销售努力与质保服务联合决策的供应链模型

以单一制造商和单一零售商组成的两级供应链为对象考虑随机需求下产品需求同时受到销售努力和质保期长度影响,研究由零售商提高销售努力因素及制造商提供质保服务情形下的供应链模型并提出了共同分摊销售努力和质保成本及收益共享契约下的供应链协调策略.其次,研究发现通过相应的供应链参数设计,基于销售努力及质保成本共担同时收益共享的契约能实现供应链的协调.最后,给出了数值算例对模型进行仿真计算与分析.     

考虑溢出效应的纵向合作广告契约

为研究经销商间广告溢出对供应链成员广告决策的影响.运用委托代理理论分析了考虑经销商广告溢出时制造商和经销商纵向合作广告契约.研究发现:信息不对称下的制造商全国广告投资努力、经销商地区广告投资努力、广告补贴及制造商收益均次优;伴随广告溢出的增大,制造商和经销商均搭广告溢出"便车"降低努力水平,制造商提高经销商的利润分成、降低广告补贴.不论信息对称与否,广告溢出的增大都能提高制造商收益.还讨论了广告弹性对合作广告的影响.     

基于规模不经济和网络外部性的捆绑手机供应链定价决策

考虑网络外部性和规模不经济的影响,对捆绑手机供应链的决策展开研究.构建了捆绑手机供应链的分散决策模型和集中决策模型,并对模型进行了比较分析.研究表明:1)规模不经济系数会阻碍系统利润的增长,而网络外部性系数促进系统利润的增长.2)手机制造商或电信运营商主导系统时所获利润远高于其不主导系统时的情形.同时手机制造商主导系统时,系统的利润要高于电信运营商主导系统时的利润.3)在分散决策下,手机制造商和电信运营商的利润均未达到最优:集中决策下,合约机套餐价格较低,总的销量更高,系统的利润更高.通过“补贴联合收益共享”协调契约,可以实现手机制造商和电信运营商的收益最大化.     

随机需求下考虑公平偏好的合作广告协调模型

在随机需求下,运用Fehr和Schmidt提出的公平偏好理论模型探讨了供应链合作广告协调问题,其中零售商具有利己和利他公平偏好.在批发价格契约下分析了零售商的公平偏好对订购和广告策略及渠道协调的影响,结果表明:除了一个测度为零的空间之外,批发价格契约不能协调供应链.设计了能协调供应链的收益共享和广告成本分担契约,并刻画了要完成渠道协调,契约参数须满足的充要条件.研究表明:1)在零售商具有利己公平偏好下,收益共享契约虽能协调供应链,但不能实现渠道收益的任意分配;2)若零售商的利他公平偏好较强,则能协调供应链(实现供应链期望利润最大化)的契约未必是帕累托最优契约,能实现公平分配的协调契约才是最优契约;3)在渠道协调下,零售商的利己和利他公平偏好对其效用均有负面影响.最后利用数值分析验证了相关结论.     

考虑运输时间和消费者偏好的水产品供应链协调研究

本文研究了由一个供应商和一个零售商组成的两级生鲜品供应链协调问题。考虑消费者水产品生鲜偏好、运输时间和保鲜努力水平等影响因素,分别构建了集中决策和分散决策下冷链保鲜存储的零售商和供应商的供应链成员之间Stackelberg博弈模型。通过理论证明和数值仿真的研究表明,在“保鲜成本分担+收益共享”契约,供应链总体利润大于一般保鲜成本共担契约,能获得更高的利润,“保鲜成本分担+收益共享”契约更能提高冷链储存的保鲜努力水平。     

规模不经济下基于一致定价和促销努力的双渠道供应链协调策略

在制造商存在规模不经济环境下,分别针对集中决策模式和分散决策模式,建立了基于一致定价和促销努力的双渠道供应链协调策略模型,分析了规模不经济和服务负溢出效应对供应链运营决策的影响,得到了集中和分散决策下各企业最优运作策略和收益。研究指出,规模不经济的双渠道供应链在分散决策批发价契约下无法实现供应链协调;而分散决策网络渠道收益共享契约能够实现双渠道总收益等于集中决策模式下供应链收益,但无法保证各主体始终获得高于批发价合同下的收益;进一步,设计了带有固定补偿的网络渠道收益共享契约,通过对固定补偿值的有效设计,不仅可以保证双渠道总收益等于集中决策模式下供应链收益,且可以始终保证各主体收益不低于分散决策批发价契约下其所得收益,从而实现各主体利益双赢以及供应链的有效协调。     

风险厌恶下的供应链收益共享契约协调模型研究

收益共享契约是实现供应链系统绩效改善或完美协调的一种机制.考虑了零售商与供应商分别具有风险厌恶决策偏好情况下,在随机市场需求下建立了由单供应商和单零售商组成的二级供应链的收益共享契约模型,并对模型进行了分析,揭示了供应商和零售商的风险厌恶决策偏好对收益共享契约参数的影响.研究结果表明:当销售商(供应商)的风险厌恶控制在...     

