带偏好的区间DEA模型及其应用

在对DEA方法归纳总结的基础之上,针对现有区间DEA模型不能体现决策者对各输入指标的偏好这一局限性,提出了带偏好的区间DEA模型,并利用带偏好的区间DEA方法建立了航空武器装备项目评价模型,进行了实例研究,说明了该模型的具体用法和应用前景.     

重视熵权的供应商选择DEA/TOPSIS联合方法

通过分析和总结供应链环境下战略供应商评价选择的准则、指标和方法,以供应链核心企业选择战略性供应商为目标,提出了战略性供应商评价的指标体系.研究了一种新的DEA模型,首先利用熵权法为各指标确定一个权重,然后利用线性加权方法将其与C2R模型的自由权重合成生成综合权重,并使用DEA/TOPSIS联合方法解决供应商选择问题,克服了DEA法与TOPSIS法单独应用时各自存在的不足.实证分析证明了该模型及方法的有效性,并为重视熵权的DEA/TOPSIS联合法在多目标规划中的运用提供了依据与参考.     

基于DEA的我国房地产业效率研究

本文通过运用DEA的C2R模型和DEA交叉评价方法对上市的具有比较典型代表意义的15家房地产公司进行评价,发现其中大部分位于中间规模的房地产行业都具有比较高的DEA效率值,而规模很大的企业则存在着一定的资源浪费,规模小的几家企业则远没取得行业平均收益率,本文对此展开分析并提出了些解决问题的建议。     

基于偏好型DEA的企业技术创新能力评价

在对企业技术创新能力评价方法评述的基础上,通过分析和比较不同的指标,建立了具有可操作性的评价指标体系.利用带偏好的数据包络分析方法建立了企业技术创新能力评价模型,并进行了实例验算,结果表明偏好型数据包络分析方法直观性好、可比性强,不仅可以科学地评价企业的技术创新状态,而且可以通过投影分析进行原因诊断,有利于企业管理者制定有效的技术创新战略.     

基于DEA的汽车工业企业投资有效性分析

运用数据包络分析方法，建立了我国主要汽车制造企业投资相对有效性的评价模型。该模型测算了各企业的总体效率、纯技术效率、纯规模效率及其规模效益状况，并且利用“投影”分析，对非DEA有效的决策单元(DMU)的投入产出值进行了调整，使之达到相对有效。文章进而结合DEA改进值，对非DEA有效的企业提出使其达到DEA有效的可行措施，同时分析了企业经营效率与资源配置效率之间的关系，为企业管理者进行科学决策提供依据和参考。     

基于个体偏好的老年橱柜物品收纳策略

目的 解决老年人厨房物品在橱柜系统收纳时个体偏好存在不确定性致使获取的收纳偏好存在偏差的问题,提出基于个体偏好的橱柜物品收纳策略.方法 首先,通过启发式访谈获取橱柜物品收纳的需求信息,因子分析提取需求核心因素,构建需求层级结构;其次,提出需求层级中收纳区域规划存在偏好的不确定性,通过对直接问询、联合分析及入户观察分别获取的收纳偏好进行比较分析,识别偏好中的不确定成分,通过一致性评判得出更为准确的偏好信息;最后,采用产品轮廓法将不同方法获取的收纳偏好信息转换为收纳区域划分方案,通过受测者评价,提炼出个体层面最优收纳区域划分方案;结论 单独采用主观直接问询或客观定量联合分析法,都不能准确获取老年橱柜物品收纳偏好,通过采用一致性评判的方法路径将多种方法得出偏好结果进行分析,可以更准确地获取老年橱柜区域划分需求偏好,为老年橱柜储物功能设计提供启发与参考.     

基于DEA的机械设备制造业上市公司效率评价

本文以国内较出名的机械设备制造业的上市公司为例,建立DEA模型分析各公司的总体效率、技术效率、规模效率;分析各上市公司在资源配置和效率的特点,对在DEA模型中非有效的企业提出改善意见。     

加工企业食品质量安全互惠偏好行为研究——以HACCP认证加工水产品为例

以HACCP认证加工水产品为例,基于实验经济学方法探究了企业规模经济和食品安全法治环境对水产品加工企业社会偏好行为的影响机理。研究结果发现:第一,水产品加工企业具备“责任”与“盈利”的双重属性,其社会偏好行为属于互惠偏好行为类型。第二,企业规模经济和食品安全法治环境均可促进该类加工水产品市场价值的实现,进而激励其更好地采用HACCP认证体系,完善水产品加工企业安全生产中的互惠偏好行为。第三,不同规模经济条件下,食品安全法治环境对水产品加工企业互惠偏好行为影响效果呈现差异性。当企业实现适度规模经济时,食品安全法治环境对水产品加工企业互惠偏好行为影响较大;当企业规模不经济或规模经济过度实现时,食品安全法治环境对水产品加工企业互惠偏好行为影响较小。     

