A stochastic data envelopment analysis model using a common set of weights and the ideal point concept

Tavana, Madjid; Kazemi, Sajad; Mavi, Reza Kiani

doi:10.1504/ijams.2015.069262

Cited by 17 publications

(8 citation statements)

References 34 publications

(35 reference statements)

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“…Researchers have solved this problem by using various methods (e.g., [4,16,50,94]). Among them, the CW models are more favorable and applicable according to the literature (e.g., [15,28,50,76,79,86]). In this research, we will use the CW model based on the ideal point method proposed by Sun et al [75].…”

Section: The Ccr Model With Non-discretionary Inputsmentioning

confidence: 99%

A common weights model for investigating efficiency-based leadership in the russian banking industry

et al. 2021

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In this race for productivity, the most successful leaders in the banking industry are those with high-efficiency and a competitive edge. Data envelopment analysis is one of the most widely used methods for measuring efficiency in organizations. In this study, we use the ideal point concept and propose a common weights model with fuzzy data and non-discretionary inputs. The proposed model considers environmental criteria with uncertain data to produce a full ranking of homogenous decision-making units. We use the proposed model to investigate the efficiency-based leaders in the Russian banking industry. The results show that the unidimensional and unilateral assessment of leading organizations solely according to corporate size is insufficient to characterize industry leaders effectively. In response, we recommend a multilevel, multicomponent, and multidisciplinary evaluation framework for a more reliable and realistic investigation of leadership at the network level of analysis.

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Section: The Ccr Model With Non-discretionary Inputsmentioning

confidence: 99%

A common weights model for investigating efficiency-based leadership in the russian banking industry

et al. 2021

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“…Researchers have used different techniques to generate a CSW, for example, compromise programming (Kao and Hung, 2005;Kiani Mavi et al, 2012), ideal point method for stochastic data (Tavana et al, 2015) and non-discretionary inputs (Kiani Mavi et al, 2013), utility function (Jahanshahloo et al, 2017), mean-variance criteria (Razavi Hajiagha et al, 2018) and regression analysis .…”

Section: Common Weight Analysis In Data Envelopment Analysismentioning

confidence: 99%

Eco-innovation analysis of OECD countries with common weight analysis in data envelopment analysis

Mavi

Saen

et al. 2021

SCM

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PurposeDespite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity index (MPI). In conventional data envelopment analysis (DEA) models, decision-making units (DMUs) are inclined to assign more favorable weights, even zero, to the inputs and outputs to maximize their own efficiency. This paper aims to overcome this shortcoming by developing a common set of weights (CSW). Design/methodology/approachUsing goal programming, this study develops a CSW model to evaluate the EI efficiency of the organization for economic co-operation and development (OECD) countries and track their changes with MPI during 2010–2018. FindingsAchieving a complete ranking of DMUs, findings show the higher discrimination power of the proposed CSW compared with the original DEA models. Furthermore, results reveal that Iceland, Latvia and Luxembourg are the only OECD countries that have incessantly improved their EI productivity (MPI > 1) from 2010 to 2018. On the other hand, Japan is the OECD country that has experienced the highest yearly EI efficiency during 2010–2018. This paper also found that Iceland has the highest MPI over 2010–2018. Practical implicationsMore investment in environmental research and development (R&D) projects instead of generic R&D enables OECD members to realize more opportunities for sustainable development through minimizing energy use and environmental pollution in any form of waste and greenhouse gas emissions. Originality/valueIn addition to developing a novel common weights model for DEA-MPI to measure and evaluate the EI of OECD countries, this paper develops a CSW model by including the undesirable outputs for EI analysis.

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“…Makui et al (2008), using goal programming approach, developed common weights for DEA models that improve the discrimination power. Kiani Mavi et al (2013) and Tavana et al (2015) used the ideal point concept to develop common set of weights. Vaz et al (2010) implemented the network-DEA model to assess the efficiency of the retail stores that have many selling divisions.…”

Section: Literature Reviewmentioning

confidence: 99%

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

Gharakhani

Eshlaghy

Hafshejani

et al. 2018

MRR

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Purpose 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/approach In 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. Findings Findings show that the proposed methodology is an effective and practical approach to measure the efficiency of DMUs with dynamic network structure. Originality/value The 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.

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A stochastic data envelopment analysis model using a common set of weights and the ideal point concept

Cited by 17 publications

References 34 publications

A common weights model for investigating efficiency-based leadership in the russian banking industry

A common weights model for investigating efficiency-based leadership in the russian banking industry

Eco-innovation analysis of OECD countries with common weight analysis in data envelopment analysis

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

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