企业社会责任对供应链减排决策及政府补贴效率的影响研究

为了探讨零售商企业社会责任(CSR)对供应链减排决策及政府补贴效率的影响,构建了包含政府决策者的三阶段博弈模型。通过对均衡结果的分析表明：(1)随着零售商CSR实施水平的增强,制造商的减排程度、制造商的利润和社会福利将提高,但对零售商的利润和供应链整体利润的影响还取决于制造商减排努力系数的大小。(2)政府补贴可以提高制造商的减排程度和渠道成员的利润。而零售商CSR实施水平的增强能够改善政府单位补贴效率,使得政府补贴促进制造商减排和利润提升的效果更显著。当零售商CSR实施水平较低时,CSR实施水平的增强同样会导致政府补贴对零售商利润的提升效果更为显著。此外,本文设计了一种二部定价-成本分担契约,证明了该契约可以实现供应链协调。在此基础上,将研究扩展到制造商实施CSR的情形及政府新目标的情形,通过理论及数值分析,详细探讨了CSR行为对供应链减排决策的影响,为政府及低碳供应链的相关决策提供参考。     

创新驱动下新零售服务供应链质量协同改进的稳态策略

技术和消费的“双升”加快了新零售服务供应链的形成和产生,同时也通过驱动其质量系统的协同改进及动态演化实现持续的发展。本文从创新驱动质量的动态视角,分析创新驱动下新零售服务供应链中多主体协同质量改进的运行机制和动态演化过程,运用演化博弈方法分析构建多主体协同的动态演化博弈模型,以此分析新零售服务供应链协同质量改进中各参与主体的博弈策略选择,并利用雅克比矩阵判断其策略稳定性。研究表明：在多元参与主体利益诉求得到满足的前提下,多主体协同质量改进能够保持系统稳定状态;多主体间的质量势差与协同质量改进稳定性呈现出反比关系;良好的质量协同效应、独立的内部监督机制等能有效的促进协同质量改进系统稳定。     

实报还是谎报——双边信息激励与供应链效率

探讨了双边不对称信息下供应链信息真实分享和谎报对效率的影响。首先,给出完全信息下的最优商品交易量和供应链利润作为比较基准。其次,构建双方信息真实分享的激励模型。研究发现激励双方信息真实共享所需的信息租金降低交易量和供应链利润。再次,构建允许信息谎报的交易量谈判模型。研究发现,供销双方都偏好高报自己的信息类型。个体谎报信息的幅度随着谈判力增加而减小。拥有绝对谈判力的一方不会谎报信息。供应链效率与谎报信息的幅度、成本上界以及销售价格相关。最后,通过数值算例对实报信息和谎报信息下交易量、供应链个体利润及效率进行对比分析。研究结果为管理实践提供一定的洞见:供应链企业是否激励双边信息分享可根据双方成本大小进行选择。     

生鲜产品供应链最优化决策综述与拓展建议

生鲜产品具有强时效、低残值、高随机的特点。为综合了解生鲜产品企业的优化决策及其供应链的契约协调,采用文献归纳法,综述生鲜产品的易逝性刻画方法、生鲜企业的优化决策模型、以及渠道契约协调机制,并分析进一步可以拓展的研究方向。拓展建议有三点,一是将市场或消费者因素纳入变质率函数;二是寻找全链保鲜投入和终端货架服务与成本效益的均衡点:三是设计兼具收益共享和成本分担功能的契约机制。     

要素禀赋、农户分化与农业价值链技术选择偏向

基于551份猕猴桃种植户调研数据,通过聚类分析方法将猕猴桃种植户分成发展型、规模种植型、劳动力富裕型三类,实证检验种植户类型对有机肥施用、新品种采纳、猕猴桃网络销售三个价值链技术活动选择的异质偏向性,分析农机补贴、产业组织检测、技术培训三个组织支持变量的调节效应。结果发现：发展型对于三个价值链技术活动及其联合采纳的选择偏向性高于其他类型,劳动力富裕型种植户对价值链技术活动的选择偏向性低于其他两个类型种植户。三个组织支持变量对同一类型种植户参与不同价值链技术活动以及不同类型种植户参与同一价值链技术活动的影响具有异质性。因此,针对不同类型价值链技术活动参与特征以及组织支持调节作用提出相应的政策建议。     