需求与销售努力相关下混合渠道供应链协调研究

建立了由一个制造商和一个分销商组成的混合渠道供应链模型,考虑了产品需求量与分销商的销售努力相关时,混合渠道供应链中分销商的订货量、销售努力的契约协调问题。并通过改进的收入共享契约使混合渠道供应链达到了分销商订货量和销售努力的同时协调。并进行了算例分析,比较了传统渠道供应链及混合渠道供应链以及供应链成员的利润变化情况,分析结果表明在一定契约参数条件下,制造商增加电子渠道对供应链及供应链成员都是有益的。     

需求依赖价格、广告投人和质量控制的供应链模型

研究了需求受零售商销售价格和广告投入以及制造商质量控制影响的供应链协调问题,分析了零售商的广告投入以及制造商的质量控制对市场需求的影响,分别给出了集中决策和分散决策下零售商的最优销售价格、最优订购量和最优广告投入努力水平以及制造商的最优质量控制努力水平和最优批发价格,利用了特许经营契约来使供应链达到完美协调.最后,通过数值算例对模型进行仿真计算与分析.     

模糊环境下零售商竞争的供应链协调研究

本文对模糊环境下两个竞争零售商供应链系统的最优决策及协调问题进行了研究。首先分析比较了在一体化决策和分散化决策下受模糊变量影响的两竞争零售商的最优决策,然后提出了收益共享契约协调模型,并通过模型求解得到了收益共享契约成立的条件,结果表明收益共享契约成立不仅与收益参数有关,还与生产成本c、需求价格弹性系数βi(i=1,2)和市场规模ai(i=1,2)的期望值以及生产成本c和竞争对手需求价格弹性β2的乐悲观值有关。最后通过数值实验分析了收益参数及模糊变量取值对收益共享契约模型中供应链系统各成员期望利润的影响。     

Productive and ineffective efforts: how student effort in high school mathematics relates to college calculus success

Relativizing the popular belief that student effort is the key to success, this article finds that effort in the most advanced mathematics course in US high schools is not consistently associated with college calculus performance. We distinguish two types of student effort: productive and ineffective efforts. Whereas the former carries the commonly expected benefits, the latter is associated with negative consequences. Time spent reading the course text in US high schools was negatively related to college calculus performance. Daily study time, however, was found to be either a productive or an ineffective effort, depending on the level of high school mathematics course and the student's performance in it.     

考虑衍生需求和粉丝效应的视频服务供应链质量努力策略研究

视频服务作为“互联网+”时代下的新型文化产业模式,日益受到人们的关注。本文构建一个视频服务平台和一个视频服务提供商组成的视频服务供应链,视频服务提供商通过视频服务平台向用户提供基础服务和两阶段衍生服务。考虑视频服务供应链成员的四种行为因素对服务需求的影响,并分别建立平台定价模式和提供商定价模式下服务供应链成员的利润函数,运用博弈理论,优化求解得到两种模式下服务供应链成员最优的质量努力策略和利润。最后,通过数值仿真,探讨了粉丝效应和收益分成比例与最优质量努力策略和最优利润的相关性,并得出相关结论,给出管理启示。     

变捕捞努力量收获模型控制

利用微分包含给出了努力量可变的收获模型,基于生存理论和求解线性规划给出了将单种群数量控制在某范围的方法.最后对于常用的Logistic模型,证明只要控制努力量就可以将种群数量控制在指定范围内.     

供应中断风险下制造商的后备采购与改善努力策略比较研究

在供应中断风险环境下,对制造商的后备采购策略和改善努力策略进行了比较分析.研究发现,制造商在改善努力策略时向主供应商的采购数量恒大于在后备采购策略时的采购数量.改善努力与后备采购策略的收益差总是随着改善努力成本投入的增大而呈现出递减的规律.当努力成本投入变得不经济时,制造商将放弃对主供应商的改善努力.     

