Review of efficiency ranking methods in data envelopment analysis

Aldamak, Abdullah; Zolfaghari, Saeed

doi:10.1016/j.measurement.2017.04.028

Cited by 122 publications

(63 citation statements)

References 145 publications

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“…The inputs are CSR implementation for government, labor, customer and community, and the output is the reputation of the business. Among a considerable number of studies on efficiency, the DEA method is commonly used to evaluate performance because of the simplicity of the model, which uses many input and output variables without assigning prior weight to indicators (Aldamak & Zolfaghari, 2017). Botsian and Karpiuk (2015) states DEA as a non-parametric analysis method that can be used to measure efficiency of CSR.…”

Section: Csr Efficiency Evaluationmentioning

confidence: 99%

Applying 2-stage DEA model to evaluate the corporate social responsibility implementing efficiency of FDI firms

Tran¹

2020

10.5267/j.msl

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From the stakeholder theory, the research evaluates the efficiency and impact of corporate social responsibility (CSR) implementation for various stakeholders including government, labor, customer, community on corporate reputation. A 2-stage Data Enveloped Analysis (DEA) model was employed using a quantitative method of questionnaire survey among a sample of 208 foreign direct investment (FDI) enterprises in Hanoi, Vietnam: Stage 1: Using DEA model to evaluate the efficiency of CSR implementation to improve the reputation of enterprises; Stage 2: Using multivariate regression model to assess the impact of CSR implementation on stakeholders in order to improve the reputation of enterprises. The result of the study should give managerial implications for the government and FDI firms in understanding the current state of CSR efficiency, as well as to formulate more target policies to promote FDI firms' efficient commitment to CSR.

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Section: Csr Efficiency Evaluationmentioning

confidence: 99%

Applying 2-stage DEA model to evaluate the corporate social responsibility implementing efficiency of FDI firms

Tran¹

2020

10.5267/j.msl

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“…It is concluded that the countries whose efficiency is high in both the models have a balanced student to teacher ratio irrespective of their socioeconomic conditions. Zolfaghari.et.al [16] have reviewed the information to enhance the inequity potential of the analytical technique i.e. DEA (Data Envelopment Analysis).…”

Section: Literature Reviewmentioning

confidence: 99%

A Non-parametric Estimation for Efficacy of Government Expenditure on Secondary Education

Khowas*¹,

Bagli²

2020

IJMH

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The paper is aimed to analyse the efficacy of government expenditure on secondary education in Purulia district of West- Bengal, India. Efficacy relates the input or the output to the final objectives of the analysis to be achieved, i.e. the outcome. Education facility is mainly a mixed good which is partly excludable and partly rivalry. India has been suffering from poverty and illiteracy problem for decades. Illiteracy and low level of education is a factor for widespread poverty in India. Among the education system, secondary education plays a crucial role to enhance the human development level which ultimately contributes in development process. So, government should give emphasis on secondary education and it should be concerned about the efficacy of the government expenditure on secondary education. As in the present scenario, the structural adjustment policy (SAP) leads to some sort of cut back on expenditure on education. This study first calculates the technical efficiency as well as the scale efficiency of government expenditure on secondary education of school using Data Envelopment Analysis (DEA), then categorize the schools into low, moderate and high according to the value of technical efficiency and scale efficiency based on three models (i) considering all inputs (Teacher Student Ratio, Expenditure per Student, % of Students belong to SC, % of Students belong to ST, % of Students belong to OBC, % of Teacher with Professional Qualification, Student- Classroom Ratio, % of Girl’s Student Enrolment) (ii) considering prime two inputs (Student-Teacher Ratio and Expenditure per Student) and (iii) considering only one input (Expenditure per Student) and try to find out the reason of differences in efficiency. The common set of schools from High, Moderate and Low efficiency schools considering above said three models are further analysed with the primary data collected from the student sets to analyse whether the school efficiency affect the student’s individual performance or not with the help of regression analysis.

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“…The super-efficiency DEA model is an important method for measuring green productivity. The degree of relative change of GTFP is obtained by comparing the actual green output level with the frontier level by a directional distance function [37]. The directional distance function (DDF) is used to represent a steady increase of the expected output during production, while minimizing undesired output.…”

Section: Super-efficiency Dea Model and ML Indexmentioning

confidence: 99%

Study on Measurement of Green Productivity of Tourism in the Yangtze River Economic Zone, China

et al. 2018

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This paper introduces energy consumption and carbon emission into the analysis framework of the green productivity of tourism. By comparing and analyzing the two main methods used to evaluate the energy consumption and carbon emission estimations of tourism, namely, the "top-down" and "bottom-up" method, and considering the availability of data, the "bottom-up" method was adopted to evaluate the energy consumption and carbon emissions of tourism in the Yangtze River Economic Zone (YREZ). Then, using the Malmquist-Luenberger (ML) index in the super-efficiency data envelopment analysis (DEA) model, the green productivity of the tourism in 11 provinces and cities in the YREZ from 2006 to 2015 was measured. The empirical results show that:(1) The energy consumption and carbon emissions of tourism in the YREZ have increased steadily over the past 10 years, which has caused a certain degree of pollution to the environment, indicating that tourism is no longer a "smoke-free industry"; (2) there are significant provincial differences between the energy consumption and carbon emissions of tourism in the YREZ, with Shanghai always ranking first, while Guizhou and Yunnan ranks last, which represents that the tourism economic development level is positively correlated with the tourism energy consumption and carbon emissions; (3) the green productivity of tourism in the YREZ shows a fluctuating increasing trend in the past 10 years, and technological progress has become the main reason for its growth in green productivity; and (4) the green productivity of tourism in 11 provinces and cities in the YREZ can be divided into three types: Progressive type of tourism green development, stagnant type of tourism green development, and declining type of tourism green development. Consequently, different types of provinces should explore effective dependency paths based on their own conditions.

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Review of efficiency ranking methods in data envelopment analysis

Cited by 122 publications

References 145 publications

Applying 2-stage DEA model to evaluate the corporate social responsibility implementing efficiency of FDI firms

Applying 2-stage DEA model to evaluate the corporate social responsibility implementing efficiency of FDI firms

A Non-parametric Estimation for Efficacy of Government Expenditure on Secondary Education

Study on Measurement of Green Productivity of Tourism in the Yangtze River Economic Zone, China

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