed model under two-folded uncertainty. Also, a sensitivity analysis suggests that the profit and order quantity will increase (or decrease) with the increase (or decrease) of the mean demand.

Profit Estimation Error in the Newsvendor Model Under a Parametric Demand Distribution

2020 ◽  
Author(s):  
Andrew F. Siegel ◽  
Michael R. Wagner
Keyword(s):  
Operations Management ◽  
Estimation Error ◽  
Expected Profit ◽  
Optimal Order ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Unknown Parameters ◽  
Demand Distribution ◽  
Heavy Tailed ◽  
Normally Distributed

We consider the newsvendor model in which uncertain demand is assumed to follow a probabilistic distribution with known functional form but unknown parameters. These parameters are estimated, unbiasedly and consistently, from data. We show that the classic maximized expected profit expression exhibits a systematic expected estimation error. We provide an asymptotic adjustment so that the estimate of maximized expected profit is unbiased. We also study expected estimation error in the optimal order quantity, which depends on the distribution: (1) if demand is exponentially or normally distributed, the order quantity has zero expected estimation error; (2) if demand is log-normally distributed, there is a nonzero expected estimation error in the order quantity that can be corrected. Numerical experiments, for light- and heavy-tailed distributions, confirm our theoretical results. This paper was accepted by Vishal Gaur, operations management.

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.

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