Integrated Data Envelopment Analysis Research Articles

Exploring the Efficiency of Mexican Universities: Integrating Data Envelopment Analysis and Multidimensional Scaling

National policy initiatives require the expenditure of large amounts of resources over several years. It is common for these initiatives to generate large amounts of data that are needed in order to assess their success. Educational policies are an obvious example. Here we concentrate on Mexico’s “Educational Modernisation Programme” and try to see how this plan has affected efficiency in teaching and research at Mexico’s universities. We use a combined approach that includes traditional ratios together with Data Envelopment Analysis models. This mixture allows us to assess changes in efficiency at each individual university and explore if these changes are related to teaching, to research, or to both. Using official statistics for 55 universities over a six year period (2007-2012), we have generated 12 ratios and estimated 21 DEA models under different definitions of efficiency. In order to make the results of the analysis accessible to the non-specialist we use models that visualise the main characteristics of the data, in particular scaling models of multivariate statistical analysis. Scaling models highlight the important aspects of the information contained in the data. Because the data is three-way (variables, universities, and years) we have chosen the Individual Differences Scaling model of Carroll and Chang. We complete the paper with a discussion of efficiency evolution in three universities.

A joint measurement of efficiency and effectiveness for the best supplier selection using integrated data envelopment analysis approach

Selecting a superior supplier is one of the most important tasks in supply chain management (SCM) which requires effective purchasing strategies. Thus, purchasing departments are looking for the kind of strategies in which can determine the efficiency and effectiveness of suppliers. This paper proposes a model for measuring efficiency, effectiveness, and the overall efficiency of suppliers in supply chain management. In addition, to rank suppliers, this paper proposes a novel super-efficiency formulation of data envelopment analysis (DEA). A numerical example addresses the applicability of the proposed model in supplier ranking context.

Integrated data envelopment analysis and neural network model for forecasting performance of wafer fabrication operations

With the rapid change of manufacturing environments, semiconductor fabricators are forced to make continuous investments in advanced technology to maintain their competitive advantage. Wafer fabrication (fab) performance evaluations are important for examining past operations such as the capacity and resource allocation. In addition, forecasting provides useful information for what-if analyses to anticipate useful strategies early to avoid potential losses. However, the integration of performance evaluation and forecast based on a consideration of the relative performance along the time horizon has rarely been addressed. In particular, the part of performance evaluation is to generate the relative performance in a period with rolling data. Then, the forecast part is to build a model for performance prediction based on the result of present performance. This study aimed to construct a performance forecast model by integrating data envelopment analysis and a back-propagation neural network for performance evaluation and forecast, respectively. Empirical data from a leading semiconductor company in Taiwan was used to test the proposed model. The results provide basic information and early alarms to adjust the resource allocation before the future performance declines. The empirical analysis demonstrated the practical feasibility of the proposed approach.

Resource Commitment, Organizational Diversity, and Research Performance: A Case of the National Telecommunication Program in Taiwan

Traditionally, a project team's resource commitment and organizational diversity are thought to be helpful to project performance; however, this relationship may falter when the project performance is considered in light of both cost and benefit. This paper integrates data envelopment analysis (DEA) and analytical hierarchy process (AHP) to evaluate project performance and explores the relationship between project performance and resource commitment and organizational diversity. The empirical study of research teams in the Taiwan National Telecommunication Program shows mixed results of this relationship. Implications for project management and governmental subsidy policy in dealing with resource commitment and organizational diversity are discussed.

Integrated data envelopment analysis: Global vs. local optimum

Chiou et al. (2010) (A joint measurement of efficiency and effectiveness for non-storable commodities: integrated data envelopment analysis approaches. European Journal of Operational Research 201, 477–489) propose an integrated data envelopment analysis model in measuring decision making units (DMUs) that have a two-stage internal network structure with multiple inputs, outputs, and consumptions. They claim that any optimal solutions determined by their DEA model are a global optimum, not a local optimum. We show that such a conclusion is a false statement due to their misuse of Hessian matrix in examining the concavity of the objective function, and their DEA model is actually a non-convex optimization problem. As a result, their DEA model is unusable in practice due to a lack of efficient algorithm for this particular non-convex DEA model. We further show that Chiou et al.’s (2010) model is a special case of a well-known two-stage network DEA model, and it can be transformed into a parametric linear program for which an approximate global optimal solution can be obtained by solving a sequence of linear programs in combination with a simple search algorithm.

