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Common weights in dynamic network DEA with goal programming approach for performance assessment of insurance companies in Iran

Common weights in dynamic network DEA with goal programming approach for performance assessment... Conventional data envelopment analysis (DEA) models permit each decision-making unit (DMU) to assess its efficiency score with the most favorable weights. In other words, each DMU selects the best weighting schemes to obtain maximum efficiency for itself. Therefore, using different sets of weights leads to many different efficient DMUs, which makes comparing and ranking them on a similar basis impossible. Another issue is that often more than one DMU is evaluated as efficient because the selection of weights is flexible; therefore, all DMUs cannot be completely differentiated. The purpose of this paper is to development a common weight in dynamic network DEA with a goal programming approach.Design/methodology/approachIn this paper, a goal programming approach has been proposed to generate common weights in dynamic network DEA. To validate the applicability of the proposed model, the data of 30 non-life insurance companies in Iran during 2013-2015 have been used for measuring their efficiency scores and ranking all of the companies.FindingsFindings show that the proposed methodology is an effective and practical approach to measure the efficiency of DMUs with dynamic network structure.Originality/valueThe proposed model delivers more knowledge of the common weight approaches and improves the DEA theory and methodology. This model makes it possible to measure efficiency scores and compare all DMUs from multiple different standpoints. Further, this model allows one to not only calculate the overall efficiency of DMUs throughout the time period but also consider dynamic change of the time period efficiency and dynamic change of the divisional efficiency of DMUs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Management Research Review Emerald Publishing

Common weights in dynamic network DEA with goal programming approach for performance assessment of insurance companies in Iran

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References (69)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
2040-8269
DOI
10.1108/mrr-03-2017-0067
Publisher site
See Article on Publisher Site

Abstract

Conventional data envelopment analysis (DEA) models permit each decision-making unit (DMU) to assess its efficiency score with the most favorable weights. In other words, each DMU selects the best weighting schemes to obtain maximum efficiency for itself. Therefore, using different sets of weights leads to many different efficient DMUs, which makes comparing and ranking them on a similar basis impossible. Another issue is that often more than one DMU is evaluated as efficient because the selection of weights is flexible; therefore, all DMUs cannot be completely differentiated. The purpose of this paper is to development a common weight in dynamic network DEA with a goal programming approach.Design/methodology/approachIn this paper, a goal programming approach has been proposed to generate common weights in dynamic network DEA. To validate the applicability of the proposed model, the data of 30 non-life insurance companies in Iran during 2013-2015 have been used for measuring their efficiency scores and ranking all of the companies.FindingsFindings show that the proposed methodology is an effective and practical approach to measure the efficiency of DMUs with dynamic network structure.Originality/valueThe proposed model delivers more knowledge of the common weight approaches and improves the DEA theory and methodology. This model makes it possible to measure efficiency scores and compare all DMUs from multiple different standpoints. Further, this model allows one to not only calculate the overall efficiency of DMUs throughout the time period but also consider dynamic change of the time period efficiency and dynamic change of the divisional efficiency of DMUs.

Journal

Management Research Review – Emerald Publishing

Published: Jul 24, 2018

Keywords: Data envelopment analysis; Common weights; Goal programming; Production and operations management; Insurance companies; Operation management; Performance assessment

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