TY - JOUR
T1 - Research on energy congestion effects in China's manufacturing sector
T2 - An analysis based on RAM-DEA
AU - Chen, Zhenling
AU - Zhao, Weigang
AU - Li, Jinkai
N1 - Publisher Copyright:
© 2019, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - The energy congestion effects refer to the abnormal economic phenomenon that output decreases with the increase of energy input. In order to investigate energy congestion effects in manufacturing sector and improve its low-carbon operational capability. Energy congestion effects are decomposed into desirable energy congestion and undesirable energy congestion according to the heterogeneity of output. The RAM-DEA model is used to establish the desirable energy congestion and undesirable energy congestion models under natural disposability and managerial disposability respectively. An empirical study on 28 sub-industries of Chinese manufacturing sector is conducted. Empirical results show that: Undesirable energy congestion have occurred in the manufacturing sector and the degree of undesirable energy congestion is increasing since 2000. Especially in the year of 2014, the amount of 962.6 million tons of coal equivalent are wasted. Most of China's manufacturing industries have poor performance of energy efficiency and there are huge gaps among sub-industries. If energy inefficiency is decomposed into congestion inefficiency and pure technical inefficiency, the traditional manufacturing industries are mainly suffered from congestion inefficiency, and the advanced manufacturing industries are mainly suffered from pure technical inefficiency, while the traditional chemical industries and energy intensive industries are suffered from both congestion and pure technical inefficiency. Additionally, the occurrence of desirable energy congestion had been improved in terms of both frequency and quantity from 2000 to 2014, which indicates that more and more China's manufacturing industries are undergoing a low-carbon technology innovation. The research conclusions have important policy implications for energy-saving and emission reduction, industrial structure optimization, as well as risk warning mechanism establishment for the over-capacity in the manufacturing sector.
AB - The energy congestion effects refer to the abnormal economic phenomenon that output decreases with the increase of energy input. In order to investigate energy congestion effects in manufacturing sector and improve its low-carbon operational capability. Energy congestion effects are decomposed into desirable energy congestion and undesirable energy congestion according to the heterogeneity of output. The RAM-DEA model is used to establish the desirable energy congestion and undesirable energy congestion models under natural disposability and managerial disposability respectively. An empirical study on 28 sub-industries of Chinese manufacturing sector is conducted. Empirical results show that: Undesirable energy congestion have occurred in the manufacturing sector and the degree of undesirable energy congestion is increasing since 2000. Especially in the year of 2014, the amount of 962.6 million tons of coal equivalent are wasted. Most of China's manufacturing industries have poor performance of energy efficiency and there are huge gaps among sub-industries. If energy inefficiency is decomposed into congestion inefficiency and pure technical inefficiency, the traditional manufacturing industries are mainly suffered from congestion inefficiency, and the advanced manufacturing industries are mainly suffered from pure technical inefficiency, while the traditional chemical industries and energy intensive industries are suffered from both congestion and pure technical inefficiency. Additionally, the occurrence of desirable energy congestion had been improved in terms of both frequency and quantity from 2000 to 2014, which indicates that more and more China's manufacturing industries are undergoing a low-carbon technology innovation. The research conclusions have important policy implications for energy-saving and emission reduction, industrial structure optimization, as well as risk warning mechanism establishment for the over-capacity in the manufacturing sector.
KW - Desirable energy congestion
KW - Manufacturing sector
KW - Rangeadjusted measure data envelopment analysis (RAM-DEA)
KW - Undesirable energy congestion
UR - http://www.scopus.com/inward/record.url?scp=85073687663&partnerID=8YFLogxK
U2 - 10.12011/1000-6788-2018-0102-14
DO - 10.12011/1000-6788-2018-0102-14
M3 - Article
AN - SCOPUS:85073687663
SN - 1000-6788
VL - 39
SP - 1831
EP - 1844
JO - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice
JF - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice
IS - 7
ER -