Modelling profitability and effectiveness of Greek-listed construction firms: an integrated DEA and ratio analysis

Existing research on construction performance measurement is dominated by project level studies, and the firm stakeholders require the development of models that compare performance in terms of efficiency. A new framework that integrates data envelopment analysis (DEA) and ratio analysis using a two-step approach is described to evaluate performance in terms of profitability and effectiveness of a sample of construction firms listed on the Athens Exchange. In the first step, profitability and effectiveness are assessed by employing DEA and by using the profit margin (i.e. income-to-sales ratio), respectively. In the second step, a Tobit and an ordinary least squares model are used in order to identify the drivers of profitability efficiency and effectiveness, respectively. Results do point out positive links between profitability efficiency and effectiveness. Profitability inefficiency can be explained by the size and expenses-to-total revenue ratio, whereas effectiveness can be explained only by the latter explanatory variable. The research framework may benefit not only Greek construction firms, but also firms in other countries to quantify their performance and improve their competitive advantages.

A new DEA method for supplier selection in presence of both cardinal and ordinal data

The success of a supply chain is highly dependent on selection of best suppliers. These decisions are an important component of production and logistics management for many firms. Little attention is given in the literature to the simultaneous consideration of cardinal and ordinal data in supplier selection process. This paper proposes a new integrated data envelopment analysis (DEA) model which is able to identify most efficient supplier in presence of both cardinal and ordinal data. Then, utilizing this model, an innovative method for prioritizing suppliers by considering multiple criteria is proposed. As an advantage, our method identifies best supplier by solving only one mixed integer linear programming (MILP). Applicability of proposed method is indicated by using data set includes specifications of 18 suppliers.

A note on “A new method for ranking discovered rules from data mining by DEA”, and a full ranking approach

In a recent paper by Toloo et al. [Toloo, M., Sohrabi, B., & Nalchigar, S. (2009). A new method for ranking discovered rules from data mining by DEA. Expert Systems with Applications, 36, 8503–8508], they proposed a new integrated data envelopment analysis model to find most efficient association rule in data mining. Then, utilizing this model, an algorithm is developed for ranking association rules by considering multiple criteria. In this paper, we show that their model only selects one efficient association rule by chance and is totally depended on the solution method or software is used for solving the problem. In addition, it is shown that their proposed algorithm can only rank efficient rules randomly and will fail to rank inefficient DMUs. We also refer to some other drawbacks in that paper and propose another approach to set up a full ranking of the association rules. A numerical example illustrates some contents of the paper.

Performance Measurement In The eCommerce Industry

<p>The Balanced Scorecard framework (BSC) developed by Kaplan and Norton (1992) has been widely accepted by most academics and adopted by numerous practitioners in industry. Despite being widely accepted by practitioners in industry, little extant research has focused on the BSC and little empirical analysis has focused on validating the model. This paper first develops performance measures specifically designed for the eCommerce industry by drawing on the BSC and other measures developed by practitioners. Next, the paper reports evidence of the utility of the BSC framework in measuring and monitoring the performance of e-commerce companies. The study utilizes an integrated Data Envelopment Analysis (DEA) model to examine and evaluate the relative efficiency of the measures identified within the BSC framework for measuring the performance of eCommerce companies. Finally, the study examines the effectiveness of the BSC framework in predicting the success or failure of eCommerce companies by focusing on three successful eCommerce and three eCommerce companies that subsequently failed.</p>

Applying integrated DEA/AHP to evaluate the economic performance of local governments in China

This paper aims at integrating data envelopment analysis (DEA) and analytic hierarchy process (AHP) to evaluate the economic development achieved by local governments in China. Since most similar evaluations are multi-objection problems, which both DEA and AHP are capable of solving, the integration of these two approaches is shown to be even more powerful. The proposed integrated DEA/AHP model can evaluate and rank different alternatives. In addition, a time-scale comparison of the economic performances of local governments in China was carried out using the malmquist productivity index (MPI), which indicated that there is a trend of economic growth. However, empirical results indicate that after discounting the advantages of location and political connections, the east district provinces of China do not have superior economic performance or a better MPI index, as compared with other districts. This result is contrary to our original hypothesis.

