A new multi-component DEA approach using common set of weights methodology and imprecise data: an application to public sector banks in India with undesirable and shared resources

Puri, Jolly; Yadav, Shiv Prasad; Garg, Harish

doi:10.1007/s10479-017-2540-1

Cited by 26 publications

(16 citation statements)

References 48 publications

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“…Since the seminal work by Charnes et al (1978), applications of efficiency models have emerged in various sectors, ranging from health care (e.g. Cordero et al 2015), water (Cherchye et al 2014), banking (Puri et al 2017), public sector (De Witte and Geys 2013), farming (Asmild et al 2016) or energy (e.g. Chen et al 2017;Hampf et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Managerial efficiency and efficiency differentials in adult education: a conditional and bias-corrected efficiency analysis

2019

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In efficiency studies, inputs and outputs are often noisy measures, especially when education data is used. This article complements the conditional efficiency model by correcting for bias within conditional draws, using the m out of n bootstrap procedure. With a unique panel dataset, we estimate managerial efficiency, which accounts for nondiscretionary variables, and explain efficiency differentials of adult education programs in Flanders. Our results suggest that the characteristics of learners in a program matter for managerial efficiency, and that teacher characteristics are strongly correlated with efficiency differentials, as more homogeneity in the teacher workforce appears to result in higher program efficiency.

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Section: Introductionmentioning

confidence: 99%

Managerial efficiency and efficiency differentials in adult education: a conditional and bias-corrected efficiency analysis

2019

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“…Charnes (1979) put forward the DEA model in 1979. Then the DEA model has been an effective mathematical programming method for assessing the relative efficiency of a set of decision‐making units (DMUs) with multiple inputs and outputs (Puri, Yadav, & Garg, 2017). According to the study of Kuosmanen and Kortelainen (2010), this paper applied DEA to calculate the eco‐efficiency.…”

Section: Methodology and Datamentioning

confidence: 99%

Estimation of eco‐efficiency and identification of its influencing factors in China's Yangtze River Delta urban agglomerations

Zhang

2020

Growth and Change

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Eco-efficiency is an important indicator which serves as a helpful instrument for the studies of sustainable development. This paper estimated the eco-efficiency of 26 cities in China's Yangtze River Delta urban agglomerations. Based on different matrixes, Moran's I was applied to analyze the spatial correlation. The spatial Durbin model was applied to analyze the direct and indirect effect of influencing factors. Some conclusions were drawn. (a) The average eco-efficiency showed an increasing trend. The regional difference of ecoefficiency decreased and then increased. Shanghai's ecoefficiency had been the highest. (b) The eco-efficiency showed positive spatial autocorrelation and it also exhibited significant characteristic of local spatial autocorrelation. (c) Economic development, fixed assets investment, and technological level of one city had a significant positive impact on the eco-efficiency of the city itself. Industrial structure, fiscal decentralization, and foreign direct investment of a city had a significant negative impact on the eco-efficiency of the city itself. Changes in the economic development and technological levels in a city had positive impacts on the eco-efficiency of its neighboring cities. Foreign direct investment had a negative spatial spillover effect. (d) This paper suggested that it is necessary to pay attention to the interaction of influencing factors among cities.

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“…Several MADM techniques have been proposed for the SSE problem: analytic hierarchy process (AHP) [34][35][36], analytic network process (ANP) [34], complex proportional assessment (COPRAS) [36][37][38], data envelopment analysis (DEA) [36,[39][40][41], elimination et choix traduisant la realité (ELECTRE) [42,43], preference ranking organization method for enrichment of evaluations (PROMETHEE) [44], technique for order of preference by similarity to ideal solution (TOPSIS) [45][46][47][48][49], visekriterijumska optimizacija i kompromisno resenje (VIKOR) [50,51], decision-making trial and evaluation laboratory (DEMATEL) [52,53], multi-objective optimisation by ratio analysis (MOORA) [54], case based reasoning (CBR) [55], fuzzy inference systems [56,57], genetic algorithm (GA) [58], mathematical and goal programming (MP) [59], simple multi-attribute rating technique (SMART) [60], and their hybrids, among others. In those MADM techniques, the supplier qualification is set according to the valuation given to different relevant factors (qualitative and quantitative) in the evaluation process.…”

Section: Main Methodologies and Factors Used In Sse Modelsmentioning

confidence: 99%

Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products

et al. 2018

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This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: a factor weighting method (WM) and a fuzzy inference system (FIS). By consulting an expert panel and using a two-tuples symbolic translation system, strong fuzzy partitions for all model variables are built. The method, based on central symmetry, permits to obtain the fuzzy label borders from their cores, which have been previously agreed among experts. The system also allows to agree the fuzzy rules to embed in the FIS. The results show the FIS method's superiority as it allows to better manage the non-linear behavior and the uncertainty inherent to the supplier evaluation process.

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A new multi-component DEA approach using common set of weights methodology and imprecise data: an application to public sector banks in India with undesirable and shared resources

Cited by 26 publications

References 48 publications

Managerial efficiency and efficiency differentials in adult education: a conditional and bias-corrected efficiency analysis

Managerial efficiency and efficiency differentials in adult education: a conditional and bias-corrected efficiency analysis

Estimation of eco‐efficiency and identification of its influencing factors in China's Yangtze River Delta urban agglomerations

Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products

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