VMI对供应链性能的影响分析

建立了分散式供应链和VMI模式供应链的模型,比较了两种模式供应链的性能,研究表明在缺乏有效的协作机制的情况下,VMI的优势不能得到有效的发挥,提出了进一步提高VMI模式供应链性能的有效途径,最后给出了数值算例对结论进行了验证。     

电子化供应链管理实施方法研究

首先总结e化供应链的特征,分析了e化供应链与传统供应链的区别,然后对e化供应链管理的实施模式进行了总结、分析和对比,在此基础上提出了基于Web Service的e化供应链的一体化解决方案,最后对基于该方案的e化供应链的实施过程进行了论述。     

销售商的努力影响需求变化的供应链的合约

本文首先重新考察报童模型,认识设计使供应链达到合作的合约的内在机制。在此基础上,提出一个设计供应链合约的一般模型,然后利用此模型分析在销售商的努力影响需求变化的情形下使供应链达到合作的合约的设计框架,同时提出一个在销售商的努力影响需求变化的情形下使供应链达到合作的合约。     

供应链环境下合作预测效果的分析

本文定量分析了供应链中合作预测对需求长鞭效应的减小作用,在多节点企业所组成的供应链中,合作预测对订单量的波动和需求预测误差的波动起到积极的抑制作用。本文通过理论研究和数值分析的结果表明,供应链信息共享和合作预测能够控制需求流动现象。     

大型供应链设计的基本数学模型与算法研究

随着信息技术与全球经济一体化的发展,供应链管理成为全球管理科学的研究热点。本文在分析国内外各种关于供应链设计的数学模型与算法的基础上,提出了具有普遍性意义且简单易行的MIP供应链设计的数学模型以及求解供应链问题的有界变量广义上界算法。实例计算表明,提出的模型和方法是可靠实用的。     

重庆汽车产业全产业链发展的现状与思考

重庆作为中国汽车产业都城之一,经过多年发展,汽车产业全产业链不断完善,品牌竞争力不断增强,但同时也出现了诸如产业链不紧密、创新能力不强等现实问题,这为研究重庆汽车产业全产业链提出了迫切要求。文章通过实证分析方法,分析重庆汽车产业全产业链发展现状,从理论与实践角度提出进一步完善重庆汽车产业全产业链的建议。     

县级政府、供应链管理与农产品上行关系研究

基于中国13省87个电子商务进农村示范县的调研材料,分析政府项目驱动下农产品上行问题。实践表明,政策利好为县域农产品电商发展提供了试错空间,“S2B2C”的供应链管理模式对农产品上行的推动作用明显。但是,多数县级政府未能认识到供应链管理之于农产品上行的作用,普遍存在政府治理方式滞后、公共服务网络不健全、农产品区域公用品牌缺乏、冷链等基础设施投入不足等问题。因此,为有效推动农产品上行,政府应进一步推动“公私合作”、构建一体化的公共服务、注重品牌营销、优化产品供应链管理。     

A new test for multivariate normality by combining extreme and nonextreme BHEP tests

In this article, we propose a new multiple test procedure for assessing multivariate normality, which combines BHEP (Baringhaus–Henze–Epps–Pulley) tests by considering extreme and nonextreme choices of the tuning parameter in the definition of the BHEP test statistic. Monte Carlo power comparisons indicate that the new test presents a reasonable power against a wide range of alternative distributions, showing itself to be competitive against the most recommended procedures for testing a multivariate hypothesis of normality. We further illustrate the use of the new test for the Fisher Iris dataset.     

Bayesian adjustment for unidirectional misclassification in ordinal covariates

In this paper, we study the identification of Bayesian regression models, when an ordinal covariate is subject to unidirectional misclassification. Xia and Gustafson [Bayesian regression models adjusting for unidirectional covariate misclassification. Can J Stat. 2016;44(2):198–218] obtained model identifiability for non-binary regression models, when there is a binary covariate subject to unidirectional misclassification. In the current paper, we establish the moment identifiability of regression models for misclassified ordinal covariates with more than two categories, based on forms of observable moments. Computational studies are conducted that confirm the theoretical results. We apply the method to two datasets, one from the Medical Expenditure Panel Survey (MEPS), and the other from Translational Research Investigating Underlying Disparities in Acute Myocardial infarction Patients Health Status (TRIUMPH).     

A delay-in-payment contract for Pareto improvement of a supply chain with stochastic demand

We consider a supply chain consisting of a single supplier and a single retailer with stochastic customer demand, which is operated over an infinite horizon. We propose a delay-in-payment contract to coordinate the supply chain. With this contract, the supplier allows the retailer to pay partial order cost at the ordering epoch, and to pay the remaining portion after a permissible number of periods. The system is formulated as a stochastic dynamic programming problem. It is shown that there exists a base-stock policy to be optimal. Compared with the traditional wholesale-price contract, the delay-in-payment contract with appropriate parameters can achieve a Pareto improvement (i.e., the performances of both the supplier and the retailer using the delay-in-payment contract are better than those using the wholesale-price contract). Numerical studies are performed to investigate both the effectiveness of the Pareto improvement, and the impact of the major parameters of the delay-in-payment contract on the system performance.