考虑策略性消费者的生鲜农产品定价和库存决策

消费者的策略性行为使零售商的生鲜农产品的定价和库存决策面临更大挑战。本文基于报童模型，综合考虑消费者的策略性行为，对生鲜农产品价值下降进行离散化处理。刻画策略性消费者的决策行为，构建零售商的单阶段和两阶段定价及库存决策模型，分析了产品价值剩余率对消费者行为、零售商最优定价、最优库存水平以及零售商利润的影响机理。研究发现，在单阶段模型中零售商最优价格和最优库存水平均随产品价值剩余率的递增而递增；而在两阶段模型中，第二阶段最优价格随价值剩余率的变化趋势可能存在阈值。     

不完备质量下带有风险厌恶的库存决策模型

在质量的不完备性诱发联动效应的环境下,考虑带有风险厌恶的库存决策问题。假设质量水平为一马尔可夫过程,并将马氏理论和条件风险值（conditional value-at-risk, CVaR）准则纳入库存决策模型的框架,进而给出了不完备质量下带有风险偏好的决策模型及其最优决策机制。模型数值实验的结果表明：最优期望订购量和期望销售利润关于供应能力和风险厌恶因子都为单调递增;库存系统的可靠性与随机质量过程的不可约性、遍历性等基本性质有关,即当随机质量过程为不可约的遍历马氏链时,模型的最优解具有平稳的极限性态。     

具有多元马氏需求的易变质多产品的EOQ模型

本文研究一类新的易变质多产品库存控制策略,即具有多元马氏需求特征的多产品的最优(Q,T,?t)策略,该策略综合考虑了市场需求在不同产品之间具有马氏转移特征和变质率因素。论文首先建立了多产品多周期的多元马尔可夫需求预测模型,并通过该模型确定了各种产品在订货周期内的需求之间的关系。同时,在该关系的理论基础上,进一步给出了多产品多周期库存的最优(Q,T,?t)策略,进而结合算例给出模型的最优策略的数值解。     

具有多元马氏需求的多产品多阶段库存优化模型

本文研究一类新的多产品库存控制策略,即具有多元马氏需求特征的多产品多阶段的订货点订货量(Q, R, SS)策略,该策略考虑市场需求在不同产品之间具有多元马氏转移特征,并考虑缺货因素设置安全库存。论文首先建立了多产品多阶段的多元马氏需求预测模型,并通过该模型确定了各种产品需求之间的关系。同时,在该模型的理论基础上,提出了多产品多阶段的总期望成本模型及其最优(Q, R, SS)策略,进而结合算例给出模型的最优策略的数值解。     

需求预测综合模型及其与库存决策的集成研究

准确的预测有助于企业做出有效的决策,包括生产计划、定价和促销决策等,以减少库存、提高客户满意度和企业竞争力． 以快速消费品为研究对象,分析其需求影响因素,建立了时间序列分析与多元回归整合的需求预测综合模型; 将此预测模型引入到库存决策中,构建了基于库存成本最小的需求预测与库存决策集成模型,并借助变邻域搜索算法获得模型的参数值; 最后,选用实际数据,验证了所构建的需求预测综合模型、物流需求预测与库存决策集成模型及其求解方法的有效性．     

多产品竞争环境中最优供货决策

在有多产品竞争的市场中,产品零售商首先需要了解每个产品在市场中的地位和市场份额,然后通过了解市场需求总量和销售支出情况来决定产品的供应数量,以达到利润的最大化的目标.怎样得到最优的供货量问题是现代库存管理的基础性问题之一.通过引进产品特征描述和消费者一般支出的概念,给出一种市场份额的分析方法和市场份额的一些数学性质及经济特点.然后引入管理中经典库存决策模型———“报童问题”模型,分析多产品竞争环境中零售商的最优供货决策问题.最后研究了在产品的某些特征描述改变的条件下,零售商最优供货量、期望利润和市场利润总量的敏感性分析及其经济含义解释.     