论秦汉铜器的一体化

秦汉铜器的一体化可划分为秦至汉初、西汉中期至晚期前段、西汉晚期后段至东汉三个阶段。第一阶段的一体化主要体现在打破了先秦族群铜器文化独立发展的格局,与秦汉帝国的统一和建立有关。第二阶段主要为铜礼器的一体化,与汉武帝的铜政即工官专控有关。第三阶段主要为实用器具的一体化,与铜器制作的放开、私家作坊的涌现所导致的产品商业化有关。不同阶段的铜器一体化程度不同：秦至汉初处于雏形阶段,西汉中期至晚期前段进程加速,西汉晚期后段至东汉得到进一步加强。     

产品质量差异与需求不确定双因素下的双渠道供应链分销策略选择

在考虑产品质量差异与需求不确定双因素影响的基础上,通过构建垂直Nash定价与库存联合博弈模型,研究当线上与线下双渠道销售特定异质产品时,供应链成员如何根据不同的产品类型选择最优分销策略以实现双渠道供应链的共赢。研究结果表明:对于质量差异化低且需求不确定性低的产品类型,供应链成员的共赢分销策略是在线下渠道销售低质量产品并在线上渠道销售高质量产品;对于质量差异化低且需求不确定性高的产品类型,共赢分销策略是在线下销售高质量产品并在线上销售低质量产品;当制造商采用“做坏品”质量差异化策略时,产品类型和分销策略之间的最佳匹配依然保持稳健。     

Dynamic reliability models with conditional proportional hazards

A dynamic approach to the stochastic modelling of reliability systems is further explored. This modelling approach is particularly appropriate for load-sharing, software reliability, and multivariate failure-time models, where component failure characteristics are affected by their degree of use, amount of load, or extent of stresses experienced. This approach incorporates the intuitive notion that when a set of components in a coherent system fail at a certain time, there is a jump from one structure function to another which governs the residual lifetimes of the remaining functioning components, and since the component lifetimes are intrinsically affected by the structure function which they constitute, then at such a failure time there should also be a jump in the stochastic structure of the lifetimes of the remaining components. For such dynamically-modelled systems, the stochastic characteristics of their jump times are studied. These properties of the jump times allow us to obtain the properties of the lifetime of the system. In particular, for a Markov dynamic model, specific expressions for the exact distribution functions of the jump times are obtained for a general coherent system, a parallel system, and a series-parallel system. We derive a new family of distribution functions which describes the distributions of the jump times for a dynamically-modelled system.     

Sample selection in radiocarbon dating

Archaeologists working on the island of O'ahu, Hawai'i, use radiocarbon dating of samples of organic matter found trapped in fish-pond sediments to help them to learn about the chronology of the construction and use of the aquicultural systems created by the Polynesians. At one particular site, Loko Kuwili, 25 organic samples were obtained and funds were available to date an initial nine. However, on calibration to the calendar scale, the radiocarbon determinations provided date estimates that had very large variances. As a result, major issues of chronology remained unresolved and the archaeologists were faced with the prospect of another expensive programme of radiocarbon dating. This paper presents results of research that tackles the problems associated with selecting samples from those which are still available. Building on considerable recent research that utilizes Markov chain Monte Carlo methods to aid archaeologists in their radiocarbon calibration and interpretation, we adopt the standard Bayesian framework of risk functions, which allows us to assess the optimal samples to be sent for dating. Although rather computer intensive, our algorithms are simple to implement within the Bayesian radiocarbon framework that is already in place and produce results that are capable of direct interpretation by the archaeologists. By dating just three more samples from Loko Kuwili the expected variance on the date of greatest interest could be substantially reduced.     

Application of Markov chain Monte Carlo methods to modelling birth prevalence of Down syndrome

Data collected before the routine application of prenatal screening are of unique value in estimating the natural live-birth prevalence of Down syndrome. However, much of these data are from births from over 20 years ago and they are of uncertain quality. In particular, they are subject to varying degrees of underascertainment. Published approaches have used ad hoc corrections to deal with this problem or have been restricted to data sets in which ascertainment is assumed to be complete. In this paper we adopt a Bayesian approach to modelling ascertainment and live-birth prevalence. We consider three prior specifications concerning ascertainment and compare predicted maternal-age-specific prevalence under these three different prior specifications. The computations are carried out by using Markov chain Monte Carlo methods in which model parameters and missing data are sampled.