Supplier Rationalization: A Sourcing Decision Model

We draw on extant literature on strategic sourcing and supply base rationalization to anchor our argument that measuring supplier performance diversity is germane to executing an effective supply base rationalization strategy. We explicate how a novel approach to data envelopment analysis (DEA) efficiency assessment can be utilized to measure this performance diversity. More specifically, our methods are anchored in cross efficiency analysis in DEA that allows for evaluating the efficiency of a supplier with respect to the optimal weights (strengths) of its peers. This methodology is applied to an actual supplier dataset of a large multinational telecommunications company in categorizing their supply base into groups for effective supplier rationalization. We conclude that measuring and analyzing the performance diversity within the framework of DEA provides a mechanism for firms to better balance a rationalized and diversified supply base with unique skills.     

基于多种DEA模型和Gini准则的效率评价方法——兼对我国高校运营绩效的评价

针对多种数据包络分析（Data Envelopment Analysis,简称DEA）模型会产生不同绩效评价结果的问题,提出基于Gini准则科学地融合各DEA模型结果的方法。首先基于Gini准则定义信息纯度以衡量各DEA模型结果的确定性并赋予权重,然后通过加权融合最终得出客观唯一的综合效率。此外,根据评价者的偏好信息或先验知识,进一步提出交互式多DEA模型-Gini准则方法。以前学者仅从单一角度出发选择DEA模型评价高校的运营绩效,考虑到从不同角度出发的多种DEA模型可以给出高校更加全面客观的运营绩效评价,利用以上方法对2011年国内25所理工类高校的运营绩效进行了实证分析,结果验证了以上方法可以合理有效的衡量各高校的运营绩效表现,对于高校运营绩效的评价研究具有实际指导意义。     

Data envelopment analysis: Prior to choosing a model

In this paper, we address several issues related to the use of data envelopment analysis (DEA). These issues include model orientation, input and output selection/definition, the use of mixed and raw data, and the number of inputs and outputs to use versus the number of decision making units (DMUs). We believe that within the DEA community, researchers, practitioners, and reviewers may have concerns and, in many cases, incorrect views about these issues. Some of the concerns stem from what is perceived as being the purpose of the DEA exercise. While the DEA frontier can rightly be viewed as a production frontier, it must be remembered that ultimately DEA is a method for performance evaluation and benchmarking against best-practice. DEA can be viewed as a tool for multiple-criteria evaluation problems where DMUs are alternatives and each DMU is represented by its performance in multiple criteria which are coined/classified as DEA inputs and outputs. The purpose of this paper is to offer some clarification and direction on these matters.     

Measuring Corporate Social Performance: An Efficiency Perspective

Aggregation of corporate social performance (CSP) metrics poses a major challenge to researchers and practitioners. This study provides a critical evaluation of current aggregation approaches and proposes a new methodology based on data envelopment analysis (DEA) to compute a CSP index. DEA is independent of subjective weight specifications and provides an efficiency index to benchmark the CSP of firms. Using CSP data from 2190 firms in three major industries from the Kinder, Lydenberg, and Domini, Inc. database in 2007, our study presents the first application of the DEA model for CSP and ordinal data and opens up a new path for future empirical CSP research.     

Understanding Drivers of Risk‐Adjusted Performance for Service Firms with International Operations*

This article investigates whether international operations of service firms increase performance while reducing risk. The article draws on a longitudinal dataset of 584 internationally operating service firms from the United States. Analysis indicates that international diversification is negatively related to risk‐adjusted performance. However, it is established that international diversification interacts with internationalization and positively influences risk‐adjusted performance. This finding offers significant promise for firms, as it indicates that international operations (if managed well), through exposure to varied foreign markets coupled with adequate global scope, can lead to firms’ increased risk‐adjusted performance. The results provide a mechanism for decision‐makers to better understand international operations of service firms and present a strategy for achieving success in international markets by effectively managing two important levers: internationalization and international market diversification.     

