Improving the discriminating power of DEA: focus on globally efficient units

Despotis, Dimitris K.

doi:10.1057/palgrave.jors.2601253

Cited by 146 publications

(34 citation statements)

References 22 publications

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“…We propose to determine the weights for sub-indicators by solving a DEA linear programming problem that requires no prior knowledge of the weights for sub-indicators. In order to rank all the DMUs on the same scale, a common weights solution is adopted (Despotis 2002;Zohrehbandian et al 2010). The approach not only differentiates efficient DMUs but also estimates the relative weight of each factor (in our case the different domains) in the SWB indicator.…”

Section: The Method: CI Indicators and Common Weight Dea-like Modelmentioning

confidence: 99%

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Statistical Methods and Applications from a Historical Perspective

Crescenzi¹,

Mignani²

2014

Studies in Theoretical and Applied Statistics

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Section: The Method: CI Indicators and Common Weight Dea-like Modelmentioning

confidence: 99%

“…As pointed in Despotis (2002), a general formulation to obtain a common set of weights is as follows:…”

Section: The Method: CI Indicators and Common Weight Dea-like Modelmentioning

confidence: 99%

Statistical Methods and Applications from a Historical Perspective

Crescenzi¹,

Mignani²

2014

Studies in Theoretical and Applied Statistics

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“…The comparison of the different DMUs is carried out by calculating the relative efficiency score for each DMU while abiding to certain constraints. Basically, DEA provides a categorical classification of the units into efficient and inefficient ones [29].…”

Section: Dea Formulationsmentioning

confidence: 99%

Selecting the Six Sigma Project: A Multi Data Envelopment Analysis Unified Scoring Framework

Arafeh¹

2015

AJOR

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The importance of the project selection phase in any six sigma initiative cannot be emphasized enough. The successfulness of the six sigma initiative is affected by successful project selection. Recently, Data Envelopment Analysis (DEA) has been proposed as a six sigma project selection tool. However, there exist a number of different DEA formulations which may affect the selection process and the wining project being selected. This work initially applies nine different DEA formulations to several case studies and concludes that different DEA formulations select different wining projects. Also in this work, a Multi-DEA Unified Scoring Framework is proposed to overcome this problem. This framework is applied to several case studies and proved to successfully select the six sigma project with the best performance. The framework is also successful in filtering out some of the projects that have "selective" excellent performance, i.e. projects with excellent performance in some of the DEA formulations and worse performance in others. It is also successful in selecting stable projects; these are projects that perform well in the majority of the DEA formulations, even if it has not been selected as a wining project by any of the DEA formulations.

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“…assurance region method; and . multi-criteria benefit/cost analysis (Despotis, 2002). This paper benchmarks India states using DEA scores, scale efficiency scores and the discriminatory power enhancing cross-efficiency scores.…”

Section: Introduction To Deamentioning

confidence: 99%

Benchmarking educational development efficiencies of the Indian states: a DEA approach

Gourishankar

Lokachari²

2012

Intl Jnl of Educational Mgt

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -In pursuit of achieving Education-For-All goals of universal primary education and improving quality of education, the Indian Government has been providing substantial resources to Indian states. The responsibility of providing access and quality remains the states' responsibility. Assessment of educational development will therefore become a focal point of the Center for Education Policy & Guidelines Formulation. While educational development indices help in ranking states, they do not help in capturing best practices and assessing the efficient utilization of resources. Assessment of the Educational Development Efficiency can augment educational development indices in vogue. The purpose of this paper is to develop an Educational Development Efficiency (EDE) model to benchmark the Indian states. Design/methodology/approach -This paper uses an input-process-output conceptual framework to identify the dimensions of educational development. This paper employs Data Envelopment Analysis (DEA) to compare relative efficiency of 28 states and seven Union territories in India and benchmark them. In order to strengthen the discriminatory power of DEA, cross-efficiency model was used. Factor analysis was performed to determine the inter-relationships between variables. The efficiency impacting variables were identified using multiple regression analysis. Findings -This paper benchmarked Indian states on educational development based on their performance. Gross enrolment ratio, students' academic performance and infrastructural investments were identified as the three key variables impacting states' EDE. This paper has shown that the educational administrators can use the EDE model to identify the best practices from efficient states. Insights into utilization of input resources to enhance educational development and consequent improvement of state efficiencies are presented. Four components have been identified to analyze the states' educational development progress -namely, financial adequacy, school resource strength, educational quality and educational access. Practical implications -Contributions of this paper pertain to evolving a decision support model for national educati...

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Improving the discriminating power of DEA: focus on globally efficient units

Cited by 146 publications

References 22 publications

Statistical Methods and Applications from a Historical Perspective

Statistical Methods and Applications from a Historical Perspective

Selecting the Six Sigma Project: A Multi Data Envelopment Analysis Unified Scoring Framework

Benchmarking educational development efficiencies of the Indian states: a DEA approach

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