A PRICE-SETTING NEWSVENDOR MODEL UNDER CVAR DECISION CRITERION WITH EMERGENCY PROCUREMENT

In this paper, we consider a newsvendor model in which a risk-averse manager faces a stochastic price-dependent demand in either an additive or a multiplicative form. An emergency purchase option is allowed after the realization of demand to satisfy the units that are short. By adopting Conditional value-at-risk （CVaR） as the decision criterion, we aim to investigate the optimal pricing and ordering decisions, and the effects of parameter changes in such a setting. We provide sufficient conditions for the uniqueness of the optimal policy for both demand models. We perforl~, comparative statics analysis to show how the optimal pricing and ordering decision behaves when changing parameters. We also compare our results with those of the newsvendor with a general utility function and with CVaR criterion under lost sales assumption. Our key results include： （i） For both demand models, the optimal selling price is decreasing in risk aversion. Hence, the optimal price of a risk-averse newsvendor is not greater than the optimal price of a risk-neutral newsvendor. （it） In contrary to the lost sales case, for the multiplicative demand model, the optimal order quantity may not be monotonic in risk aversion. Consequently, the optimal risk-averse order quantity may be lower or higher than the optimal risk- neutral counterpart. （iii） For the additive model, the optimal order quantity is strictly increasing in the emergency purchase price, while for the multiplicative model the optimal order quantity has no such a monotonic property. Some numerical examples are conducted to verify our claims and gain more insights about the risk-averse decision-making behaviors.

OPTIMAL DECISIONS WHEN BALANCING EXPECTED PROFIT AND CONDITIONAL VALUE-AT-RISK IN NEWSVENDOR MODELS

This paper investigates a risk-averse inventory model by balancing the expected profit and conditional value-at-risk （CVaR） in a newsvendor model setting. We find out that： i） The optimal order quantity is increasing in the shortage cost for both the CVaR only criterion and the tradeoff objective, ii） For the case of zero shortage cost, the optimal order quantity to the CVaR criterion or tradeoff objective is increasing in the selling price, respectively. However, it may not be monotonic in the selling price when incorporating a substantial shortage cost. Moreover, it may be larger or less than the risk-neutral solution, iii） Under the tradeoff objective function, although the optimal order quantity for the model without shortage cost is increasing in the weight put on the expected profit, this property may not be true in general for the model with a substantial shortage cost. Some numerical examples are conducted to verify our results and observations.

A RISK-AVERSE NEWSVENDOR MODEL WITH LIMITED CAPACITY AND OUTSOURCING UNDER THE CVAR CRITERION

For seasonal products, the retailers usually launch various marketing ettorts, llKe aaverusmg tmu promotion, to promote them in a selling season. While facing large demand from the customers, one should take the capacity constraint and outsotlrcing into consideration. Considering the shorten life cycles of most products, in this paper we adopt the traditional newsvendor model to investigate the optimal marketing effort along with optimal order quantity. We address the risk aversion issue and characterize the influence of the sellers＇ risk propensity with CVaR criterion, and we develop an effective algorithm to obtain the optimal strategy. The impact of sellers＇ risk propensity on the performance of the system is illustrated via numerical examples, The innovation of this paper is threefold. First, the optimal joint strategy of the marketing effort and order quantity is investigated and an efficient algorithm to find the optimal strategy is developed. Second, the capacity constraint option and an outsourcing strategy are studied jointly for excess products. Finally, the risk propensity of the seller and its influence are investigated by using the CVaR criterion, through which we obtain some new managerial insights.

Joint Bidding Decision of Wind Farms and Energy Storage Based on Newsvendor Model

Currently,renewable energy generation has received more and more attention.This article focuses on wind energy generation,one of the renewable energy sources.Aiming at the intermittent and unpredictable wind power problems,according to the day ahead bidding mechanism in the power market,this paper introduces the energy storage system to maximize wind power merchants profit based on the newsvendor model.First,this paper focuses on the wind farms combined with storage system to put forward the optimal bidding decision of selling or buying electricity to the market one day in advance and the optimal bidding amount.Then,we analyze the relationship between the optimal bid amount and the market penalty price coefficient,government subsidy,storage system charge and discharge efficiency,and other parameters.Based on the analysis of various parameters,power generation companies can make reasonable bidding decisions and amount to maximize profits.

The newsvendor model revisited： the impacts of high unit holding costs on the accuracy of the classic model

The newsvendor problem has been applied in various business settings. It is often assumed that the decision variable, i.e., order-up-to level, has no impacts on the holding costs for average inventory cycled in a given period, which is the difference between beginning and ending inventory levels on hand in that period. The average holding cost for this portion of inventory is conveniently and approximately calcutated as half the product of the unit holding cost and the expectation of the demand in one period if it is assumed that the inventory is approximately evenly consumed. It is a good approximation when the unit holding cost is significantly lower than the unit backorder cost as this optimal solution to inventory level is able to guarantee a low probability of understocking. However, if this condition does not hold, the approximation may deviate from the actual cost and cannot measure the expected holding cost for this portion of inventory. This paper examines the impact of the cycle stock holding cost on the newsvendor model and the conditions under which this portion of cost is not negligible.

