Presenting DEA graphically

This paper introduces a methodology that permits presentation of the results of data envelopment analysis (DEA) graphically. A specialized form of multi-dimensional scaling, Co-Plot, enables presentation of the DEA results in a two-dimensional space, hence in a clear, understandable manner. When plotting ratios rather than original data, DEA efficient units can be visualized clearly, as well as their connections to specific variables and/or ratios. Furthermore, Co-Plot can be used in an exploratory data analysis to identify outliers, whose data require additional scrutiny, and potentially inconsequential variables that could be aggregated or removed from the analysis with little effect on the subsequent DEA results.     

A fair evaluation of certain stage in a two-stage structure: revisiting the typical two-stage DEA approaches

The efficiency of decision processes with a two-stage structure has been studied by some modified versions of Data Envelopment Analysis (DEA) methodology, such as the relational or centralized model, and the non-cooperative model. After revisiting the rationale of the centralized model provided by the literature, we find that some unfairness exist in its efficiency evaluation of certain stage. This unfairness leads to the usual underestimation of the overall efficiency by the centralized model. Furthermore, because the independent DEA model for one stage ignores its relation and coordination with the other stage and the two-stage system, externalities between these members may arise and lead to the seeming contradiction in efficiencies derived by independent DEA models for the stages and the black box system. Therefore, we argue that the efficiency of certain stage in the context of a two-stage structure should be reevaluated instead of simply using the independent DEA model. A sequence of leader-follower procedures, with data adjustment on intermediates, is proposed to eliminate the externalities and to ensure a fair evaluation. We find that, after this data adjustment, the reevaluation of the second stage for a given Decision Making Unit (DMU) yields the same result as obtained by the standard DEA model regarding the two-stage as a black box. Moreover, some explicit relations are established between the black box model, the centralized model, and the non-cooperative model. Two typical examples taken from the literature illustrate our main results. Our findings also imply that more emphasis should be placed on the game theoretic DEA approach to model the efficiency evaluation of two-stage processes.     

Internal resource waste and centralization degree in two-stage systems: An efficiency analysis

Internal resource waste refers to the waste in the intermediate resources between the upstream stage and downstream stage in a production or service system. This study examines a system with a two-stage structure, in which the outputs from the first stage are taken as the inputs for the second stage. Two-stage systems can exist in centralized, decentralized, or mixed organizational modes. In this paper, we propose two-stage DEA models considering a degree of centralization that makes it possible to measure internal resource waste in different system modes. Some managerial insights are tested and verified from the perspective of efficiency analysis. We find that: 1) when there is only one intermediate measure in a centralized two-stage system, internal resource waste can be eliminated completely, and 2) a higher degree of centralization in a two-stage system can lead to less internal resource waste and more expected outputs. Finally, we present a numerical example and two practical real-world examples that illustrate our approach and findings.     

Centralized resource allocation BCC models

In two recent papers, Lozano and Villa [Centralized resource allocation using data envelopment analysis. Journal of Productivity Analysis 2004;22:143–61. [1]] and Lozano et al. [Centralized target setting for regional recycling operations using DEA. OMEGA 2004;32:101–10. [2]] introduce the concept of “centralized” data envelopment analysis (DEA) models, which aim at optimizing the combined resource consumption by all units in an organization rather than considering the consumption by each unit separately. This is particularly relevant for situations where some variables are controlled by a central authority (e.g. Head Office) rather than individual unit managers. In this paper we reconsider one of the centralized models proposed by the above-mentioned authors and suggest modifying it to only consider adjustments of previously inefficient units. We show how this new model formulation relate to a standard DEA model, namely as the analysis of the mean inefficient point. We also provide a procedure that can be used to generate alternative optimal solutions, enabling a decision maker to search through alternate solution possibilities in order to select the preferred one. We then extend the model to incorporate non-transferable as well as strictly non-discretionary variables and illustrate the models using an empirical example of a public service organization.     

