供应中断风险承担策略下供应链产品质量决策

研究由一个制造商和一个零售商构成的二级供应链,引入供应中断风险并通过斯塔克伯格博弈对比分析制造商风险承担策略、零售商风险承担策略以及风险-收益协调策略三种不同的风险承担策略下供应链的产品质量决策及其影响.结果显示:当供应中断损失率较低时,无论采取哪种风险承担策略,供应中断风险损失率上升都会降低制造商的产品质量,影响零售商的销售价格以及市场需求,降低制造商和零售商的利润;制造商风险承担策略会降低产品质量、产品价格、市场需求以及供应链成员绩效;而零售商承担风险策略则有利于提高产品质量和供应链成员绩效;采取风险-收益协调策略能提高产品质量以及供应链成员利润,其程度取决于制造商和零售商的议价能力,制造商的议价能力越强,其产品质量和利润就越高,零售商的利润就越低.比较而言,风险-收益协调策略是最优的.     

零售商风险规避条件下基于期权契约的生鲜农产品供应链协调研究

民以食为天,随着生活水平的不断提高,生鲜农产品在消费结构中的重要性越来越突出,本文将期权思想引入生鲜农产品供应链运作当中,针对由一个零售商和一个供应商组成的二级生鲜农产品供应链,结合生鲜农产品的自然属性,考虑在途损耗对产品数量的影响以及保鲜投入对产品新鲜度的影响,运用CVaR模型研究了零售商的风险规避程度对供应链决策的影响以及期权契约协调机制。研究表明,期权机制可实现风险在供需双方之间共担,可解决随机需求下生鲜农产品供应链的协调问题并合理分配整体利润;仅当零售商的风险规避程度较低时系统协调和帕累托改进才能同时达成。     

供应中断下零售商的最优定价和最优分批订购策略

考虑了由两个可靠性不同的供应商,一个零售商和一个竞争零售商组成的供应链系统,研究了以双垄断市场为背景,在供应中断条件下,建立了零售商的最优定价模型,给出了最优销售价格和分批订购策略.最后通过数值算例就零售商和竞争零售商价格对竞争零售商的采购成本在不中断和中断情形下做了比较.     

树形供应链中断风险应急模型研究

基于战略应急库存与实物期权组合策略,设计了树形供应链中断风险应急模型,并通过求解模型得到系统最优策略.应急模型既考虑了风险防范与应急供应所引发的成本,同时考虑了供应链系统中断导致的损失收益.最后进行了仿真分析,结果表明应急模型能够显著降低树形供应链系统的中断风险成本与系统中断时间.     

不同主导权下线上零售商定价与O2O渠道策略研究

随着消费水平的提高和消费观念的转变,越来越多的线上零售商引入线下体验渠道,将线下体验与线上零售相结合,以改善消费者购物体验、降低产品退货率.文章针对由一个制造商和一个线上零售商组成的供应链,考虑线上零售商向消费者提供退款保证服务,并引入线下体验渠道为消费者提供线下的产品体验,建立了单渠道策略和020渠道策略下的供应链权力结构博弈模型,研究了退款保证、不同主导权以及体验渠道的引入对供应链均衡和消费者剩余的影响.研究结果表明,退款保证会导致制造商、零售商以及供应链系统利润的损失,消费者也有可能需要为此支付一定的溢价;体验渠道的引入能够有效提升供应双方和供应链系统的利润以及消费者剩余;供应双方不同主导权并不会对供应链系统利润和消费者剩余产生影响,仅导致利润在供应链系统内部的重新分配.     

基于供应链协同的生鲜农产品订货策略研究

针对生鲜农产品易变质易损耗的特点,提出了一种基于CPFR的供应链协同运作模式,实现信息共享,协同计划、预测与补货,协同集中决策机制.然后以多家供应商、一家批发商和多家零售商构成的生鲜农产品供应链系统为例,分析了库存损耗随时间和库存量变化,允许缺货,且由批发商协同集中订货的订货策略.     

生鲜农产品双渠道供应链库存合作策略研究

随着我国"互联网+农业"战略的不断推进,生鲜农产品的网络销售渠道呈现出快速增长的趋势,但是生鲜农产品易腐易损、贮藏周期短、流通损耗大的特点在一定程度上加大了其网络销售渠道的运作难度.为此,从生鲜农产品传统销售渠道与网络销售渠道的库存协调与合作的视角,针对生鲜农产品双渠道供应链系统的特性,运用系统动力学的理论与方法构建了双渠道供应链库存独立系统、单级库存合作系统和多级库存合作系统的动力学模型.通过系统模型的仿真模拟,结果表明零售商与网络配送点进行库存紧急调拨的单级库存合作系统在牛鞭效应、服务水平和供应链总成本三个指标上表现最优,在供应链总库存指标上表现次优,整体上是最优的,并针对模型仿真结果,有针对性的提出对策与建议.     

