dea approach
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2022 ◽  
pp. 101226
Author(s):  
C.O. Henriques ◽  
J.M. Chavez ◽  
M.C. Gouveia ◽  
O.D. Marcenaro-Gutierrez

2021 ◽  
Vol 2 (6) ◽  
pp. 30-39
Author(s):  
R. Nellutla ◽  
R. Ashok ◽  
M. Ramesh ◽  
V. V. Haragopal

In this present research paper we analyze the universities data by CCR, BCC models through Data Envelopment Analysis (DEA) approach for the State of Telangana. To know the Performance of student’s university wise in state of Telangana. University wise Performances is presented along with technical efficiency, Pure Technical Efficiency, Scale Efficiency, CRS, VRS, Reference set and Peers. Measuring the Technical Efficiency (TE) and Pure Technical Efficiency (PTE) of the universities by CCR, BCC Model through DEA approach.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aparajita Singh ◽  
Haripriya Gundimeda

PurposeThe Indian leather industry contributes to economic growth at a significant environmental cost. Due to the rising global demand for sustainable leather products, promoting efficient input utilisation has become vital. This study measures input efficiency and its determinants for leather industry in order for it to improve its future performance.Design/methodology/approachIn the first stage, bootstrap data envelopment analysis (DEA) approach is used for measuring efficiency and analysing firms' differences based on their geographical location, organisational structures, urban-rural location and sub-industrial groups. A second stage regression examines efficiency determinants using size, age, skill and capital-labour intensity as the explanatory variables.FindingsEfficiency result shows a significant potential of minimising inputs by 47% provided the firms adopt best practices. West Bengal firms, urban located firms, individual and proprietorship owned firms and leather consumer goods firms are found to be relatively efficient to their counterparts. Size, skilled managerial staff and labour-intensive firms positively affect efficiency.Practical implicationsConstruction of well-connected roads for accessing urban retail markets and provision of reliable electricity would improve efficiency of rural firms. Small-scale enterprises have a larger share in Indian leather industry; therefore, policy should focus on enhancing the firms' scale and investing in training facilities to skill employed labour for ensuring optimal use of inputs.Originality/valuePrevious studies on the leather industry have used the conventional DEA efficiency measurement approach. This study uses DEA bootstrapping model for robust efficiency estimates and provides consistent inferences about the determinants.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fazıl Gökgöz ◽  
Engin Yalçın

Purpose This paper aims to assess the efficiency levels of World Cup teams via the slack-based data envelopment analysis (DEA) approach, which contributes to filling an important gap for performance measurement in football. Design/methodology/approach This study focuses on a comparative analysis of the past two World Cups. The authors initially estimate the efficiency of the World Cup teams via the slack-based DEA approach, which is a novel approach for sports performance measurement. The authors also present the conventional DEA results to compare results. The authors also include improvement ratios, which provide significant details for inefficient countries to enhance their efficiency. Besides, the authors include effectiveness ratings to present a complete performance overview of the World Cup teams. Findings According to the analysis results of the slack-based DEA approach, titleholder Germany and France are found as efficient teams in the 2014 and 2018 World Cup, respectively. Besides, Belgium and Russia recorded the highest efficiency improvement in the 2018 World Cup. The novel approach for sports performance measurement, the slack-based DEA approach, significantly overlaps with the actual performance of teams. Originality/value This study presents novelty in football performance by adopting the slack-based DEA with an undesirable output model for the performance measurement of the World Cup teams. This empirical analysis would be a pioneer study measuring the performance of football teams via the slack-based DEA approach.


2021 ◽  
Vol 6 (1) ◽  
pp. 57-69
Author(s):  
Nadeem Iqbal ◽  
Qaiser Abbas ◽  
Mukhtiar Ali Erri ◽  
Dr. Shams ur Rehman

Like many developing countries, Pakistan has limited energy production and governmental funding to support its development. This research focuses on energy efficiency levels and governmental funds distribution among four provinces in Pakistan. Based on balanced panel data from 2006 to 2016, this study develops a novel Zero-Sum Gain (ZSG) DEA approach to simultaneously assess energy efficiency levels and reallocate limited financial resources among provinces. Under the assumption of constant outputs, energy production and governmental funds are considered as input variables, while GDP and population as output variables. Results indicate that efficiency levels of Pakistan provinces range between 0.62 to 0.88, thus suggesting room for improvement in funding allocation.


Author(s):  
Mohd Afjal ◽  
Kavya C S

This study uses the Data Envelopment Analysis (DEA) slack-based model (SBM) and Malmquist Productivity Index (MPI) to evaluate energy efficiency based on CO2 emissions in 42 countries belonging to 6 continents. First, the data envelopment analysis was employed to calculate the efficiency scores for the countries individually and continent basis and then Malmquist index was used to examine the improvement. The study period chosen was 2011-2020. The results of this study showed that on the basis of continents there has been fluctuations in energy efficiency except for Australia, with an efficiency score of equal to one throughout the study period. Additionally, from the results of Malmquist Productivity Index it was found that the 42 countries showed no significant energy enhancement during the period of 2011-2020. KEYWORDS: Energy Efficiency, CO2 emissions, Continents, Data Envelopment Analysis, Malmquist Productivity Index


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