基于报童模型的供应链网络均衡决策研究

在不确定性需求下构建了基于报童模型的两层供应链网络,供应链网络是由原料供应商、产品生产商和需求市场构成。针对不确定性需求引入报童模型到供应链网络均衡模型中,用于供应链网络中厂商的产量和价格决策。模型构建了基于报童模型的变分不等式来表达供应链网络在不确定性需求下的均衡条件。最后,通过数值案例给出了需求均匀分布下,方差对于产品价格、原料供应商产品流量的影响分析。

考虑库存风险的服装行业新产品预售策略博弈研究

电子商务时代,服装行业线上销售的退货率居高不下。为缓解高退货率连带的库存风险,部分服装企业采用超长预售策略,在相对较长的预售期内次第发货满足顾客订单。在此现实背景下,文章基于报童模型,探讨商家在正常预售和超长预售中的策略选择,并求解两种策略的最优定价、产量、利润和可行条件。结果表明:当需求不确定性较大且产品残值较小,预售时长在合理的范围内且顾客更愿意等待时,应选择超长预售策略,反之选择正常预售策略;并且,超长预售策略能够显著降低库存剩余风险。研究结论对服装企业的预售决策和库存管理具有一定的现实参考价值。

生鲜农产品零售商的区块链技术投资决策与订货策略

区块链技术在生鲜农产品供应链中已经得到广泛应用。本文以报童模型为基础,研究了零售商在生鲜农产品市场中订货决策以及区块链投资策略问题。在模型中考虑了需求和农产品新鲜度的随机性、区块链的投资成本以及区块链技术的预测精度水平等特征的基础上,比较零售商在使用区块链前后的订货策略和绩效水平,分析区块链为农产品供应链带来的商业价值以及零售商对于区块链的投资策略。研究表明:零售商利用区块链技术可以及时预测到农产品的新鲜度状态,优化了零售商的订货策略,从而在减少食品浪费和提高供应链绩效水平方面发挥重要作用。然而在一些特定情况下,零售商投入过多资源以实现高精度的区块链预测并不是一个最优选择,此时零售商采用低精度的区块链技术也能实现收益的增长。而当区块链投资成本超过特定阈值时,零售商将不会采用区块链技术。

需求正态分布条件下基于报童模型的供应链网络均衡模型

针对不确定性需求引入报童模型到供应链网络均衡模型中,用于供应链网络中厂商的产量和价格决策。考虑到在实际生活中正态分布的更为常见性和重要性,在需求正态分布条件下运用博弈理论、网络均衡理论、报童模型以及变分不等式等方法建立了需求正态分布条件下基于报童模型的供应链网络均衡模型,研究了当需求服从正态分布条件下供应链与供应链之间的竞争行为和竞争结果。

“蔬菜类商品的自动定价与补货决策”问题解析

给出2023年“高教社杯”全国大学生数学建模竞赛C题“蔬菜类商品的自动定价与补货决策”的可行解法,并对赛题评阅中发现的问题作了简要的评述.该题旨在通过对6个典型蔬菜品类的交易数据进行分析,探索蔬菜类商品的订购和定价问题.蔬菜需求具有明显的时间趋势和价格敏感性,由于保鲜期短,通常采用每日补货的运营方式.首先,通过剥离销量的时间效应,揭示销量的分布规律、价格与销量的耦合关系以及品类之间的相关性;其次,利用随机优化,建立优化模型并对补货和定价策略进行求解;最后,基于成本预测并叠加销量的时间效应,得到最优的补货量和销售价格.

基于顾客惰性行为的无理由退货策略研究

通过对加入了顾客惰性因素的无理由退货策略建立数学模型,发现当惰性顾客存在时,商家的最优销售价格为只考虑理性顾客时的标准价格与惰性损失之差;最优退货价格为产品的清货价格与边际惰性效用贡献率之和;与只考虑理性顾客的无理由退货策略相比,惰性在一定程度上会对销量产生负影响,但在相同环境下却能为商家带来更多的利润。

零售业供应链企业RFID技术应用决策研究

采用RFID技术产生的成本是制约RFID应用的主要因素。通过采用报童模型分析了由1个生产商和1个零售商组成的供应链,考虑了零售商商品摆放错误对供应链利润的影响。分别研究了集中决策和分散决策情况下,采用RFID技术对生产商和零售商利润的影响,以及可以承担的最大RFID标签成本,为供应链成员企业采用RFID技术的决策提供了定量化、模型化的依据。

