A DEA-based tool for tracking best practice exemplars: The case of telecommunications in EBRD countries

Benchmarking is a strategic management tool that can help to gain competitive advantage, but the question is how to decide the relevant practice exemplars to be used as role models. Data Envelopment Analysis (DEA) is a very helpful method for tracking corresponding benchmarks, but the question remains of how to record them when performance is fluctuating and unstable, as is the case in a transition period to an open market. To address this issue a new DEA-based tool is proposed, the Corresponding Benchmark Matrix (CBM), which helps to reveal ?leader? countries and the most suitable benchmarks for less successful countries. The approach is illustrated for telecommunications in 22 European Bank for Reconstruction and Development (EBRD) countries.

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DATA ENVELOPMENT ANALYSIS (DEA) AS A TOOL FOR EVALUATING THE PERFORMANCE OF THE STRATEGIC MANAGEMENT

Revista Universo Contábil ◽

10.4270/ruc.2011323 ◽

2011 ◽

pp. 77-94

Author(s):

Ana Lúcia Miranda Lopes ◽

João Roberto Lorenzett ◽

Maurício Fernandes Pereira

Keyword(s):

Data Envelopment Analysis ◽

Strategic Management ◽

Data Envelopment

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Performance of Village Unit Co-Operatives in Yogyakarta Special Region: A Data Envelopment Analysis Approach

Ilmu Pertanian (Agricultural Science) ◽

10.22146/ipas.10656 ◽

2017 ◽

Vol 1 (2) ◽

pp. 067

Author(s):

Abi Pratiwa Siregar ◽

Jamhari Jamhari ◽

Lestari Rahayu Waluyati

Keyword(s):

Data Envelopment Analysis ◽

Technical Efficiency ◽

Best Practice ◽

Negative Impact ◽

Positive Impact ◽

Three Dimensions ◽

Scale Efficiency ◽

Data Envelopment ◽

Rice Milling ◽

Special Region

This study assessed the performance of 32 village unit co-operatives (KUD) in Yogyakarta Special Region during 2011 to 2012. The efficiency level of the KUD were evaluated by employing the data envelopment analysis and multiple regression analysis using panel data to determine the factors affecting efficiency level. Efficiency analysis was decomposed into three dimensions to explore possible sources of inefficiency. According to Marwa and Aziakpono (2016), the first dimension was technical efficiency, which explored the overall effectiveness of transforming the productive inputs into desired outputs compared to the data-driven frontier of best practice. The second dimension was pure technical efficiency, which captured managerial efficiency in the intermediation process. The third dimension was scale efficiency, which explored whether KUD were operating in an optimal scale of operation or not. The results found that the average scores are 64%, 92%, and 68% for technical, pure technical, and scale efficiency respectively in 2011, while in 2012 the average scores are 57%, 94%, and 60% for technical, pure technical, and scale efficiency. Factors having significantly positive impact on several measures of efficiency are incentive and dummy variables (agriculture inputs and hand tractor). Accounts receivable only has positive relationship to pure technical efficiency. On the other hand, rice milling unit and electricity services have negative impact with several measures of efficiency.

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Evaluating European Bank Efficiency Using Data Envelopment Analysis: Evidence in the Aftermath of the Recent Financial Crisis

International Advances in Economic Research ◽

10.1007/s11294-020-09807-y ◽

2020 ◽

Vol 26 (4) ◽

pp. 391-405

Author(s):

Cândida Ferreira

Keyword(s):

Data Envelopment Analysis ◽

Financial Crisis ◽

Data Envelopment ◽

Bank Efficiency ◽

European Bank ◽

Recent Financial Crisis ◽

Using Data

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How to use the Evaluation of Suppliers to Develop the Supply System

Supply Chain Innovation for Competing in Highly Dynamic Markets ◽

10.4018/978-1-60960-585-8.ch017 ◽

2012 ◽

pp. 253-268

Author(s):

Emilio Esposito ◽

Renato Passaro

Keyword(s):