Carbon Emissions Abatement (CEA) allocation and compensation schemes based on DEA

As environment constraints on economic growth are strengthening, Carbon Emissions Abatement (CEA) allocation becomes a significant issue that draws academia׳s attention. In the literature, the Data Envelopment Analysis (DEA) technique has been applied to obtain CEA allocation with centralized models. Nevertheless, a centralized allocation plan suffers from an implementation difficulty in persuading decision-making units (DMUs) into an agreement. In this paper, we propose a new two-step method to mitigate this side effect. In the first step, we provide improved DEA-based centralized allocation models under the assumptions of constant returns-to-scale (CRS) and variable returns-to-scale (VRS) respectively and in the second step, two compensation schemes are developed for centralized allocation plans. An empirical application to the countries in Organization for Economic Co-operation and Development (OECD) is presented to elaborate the main idea.     

Additive slacks-based measure: Computational strategy and extension to network DEA

The current paper visits a set of data envelopment analysis (DEA) models that identify inefficiency by optimizing input and output slacks. These slacks are aggregated either in an additive or ratio form. Only the ratio slacks-based DEA models can be solved as a linear program and generate a DEA score between zero and unity. The additive slacks-based model can be equivalent to the Russell graph measure and converted into a second order cone programming (SOCP) problem whose solving procedure has become a mature technology. As such, the additive slacks-based model can also yield a DEA score between zero and unity. This study shows that the additive slacks-based model can be applied to modelling network DEA where the internal structures of decision making units (DMUs) are of interest. The additive slacks-based network DEA can be solved using SOCP technique and adapted to the preference of the decision maker by choosing the weights for aggregating individual components in the network structures. It is shown that the additive slacks-based approach can yield divisional efficiencies of Pareto optimal equivalences to be selected by the decision maker when compared to the existing ratio slacks-based measure. An example and solving codes are provided in the current study.     

Attracting and retaining talent: exploring human resources development trends in Australia

Drawing from the resource based view of the firm (RBV) the argument developed in the paper is that in an environment characterized by increasing levels of skilled labour shortages organisations need to design employment systems that prioritize human resource development to enable competitive advantage. The literature review examines the issues associated with the attraction, retention and development of human resources, and the major contextual issues and debates underpinning skill and labour shortages. A research question is then framed to capture the HR priorities of Australian organisations. We examine responses from 1372 Australian human resources (HR) professionals who participated in an online survey of a national HR professional association and results are interpreted with respect to HR efforts to attract, develop and retain talent.

Our findings suggest that employers are addressing issues related to attraction - recruitment and selection. However, in critical HR development areas associated with retention such as training, job design, skill development, careers management and team building, results indicate a lower level of resource allocation. We conclude that this lack of resource allocation is of concern for Australian organisations that are struggling to compete both domestically and internationally for skilled workers.     

供应链的利润博弈与均衡定价

供应链涉及多个利益主体,优化供应链的全局效益需要成员企业的协调来实现。效率评估的非参数法应用广泛,但是单纯的效率优化未考虑资源的可替代性和再分配,忽视了投入(产出)结构调整释放的优化空间。对于效率分解,取折衷或单边最优的方案不完全符合企业追求各自利益最大化的目标。本文针对两级供应链的利润优化问题建立一般化的分析框架,同时考虑了技术进步和资源可替代性的影响,对成员企业的利润博弈展开讨论,探讨了合作博弈如何促成供应链实现集权模式下的最优。通过建立议价模型得出了纳什均衡基础上的成员企业最优利润组合,并给出了实现最优分配方案的中间产品均衡定价。     

Stage efficiency evaluation in a two-stage network data envelopment analysis model with weight priority

Conventional DEA models treat the entire production system as a black box and ignore its internal structures. To address this issue, many studies have examined the DEA efficiencies of two-stage systems in which all outputs of the first stage are the only inputs to the second stage. Based on game theory, the non-cooperative model and centralized model were developed for such a two-stage network structure. However, for the centralized model with multiple optimal solutions and the non-cooperative model, an assumption is required as to whether the first or second stage should be assigned the absolute priority for optimization. In many cases, certain circumstances might exist in which one stage does not completely dominate the other stage. In this paper, we develop a methodology for assessing the overall and stage efficiencies by considering the different and DMU-specific degree of priority given to the stages. Particularly, the non-cooperative model and the centralized model can be deemed as special cases. Moreover, we compare the proposed approaches with the existing approaches, which indicates that our approaches can greatly reduce the computational burden. Two empirical examples are used to demonstrate the proposed approach.     

