基于分段参数型DEA前沿面的投入—产出型技术效率

由传统DEA模型可以直接测算投入固定(产出固定)的条件下,面向产出(投入)的技术效率。尽管加型DEA模型同时考虑了投入和产出的松弛,但却不能像传统模型一样直接测算投入—产出型技术效率。为了直接由加性模型测算投入产出型技术效率,本文将利用DEA有效决策单元建立分段参数型DEA生产前沿面,并根据古典技术效率的定义,解决投入产出型技术效率的测算问题。研究发现,这种效率实质上是产出型技术效率与投入配置效率的乘积。由于同时考虑了投入和产出的技术无效性,与其它类型的技术效率相比,这种投入产出型技术效率的可分性更强。     

供应链前沿生产函数的DEA估计研究

技术效率评价在管理学理论研究与企业市场实践中均具有重要意义,而对技术效率的评价必须立足于对前沿生产函数的估计。供应链管理已经被证实是降低成本以提供更大产品与更好服务的有效方法,然而,对于供应链的前沿生产函数的估计尚未得到研究。这主要是因为两方面研究的缺乏;其一,多产出的生产系统的前沿生产函数估计方法;其二,多阶段的生产系统的前沿生产函数估计方法。本文将提出一种供应链前沿生产函数的估计方法,以解决上述两个主要障碍。有关商业银行运作的实证研究表明,该方法能够估计供应链的前沿生产函数。     

基于非参数投入前沿面的Malmquist生产率指数研究

本文采用生产前沿面理论及其非参数方法,对假定产出确定条件下投入压缩的生产率指数──基于投入前沿面的Malmquist生产率指数进行了理论与测度方法研究。通过规模收益不变且要素自由(C,S)前沿面条件下的技术效率、距离函数及其非参数模型的分析,本文给出了基于非参数(C,S)投入前沿面的Malmquist生产率指数的非参数测度模型,并从技术变化和资源配置效率变化两个方面进行了分解。     

拟凹生产函数的分区域估计

本文提出了规模报酬递增生产前沿面的概念并证明了以下两个结论:(1)基于样本数据的DEA生产投入集可划分为规模报酬递增、不变和递减区域;(2)C-D生产函数是拟凹函数,且在规模报酬递增区域非凹,在规模递减区域严格凹。基于上述结论及对生产函数曲面,BCC生产前沿面,规模报酬递增生产前沿面的相互关系的分析,提出了一种生产函数分区域估计方法:在对样本数据(决策单元)依据规模报酬增减性进行分类的基础上进行投入可能集的分划,进而在规模报酬递减(不变)和递增区域上分别通过决策单元的BCC弱有效投影和规模报酬递增弱有效投影估计生产函数。文末,通过实例验证了估计方法的有效性。     

基于多准则随机DEA模型的投资决策评价方法及应用

在经典DEA模型的基础上,对随机输入、产出指标进行更进一步的分析,增加了多个评价准则,从而提出了多准则随机DEA评价模型。最后,通过在项目投资评价中的运用说明了该模型的实用性。     

考虑交易成本的投资组合效率估计方法

投资组合绩效评价是学术界研究的热点问题。本文在经典的经济学框架下,基于真实前沿面,给出了投资组合效率的明确定义。由于实际投资环境的影响,投资组合优化模型非常复杂,难以获得真实前沿面的解析解,这给投资组合效率的应用带来了很大的困难。本文基于投资组合理论,在投资组合模型所对应的前沿面为凹函数的情况下,采用基于数据的投资组合DEA评价模型构造前沿面来逼近真实的前沿面,从而估计一般情形下投资组合的效率。在此基础上研究了考虑交易成本的投资组合效率评价问题,并用实例说明了本文方法的合理性与可行性。     

基于双前沿面数据包络分析的循环全局Malmquist指数

利用全部时期的技术构成的前沿面为参照,将双前沿面数据包络分析下的Malmquist指数拓展为双前沿面数据包络分析下的全局Malmquist指数。该全局Malmquist指数不仅较好地综合了乐观前沿面和悲观前沿面两部分信息,而且满足循环性检验;不仅可以避免由于前沿面选择的不同而导致的差异,还可以避免因时期选择的任意性而导致的差异。将其用于福建省工业行业2001-2008年的全要素生产率分析,研究结果较好地说明了该方法的有效性和实用性。     

基于AHP/DEA的自然灾害损失评估模型初探

层次分析法(AHP)以及数据包络分析(DEA)的结合使用,可以避免人为设定AHP判断矩阵的主观性和随意性,以及DEA决策单元不能在同一尺度上全排序的缺点.本文探索性地把AHP和DEA模型结合用于自然灾害损失评估中,阐述了基本原理和算法,并且结合实例给出灾害损失排序.     