基于内容分析法的阅读类APP用户使用偏好研究

目的 通过对阅读类APP的用户评价文本进行语意分析,挖掘用户的潜在需求和使用偏好,为此类产品提供优化设计方向。方法 通过内容分析法进行用户使用偏好研究。首先选择一些评分较高的阅读类APP的用户评价,对文本进行归纳和整理。其次利用ROST CM6软件对用户评价文本进行语句的拆解和词频的计算。再对用户的需求进行编码和排序,量化分析用户在使用阅读类APP时的偏好度,明确优化设计方向,构建阅读类APP的偏好模型,并对模型结果进行应用和验证。结论 通过阅读类APP用户评价可以定性分析用户对产品的满意度,定量挖掘用户潜在的需求和偏好,从而明确此类产品的优化设计方向,培养用户养成良好的阅读习惯,提高其阅读质量,最终提升用户的使用效率和满意度。     

直觉模糊环境下考虑用户动态偏好的云服务选择方法研究

云制造平台上集中了大量云服务,如何为没有专业知识的用户选择合适的云服务是一个重要的挑战。云服务选择过程中,当用户处在产品生命周期的不同阶段时,用户偏好随时间动态发生变化,进而对云服务QoS属性的偏好程度发生变化,这将直接影响云服务选择结果。因此,本文提出一种考虑用户动态偏好的云服务选择方法。首先,云服务QoS属性存在多种数据格式,故使用直觉模糊数处理异构的QoS数据。其次,在直觉模糊环境下采用熵权法确定用户初始偏好,进而使用马尔可夫链确定用户的动态偏好。最后,在直觉模糊环境下采用VIKOR方法评估备选云服务。实验结果表明,本文方法可以有效地帮助处在产品不同生命周期的用户选择满意的服务,且在不同的场景下,本文提出的方法是可靠的。     

A hierarchical model for optimal supplier selection in multiple sourcing contexts

This paper addresses a crucial objective of the strategic purchasing function in supply chains, i.e. optimal supplier selection. We present a hierarchical extension of the data envelopment analysis (DEA), the most widespread method for supplier rating in the literature, for application in a multiple sourcing strategy context. The proposed hierarchical technique is based on three levels. First, a modified DEA approach is used to evaluate the efficiency of each supplier according to some criteria proposed by the buyer. Second, the well known technique for order preference by similarities to ideal solution (TOPSIS) is applied to rank the maximally efficient suppliers given by the previous step. Third and finally, a linear programming problem is stated and solved to find the quantities to order from each maximally efficient supplier in the multiple sourcing context. The presented approach is able to straightforwardly discern between efficient and inefficient partners, avoid the confusion between efficient and effective suppliers and split the supply in a multiple sourcing context. The hierarchical model is applied to the supply of a C class component to show its robustness and effectiveness, while comparing it with the DEA and TOPSIS approaches.     

基于DEA的评价模型及其输入输出指标确定

产品包装方案的评价是一个多目标规划问题.应用数据包络分析原理(DEA),通过对包装设计方案的横向比较,构建产品包装方案的评价模型.采用两步法对评价模型求解,首先对输入变量进行比例收缩(或对输出变量进行比例扩张),求出各方案的相对效率;然后计算各方案每项指标的松弛变量.结合包装行业的特点,将越小越好的指标作为输入指标、越大越好的指标作为输出指标,建立了相应的输入输出指标体系.     

Supplier post performance evaluation: the effects of buyer preference weight variance

We use empirical post performance data of suppliers and buyers to demonstrate that degrees of variability of buyer evaluation team weight preferences can have varying effects on the perception of supplier performance attributes. We first justify then use data envelopment analysis (DEA) as a research tool to integrate buyer performance and buyer weight preferences with supplier performance and then use the results of the dyadic DEA evaluation model to analyse three propositions. This integration is essential to a dyadic approach. Results indicate that buyer preference weights on supplier performance attributes influence the perception of supplier performance sometimes in unexpected ways dependent on the degree of conformity versus disparity in the factor weights that was put into operation using assurance regions. As a result, buyer performance factors and preferences must be measured and their effects understood before post performance supplier evaluation is completed and other components of a relationship management plan are implemented.     

