A classification of DEA models when the internal structure of the Decision Making Units is considered

We classify the contributions of DEA literature assessing Decision Making Units (DMUs) whose internal structure is known. Starting from an elementary framework, we define the main research areas as shared flow, multilevel and network models, depending on the assumptions they are subject to. For each model category, the principal mathematical formulations are introduced along with their main variants, extensions and applications. We also discuss the results of aggregating efficiency measures and of considering DMUs as submitted to a central authority that imposes constraints or targets on them. A common feature among the several models is that the efficiency evaluation of the DMU depends on the efficiency values of its subunits thereby increasing the discrimination power of DEA methodology with respect to the black box approach

The Chinese position as a global player in international comparison with the WTO members: Efficiency analysis and 4IR

During the last quarter-century, globalisation processes affected changes in the world economy in the form of intensifying competition in the international and internal markets. The result is the creation of a global marketplace that is mostly indifferent to national borders and governmental influences. This development has generated widespread interest in competitiveness. Competitiveness affects international relations, especially nowadays, given the changing position of the global leaders and the growth of new economic powers such as China. China has come a long way and has the opportunity to be a global leader in several required fields that will be the cornerstones of global growth in the next decades. Led by China, emerging economies are increasing their share in the worldwide economy and intensifying competition in nearly all sectors. It creates new threats and challenges for players in the global economy, and growing competitiveness must be efficient. The article evaluates the Chinese competitiveness in comparison with the World Trade Organization members by the Data Envelopment Analysis in the pre-in-post crisis period and considering the Fourth Industrial Revolution shifting humanity into a new phase.Web of Science6148

Productivity drivers in European banking: Country effects, legal tradition and market dynamics

This paper analyses efficiency drivers of a representative sample of European banks by means of the two-stage procedure proposed by Simar and Wilson (2007). In the first stage, the technical efficiency of banks is estimated using DEA (data envelopment analysis) in order to establish which of them are most efficient. Their ranking is based on total productivity in the period 1993-2003. In the second stage, the Simar and Wilson (2007) procedure is used to bootstrap the DEA scores with a truncated bootstrapped regression. The policy implications of our findings are considered

CAN FISCAL POLICY EXPLAIN TECHNICAL INEFFICIENCY OF PRIVATISED FIRMS? A PARAMETRIC AND NONPARAMETRIC APPROACH

The massive interests of economic literature about the privatisation gave a notable impulse to the discussion about this theme in the pre and post privatisation firms performance. Basically in every case after privatisation the level of profit increases. Does this mean that privatisation is certainly able to increase efficiency? In this field a large part of the literature leave out the complex problem that public firms usually are subject to objectives and constraints that differently from private firms can affect the overall economic efficiency. Unfortunately many authors ignore the effects of taxation during the process of privatisation, but in real term there are significant tax issues that must be considered by public and private decision maker. In this paper we concentrate the attention on the efficiency measures with the purpose to identify and measure sources of successful performance that can be used in policy planning and allocation of resources. Several techniques to calculate these frontier functions have been used, some of them parametric, others non-parametric to empirically investigate the relationship between taxation on firm’s income and efficiency in the period pre and post-privatisation. In this work we use both econometric and mathematical programming approaches for measuring efficiency. The econometric tool provide maximum likelihood estimates of a stochastic production and cost functions to distinguish noise from inefficiency. Instead, the mathematical programming approaches are nonstochastic and they do not make strict assumptions on the functional form of production and the statistical properties of the data. The general results obtained from the 3 different tools (Stochastic Frontier, Data Envelopment Analysis and Neural Network) are consistent. In fact, we see that privatization enhanced efficiency in three out of four sample firms.Privatization, Fiscal policy, Data Envelopment Analysis, Stochastic Frontier, Neural Network

COOPER-framework: A Unified Standard Process for Non-parametric Projects

Practitioners assess performance of entities in increasingly large and complicated datasets. If non-parametric models, such as Data Envelopment Analysis, were ever considered as simple push-button technologies, this is impossible when many variables are available or when data have to be compiled from several sources. This paper introduces by the ‘COOPER-framework’ a comprehensive model for carrying out non-parametric projects. The framework consists of six interrelated phases: Concepts and objectives, On structuring data, Operational models, Performance comparison model, Evaluation, and Result and deployment. Each of the phases describes some necessary steps a researcher should examine for a well defined and repeatable analysis. The COOPER-framework provides for the novice analyst guidance, structure and advice for a sound non-parametric analysis. The more experienced analyst benefits from a check list such that important issues are not forgotten. In addition, by the use of a standardized framework non-parametric assessments will be more reliable, more repeatable, more manageable, faster and less costly.DEA, non-parametric efficiency, unified standard process, COOPER-framework.