Using data envelopment analysis for the assessment of technical efficiency of units with different specialisations: An application to agriculture

In this paper we consider the use of data envelopment analysis (DEA) for the assessment of efficiency of units whose output profiles exhibit specialisation. An example of this is found in agriculture where a large number of different crops may be produced in a particular region, but only a few farms actually produce each particular crop. Because of the large number of outputs, the use of conventional DEA models in such applications results in a poor efficiency discrimination. We overcome this problem by specifying production trade-offs between different outputs, relying on the methodology of Podinovski (J Oper Res Soc 2004;55:1311–22). The main idea of our approach is to relate various outputs to the production of the main output. We illustrate this methodology by an application of DEA involving agricultural farms in different regions of Turkey. An integral part of this application is the elicitation of expert judgements in order to formulate the required production trade-offs. Their use in DEA models results in a significant improvement of the efficiency discrimination. The proposed methodology should also be of interest to other applications of DEA where units may exhibit specialization, such as applications involving hospitals or bank branches.     

Evaluating the administrative efficiency of courts

In addition to being held accountable for judicial decision, courts, like other public agencies, can and should be evaluated in terms of their administrative efficiency. This paper illustrates how courts can be evaluated in terms of their relative administrative efficiency, using a new approach—data envelopment analysis (DEA)—first proposed by Charnes et al. [1]. The DEA is based upon the economic notion of Pareto optimality which states that a given decision making unit (DMU) is inefficient if some other DMU, or some combination of other DMUs, can produce at least the same amounts of all outputs with less of some resource input and not more of any other resource. Conversely a DMU is said to be efficient if the above is not possible. Charnes et al. [1] generalized the usual input/output ratio measure of efficiency for a given unit in terms of a fractional linear program with fractional constraints. In the case of courts, the efficiency of any particular court is calculated by forming the ratio of a weighted sum of outputs to a weighted sum of inputs, where the weights for both outputs and inputs are to be selected in a manner that calculates the Pareto-Koopmans efficiency of the court. This paper reviews the DEA method and illustrates its application to a data base for 100 criminal superior courts in North Carolina.     

The Intrinsic Value of Decision Rights

Philosophers, psychologists, and economists have long argued that certain decision rights carry not only instrumental value but may also be valuable for their own sake. The ideas of autonomy, freedom, and liberty derive their intuitive appeal—at least partly—from an assumed positive intrinsic value of decision rights. Providing clean evidence for the existence of this intrinsic value and measuring its size, however, is intricate. Here, we develop a method capable of achieving these goals. The data reveal that the large majority of our subjects intrinsically value decision rights beyond their instrumental benefit. The intrinsic valuation of decision rights has potentially important consequences for corporate governance, human resource management, and optimal job design: it may explain why managers value power, why employees appreciate jobs with task discretion, why individuals sort into self‐employment, and why the reallocation of decision rights is often very difficult and cumbersome. Our method and results may also prove useful in developing an empirical revealed preference foundation for concepts such as “freedom of choice” and “individual autonomy.”     

组织支持对人力资源措施和员工绩效的影响

通过两项研究,对中国企业情境下员工感知到的组织支持、人力资源管理措施和个人绩效的关系进行了探讨.采用因子分析和回归分析等方法对来自合资,国有,私有等企业的员工及其主管的问卷调查结果进行了数据分析.结果表明:这些企业的人力资源管理措施可以分为保健措施和激励措施两大类.保健措施包括:员工福利、工作环境改善、工作保障、员工薪酬、员工关怀计划;激励措施包括员工培训、职业发展规划.保健措施和激励措施与感知到的组织支持存在交互作用,共同影响员工个人绩效.保健措施对员工绩效的正向影响作用在低水平感知到的组织支持下更显著,激励措施则在高水平感知到的组织支持下具有更显著的正向影响.     