Effort Games and the Price of Myopia

We consider Effort Games, a game‐theoretic model of cooperation in open environments, which is a variant of the principal‐agent problem from economic theory. In our multiagent domain, a common project depends on various tasks; carrying out certain subsets of the tasks completes the project successfully, while carrying out other subsets does not. The probability of carrying out a task is higher when the agent in charge of it exerts effort, at a certain cost for that agent. A central authority, called the principal, attempts to incentivize agents to exert effort, but can only reward agents based on the success of the entire project. We model this domain as a normal form game, where the payoffs for each strategy profile are defined based on the different probabilities of carrying out each task and on the boolean function that defines which task subsets complete the project, and which do not. We view this boolean function as a simple coalitional game, and call this game the underlying coalitional game. We suggest the Price of Myopia (PoM) as a measure of the influence the model of rationality has on the minimal payments the principal has to make in order to motivate the agents in such a domain to exert effort. We consider the computational complexity of testing whether exerting effort is a dominant strategy for an agent, and of finding a reward strategy for this domain, using either a dominant strategy equilibrium or using iterated elimination of dominated strategies. We show these problems are generally #P‐hard, and that they are at least as computationally hard as calculating the Banzhaf power index in the underlying coalitional game. We also show that in a certain restricted domain, where the underlying coalitional game is a weighted voting game with certain properties, it is possible to solve all of the above problems in polynomial time. We give bounds on PoM in weighted voting effort games, and provide simulation results regarding PoM in another restricted class of effort games, namely effort games played over Series‐Parallel Graphs (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Recursions for the Individual Risk Model

In the actuarial literature,several exact and approximative recursive methods have been proposedfor calculating the distribution of a sum of mutually independent compound Bernoulli distributed randomvariables.In this paper,we give an overview of these methods.We compare their performance with the straight-forward convolution technique by counting the number of dot operations involved in each method.It turns outthat in many practicle situations,the recursive methods outperform the convolution method.     

Discrete Mobile Centers

   Abstract. We propose a new randomized algorithm for maintaining a set of clusters among moving nodes in the plane. Given a specified cluster radius, our algorithm selects and maintains a variable subset of the nodes as cluster centers. This subset has the property that (1) balls of the given radius centered at the chosen nodes cover all the others and (2) the number of centers selected is a constant-factor approximation of the minimum possible. As the nodes move, an event-based kinetic data structure updates the clustering as necessary. This kinetic data structure is shown to be responsive, efficient, local, and compact. The produced cover is also smooth, in the sense that wholesale cluster re-arrangements are avoided. This clustering algorithm is distributed in nature and can enable numerous applications in ad hoc wireless networks, where mobile devices must be interconnected to perform various tasks collaboratively.     

Discrete Mobile Centers

Abstract. We propose a new randomized algorithm for maintaining a set of clusters among moving nodes in the plane. Given a specified cluster radius, our algorithm selects and maintains a variable subset of the nodes as cluster centers. This subset has the property that (1) balls of the given radius centered at the chosen nodes cover all the others and (2) the number of centers selected is a constant-factor approximation of the minimum possible. As the nodes move, an event-based kinetic data structure updates the clustering as necessary. This kinetic data structure is shown to be responsive, efficient, local, and compact. The produced cover is also smooth, in the sense that wholesale cluster re-arrangements are avoided. This clustering algorithm is distributed in nature and can enable numerous applications in ad hoc wireless networks, where mobile devices must be interconnected to perform various tasks collaboratively.     

一直在努力?——基金管理者买卖行为的有效性分析

通过构建收益缺口-基金的净资产收益与投资组合收益之差,探讨了我国证券市场中开放式基金管理者的买卖行为及其对基金业绩的影响.研究结果表明,在2004至2007年中,基金月收益缺口的均值显著大于零,表明基金管理者的努力总体上能增加基金的价值;投资者若模拟基金的股票构成进行投资,在熊市中,其平均回报小于基金的收益,但在牛市中,却显著地大于基金的收益,这一差异对配置型基金更明显.同时,基金收益缺口的大小与基金的类型和规模显著相关.     

Inventory and sales effort management under unobservable lost sales

A retailer needs to make decisions regarding how much to order and how much sales effort to exert in an environment with uncertain demand. One intrinsic complexity in a typical retail environment is caused by the fact that the retailer can obtain information about demand only based on sales, as demand itself is unobservable. Taking a Bayesian approach, Lariviere and Porteus (1999) show that in such a setting a retailer should stock more to increase the probability of an exact demand observation. In this article, we extend their work by allowing the retailer to control both the stocking quantity and sales effort, which can be used to affect demand. We show that their insights with respect to information stalking carry over to this setting. In addition, our model allows gaining a better understanding of optimal sales effort strategies. We find that demand management has a dual role in supporting information gathering: while at the beginning of a product life cycle it is optimal to support learning effects by sharply reducing sales effort, at later stages of the product life cycle an aggressive strategy of increased promotional activities can be used to harvest the information gathered in earlier periods.