考虑环境属性约束的平行结构DEA模型

针对平行结构DEA模型在构造虚拟参考单元时没有考虑任何约束可能存在低估效率的情况,通过加入决策单元的环境属性对现有的平行结构模型进行了改进,从而在组合为虚拟参考单元的子决策单元之间添加必要的约束,使得模型所得的效率值更具现实意义。最后,将改进后的平行结构模型应用于中国各省份污染治理效率评价问题,从实证角度验证了模型的合理性和有效性。     

基于偏好DEA模型的中国纺织业效率评价

基于具有输入输出指标偏好信息的数据包络分析模型评价中国纺织工业的效率,给出了描述规模报酬不变和规模报酬可变假设的DEA模型及其对偶规划的一种形式。模型克服传统DEA模型应用中常见的决策单元权重为零进而高估决策单元效率的不合理现象,有效地测算了中国31个地区纺织工业的经济运行效率,并分析了地区间效率水平差异的原因。利用各决策单元在经验生产前沿面上的投影点,估计了中国纺织工业的随机生产前沿函数,最后用效率弹性线性递减模型分析了销售收入、人均资产、台港澳和外商投资对各地区效率的微观影响关系。     

随机环境中的生产作业计划问题

生产系统中通常会涉及各种不确定因素 ,如不确定的顾客定单、不确定的生产作业时间等 .在当今时间竞争非常激烈的时代中 ,生产型企业如何把握生产系统中的这些不定因素变得尤为关键 .本文研究在不确定的作业时间、工序间延迟时间等情况下的生产作业计划问题 ,利用 scenario模型把这类随机生产计划问题归纳为一个多阶段随机决策问题 .进而 ,采用Lagrangian松弛和 scenario分解的方法求解这样一个大型的决策问题 .最后 ,就一个实例建立模型、进行计算和分析 ,以说明本文提出的随机生产计划方法的特点和有效性     

An evaluation of flow-shop scheduling algorithms for makespan reduction in a stochastic environment

This paper addresses the problem of makespan reduction and improvement in related performance measures in the stochastic flow shop. The experimental design addresses the issues of the problem size in terms of the number of jobs and machines, the bottleneck location within the production facility, and the processing time distribution and sensitivity to variance. In other words, many of the assumptions that are typically made in the published literature are violated in favour of a more realistic production basis. Experiments are performed via simulation to examine the performance of several well known flow-shop scheduling algorithms and one new algorithm in this challenging environment. The authors conclude that distributional effects and bottleneck considerations can play a role in the performance of the various algorithms considered. This paper further indicates that the problem size also tends to drive the effectiveness of the scheduling strategies examined, and presents information regarding interesting interaction effects between the problem size and the other elements of experimental concern.     

服务多类需求串行供应链的最优控制策略

研究由一系列生产环节采用串行方式组成多级供应链的最优控制策略.在此供应链中,原材料经过各级生产环节顺序加工形成最终产品.各级生产环节的加工时间服从随机分布.对最终产品存在多类随机需求.在每个时刻,管理者需要决定:1)是否该启动某个生产环节的生产;2)当有需求到达时,是否该满足此需求.管理者期望系统运行的总期望折扣成本最小.构造了该系统的马尔可夫决策模型并深入研究了其最优控制策略及其动态协同特性.在生产策略方面,证明系统的最优生产策略就是对各级生产环节采用动态的基本库存策略.该策略的动态协同特性主要体现在各级生产环节的最优基本库存水平受其他生产环节的库存水平影响.在产品分配方面,证明系统的最优分配策略是动态配给策略.该策略的动态协同特性主要体现在每类随机需求最优配给水平受各级生产环节的库存水平影响.     

An algorithm to dynamically adjust the number of Kanbans in stochastic processing times and variable demand environment

In a real-life environment, the just-in-time JIT system is subjected to various types of uncertainties such as stochastic processing times and variable demand. Since, JIT was only meant to operate in a deterministic environment, its performance is seriously affected by variations in processing times and demand. In this paper, a newly developed Kanban system is presented which uses an algorithm to dynamically and systematically manipulate the number of Kanbans in order to offset the blocking and starvation caused by the said uncertainties during a production cycle. The new system is termed a flexible Kanban system FKS . The steps of the algorithm are detailed and the effectiveness of FKS is demonstrated using an example model. For the example model, the solution procedure, results and a discussion are presented.     