Governance Structures,Multidimensional Efficiency and Firm Profitability

Using a panel data set of 361 German corporations for the period 1991–1996 we test the hypothesis that firms with more efficient governance structures have higher profitability. To determine efficiency we compare firms with respect to ownership concentration, the identity of owners, capital structure, investment and firm growth by a multi-input/multi-output Data Envelopment Analysis (DEA). This non-parametric linear programming technique considers both multiple in- and out- puts. Based on the concept of pareto efficiency, it computes an efficiency score where the associated weights of the inputs and outputs are determined endogenously. The DEA efficiency scores are then used as explanatory variables in panel data regressions of profitability. Our main finding is that the efficiency scores indeed contribute significantly to explaining profitability differences between firms, even after controlling for industry effects and unobserved systematic firm effects.     

Models for measuring and benchmarking olympics achievements

As demonstrated in several recent studies, data envelopment analysis (DEA) is a useful tool for evaluating and comparing the performance of nations competing in the Olympic Games. Assurance regions (ARs) have been used to further refine the DEA results. These AR DEA models assume that ARs apply uniformly across all nations. Such models can have shortcomings in the sense that different nations may impose different ARs, as nations may value gold, silver, and bronze medals differently. This paper extends previous DEA studies by incorporating multiple sets of nation-specific ARs into the DEA. By doing so, we establish fair models for measuring and benchmarking the performance of nations at six summer Olympic Games.     

Performance evaluation based on multiple attributes with nonparametric frontiers

Performance rating and comparison of a group of entities is frequently based on the values of several attributes. Such evaluations are often complicated by the absence of a natural or obvious way to weight the importance of the individual dimensions of the performance. This paper proposes a framework based on nonparametric frontiers to rate and classify entities described by multiple performance attributes into ‘performers’ and ‘underperformers’. The method is equivalent to Data Envelopment Analysis (DEA) with entities defined only by outputs. In the spirit of DEA, the weights for each attribute are selected to maximize each entity’s performance score. This approach, however, results in a new linear program that is more direct and intuitive than traditional DEA formulations. The model can be easily understood and interpreted by practitioners since it conforms better to the practice of evaluating and comparing performance using standard specifications. We illustrate the model’s use with two examples. The first evaluates the performance of employees. The second is an application in manufacturing where multiple quality attributes are used to assess and compare performance of different manufacturing processes.     

部分中间产出作为最终产品的两阶段合作效率

网络DEA模型研究多个进程和多个子系统的复杂系统的效率度量.针对中间产出无法为第2阶段完全消耗的情形,传统DEA模型对系统效率的评价偏高,已有网络DEA模型则对系统效率的评价偏低.本文提出部分中间产出作为最终产品,进入流通渠道的两阶段效率模型,用来测度两阶段生产过程的真实效率.采用乘积形式描述两阶段合作的特征,给出不同...     

Dynamic performance assessment of bus transit with the multi-activity network structure

This paper proposes a multi-activity dynamic network data envelopment analysis model that combines the multi-activity, network and dynamic DEA models to assess the performance in terms of individual activities, individual processes, individual periods and overall operation. The main advantage of this model is that the linkages among activities and processes, the shared inputs among activities and processes, and the carry-over items among periods are included in a unified model. It can provide more appropriate performance measures. An empirical application of 20 bus transit firms in Taiwan for the period 2004–2012 is provided. Based on the operational characteristics of bus transit firms, both desirable and undesirable outputs are also incorporated into this model. The results show that none of the bus transit firms was effective in terms of the operational effectiveness, and the sources of operational ineffectiveness among bus transit firms were different. Over the period 2004–2012, the period-operational effectiveness scores maintained stable variance, the period efficiencies of highway and urban bus services appeared to have similar patterns, and transit bus firms performed well in the consumption process.     