基于不同政府补贴策略的供应链绿色努力决策比较研究

研究由单一制造商与单一零售商组成的二级绿色供应链,探讨在同时考虑制造商与零售商绿色努力情况下政府补贴策略对供应链绿色努力与定价决策的影响,比较分析无补贴策略、制造商补贴策略与消费者补贴策略对决策影响的差异性,并进一步考虑零售商的风险规避特征对最优决策的影响。结果表明,政府补贴能够激励制造商与零售商的绿色努力行为,对供应链的绿色发展总是有利的;且制造商补贴策略下的绿色质量水平高于消费者补贴策略,但对供应链利润而言并不是最优的;而在消费者补贴策略下,尽管产品的绿色质量水平不是最优的,但供应链可以获得最高的利润。研究还发现,风险规避特征不会改变参数对最优决策与最优利润的影响趋势,但会降低零售商的绿色努力积极性,导致其利润的下降。     

基于期权的树形供应链应急模型与仿真

在多级树形供应链网络环境下,基于实物期权策略并引入中断风险成本,建立了树形供应链应对中断风险的保护与应急模型,通过求解模型得到最优策略并进行了数值仿真分析.仿真结果表明该模型能够显著降低树形供应链系统的中断风险成本与系统中断时间,从而提高供应网络的鲁棒性.     

随机中断和随机需求下闭环供应链最优回收定价模型

讨论了由一个制造商、一个零售商和一个第三方回收商组成的闭环供应链的差别定价问题.基于博弈论的理论和方法在集中式和分散式决策情形下分别建立了第三方回收定价模型,并给出了随机中断和随机需求下闭环供应链的最优定价策略组合,最后通过数值例子分析了供应中断对最优批发价和零售价的影响.     

外部市场存在替代产品的VMI系统研究

供应商管理用户库存(VMI)作为一种有效的补货机制,能对购买渠道的需求信息做出积极正确的反应.现在对VMI的研究往往集中于单个零售商和单个供应商组成的系统,不考虑VMI系统受市场上其他零售商或供应商的影响.假设市场上多个零售商出售相互之间可替代的产品,某个零售商与其供应商之间应用VMI系统.我们的研究主要有两方面:1)VMI系统是否有助于零售商和供应商组成的供应链在差异产品市场上获得更大的收益;2)供应商和零售商如何决策是否应用VMI系统。     

Multi-echelon multi-company inventory planning with limited information exchange

Supply chain planning concepts from multi-echelon inventory theory are generally based on some form of centralised planning of supply chains. Those multi-echelon models that do consider decentralised planning, assume complete information and/or a specific single objective function. This paper investigates how multi-echelon inventory theory can accommodate a setting with decentralised decision makers (a supplier and a number of retail groups) without complete information. We present a coordination procedure that does not require the retail groups to exchange demand information, but does allow using opportunities for demand pooling between them. We illustrate our ideas by way of a quantitative analysis of a two-echelon divergent supply chain, with both cooperative and non cooperative retail groups. We conclude that coordination across a supply chain with decentralised control and limited centralised information is feasible by using available algorithms with satisfactory service level and cost performance.     

随机弹性需求下供应链销售价格与提前期联合决策及协调机制

研究了市场需求随机且对销售价格及提前期敏感的条件下,供应链如何制定最优的销售价格、提前期以及库存因子使得利润最大化。首先,分析了集中决策与分散决策供应链的最优决策,发现集中决策与分散决策模式下的提前期与库存因子是相同的,但分散决策下的销售价格更高、期望利润更低,且分散决策与集中决策供应链的利润之比随着需求对价格的敏感程度的增大而增大。然后建立了收入共享与成本分担的协调机制,并分析了其最优决策。研究发现,协调决策机制可以有效地压缩提前期,并能同时使供应链达到帕累托改进,但不能达到完美协调,而且还发现协调决策下制定的最优销售价格比分散决策要低。最后通过数值计算对三种供应链决策模式下的绩效进行了比较分析,结果表明供应链利润随着需求方差增大而减小,提前期压缩程度随着材料成本承担比例增大而增大。上述结论可以为企业制定销售价格与提前期决策以及企业间的协调提供有益的指导。     