Turbofan aero-engine efficiency evaluation: An integrated approach using VSBM two-stage network DEA

The application of Data Envelopment Analysis (DEA) has been wide, especially for the purpose of evaluating efficiency among similar production processes within enterprises belonging to particular industries. Although research pertinent to DEA has primarily focused on efficiency of production systems or corporate entities/organizations (e.g., terminals, hospitals, universities/schools, banks), fairly little attention has been given to efficiency evaluation among engineering systems featuring common configurations (e.g., automobiles, power plants). Furthermore, the limited previous literature involving efficiency evaluation of engineering systems has implemented DEA methodologies with limited discriminative power, i.e. there is a quite increased portion of efficient Decision Making Units (DMUs). In the current paper, a methodological framework deploying Variable intermediate measures Slacks-Based Measure (VSBM) Two-Stage Network DEA is implemented, in order to evaluate the efficiency of turbofan aero-engines, currently utilized by active-duty commercial and military aircraft. Apart from exploring the positive correlation of DEA efficiency with engineering efficiency, we also develop a methodology evaluating the features of near-future turbofan designs in terms of DEA efficiency, thus comprising a potential tool for efficiency assessment of any turbofan aero-engine being in the conceptual or preliminary design stage.     

An Empirical Model of Growth Through Product Innovation

Productivity differences across firms are large and persistent, but the evidence for worker reallocation as an important source of aggregate productivity growth is mixed. The purpose of this paper is to estimate the structure of an equilibrium model of growth through innovation designed to identify and quantify the role of resource reallocation in the growth process. The model is a version of the Schumpeterian theory of firm evolution and growth developed by Klette and Kortum (2004) extended to allow for firm heterogeneity. The data set is a panel of Danish firms that includes information on value added, employment, and wages. The model's fit is good. The estimated model implies that more productive firms in each cohort grow faster and consequently crowd out less productive firms in steady state. This selection effect accounts for 53% of aggregate growth in the estimated version of the model.     

The management of offshore resources—Some implications of the 200-mile limit

This article examines in depth the strategic implications for those States who have recently declared 200 mile off-shore resource management zones. The authors, in a comprehensive and stimulating paper, examine the implications of so-calling a nation's offshore limit. It is an appropriate name for a nation's offshore limit since the primary reason for many nations declaring a 200 mile limit has been the abundance of resources which have often been found within those limits either in the sea or the sea bed itself. This paper reviews the current background of off-shore resource management and outlines suitable roles for adoption by the coastal States in the management of their off-shore renewable and non-renewable resources. Furthermore, it examines the contentious but nonetheless central issue of the benefits and costs which accrue through coastal state jurisdiction. The authors also examine an appropriate resource management process and the implications of resource use conflicts within the off shore limit as well as defining these conflicts on the basis of ‘stakeholder’ interests and introduces a new concept of the maximization of economic equity amongst competing stakeholders. The problem remains that the measurement of economic equity perhaps leaves the States concerned within a situation of only having defined the problem; the political process has then to deal with any reallocation measures that may be deemed appropriate.     

A survey of DEA applications

The literature of data envelopment analysis (DEA) encompasses many surveys, yet all either emphasize methodologies or do not make a distinction between methodological and application papers. This study is the first literature survey that focuses on DEA applications, covering DEA papers published in journals indexed by the Web of Science database from 1978 through August 2010. The results show that on the whole around two-thirds (63.6%) of DEA papers embed empirical data, while the remaining one-third are purely-methodological. Purely-methodological articles dominated the first 20 years of DEA development, but the accumulated number of application-embedded papers caught up to purely-methodological papers in 1999. Among the multifaceted applications, the top-five industries addressed are: banking, health care, agriculture and farm, transportation, and education. The applications that have the highest growth momentum recently are energy and environment as well as finance. In addition to the basic statistics, we uncover the development trajectory in each application area through the main path analysis. An observation from these works suggests that the two-step contextual analysis and network DEA are the recent trends across applications and that the two-step contextual analysis is the prevailing approach.     

