Efficiency evaluation of China's provincial power systems based on the dynamic network slacks-based measure model

Xie, Bai-Chen; Wang, Jieyong; Ma, Jia-Jun; Duan, Na

doi:10.1016/j.jclepro.2017.11.007

Cited by 21 publications

(12 citation statements)

References 45 publications

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“…[23] proposed the Malmquistbased energy saving and emission reduction performance indicator, which is used to evaluate the performance changes of energy use and pollutant emissions over time in more than 200 Chinese cities. [24] applies DNSBM method to analyze environmental efficiency and force of Chinese electric power system and its provincial administrative divisions. These studies considered the dynamic effect of efficiency, but did not consider its dynamic effect on efficiency in the presence of carry forward variables.…”

Section: Literature Reviewmentioning

confidence: 99%

Eco-efficiency evaluation of Chinese provincial industrial system: A dynamic hybrid two-stage DEA approach

Zhu

2022

PLoS ONE

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In China, industrial pollution has become an urgent problem for policy makers and enterprise managers. To better support industrial development, we need to determine the effectiveness of policies through efficiency evaluation. China’s provincial industrial system consists of two stages: production and emission reduction. The emission reduction stage is composed of three parallel sub stages: solid waste treatment, waste gas treatment and wastewater treatment. In this process, the treatment capacity of industrial wastewater treatment facilities can be used as carry forward variable, which is not only the desirable output of the previous emission reduction stage, but also the input of the current emission reduction stage. Therefore, this paper proposes a dynamic hybrid two-stage data envelopment analysis (DEA) model for eco-efficiency evaluation of industrial systems, and applies it to a case study of Chinese regional industry. Applying the data collected from 2011 to 2015 to the model, the following conclusions can be drawn: (1) During the whole survey period, the average eco-efficiency was 0.9027. The overall eco-inefficiency of China’s provincial industrial system during the study period is mainly due to low efficiency of solid waste treatment and waste gas treatment. (2) The average eco-efficiency of provincial industrial system increased steadily from 2011 (0.6448) to 2014 (0.6777), but decreased slightly in 2015 (0.5908). (3) The carry forward treatment capacity of industrial wastewater treatment facilities has a remarkable impact on provincial industrial system efficiency scores, especially at the wastewater treatment stage (0.6002 vs 0.3691). (4) Provincial industrial system exists distinct geographical characteristics of low efficiency. This study has important guiding significance for policy makers and enterprise managers who are concerned about industrial pollution control.

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Section: Literature Reviewmentioning

confidence: 99%

Eco-efficiency evaluation of Chinese provincial industrial system: A dynamic hybrid two-stage DEA approach

Zhu

2022

PLoS ONE

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“…The sensitivity coefficient indicates the degree of a sector that is increasing their output as the intermediate goods that satisfying an increase in demand from other sectors. The influence coefficient and sensitivity coefficient of each sector in Guangdong were measured using Equations (5) and (6), respectively, as demonstrated in Table 6. In 2012, the influence coefficient of Electricity and Heat Production (one of the energy sectors) was relatively low (0.864), while its sensitivity coefficient was relatively large (2.162).…”

Section: Importance Of Energy Sector On Guangdong's Economic Systemmentioning

confidence: 99%

“…In the hope of decelerating global warming and alleviating consequent economic loss, China, as a member of the global markets, is expected to take on more responsibility for environmental protection. China has since implemented a large number of energy policies to improve the efficiency of the energy industry and to mitigate CO 2 emission (e.g., Formulating the plan for total amount control of pollutant emission) [4,5]. For example, in its 11th Five-year Plan (from 2006 to 2010) and the subsequent 12th Five-year Plan (from 2011 to 2015), China aimed to decrease its energy consumption intensity in terms of per unit gross domestic product (GDP) by 20% and 16%, respectively [6].…”

Section: Introductionmentioning

confidence: 99%

Sustainable Performance of Low-Carbon Energy Infrastructure Investment on Regional Development: Evidence from China

Lin

Chiu

2018

Sustainability

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In the 13th Five-Year Plan, the Chinese government declared that one of the sustainable policy priorities is improving the energy supply composition in order to reduce greenhouse gas emissions. In accordance with the Plan, the Guangdong government subsequently planned to invest in low-carbon energy infrastructure from 2016 to 2020. Using data from Guangdong province and other regions in China for 2007–2016, we propose a two-stage network data envelopment analysis (Network DEA) model to examine the sustainable performance of the Chinese regional/provincial economic system. We postulated that the less sustainable performance of Chinese regional economic systems may be attributed to lower energy productivity performance. However, we found that increased governmental and industrial spending on electricity mix improvement by building new low-carbon power plants created momentum in Guangdong’s economic growth, which experienced an annual rise of roughly 1.16%. Finally, the results from the two-stage Network DEA model showed that Guangdong fared better than other provinces with respect to sustainable performance. Investment in low-carbon energy infrastructure is not only a measure to combat CO2 emission, but could act as the driving force of regional economic systems.

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“…However, some crucial but often neglected ingredients in modelling energy and/or environmental performance in Chinese provincial regions are intermediate and intertemporal structures, which incorporate (but are not limited to) energy consumption, gross regional product, and CO 2 emissions. There were a handful of studies working on that aspect: when evaluating the generation performance of China's provincial power systems, Xie et al [13] treated power capacity as an intertemporal factor in their model specification; Guo et al [14] incorporated energy stock in their study, and treated it as a carry-over input/output from one period to another. As the previous literature had pointed out, the electricity generated from power infrastructure is idle before it is used to support economic or household activities.…”

Section: Introductionmentioning

confidence: 99%

Measuring Energy Performance for Regional Sustainable Development in China: A New Framework based on a Dynamic Two-Stage SBM Approach

2020

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Sustainable development has always been an important issue for all policy makers, even more so now, as global warming has seriously threatened the whole world. To understand the efficacy of regional sustainable policies, we proposed a dynamic, two-stage, slacks-based measure (SBM) model with carry-over and intermediate variables, highlighting the importance of an electricity portfolio, to measure overall energy performance for the purpose of regional sustainable development. In this unified linear programming framework with intertemporal evaluation, we estimated the effects of a clean electricity supply by the abatement of CO 2 emissions and the gain of economic growth. The results can be used as a reference for decision makers to shape regional sustainable development policies. Using data of 30 provincial administration regions in China for the period of 2012-2017, we postulate that the lower energy performance of the Chinese regional economic system for sustainable development may be attributed to a lower electricity portfolio performance. We then postulate that investment in low-carbon energy infrastructure can combat CO 2 emissions, and is also a major driving force in the regional economic growth.

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Efficiency evaluation of China's provincial power systems based on the dynamic network slacks-based measure model

Cited by 21 publications

References 45 publications

Eco-efficiency evaluation of Chinese provincial industrial system: A dynamic hybrid two-stage DEA approach

Eco-efficiency evaluation of Chinese provincial industrial system: A dynamic hybrid two-stage DEA approach

Sustainable Performance of Low-Carbon Energy Infrastructure Investment on Regional Development: Evidence from China

Measuring Energy Performance for Regional Sustainable Development in China: A New Framework based on a Dynamic Two-Stage SBM Approach

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