China’s Input-Output Efficiency of Water-Energy-Food Nexus Based on the Data Envelopment Analysis (DEA) Model

Li, Guijun; Huang, Daohan; Li, Yulong

doi:10.3390/su8090927

Cited by 80 publications

(36 citation statements)

References 19 publications

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“…DEA-MI was first used to measure the changes in DMU yield over two time periods under multiple inputs and outputs. The change in efficiency is based on change in product technology (transitive effect) and change in efficiency (effect catch up) [15][16][17][18]. The change in efficiency is a two-stage performance measurement of 1 and 2 changes.…”

Section: Data Envelopment Analysis-malmquist Models (Dea-mi)mentioning

confidence: 99%

Using the Optimization Algorithm to Evaluate the Energetic Industry: A Case Study in Thailand

Wang

Nguyen

et al. 2019

Processes

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Thailand’s economy is developing rapidly, with energy being a significant factor in this development. This study uses a variety of models to assess the performance of Thailand’s energy industry in two different phases, the first being from 2013 to 2017 and the second from 2018 to 2020. The Malmquist model-one of data envelopment required input and output data that showed Thailand’s productivity index and the rate-of-change ratio, which is used to assess technical changes, change efficiency, and productivity changes of the 12 listed companies in energetic generation and distribution in Thailand. To calculate future indicators, the forecast data are generated by applying the Grey model (1,1) GM(1,1). Accuracy prediction is determined by the mean absolute percentage error (MAPE). The results show that the magnitude of the change in efficiency during the first period is stable, and some major changes in the technical level of some companies may be observed. In the future, the performance of most companies has increased steadily, but performance has been outstanding. This research provides insights into Thailand’s energy over the past few years, and predictions of future performance may be used as a reference for more purposes.

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Section: Data Envelopment Analysis-malmquist Models (Dea-mi)mentioning

confidence: 99%

Using the Optimization Algorithm to Evaluate the Energetic Industry: A Case Study in Thailand

Wang

Nguyen

et al. 2019

Processes

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“…According to Table 2 and Figure 1, 45 high-quality journals published several articles on the application of DEA models in these fields. Li, et al [163] 30 provinces CRR and BCC DEA Efficiency of Water-Energy…”

Section: Distribution Of Paper Based On Journal Selectionmentioning

confidence: 99%

Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends

et al. 2018

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Measurement of environmental and energy economics presents an analytical foundation for environmental decision making and policy analysis. Applications of data envelopment analysis (DEA) models in the assessment of environmental and energy economics are increasing notably. The main objective of this review paper is to provide the comprehensive overview of the application of DEA models in the fields of environmental and energy economics. In this regard, a total 145 articles published in the high-quality international journals extracted from two important databases (Web of Science and Scopus) were selected for review. The 145 selected articles are reviewed and classified based on different criteria including author(s), application scheme, different DEA models, application fields, the name of journals and year of publication. This review article provided insights into the methodological and conceptualization study in the application of DEA models in the environmental and energy economics fields. This study should enable scholars and practitioners to understand the state of art of input and output indicators of DEA in the fields of environmental and energy economics.

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“…Based on the innovative adjustments on our theoretical model in Section 3.1, we have included the undesirable outputs into our model as important outputs. In empirical studies, Ma (2012) and Li et al (2016) have also adopted similar model settings [35,36]. In our model, we have selected the official statistical data on annual wastewater emissions (in ten thousand tons) of each province published by National Bureau of Statistics of China each year (from 2003 to 2014) as our undesirable output data [2].…”

Section: Variables and Data Sourcementioning

confidence: 99%

Analysis of Total Factor Efficiency of Water Resource and Energy in China: A Study Based on DEA-SBM Model

Yang

2017

Sustainability

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Abstract:One of the serious issues that China faces during its fast economic development is the low input-output efficiency of water and energy resources and growing water pollution. With the current economic development model of China, economic growth still requires large input of water resource and energy resource. This paper has focused on the total factor efficiency of water resource and energy resource by each province in China. We treat the undesirable outputs as outputs in the DEA-SBM Model instead of as inputs in previous studies, and design a new MATLAB programming to achieve optimization solutions of multi-variable constrained nonlinear functions to evaluate the Total Factor Efficiency of Water resource (TFEW) and the Total Factor Efficiency of Energy (TFEE) in China accurately. By using the method, this paper has analyzed the TFEW and TFEE in China from 2003 to 2014 by economic zones and typical provinces and provided corresponding policy recommendations.

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China’s Input-Output Efficiency of Water-Energy-Food Nexus Based on the Data Envelopment Analysis (DEA) Model

Cited by 80 publications

References 19 publications

Using the Optimization Algorithm to Evaluate the Energetic Industry: A Case Study in Thailand

Using the Optimization Algorithm to Evaluate the Energetic Industry: A Case Study in Thailand

Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends

Analysis of Total Factor Efficiency of Water Resource and Energy in China: A Study Based on DEA-SBM Model

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