Measuring strategic decision making efficiency in different country contexts: A comparison of British and Turkish firms

This paper compares the relative efficiency of the strategic decision making (SDM) processes of British and Turkish firms. The technique of data envelopment analysis (DEA) is used to measure the relative efficiency of these firms. The evidence obtained by the DEA analysis reveals that the Turkish firms tend to be superior to the British firms in terms of their SDM efficiency. There is a significant difference in scale returns with respect to the country of origin of the firms. The analysis of the improvement potential of inputs indicates that Turkish firms place more emphasis on managing environmental turbulence to enhance their SDM efficiency, while British firms tend to overly focus on the design of an appropriate organizational structure. However, no significant difference was noted between the two groups of firms with regard to the level of resources and effort exerted on formal strategic planning practices. The analysis of output deficits reveals that there is a significant difference between British and Turkish firms in the sources of inefficiency.     

随机环境下的多投入多产出生产前沿面估计

传统的DEA模型假设观测样本的投入产出都是确定型数据, 这使得DEA在实际应用中受到限制, 本文提出的基于拟似然估计的多投入多产出随机非参数包络数据 (PLE-StoNED) 方法拓展了这个假设, 能够估计随机环境下的生产前沿面.本文证明, 生产可能集假设条件下的前沿面可以用一个有凹凸性和单调性限制的函数来表示.相较之前的StoNED方法, 本文提出的方法可以估计随机环境下多投入多产出决策单元 (DMU) 的前沿面.通过Monte Carlo实验, 多投入多产出PLE-StoNED方法的有效性得到验证, 它可纠正DEA等传统方法产生的偏误.最后, 实证研究部分运用这一新提出的方法估计了中国大陆商业银行的生产前沿面和效率.本文提出的方法弥补了DEA缺乏统计性的不足, 可为决策者在随机环境下对多投入多产出决策单元进行生产力和效率评估提供决策参考.     

矩阵型网络DEA模型及其实证检验

针对传统DEA模型无法有效的评价矩阵型网络系统的效率,本文构建了矩阵型网络决策单元的生产可能集,建立了矩阵型网络DEA模型。在此基础上证明了决策单元在矩阵型网络DEA模型下为弱DEA有效的充分必要条件为其每个子系统均为弱DEA有效。最后,选用美国的十个电力公司作为决策单元对模型进行实证检验,得出结论:矩阵型网络DEA模型弥补了传统DEA模型无法反映内部有效性从而可能得到错误结果的缺陷,并能精确地计算出各个子过程的效率,辨识出具体需要改进的子过程。同时新模型为评价复杂系统的效率提供了新的思路。     

A slack-based measure of efficiency in context-dependent data envelopment analysis

Data envelopment analysis (DEA) has been proven as an excellent data-oriented performance evaluation method when multiple inputs and outputs are present in a set of peer decision-making units (DMUs). In the DEA literature, a context-dependent DEA is developed to provide finer evaluation results by examining the efficiency of DMUs in specific performance levels based upon radial DEA efficiency scores. In DEA, non-zero input and output slacks are very likely to present after the radial efficiency score improvement. Often, these non-zero slack values represent a substantial amount of inefficiency. Therefore, in order to fully measure the inefficiency in DMU's performance, it is very important to also consider the inefficiency represented by the non-zero slacks in the context-dependent DEA. This study proposes a slack-based context-dependent DEA which allows a full evaluation of inefficiency in a DMUs performance. By using slack-based efficiency measure, we obtain different frontier levels and more appropriate performance benchmarks for inefficient DMUs.     

Using Malmquist Indexes to measure changes in the productivity and efficiency of US accounting firms before and after the Sarbanes–Oxley Act

There have been many criticisms of the Sarbanes–Oxley (SOX) Act passed in July of 2002 to correct business accountability and performance practices. The act has a major emphasis on accounting and its practices. This paper attempts a response to these criticisms by investigating changes in productive efficiency for 62 of the largest US public accounting firms between the periods (2000–2001) and (2003–2004)—the periods before and after enactment of SOX in July of 2002. DEA is used to calculate Malmquist indexes of productivity and efficiency changes. This index is used because it can distinguish between changes in technical efficiency, which limit the possibilities, and changes in the performance efficiencies for each firm. Contrary to many of the criticisms, results indicate that accounting firms have exhibited significant post SOX growth in productive efficiency which is better than pre-SOX performances.     