需求不确定环境下多个零售商竞争的鲁棒随机优化模型

在需求不确定环境下构建了由一个制造商和多个零售商组成的供应链系统,考虑不同产品的可替代性,建立了多个零售商竞争的随机优化模型。利用鲁棒优化方法研究了需求不确定环境下多个零售商竞争的绝对鲁棒优化问题、偏差鲁棒优化问题和相对鲁棒优化问题。最后通过数值算例比较分析了不同产品替代率下的绝对鲁棒优化解、偏差鲁棒优化解及相对鲁棒优化解。

基于顾客策略行为的供货水平与供应链绩效

基于顾客策略行为,考虑报贩模型和分散式供应链模型。通过分析销售商与顾客的理性预期均衡,研究了批发价格契约、数量折扣契约和两部定价契约下的供货水平和供应链绩效。研究结果表明:两部定价契约能提升供应链利润,高利润同时伴随着高供货水平,而批发价格契约或数量折扣契约下的供应链绩效则小于一体化供应链绩效。由于顾客策略行为的存在,生产商应该把两部定价契约中的批发价设定在低于生产商边际生产成本,以增大供应链的供货水平,从而提高供应链利润。

基于消费者时间偏好的供应链订货策略

结合产品的生命周期特征以及消费者的有限理性行为理论,扩展bass市场需求曲线,利用准双曲变化因子来描述不同销售期的需求变化;假设市场终端不同消费层次的客户对于同一款产品不同阶段的价值感知具有相同程度的时间偏好,从而导致时尚类产品从流行期到衰落期,其市场需求呈现出在近期内骤减、在远期则相对缓慢下降的总体趋势。并基于此种需求变化假设,建模分析销售商的订货策略。经过分析发现,在考虑了市场需求的有限理性因素情形时,当产品进入其销售衰退期,建议的实际订货量应该较之传统方式下有所降低,以规避经营风险。订货量降低的情况,受产品的时尚程度所影响。

过度自信的报童模型研究

将过度自信定义为报童对市场需求信息的过度精确,建立了过度自信的报童模型,得到了过度自信报童的最优订货量和理性报童最优订货量之间的线性解析关系,并分析了过度自信水平对订货偏差及利润损失的影响。研究发现,随着报童过度自信水平的增加,其订货量会越来越偏离理性的最优订货量,而且过度自信导致的利润损失是关于过度自信水平的递增的凸函数,最后通过算例对上述的模型和结论进行了分析验证。

考虑锚定心理的零售商订货问题

在传统报童模型理性人假设的基础上,引入锚定心理研究零售商的订货问题。建立了考虑零售商锚定不充分调整偏差的新的订购模型,通过模型分析发现零售商受锚定心理影响,其订货行为出现"偏向均值"现象。分析了锚定心理对零售商实际利润的影响,发现锚定心理水平越严重,零售商的实际利润越偏离最大期望利润。通过灵敏度分析探讨了零售商锚定心理水平对于零售商实际订货量以及实际利润的影响程度,证明了在分析零售商库存行为时考虑锚定心理的合理性。

基于条件风险值准则的战略顾客报童模型

针对具有风险厌恶特性的报童在面临战略顾客时应如何做出订购和定价决策的问题,在分析战略顾客购买行为的基础上,运用CVaR准则建立考虑战略顾客行为的风险厌恶报童模型。进一步研究了存在战略顾客时数量折扣契约能否实现供应链协调的问题。研究表明,零售商存在最优订购和定价策略,零售商可以根据自身以及顾客的风险态度、产品成本和处理价格来制定库存和价格策略,增加顾客低价购买不到产品的风险,以避免战略顾客行为;零售商的风险态度加剧了双重边际效应,恶化了供应链绩效,此时数量折扣契约能实现供应链协调。

季节性商品销售活动中的两次订购模式

考虑由1个供应商和1个零售商组成的两级供应链模型,提出了一个推广的报童模型,比较分析供应商和零售商在不同订购模式下的最优决策。引入两次订购模式,研究季中批发价变动对供应链成员期望收益的影响,探讨优化供应链性能的途径。利用算例对结论进行了说明。

考虑战略顾客行为时的两阶段报童模型

在季节性产品销售环境下,考虑由一个零售商和可以无限细分的顾客群体组成的两级供应链系统,研究了考虑战略顾客行为时两阶段报童模型的库存与定价决策问题。传统的两阶段报童模型没有考虑战略顾客行为对于零售商的库存和定价决策的影响,实际上顾客在购买时将会考虑产品在销售期内完整的价格路径,以最大化期望效用为目标确定最优购买时机,而零售商则以最大化期望收益为目标确定最优订货数量和设定价格路径。引入理性预期均衡分析,研究了零售商和战略顾客双方同时行动静态博弈时的理性预期均衡解,并进一步分析了零售商承诺销售价格不变时的理性预期均衡解,最后,通过2组数值算例对模型进行了说明。