报童问题的最优竞争比策略及其风险补偿模型

报童问题是库存管理中一个重要的模型。对报童问题在不同的目标函数和约束条件下的扩展模型已有了大量的研究。已有研究假设产品的需求分布已知,然而,在实际中完全刻画需求分布信息常常是很困难的,因此,部分信息下的报童模型研究近年越来越受到重视。在竞争比分析方法下,对报童问题进行了讨论,建立概率预期下风险补偿模型用于解决部分信息的报童问题。在确定性预期和基本概率预期下,分别为具有风险偏好的报童设计了最优订购策略,使报童可以根据自己不同的风险容忍度和未来预期选择订购策略。     

带有能力约束的多元马氏需求报童模型

在随机需求环境下考虑带有能力约束的多产品报童问题.为了对多产品的需求进行预测,并度量其需求间的关系,本文首先建立了多元马氏需求模型.其次,在该模型的理论基础上,提出了带有能力约束的多元马氏需求报童模型,进而给出多产品的最优订购策略解.最后,利用期望需求状态的概率值及其截尾概率分析了模型最优解的性质.模型的结论表明,在能力约束的条件下,最优订购量关于左截尾概率单调递减,关于右截尾概率单调递增,而期望需求状态的概率值对最优订购量具有双重的特殊影响.     

基于交货期库存协调的供应链转移定价研究

在将缺货成本和延期惩罚成本纳入决策模型的前提下,对供应商—制造商两阶供应链在转移定价、安全库存,以及总成本之间的相互作用进行了探讨:首先探讨基于 Stackelberg 收益共享定价机制的最优决策;然后,以一体化供应链为参照系,探讨对供应链各成员的行为进行优化的两部制(two-part scheme)收益共享转移定价决策在实践中的运用;最后,探讨模型中部分变量变化对最优决策所产生的影响.通过分析发现,承诺的交货期、延期惩罚成本与缺货成本将会影响供应链的总成本和转移定价决策,进而影响供应商的最优库存决策,而制造商则可以通过适当的激励机制设计,激励供应商按照供应链整体最优的方式进行转移定价、安全库存及相关决策.     

考虑顾客缺货反应的多产品两阶段JIT联合订货

为了解决多产品两阶段联合订货决策问题,综合考虑顾客缺货反应及资源限制对订货决策的影响,提出资源限制条件下考虑CRS的多产品两阶段JIT联合订货策略。在此基础上,以零售商收益最大化为目标,建立了多产品两阶段JIT联合订货决策模型,并从初始解生成和殖民地国家革命方式两方面设计了改进的帝国主义竞争算法。从Gruen调查报告中选取三种不同规模的算例验证了模型和算法的适用性和有效性。研究表明：本文提出的考虑顾客缺货反应的多产品两阶段JIT联合订货方法既可以提高零售商的总收益,也能提高顾客的服务水平;当单位库存资源机会收益相近时,同组产品间不会发生替代情况,而当同组产品间的单位库存资源机会收益差距较大,且高于其他产品组的单位库存资源机会收益时,则该产品组便会出现缺货和替代情况,且若该组缺货产品的剩余资源单位机会收益小于其他组产品的单位资源机会收益,则该产品的剩余资源便会转移给其他缺货产品。研究结论可为零售商多产品两阶段JIT联合订货决策提供有益的参考。     

Modeling Strategic Behavior in The Competitive Newsvendor Problem: An Experimental Investigation

This study experimentally investigates ordering behavior in the competitive newsvendor problem. We consider a duopoly market setting with two identical newsvendors selling the same perishable goods in a common market. Our experimental results show that average observed orders systematically deviate from the Nash equilibrium, and exhibit a similar pull‐to‐center pattern as in the classic non‐competitive newsvendor experiments: average orders fall below the Nash equilibrium in the high‐margin condition, and above the Nash equilibrium in the low‐margin condition. More importantly, the observed orders in the duopoly market are significantly higher than that in the non‐competitive newsvendor market, even in situations where standard inventory models predict no difference. We explain the ordering behavior using a strategic experience‐weighted attraction (EWA) model, which captures players' propensities for strategic thinking in game settings. Our empirical analysis suggests that the strategic EWA model generates more accurate predictions of future ordering behavior than an existing linear adaptive model without concerning strategic thinking. Further analysis shows that individuals are heterogeneous in their propensities to be a strategic player. Our research indicates the importance of modeling strategic behavior when analyzing behavioral decisions in competitive (game) environments.     

How to Compete Against a Behavioral Newsvendor

We investigate newsvendor ordering behavior under competition. We present a laboratory experiment that documents the behavioral ordering regularities in competitive newsvendor environments, and an analytical model extending the standard theory of newsvendor competition by including an optimal best‐response policy for competing with a behaviorally biased newsvendor. We test the effectiveness of this policy using an out‐of‐sample experiment and find that it results in improved market share, service level and profitability.     