Multi-valued measures in DEA in the presence of undesirable outputs

Data envelopment analysis (DEA) evaluates the relative efficiency of a set of comparable decision making units (DMUs) with multiple performance measures (inputs and outputs). Classical DEA models rely on the assumption that each DMU can improve its performance by increasing its current output level and decreasing its current input levels. However, undesirable outputs (like wastes and pollutants) may often be produced together with desirable outputs in final products which have to be minimized. On the other hands, in some real-world situations, we may encounter some specific performance measures with more than one value which are measured by various standards. In this study, we referee such measures as multi-valued measures which only one of their values should be selected. For instance, unemployment rate is a multi-valued measure in economic applications since there are several definitions or standards to measure it. As a result, selecting a suitable value for a multi-valued measure is a challenging issue and is crucial for successful application of DEA. The aim of this study is to accommodate multi-valued measures in the presence of undesirable outputs. In doing so, we formulate two individual and summative selecting directional distance models and develop a pair of multiplier- and envelopment-based selecting approaches. Finally, we elaborate applicability of the proposed method using a real data on 183 NUTS 2 regions in 23 selected EU-28 countries.     

Optimizing lot size and setup time in a JIT environment: a multiple objective application

The just-in-time (JIT) system has been studied extensively and implemented by a number of US firms as an ell'ective production system. The core of JIT involves determination of lot size and setup time reduction so as to increase manufacturing flexibility while minimizing the inventory level. This decision problem usually involves multiple conflicting objectives and mixed-model production. In this paper, goal programming (GP) is applied to a real-world JIT problem involving fabrication of different automotive and industrial rubber composite belts. The model results provide new insights concerning the conflicting nature of several goals, especially between meeting demand and reducing setup or idle time. Also, the GP solution is superior to the current JIT practice of the company.     

Single vs. multiple objective supplier selection in a make to order environment

The problem of allocation of orders for custom parts among suppliers in make to order manufacturing is formulated as a single- or multi-objective mixed integer program. Given a set of customer orders for products, the decision maker needs to decide from which supplier to purchase custom parts required for each customer order. The selection of suppliers is based on price and quality of purchased parts and reliability of on time delivery. The risk of defective or unreliable supplies is controlled by the maximum number of delivery patterns (combinations of suppliers delivery dates) for which the average defect rate or late delivery rate can be unacceptable. Furthermore, the quantity or business volume discounts offered by the suppliers are considered. Numerical examples are presented and some computational results are reported.     

大数据背景下商务管理研究若干前沿课题

鉴于市场创新对于企业发展的重要性及已有研究的不足,在界定市场创新概念和特征的基础上,区分探索式和开发式两种创新方式,遵循行为/能力-地位-绩效的理论逻辑,构建以市场创新(探索式和开发式)-地位(低成本优势和差异化优势)-绩效为主线的概念模型,分析不同创新方式的作用机理;基于配置理论提出市场竞争强度的调节作用,从交互和匹配的双重视角重点阐释两种方式的二元平衡关系;基于297家中国企业的调研数据,利用多元层级回归检验研究假设.研究结果表明,探索式和开发式两种市场创新方式均显著提升企业绩效,但是作用机理不同,前者主要促进差异化优势,后者主要建立低成本优势;市场竞争强度正向调节探索式创新与绩效的关系,负向调节开发式创新与绩效的关系;与技术创新一样,市场创新的两种方式也存在二元平衡,具体表现为探索式和开发式市场创新正向交互影响绩效.因此,企业在进行技术创新的同时也要重视市场创新,根据不同的市场环境侧重选择合适的创新方式,并学会合理分配资源,避免追求单一创新方式的负面效应.     

大数据背景下商务管理研究若干前沿课题

从商务管理在大数据背景下所面临的时代挑战出发,给出了社会化的价值创造、网络化的企业运作、实时化的市场洞察三个重要研究视角.同时,描述了社会化网络环境中的行为机理与社会资本结构、企业网络生态系统及其协同共生机制、大数据环境下的顾客洞察与市场营销策略、基于大数据的商业模式创新等研究方向,讨论了若干重要的研究课题.