Estimation of portfolio efficiency via DEA

Traditional DEA models and nonlinear (diversification) DEA models are often used in performance evaluation of portfolios. However, the diversification models are usually very complicated to compute except the very basic models. And the classic DEA models still need to be further justified and tested, since it is not clear whether they are over-linearised according to the diversification models. The existing studies on performance evaluation via the classic DEA models generally focus on the selection of inputs and outputs. In this work, we investigate theoretical foundation of DEA models for portfolios from a perspective of sampling portfolio. We show the classic DEA provides an effective and practical way to approximate the portfolio efficiency (PE). We further verify this approach through different portfolio models with various frictions and bounds on the market. Through the comprehensive simulations carried out in this study, we show that with adequate data sets, the classic DEA models can effectively sample portfolios to take into account sufficient diversification, and thus can be used as an effective tool in computing the PE for their performance assessments. This study can be viewed as a justification of the classic DEA performance assessments and the way to introduce other efficiency notions (like allocation efficiency, scale efficiency, etc) into assessment of portfolios.     

DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment

Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success. The proposed approach is applied to a random sample of 1001 firms, which is composed of 50 large US bankrupt firms randomly selected from Altman's bankruptcy database and 901 healthy matching firms. This sample represents the largest firms that went bankrupt over the period 1991–2004 and represents a full spectrum of industries. Our findings demonstrate that the DEA model is relatively weak in predicting corporate failures compared to healthy firm predictions, and the assessment index improves this weakness by giving the decision maker various options to achieve different precision levels of bankrupt, non-bankrupt, and total predictions.     

Evaluating the impact of lean practices on environmental performance: evidences from five manufacturing companies

Abstract

Previous evidence suggests that lean practices help organizations to enhance environmental performance. However, the impact of lean practices on the environment is still unclear. This study, therefore, aims to analyse the relationship between lean and environmental performance in two main stages: first, a review of the relevant literature was developed, followed by a multiple case study analysis conducted in five manufacturing companies. Onsite data were collected from the firms during a 5 years’ time span of research and developing semi-structured interviews. Findings indicate that the environmental performance of the companies analysed is generally enhanced in the long-term after the implementation of lean. Moreover, the results suggest that the environmental performance of the firms investigated is mainly improved by using JIT and TQM practices in a lean transformation context. The research findings provide further results remarking the possible negative impact of Kanban deliveries, 5S and TPM on various environmental performance indicators.     

Enhancing standard performance practices with DEA

Data envelopment analysis (DEA) can be interpreted as a natural generalization of elemental practices for efficiency and performance evaluation used in diverse areas, some of which have evolved independently of each other and of the traditional efficiency framework of Charnes et al. [Measuring the efficiency of decision making units. European Journal of Operational Research 1978;2(6):429–44]. The paper aims to show that some standard “real-world” procedures employed by practitioners in the fields of retailing, finance, and social science can be interpreted as unconscious applications of DEA, and that such analyses could be enhanced by the explicit use of DEA. A supplementary aim is to demonstrate that DEA can be derived from concrete examples and first principles. The choice of the examples covers the two typical returns to scale environments of constant returns to scale (CRS) and variable returns to scale (VRS). Motivating and deriving DEA as a generalization of established performance evaluation practices will help to explain and disseminate this methodology to practitioners and to those who find their methods familiar.     

制造型企业市场导向执行模式及前因变量和绩效

考察了市场导向执行的具体模式,以及市场导向模式选择的影响因素和绩效。对227家制造型企业的问卷调查结果显示:MKTOR量表在中国制造业环境下具有良好的信度和效度;我国制造型企业市场导向的具体模式可以分为6种;不同模式市场导向下的产品创新绩效和企业财务绩效存在明显差异;市场导向的模式选择与内部组织因素和外部环境因素有关。