Cognitive strategic groups and long-run efficiency evaluation : the case of Spanish savings banks

In the framework of Cognitive Approach, this paper proposes a new method to identify strategic groups (SG) using Data Envelopment Analysis (DEA) methods. Two assumptions are maintained in the SG literature: first, firms grouped together value inputs and outputs similarly, and, second, some degree of stability in those valuations should be identified. Virtual weights obtained from DEA are extremely useful in the valuation of the strategic variables, but a problem emerges when longitudinal analysis is performed. This problem is addressed by defining a long run DEA evaluation. SGs are determined by means of Cluster Analysis, using virtual outputs and virtual inputs as variables and Spanish savings banks as observations. The traditional method of determining SGs by clustering on the original variables is also applied and the results are compared. It is shown that the long run DEA weights approach has advantages over the traditional methodology

A reasonable benchmarking frontier using DEA : an incentive scheme to improve efficiency in public hospitals

There exists research relating management concepts with productivity measurement methods that offers useful solutions for improving management control in the public sector. Within this sphere, we connect agency theory with efficiency analysis and describe how to define an incentives scheme that can be applied in the public sector to monitor the efficiency and productivity of managers. To fulfill the main objective of this research, we propose an iterative process for determining what we define as a ‘reasonable frontier’, a concept that provides the foundation required to establish the incentive scheme for the managers. Our ‘reasonable frontier’ has the following properties: i) it detects the presence of outliers, ii) it proposes a procedure to establish the influence introduced by extreme observations, and iii) it sorts out the problem of data masking. The proposed method is applied to a sample of hospitals taken from the public network of the Spanish health service. The results obtained confirm the applicability of the proposal made. Summing up, we define and apply a useful method, combining aspects of agency theory and efficiency analysis, which is of interest to those public authorities trying to design effective incentive schemes which influence the decision making of the public managers

An application of the data envelopment analysis methodology in the performance assessment of the Zaragoza University Departments

The increasing interest in the measurement of the performance and efficiency in non-profit public organisations, has led to the development of performance indicators, each of which attempts to measure the output (input) of a group of nearly homogeneous products (factors of production). The Data Envelopment Analysis (DEA) methodology enables to aggregate performance indicators in order to obtain an overall performance measure through the comparison of a group of decision units. This paper conducts an application of the DEA methodology in the assessment of the performance of the Zaragoza University’s departments (Spain). The indicators included concerns both the teaching and the research activity of the departments. The results reveal those departments that more efficiently carry out these activities. Finally, we discuss about the existence of differences in the strengths and weaknesses between departments of different areas.Data Envelopment Analysis, performance assessment, higher education efficiency, performance indicators

Neural Network Based Models for Efficiency Frontier Analysis: An Application to East Asian Economies' Growth Decomposition

There has been a long tradition in business and economics to use frontier analysis to assess a production unit’s performance. The first attempt utilized the data envelopment analysis (DEA) which is based on a piecewise linear and mathematical programming approach, whilst the other employed the parametric approach to estimate the stochastic frontier functions. Both approaches have their advantages as well as limitations. This paper sets out to use an alternative approach, i.e. artificial neural networks (ANNs) for measuring efficiency and productivity growth for seven East Asian economies at manufacturing level, for the period 1963 to 1998, and the relevant comparisons are carried out between DEA and ANN, and stochastic frontier analysis (SFA) and ANN in order to test the ANNs’ ability to assess the performance of production units. The results suggest that ANNs are a promising alternative to traditional approaches, to approximate production functions more accurately and measure efficiency and productivity under non-linear contexts, with minimum assumptions.total factor productivity, neural networks, stochastic frontier analysis, DEA, East Asian economies

An evaluation of vendor selection models from a Total Cost of Ownership perspective.

Many different vendor selection models have been published in the purchasing literature. However there has been no systematic approach to compare the relative efficiency of the systems. In this paper we propose to use the concept of Total Cost of Ownership as a basis for comparing vendor selection models. We illustrate the comparison with real life data set of the purchasing problem of ball bearings at Cockerill Sambre, a Belgian multinational company in the steel industry. Mathematical programming models outperform rating models and multiple item models generate better results than single item models from a Total Cost of Ownership perspective for this specific case study.Evaluation; Models; Selection;