Proposing new models for finding the most efficient DMUs in DEA

This paper improves the integrated Data Envelopment Analysis (DEA) model introduced by Amin (2009) [1]. for finding the most efficient Decision Making Units In addition this research introduces an integrated DEA model called “MinMin” and using comparisons between earlier models and the proposed model determines the most efficient Decision Making Unit (DMU). The properties are included in an improved mathematical calculation and this is applied to a real data set consisting of the 19 facility layout alternatives to demonstrate the usefulness and intelligibility of the study.

An integrated Data Envelopment Analysis–Artificial Neural Network–Rough Set Algorithm for assessment of personnel efficiency

Personnel specifications have greatest impact on total efficiency. They can help us to design work environment and enhance total efficiency. Determination of critical personnel attributes is a useful procedure to overcome complication associated with multiple inputs and outputs. The proposed algorithm assesses the impact of personnel efficiency attributes on total efficiency through Data Envelopment Analysis (DEA), Artificial Neural Network (ANN) and Rough Set Theory (RST). DEA has two roles in the proposed integrated algorithm of this study. It provides data ANN and finally it selects the best reduct through ANN result. Reduct is described as a minimum subset of attributes, completely discriminating all objects in a data set. The reduct selection is achieved by RST. ANN has two roles in the integrated algorithm. ANN results are basis for selecting the best reduct and it is also used for forecasting total efficiency. The proposed integrated approach is applied to an actual banking system and its superiorities and advantages are discussed.

A joint measurement of efficiency and effectiveness for non-storable commodities: Integrated data envelopment analysis approaches

Efficiency and effectiveness for non-storable commodities represent two distinct dimensions and a joint measurement of both is necessary to fully capture the overall performance. This paper proposes two novel integrated data envelopment analysis (IDEA) approaches, the integrated Charnes, Cooper and Rhodes (ICCR) and integrated Banker, Charnes and Cooper (IBCC) models, to jointly analyze the overall performance of non-storable commodities under constant and variable returns to scale technologies. The core logic of the proposed models is simultaneously determining the virtual multipliers associated with inputs, outputs, and consumption by additive specifications for technical efficiency and service effectiveness terms with equal weights. We show that both ICCR and IBCC models possess the essential properties of rationality, uniqueness, and benchmarking power. A case analysis also demonstrates that the proposed novel IDEA approaches have higher benchmarking power than the conventional separate DEA approaches. More generalized specifications of IDEA models with unequal weights are also elaborated.

Information technology project evaluation: An integrated data envelopment analysis and balanced scorecard approach

Information technology (IT) is a tool crucial for enterprises to achieve a competitive advantage and organizational innovation. A critical aspect of IT management is the decision whereby the best set of IT projects is selected from many competing proposals. The optimal selection process is a significant strategic resource allocation decision that can engage an organization in substantial long-term commitments. However, making such decisions is difficult because there are lots of quantitative and qualitative factors to be considered in evaluation process. This paper has two main contributions. Firstly, it combines two well-established managerial methodologies, balanced scorecard (BSC) and data envelopment analysis (DEA), and proposes a new approach for IT project selection. This approach uses BSC as a comprehensive framework for defining IT projects evaluation criteria and uses DEA as a nonparametric technique for ranking IT projects. Secondly, this paper introduces a new integrated DEA model which identifies most efficient IT project by considering cardinal and ordinal data. Applicability of proposed approach is illustrated by using real world data of Iran Ministry of Science, Research and Technology.

An integration model of DEA and RST for measuring transport sustainability

This paper addresses the issue of measuring transport sustainability for decision-makers. The Pareto rule states that 80% of important information is concentrated in 20% of content. Simplifying useful information for decision-makers is becoming increasingly more important in a complicated society. This paper integrates data envelopment analysis (DEA) and rough set theory (RST) methods for measuring transport sustainability to obtain effective and clear decision-support information for decision-makers, including transport sustainability performance and its related knowledge base. The current work first compiles and summarizes transport sustainability indicators into five generalized efficiency indicators, termed ‘cost efficiency’, ‘cost effectiveness’, ‘service effectiveness’, ‘service reduction’, and ‘service impact’. Then, applies the layered DEA to classify the decision making units (DMUs: time series data of indicator systems) according to five generalized efficiency indicators. The RST application sets up the related knowledge base, including decision rules and core indicators. An empirical study demonstrates Taiwan's transportation sector during the 1993–2007 period. The empirical study results show core indicators of ‘cost efficiency’, ‘service reduction’, and ‘service impact’. Certain important decision rules indicate that if the ‘cost efficiency’ or ‘service reduction’ indicator performs well, the transport system will move toward more sustainable development. Simplified and important information provided to decision-makers introduces them to strategic tools for improving transport sustainability.