缺货情形下轴辐式库存的纵横向协作调拨

电子商务发展要求缩短供需端距离,便于提高供应链柔性运作水平,以更好的响应市场需求,这使得仓配环节的纵横向库存协作调拨面临严峻挑战。为此,本文针对零售行业的轴辐式二级库存系统,考虑可用库存及调拨能力限制,以缺货情形下的额外履约成本及销量损失最小化为优化目标,构建纵向及横向综合库存调拨模型,优化每日库存调拨方案。在此基础上,利用改进的三层编码形式的遗传算法对模型进行求解,并通过算例验证了模型及算法的有效性。     

Multi-period modeling of two-way price commitment under price-dependent demand

This paper examines the use of price-commitment policies in dynamic contracting in multiple-period, finite-time horizons. Two specific forms of price commitment are considered: one on the part of the retailer through a retail-fixed-markup contract and one on the part of the manufacturer through a price-protection contract. Optimal policies for each form of price commitment are analytically derived, as are optimal policies for the traditional price-only and centralized supply chain scenarios that we use as comparisons. We prove that optimal retail price and order size solutions exist in each period under the assumption of non-increasing price-dependent demand. We show that the existence of retailer inventory between periods causes the optimal policies to differ from a static single-period model. Further, we show that a supplier offers a price-protection policy as a signal to the retailer to resolve the gaming that naturally occurs under price-only; this effectively decouples the multi-period dynamic contracting setting into repeated single-period scenarios. However, the resulting behavior can actually inhibit supply chain performance. On the retail commitment side, we find that retail-fixed-markup policies are quite effective in improving supply chain efficiency. We show that such policies can lead to Pareto-improvement over price-only contracts and can even coordinate the supply chain in some situations.     

Multi-item single source ordering problem with transportation cost: A Lagrangian decomposition approach

As a part of supply chain management literature and practice, it has been recognized that there can be significant gains in integrating inventory and transportation decisions. The problem we tackle here is a common one both in retail and production sectors where several items have to be ordered from a single supplier. We assume that there is a finite planning horizon to make the ordering decisions for the items, and in this finite horizon the retailer or the producer knows the demand of each item in each period. In addition to the inventory holding cost, an item-base fixed cost associated with each item included in the order, and a piecewise linear transportation cost are incurred. We suggest a Lagrangean decomposition based solution procedure for the problem and carry out numerical experiments to analyze the value of integrating inventory and transportation decisions under different scenarios.     

Managing a dual-channel supply chain under price and delivery-time dependent stochastic demand

Several leading manufacturers recently combined the traditional retail channel with a direct online channel to reach a wider range of customers. We examine such a dual-channel supply chain under price and delivery-time dependent stochastic customer demand. We consider five decision variables, the price and order quantity for both the retail and the online channels and the delivery time for the online channel. Uncertainty frequently arises in both retail and online channels and so additional inventory management is required to control shortage or overstock and that has an effect on the optimal order quantity, price, and lead time. We developed mathematical models with the profit maximization motive. We analyze both centralized and decentralized systems for unknown distribution function of the random variables through a distribution-free approach and also for known distribution function. We examine the effect of delivery lead time and customers’ channel preference on the optimal operation. For supply chain coordination a hybrid all-unit quantity discount along a franchise fee contract is used. Moreover, we use the generalized asymmetric Nash bargaining for surplus profit distribution. A numerical example illustrates the findings of the model and the managerial insights are summarized for centralized, decentralized, and coordinated scenarios.     

Reverse bullwhip effect in pricing

Price variability is one of the major causes of the bullwhip effect. This paper analyzes the impact of procurement price variability in the upstream of a supply chain on the downstream retail prices. Procurement prices may fluctuate over time, for example, when the supply chain players deploy auction type procurement mechanisms, or if the prices are dictated in market exchanges. A game theory framework is used here to model a serial supply chain. Sequential price game scenarios are investigated to show that there is an increase in retail price variability and an amplified reverse bullwhip effect on prices (RBP) under certain demand conditions.     

基于蒙特卡罗模拟的供应链风险估计研究

以市场需求波动风险为例,基于蒙特卡罗模拟研究了供应链风险估计问题.首先,对市场需求波动风险及其损失度量进行理论分析,利用市场需求波动风险情境下的供应链系统库存成本损失来度量市场需求波动风险的损失.其次,选择供应链末端需求为蒙特卡罗方法待模拟的随机变量,基于需求建立了市场需求波动风险概率测度模型和风险损失度量模型,确定了市场需求波动风险概率和风险损失为需求的相关量.然后,通过实例的仿真求解验证了模型.最后,给出了利用本模型方法进行供应链风险估计时需要注意的问题及进一步研究的问题.研究表明:蒙特卡罗方法对供应链风险估计具有较强的鲁棒性.