我国物流企业效率与效率持续性评价的实证

通过运用超效率方法对处在前沿上的物流企业进行排序和效率对比,分析了我国上市物流企业的效率变化情况;通过计算马姆奎斯特TFP指数,评价了上市物流企业效率的持续性,分析了其效率的动态变化趋势。经实证研究,得出目前我国上市物流企业效率较低,技术进步贡献率大于规模效率贡献率,从而认为物流企业在追求规模扩张的同时要增加技术投入。     

Building performance standards into data envelopment analysis structures

Data Envelopment Analysis (DEA) is a mathematical approach to measuring the relative efficiency of peer Decision-Making Units (DMUs). DEA is particularly useful where no a priori information on the trade-offs or relations among various performance measures is available. However, it is very desirable if “evaluation standards,” when they can be established, be incorporated into DEA performance evaluation. This is particularly important when service operations are under investigation, because service standards are generally difficult to establish. A number of approaches have been developed to incorporate evaluation standards into DEA as reported in the literature. These approaches tend to be rather indirect, focusing primarily on the multipliers in the DEA models. This paper introduces a new way of building performance standards directly into the DEA structure. Based upon the conventional DEA model and an activity matrix, a set of standard DMUs can be generated and incorporated directly into the DEA analysis. The proposed approach is applied to a sample of 100 branches of a major Canadian bank where time standards are used to generate a set of standard bank branches.     

Supplier evaluation and selection: an augmented DEA approach

Evaluating and selecting suppliers is an essential part of effectively managing today's dynamic and global supply chains. In this paper, we propose a supplier evaluation and selection methodology based on an extension of data envelopment analysis (DEA) that can evaluate suppliers in an efficient manner. Through the incorporations of a range of virtual standards, the proposed methodology termed augmented DEA, has enhanced discriminatory power over basic DEA models to rank suppliers. In addition, weight constraints are introduced to reduce the possibility of having inappropriate input and output factor weights. We demonstrate the application of augmented DEA with comparison experiments and find that the augmented DEA model has advantages over the basic DEA model as well as the cross-efficiency and super-efficiency models. Finally, we present a case application with data obtained from a communication and aviation electronics company to demonstrate the applicability and use of augmented DEA.     

Efficiency measurement of research groups using Data Envelopment Analysis and Bayesian networks

Applications of non-parametric frontier production methods such as Data Envelopment Analysis (DEA) have gained popularity and recognition in scientometrics. DEA seems to be a useful method to assess the efficiency of research units in different fields and disciplines. However, DEA results give only a synthetic measurement that does not expose the multiple relationships between scientific production variables by discipline. Although some papers mention the need for studies by discipline, they do not show how to take those differences into account in the analysis. Some studies tend to homogenize the behaviour of different practice communities. In this paper we propose a framework to make inferences about DEA efficiencies, recognizing the underlying relationships between production variables and efficiency by discipline, using Bayesian Network (BN) analysis. Two different DEA extensions are applied to calculate the efficiency of research groups: one called CCRO and the other Cross Efficiency (CE). A BN model is proposed as a method to analyze the results obtained from DEA. BNs allow us to recognize peculiarities of each discipline in terms of scientific production and the efficiency frontier. Besides, BNs provide the possibility for a manager to propose what-if scenarios based on the relations found.     

基于DEA方法的绿色矿山标准效果评估

随着绿色矿山理念深入、绿色矿山全面推广,越来越多的矿山企业申请成为试点单位并且接受验收,这就需要建立绿色矿山建设评价体系加以支持.合理地评价各地区绿色矿山创建标准的投入产出,对于矿山资源的合理开发,提升矿区生态环境质量具有十分重要的现实意义.本文介绍了DEA评价模型的基本特点和评价步骤,建立了绿色矿山标准效果评价指标体系,利用DEA法对绿色矿山标准效果进行评价,分析了DEA评价法的优缺点.     

Developing a new chance constrained NDEA model to measure the performance of humanitarian supply chains

Data envelopment analysis (DEA) is a method for measuring performance of decision making units (DMUs). Conventional DEA models view DMUs as black boxes. Network DEA (NDEA) models have been developed to overcome this shortfall. This paper develops a new NDEA model based on modified enhanced Russell measure model. This paper measures performance of humanitarian supply chains (HSCs) by an NDEA model. Capabilities of the proposed model are addressed by theorems. However, in the real world, there might be stochastic data. This paper presents a stochastic version of the proposed NDEA model to measure the performance of HSCs. We analyse main properties of our model. We present a case study to demonstrate the applicability of the proposed model.     

A new decision support system for performance measurement using combined fuzzy TOPSIS/DEA approach

It is apparent that there is a need for integrated criteria in the performance measurement of modern organisations when dealing with the performance measurement of manufacturing businesses. This paper addresses this issue in the context of measuring the performance of the 2nd Air Supply and Maintenance Center Command manufacturing/maintenance jobshops of Turkey by using a new framework which combines fuzzy TOPSIS (technique for order preference by similarity to ideal solution) for measuring qualitative performance with DEA (data envelopment analysis) for measuring quantitative performance. This proposed approach provides a comprehensive measure of performance incorporating both quantitative and qualitative attributes, which in general reflect efficiency and effectiveness of the manufacturing jobshops respectively.