工业用水系统效率评价:考虑污染物可处理特性的两阶段DEA

提高水资源使用效率和污水处理效率是解决目前水资源短缺的重要途径。中国工业用水系统可分为生产用水子系统和污水处理子系统。本文考虑两个子系统之间的联系,并区分污染物在两个子系统中的弱处理和强处理特性,提出了一种基于DEA的两阶段评价模型。应用本文提出的新模型分析中国30个省级区域的工业用水系统的效率,结果表明: 中国省级区域工业用水整体效率不高,且地域分布特征明显,东部、西部、中部效率依次递减; 中国工业用水系统的非有效性主要源于污水处理效率的影响;工业用水系统效率与地区水资源禀赋存在一定的关系,水资源短缺的地区用水效率相对较高。文章所提出的方法兼顾生产用水子系统和污水处理子系统之间的相互影响,能够同时评价两个子系统效率和工业用水系统的整体效率,能有效发现系统中影响整体效率的关键环节,且可以应用于其他能源效率评价问题,具有明显的实际应用价值。     

基于开工柔韧性的关键链项目缓冲分配方法

缓冲应该进行集中式还是分散式管理是项目缓冲管理的一个核心问题，经典缓冲管理方法没有对此进行研究。基于此，本文在考虑开工柔韧性的情况下，研究并比较分析了两种项目缓冲的分配模式。通过对两种缓冲管理模型的研究，结合MATLAB仿真结果发现，缓冲集中式管理模式在考虑开工柔韧性的情况下，主要通过活动资源提前就位来抓住项目活动可能出现的提前完工机会，即通过可能的成本增加来换取可能的工期降低。仿真结果显示，在这种模式下，项目工期提前了8.67%，而总成本只上升了2.02%（主要是因为增加了资源库存成本和计划变动成本），由此可见，集中式缓冲管理模式可以有效降低工期。而缓冲分散式管理模式则是现有缓冲管理方法的延伸，在考虑开工柔韧性的情况下，将项目计划做出不同程度延缓，相较于缓冲集中式管理没有了库存成本的增加，实验结果表明，当活动完工率落在概率分布函数的50%~60%之间时可得到项目的最佳缓冲分散程度。     

带权重约束的DEA超效率评价模型及其应用研究

针对产学研协同创新项目的相对效率比较问题,数据包络分析（DEA）法是比较有效的数量分析方法。但DEA法所构建的优化模型中,由于约束条件没有充分考虑评价指标体系内部指标之间客观存在的内在权重大小信息,从而导致模型过分强调了评价单元的投入产出特征差异,甚至出现了原本非常重要的指标其权重却为0的不合理现象。本文提出DEMATEL法和数据包络分析法有机结合的思想,将运用DEMATEL法获得的指标之间内在的权重大小信息,纳入DEA法非阿基米德无穷小量ε限制的CCR模型及其超效率模型的约束条件,创新模型的可行域,构建了权重约束型ε-CCR模型和超效率ε-CCR模型。并以美国2014-2015年度国家科学基金会产学研合作研究中心发布的年度报告数据,对美国71个以高校为主导的产学研协同创新中心的相对效率进行了实证分析。实证结果显示,权重约束型超效率ε-CCR模型比没有权重约束的超效率ε-CCR模型更有效,不仅能对多个评价单位进行全排序,而且能克服无权重约束的超效率ε-CCR模型存在的评价结果不合理现象。这些结果有助于进一步推动DEA法的理论创新和应用推广,并能为多投入多产出项目的决策提供新的方法,使实际问题决策更合理更科学。