A competitive multiple-product newsboy problem with partial product substitution

This paper studies a multi-product competitive newsboy problem with shortage penalty cost and partial product substitution. We characterize the unique Nash equilibrium of the competitive model and analyze some properties of the equilibrium. An iterative algorithm is developed on the basis of approximating the effective demand as well as the expected profit function for each product. Numerical experiments are conducted to illustrate the impacts of product substitution, demand correlation and demand variation on the optimal order quantities and the corresponding expected profits, and to compare the total optimal inventory level of the competitive case with that of the centralized case. The conclusion that competition always results in a higher total inventory level, even under the effect of product substitution is drawn in the symmetric case.     

A heuristic approach to in-season capacity allocation in a multi-product newsvendor model

Based on an actual problem, we develop and test two heuristics for optimizing the newsvendor’s response to new in-season demand information for a multi-product single-period problem. In this model, in addition to the quantities produced prior to the beginning of the selling season, the newsvendor can produce additional quantities of some products after the selling season begins. Sales data of all products is updated daily, and using these updates, the newsvendor can test if the quantities already produced are still optimal. If the newsvendor finds that the actual demand of a product up to a point in time indicates that the quantity already produced is too small, then the product becomes a candidate for an incremental production quantity. In Heuristic I, we fix the pre-season production quantities to those that are optimal for the classic newsvendor model. In Heuristic II, because the newsvendor may have some recourse during the selling season, we allow for reductions in the pre-season production quantities from the optimal classic newsvendor model production quantities. Using a simulation experiment, we show that even under an unbiased forecast, both heuristics result in higher profit, with Heuristic II outperforming Heuristic I. The increase in profits from using the heuristics increases significantly with the number of products for which the forecast is biased. In addition, the improvements in profits decrease significantly as the lead time and the penalty for late production increase.     

一类供应链中多产品的订购策略及实证研究

本文针对变质产品供应链,建立了多产品的库存模型,分析了基于五种不同订购策略下总成本函数的性质,提出了多种变质商吕的近似最优订购策略.并且运用本文的理论,对南京市某花卉礼品公司2004年9月的鲜切花订购决策进行了实证分析.     

On the benefits of operational flexibility in a distribution network with transshipment

We consider a centralized distribution network with multiple retailers who receive replenishment inventory to satisfy customer demand of the local markets. The operational flexibility of the network is defined as the opportunity that one retailer's excess inventory can be transferred to satisfy other retailers’ unmet customer demand due to stock-outs. A general modeling framework is developed to optimize retailers’ order quantities under any possible flexibility level of a stylized two-stage distribution network. We apply the framework to formulate and solve the transshipment problem of a distribution network with three retailers. Six typical flexibility levels are investigated to make the comparison study on the firm's profit performance under three ordering quantity policies: average demand, newsvendor order quantity, and optimal order quantity. We find that the operational flexibility and system optimization are complements to the firm's performance. The ordering policy with newsvendor ordering quantity can perform fairly well with moderate flexibility level when compared with the optimized ordering policy with full flexibility.     

需求依赖于库存的易变质品在线采购问题研究

根据现实生活中常见的库存量越大越吸引消费者购买兴趣的现象，本文建立了需求依赖于库存的易变质品采购模型。在不假设价格服从任何分布的条件下，提出了采购价格不确定背景下的易变质品在线采购策略。本文采用在线问题及其竞争分析的方法来进行建模分析，设计出有效的在线竞争采购价格驱动的(s,S)策略，与离线最优策略进行比较，得出理论竞争比和最优经济采购数量和采购时间间隔。最后，通过数值算例说明该策略在现实中具有较好的实际竞争性能比，且在多个价格序列下都表现良好，从而说明了该策略是鲁棒的，可以为企业提供有价值的决策建议。     

需求分布规律变化情况下的报童订货策略

在需求分布规律变化情况下，报童在进行订货决策时会因为错误判断需求分布规律而导致期望库存成本增加。为了解决这一问题，本文集成传统历史需求信息和非传统需求信息以正确地认知需求分布规律，在此基础上决策订货量。假设需求服从均值不同、方差相同的两种类型的正态分布，每一种正态分布的概率已知。利用信号检测理论构建基于历史需求信息与需求分布概率的报童最优订货策略，并与只基于需求分布概率的直觉规则订货策略进行对比。结果表明：只要排除需求分布概率很大或很小两种极端情况，最优订货策略比直觉规则订货策略在控制期望库存成本方面的作用更明显，即利用历史需求信息可以有效修正报童对实际需求分布的检测结果，从而提高实际订货决策的准确性。研究结果对传统历史需求信息和非传统需求信息的集成以及需求信息交换等有一定的管理学启示和应用价值。