Research Fronts and Prevailing Applications in Data Envelopment Analysis

Liu, John S.; Lu, Louis Y. Y.; Lu, Wen‐Min

doi:10.1007/978-1-4899-7684-0_18

Cited by 12 publications

(12 citation statements)

References 144 publications

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“…The traditional two staged approach involves regressing efficiency estimate against proposed environmental factors (Liu et al, 2016). The applications started with the standard linear models like ordinary, generalized and truncated leastsquared models.…”

Section: Causes Of Inefficienciesmentioning

confidence: 99%

Measuring the Technical and Cost Efficiencies of Maize Farming in the Northern Region of Ghana: Deterministic and Stochastic Approaches

Abukari

Alemdar

2019

AGRISE

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The study sets out to measure the technical, allocative and cost efficiencies of maize farming in the Northern Region of Ghana for the 2014-2015 farming season. The region has 73% of its population as farmers, with maize being the most cultivated and consumed cereal. Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) are employed in the estimation. Interviews were conducted on 121 farmers selected through a mixed sampling technique. The study also segregated the quantities and prices of nitrogen and phosphorus from compound fertilizers. Under DEA, the study found an average efficiency of 79%, 67% and 53% for technical, allocative and cost efficiencies respectively. For SFA the results respectively are 77%, 27% and 21%. Cost and allocative efficiency estimates were very low especially for SFA. Using fractional regression analysis, it was found that household structure of farmers determined their technical efficiencies. Maize land size, marital status, education, and maize farming experience were found to affect allocative efficiency whiles marital status, household structure and maize farming experience affected cost efficiency. The study also found that labor was excessively used in the production process. Fertilizer application increased maize productivity more than other inputs. Policy recommendations were made following these findings.

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Section: Causes Of Inefficienciesmentioning

confidence: 99%

Measuring the Technical and Cost Efficiencies of Maize Farming in the Northern Region of Ghana: Deterministic and Stochastic Approaches

Abukari

Alemdar

2019

AGRISE

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“…In the second step, DEA determines quantitative targets for an inefficient unit to become efficient, via the projection of that unit onto the best-practise frontier, so it is no longer dominated by any other units. Owing to its flexibility, ease of use and decision-aiding capabilities, DEA has been applied to a wide variety of systems, including hospitals, universities, cities, banks, countries, molecules and technologies [44][45][46][47][48] .…”

Section: Methodsmentioning

confidence: 99%

Data envelopment analysis approach to targeting in sustainable chemical process design: Application to liquid fuels

et al. 2018

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This paper presents a framework for combining data envelopment analysis with process systems engineering tools, aiming to improve the sustainability of chemical processes. Given a set of chemical processes, each characterised by performance indicators, the framework discriminates between efficient and inefficient processes regarding those indicators. We develop an approach to quantifying the closest targets for an inefficient process to become efficient, while preventing unrealistic targets by accounting for its thermodynamic limitations represented as mass and energy flow constraints. We demonstrate the capabilities of the framework by assessing a methanol production process with captured CO 2 and fossil-based H 2 , in comparison to ten alternatives. The methanol fuel is found to be suboptimal in comparison with other fuels. Making it competitive would require a significant (unrealistic in the short term) reduction in H 2 price. Alternatively, the methanol fuel could become competitive upon combining fossil-based H 2 with sustainably produced H 2 via windpowered electrolysis.

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“…In other words, DEA is a highly effective technique for evaluating the performance of systems with multiple inputs and outputs (Charnes et al, 1978). The DEA approach is widely considered the standard methodology for comparing similar DMUs (Liu et al, 2016). DEA has proven beneficial in a variety of sectors of society, including airports (Adler et al, 2013), banking (Paradi & Zhu, 2013), hotels (Manasakis et al, 2013), railways (Bhanot & Singh, 2014), financial services (Kaffash and Marra, 2016), airlines (Duygun et al, 2016), telecommunications (Masson et al, 2016) and other industries (Dahmani et al, 2021;Jauha & Pant, 2013;Jauhar et al, 2012;Murugesan et al, 2021).…”

Section: Data Envelopment Analysis and Deep Learningmentioning

confidence: 99%

A deep learning-based approach for performance assessment and prediction: A case study of pulp and paper industries

et al. 2022

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The pulp and paper industry is critical to global industrial and economic development. Recently, India's pulp and paper industries have been facing severe competitive challenges. The challenges have impaired the environmental performance and resulted in the closure of several operations. Assessment and prediction of the performance of the Indian pulp and paper industry using various parameters is a critical task for researchers. This study proposes a framework for performance assessment and prediction based on Data Envelopment Analysis (DEA), Artificial Neural Networks, and Deep Learning (DL) to assist industry administration and decision-making. We presented a case study based on eight industries to demonstrate the methodology's applicability. This study analyses and predicts industry performance based on sample data observations over 30 years. The result suggests the DEA-DL-based efficiency prediction has an overall MSE of 0.08 compared with the actual efficiency. Furthermore, the efficiency rankings are compared between the three techniques. The results suggest that the integrated DEA-DL method is primarily accurate in most scenarios with the actual values. The findings of this study provide a comprehensive analysis of environmental performance for policymakers.

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Research Fronts and Prevailing Applications in Data Envelopment Analysis

Cited by 12 publications

References 144 publications

Measuring the Technical and Cost Efficiencies of Maize Farming in the Northern Region of Ghana: Deterministic and Stochastic Approaches

Measuring the Technical and Cost Efficiencies of Maize Farming in the Northern Region of Ghana: Deterministic and Stochastic Approaches

Data envelopment analysis approach to targeting in sustainable chemical process design: Application to liquid fuels

A deep learning-based approach for performance assessment and prediction: A case study of pulp and paper industries

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