Energy efficiency evaluation model based on DEA-SBM-Malmquist index

Zheng, Zile

doi:10.1016/j.egyr.2021.10.020

Cited by 42 publications

(16 citation statements)

References 10 publications

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“…Hence, (Tone, 2001) suggested a slack-based measurement DEA (SBM-DEA) model to address the slack issues of input and output. Consequently, a plethora of scholars followed the SBM-DEA model to evaluate energy efficiency (Zheng, 2021), explore the impact of the quality of FDI on energy efficiency (Pan et al, 2020), assess educational efficiency across the world (Chen and Liu, 2022), compute the effect of industrial agglomeration on green development efficiency (Guo et al, 2020), analyze social organization performance (Shao et al, 2021), etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable development efficiency and its influencing factors across BRICS and G7 countries: An empirical comparison

Cheng

Addis²,

Chen³

et al. 2023

Front. Energy Res.

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Sustainable development is the global overarching paradigm and essential for achieving economic, social, and environmental development. The primary goal of this study is to compare the efficiency of sustainable development and evaluate its influencing factors across the BRICS (Brazil, Russia, India, China, and South Africa) and G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and United States) countries by examining total factor productivity, efficiency change, and technological change. For this, we adopted the super-efficiency SBM-DEA model with undesirable output and Global Malmquist-Luenberger (GML) productivity index model to overcome inaccurate efficiency results while avoiding environmentally unwanted outputs and to resolve the shortcomings of the conventional Malmquist-Luenberger index. It is also necessary to explore relevant influencing factors on the environmental pollution thereby affects the sustainable development efficiency of the study countries, thus, this study employed STIRPAT approach. A panel data of BRICS and G7 countries from 2005 to 2015 is used. The findings reveal that sustainable total factor productivity (GML) in China (1.0165), the US (1.0150), and UK (1.0024) is on the rise. China is also one of the countries that experienced the highest positive efficiency change (GMLEC) (1.0147) and the US has the highest positive technical change (GMLTC) (1.0103). Contrarily, Russia experienced the highest decline in GMLTC (0.9316) as well as GML indexes (0.9337), whereas South Africa experienced the highest decline in GMLEC (0.9707). Additionally, GDP per capita (.0969) and population (.4178) have a positive influence on CO2 emissions in the BRICS countries, whereas in the G7 nations, GDP per capita (−.2180) and population (−.1249) have negative influences on CO2 emissions. The study also offers practical recommendations to address identified limitations and improve sustainable productivity and environmental efficiency. The inverse link between GDP and CO2 emissions might imply that the G7 nations have passed the turning point on an environmental Kuznets curve (EKC), but this finding does not support the EKC hypothesis in the BRICS nations.

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Section: Literature Reviewmentioning

confidence: 99%

Sustainable development efficiency and its influencing factors across BRICS and G7 countries: An empirical comparison

Cheng

Addis²,

Chen³

et al. 2023

Front. Energy Res.

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“…Both the input and the output aspects cannot be considered simultaneously, leading to the distortion of the efficiency value. The non-radial, non-angular SBM (Slack-based Measure, SBM) directional distance function can overcome the above defects [32].…”

Section: The Sbm Directionality Distance Functionmentioning

confidence: 99%

Improvement of Agricultural Supply Quality in China: Evidence from Jiangsu Province

et al. 2023

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Promoting the reform of the agricultural supply side and its quality improvement are crucial for realizing agricultural modernization. This paper tests the varied trajectory of agricultural total factor productivity (ATFP) in Jiangsu Province over the past 21 years. The paper used the three-stage DEA empirical analysis method—Stochastic Frontier Approach (SFA), to address the uncertainty in the development of the agricultural industry. The paper introduces environmental variables such as urbanization level, import and export trade, financial support for agriculture, and transportation convenience. The research results show that: (1) the ATFP growth in Jiangsu Province presents a fluctuating trend; (2) The further sub-index research of ATFP in Jiangsu Province shows that the average rate of growth for agricultural technology efficiency (AEC) in Jiangsu is negative, indicating that the input cost of agricultural factors in Jiangsu increases and marginal efficiency decreases; (3) The empirical analysis of ATFP growth by region shows that there are still large differences in agricultural economic development level, the level of modern agricultural technology and ATFP in the southern, the central and the northern parts of Jiangsu. (4) Stage III: DEA empirical results showed that improving urbanization level, net export trade, and transportation convenience is conducive to improving agricultural production efficiency; financial support for agriculture is weakly conducive to improving agricultural production efficiency. On this basis, the paper puts forward countermeasures and suggestions to promote agricultural structural reform.

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“…Based on the DEA model, improvement methods have emerged by modifying the constraints. Scholars have evaluated the interprovincial eco‐efficiency in China using the super‐efficiency DEA model (Yue et al, 2020), the three‐stage DEA model (Bo et al, 2011), and the SBM‐DEA model (Zheng, 2021), respectively. Andersen and Petersen (1993) proposed a super‐efficiency DEA model that can rank DEA effective units, and some scholars have conducted a series of studies on efficiency issues using super‐efficiency models.…”

Section: Literature Reviewmentioning

confidence: 99%

Influencing factors on ecological efficiency: Based on 11 cities in Zhejiang Province, China

Huang

Zhang

Hong

et al. 2022

Integr Envir Assess & Manag

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Ecological efficiency (eco-efficiency) is the effectiveness of ecological resources in meeting human needs and is a good representation of the quality of a region's development. The traditional concept of improving eco-efficiency refers to maximizing economic benefits by minimizing resource costs and environmental loads. This article argues that the goal of eco-efficiency evaluation is not only to maximize economic benefits but also to achieve high-quality and coordinated development in many aspects so that more people can enjoy the fruits of development. Therefore, in the evaluation system of eco-efficiency, the input indexes take into account the consumption of human, energy resources, and the environmental load caused by them in a region. The output indexes take into account the four dimensions of "economy, innovation, social harmony, and openness." This study first establishes the nonexpected output superefficiency slacks-based measure model under the assumption of variable returns to scale to measure eco-efficiency in 11 cities of Zhejiang Province, China. Second, the spatial and temporal trends of eco-efficiency are studied with the help of the Malmquist index model. Moreover, regression analysis was conducted using the panel Tobit method to discuss the influencing factors of eco-efficiency. Several key results were obtained in this study: (1) The overall eco-efficiency in Zhejiang Province is rising steadily, but there are serious regional imbalances. (2) The improvement of eco-efficiency mainly relied on the scale efficiency from 2008 to 2013, but on pure technical efficiency from 2013 to 2018. (3) The share of tertiary industry, the number of scientific researchers, and the foreign trade dependence positively affect the improvement of eco-efficiency, but highway transportation mileage has a negative impact on the improvement of eco-efficiency.

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Energy efficiency evaluation model based on DEA-SBM-Malmquist index

Cited by 42 publications

References 10 publications

Sustainable development efficiency and its influencing factors across BRICS and G7 countries: An empirical comparison

Sustainable development efficiency and its influencing factors across BRICS and G7 countries: An empirical comparison

Improvement of Agricultural Supply Quality in China: Evidence from Jiangsu Province

Influencing factors on ecological efficiency: Based on 11 cities in Zhejiang Province, China

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