The Productivity of Listed Companies of Computers and Related Equipment Manufacturing Industry

Indicators system of China’s computer manufacturing enterprises of listed companies in Shanghai and Shenzhen can be established to reflect the efficiency of production, which accord to the number of employees, fixed assets and other economic data. Integrated data envelopment analysis (DEA) models are used, combining with evaluation and statistical tests of Synthetic Average method, Borda method, Copeland method and Fuzzy Borda method (SABCB Method). The productivities and returns to scale (RTS) of these computer companies can be figured out. Some results could be obtained through the empirical analysis: firstly, productivities of China’s computer manufacturers are acceptable in general, although there are still great differentiations among them; secondly, due to the lack of outputs, RTS in some enterprises are decreasing; thirdly, it is currently urgent task that most of computer manufacturers continue to refine and deepen specialization transform existing business processes.

Measuring the operating efficiency of internet channels with DEA

The emergence of the internet has forced a wealth of firms to explore a new form of channels of distribution, i.e., internet channels. Managing the impact of introducing an internet channel into an existing distribution system is probably one of the greatest challenges today. This research employs data envelopment analysis (DEA) approach to measure the operating efficiency of internet channels. To improve the effectiveness of the DEA in contributing to group consensus and decision-making, the integration of DEA with Delphi method is proposed. Empirical data are collected from the financial service sector in Taiwan. The findings demonstrate the existence of large inefficiencies. In order to improve the logisitics economics of the inefficient firms, this study further provides guidelines for managers that will eventually benefit policy-making in resource allocation and in strengthening its management.

The impact of decision-making units features on efficiency by integration of data envelopment analysis, artificial neural network, fuzzy C-means and analysis of variance

In today's working environment, there is a great desire to identify the critical attributes for sensitivity analysis of inefficient decision-making units (DMUs) regarding personnel attributes. An integrated algorithm, which uses data envelopment analysis (DEA) and data mining tools including fuzzy C-means (FCM), rough set theory (RST), artificial neural network (ANN), cross validation test technique (CVTT) and analysis of variance (ANOVA), is proposed to asses the impact of personnel attributes on efficiency. DEA is used for DMUs' efficiency evaluation. ANN is employed with regard to its ability to model linear and non-linear systems. As numerous inputs are not useful for ANN modelling, RST and ANN are combined to resolve this issue. RST is used to decrease the time of decision-making. FCM is used for data clustering and finally ANOVA is utilised for identification of attributes importance. The proposed algorithm is applied to an actual banking system.

A hybrid approach for efficient ensembles

An ensemble of classifiers, or a systematic combination of individual classifiers, often results in better classifications in comparison to a single classifier. However, the question regarding what classifiers should be chosen for a given situation to construct an optimal ensemble has often been debated. In addition, ensembles are often computationally expensive since they require the execution of multiple classifiers for a single classification task. To address these problems, we propose a hybrid approach for selecting and combining data mining models to construct ensembles by integrating Data Envelopment Analysis and stacking. Experimental results show the efficiency and effectiveness of the proposed approach.

An integrated DEA–COLS–SFA algorithm for optimization and policy making of electricity distribution units

This paper presents an integrated data envelopment analysis (DEA)–corrected ordinary least squares (COLS)–stochastic frontier analysis (SFA)–principal component analysis (PCA)–numerical taxonomy (NT) algorithm for performance assessment, optimization and policy making of electricity distribution units. Previous studies have generally used input–output DEA models for benchmarking and evaluation of electricity distribution units. However, this study proposes an integrated flexible approach to measure the rank and choose the best version of the DEA method for optimization and policy making purposes. It covers both static and dynamic aspects of information environment due to involvement of SFA which is finally compared with the best DEA model through the Spearman correlation technique. The integrated approach would yield in improved ranking and optimization of electricity distribution systems. To illustrate the usability and reliability of the proposed algorithm, 38 electricity distribution units in Iran have been considered, ranked and optimized by the proposed algorithm of this study.