Strategic Management ◽

Competitive Advantage ◽

Empirical Evidence ◽

Supply System ◽

Strategic Decision ◽

Management Tool ◽

Supplier Evaluation ◽

Competitive Position ◽

Practical Usefulness ◽

Managerial Implications

In recent decades several studies have highlighted that the competitive advantage of large customer firms arises significantly from their ability to achieve a successful supply system through the adoption of effective tools and methodologies for evaluating suppliers. Nevertheless it emerges that a gap exists between a growing number of applications and the scarce empirical evidence of the practical usefulness of such applications. The purpose of this chapter is to provide a contribution to bridging this gap through applying the Analytical Hierarchical Process (AHP) methodology suppliers’ evaluation. The evaluation tree of the AHP assures transparency and traceability, features that allow using it as a tool for strategic management of the supply system. The AHP evaluation tree provides relevant indications for the strategic decision that both customers and suppliers have to adopt to reinforce the supply system and their competitive position. Relevant issues arising from the application and managerial implications for both customer and suppliers are discussed. In particular, we underline how the AHP methodology is not only a tool for supplier evaluation but also a strategic management tool to develop the supply system.

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Dynamic network data envelopment analysis for university hospitals evaluation

Revista de Saúde Pública ◽

10.1590/s1518-8787.2016050006022 ◽

2016 ◽

Vol 50 (0) ◽

Cited By ~ 3

Author(s):

Maria Stella de Castro Lobo ◽

Henrique de Castro Rodrigues ◽

Edgard Caires Gazzola André ◽

Jônatas Almeida de Azeredo ◽

Marcos Pereira Estellita Lins

Keyword(s):

Data Envelopment Analysis ◽

Best Practice ◽

Assessment Tool ◽

Health Planning ◽

Dynamic Network ◽

Medical Residents ◽

Network Data ◽

Data Envelopment ◽

Research Projects ◽

Network Data Envelopment Analysis

ABSTRACT OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier.

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Chance-constrained data envelopment analysis modeling with random-rough data

RAIRO - Operations Research ◽

10.1051/ro/2016076 ◽

2018 ◽

Vol 52 (1) ◽

pp. 259-284 ◽

Cited By ~ 5

Author(s):

Rashed Khanjani Shiraz ◽

Madjid Tavana ◽

Debora Di Caprio

Keyword(s):

Data Envelopment Analysis ◽

Deterministic Model ◽

Equivalent Model ◽

Management Tool ◽

Data Envelopment ◽

Output Data ◽

Quadratic Constraints ◽

Dea Model ◽

Deterministic Equivalent ◽

Input And Output

Data envelopment analysis (DEA) is a useful management tool for measuring the relative efficiency of decision making units (DMUs) which consumes multiple inputs to produce multiple outputs. Although precise input and output data are fundamentally indispensable in classical DEA models, real-world problems often involve random and/or rough input and output data. We present a chance-constrained DEA model with random and rough (random-rough) input and output data and propose a deterministic equivalent model with quadratic constraints to solve the model. The main contributions of this paper are fourfold: (3.1) we propose a DEA model for problems characterized by random-rough variables; (3.2) we transform the proposed chance-constrained model with random-rough variables into a deterministic equivalent non-linear form that could be simplified as a deterministic model with quadratic constraints; (3.3) we perform sensitivity analysis to investigate the stability and robustness of the proposed model; and (3.4) we use a numerical example to demonstrate the feasibility and richness of the obtained solutions.

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Research Governance in Public University: Proposal of a Composite Index

Journal of Education ◽

10.1177/00220574211032582 ◽

2021 ◽

pp. 002205742110325

Author(s):

Driss El Kadiri Boutchich

Keyword(s):

Data Envelopment Analysis ◽

Strategic Management ◽

Geometric Mean ◽

Composite Index ◽

Organizational Management ◽

Public University ◽

Research Governance ◽

Data Envelopment

This work aims to elaborate a governance composite index for research laboratories in public university. This index is composed by an indicator of responsible liberalism associating effectiveness and ethics, to which are added an organizational management indicator and a strategic management indicator. To achieve the above aim, several methods are used, such as adjusted data envelopment analysis and geometric mean to aggregate indicators to calculate the composite index, Vigier index to compute responsible liberalism indicator, and tools to measure the validity and the reliability of indicators. The findings show that the developed index can be applied in any context.

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