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。     

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.     

一类供应链的线性转移支付激励机制研究

针对不同的供应链设计不同的契约是供应链协作的一个重要手段。在由一个零售商和一个供应商组成的供应链中,零售商的促销努力水平对供应链的效率有重大的影响,本文提出了一种线性转移支付激励机制,且证明了在该机制的作用下,零售商将付出对整个供应链最优的促销努力水平,这时供应链的总收益将得到提高,而对新增收益的划分则取决于供应商和零售商之间的讨价还价能力。     

多分销中心供应链模型及其牛鞭效应的H∞控制

本文在文^[1]具有一个分销中心供应链模型的基础上,建立了具有多个分销中心的供应链结构模型,采用供应链上游库存与订货偏差波动之和与下游顾客需求偏差波动之比描述牛鞭效应。提出顾客末端需求波动最差条件下H_∞控制方法,以抑制牛鞭效应。这一方法本质就是供应链末端需求波动最差情况下,制定供应链管理的最优决策。并且以一个石油分销系统为对象进行了供应链牛鞭效应的H_∞控制仿真实验。