2019
DOI: 10.1016/j.jclepro.2019.03.285
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The impact of polycentric development on regional gap of energy efficiency: A Chinese provincial perspective

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Cited by 31 publications
(9 citation statements)
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References 77 publications
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“…Some scholars have found that a polycentric spatial structure will promote the improvement of energy utilization efficiency [ 74 ], economic efficiency [ 75 ], green land use efficiency [ 8 ], etc. Although there are important discoveries revealed by these studies between polycentric spatial structures and efficiency, there are also limitations.…”
Section: Discussionmentioning
confidence: 99%
“…Some scholars have found that a polycentric spatial structure will promote the improvement of energy utilization efficiency [ 74 ], economic efficiency [ 75 ], green land use efficiency [ 8 ], etc. Although there are important discoveries revealed by these studies between polycentric spatial structures and efficiency, there are also limitations.…”
Section: Discussionmentioning
confidence: 99%
“…The model considers the region to be a group, with research and development departments clustered in the center area, and primary manufacturing departments clustered in the peripheral area (Duranton and Puga, 2005). Studies have limited the measurement of the regional energy efficiency gap at the province level or country level (Alcantara and Duro, 2004;Zou et al, 2019). Analysis of the gap in city-level energy efficiency in specific regions has received little attention.…”
Section: Literature Reviewmentioning
confidence: 99%
“…These statistics show that China's average energy efficiency has a large space for improvement. From a regional perspective, Zou et al (2019) point out that the energy efficiency gap in different cities even reached more than six times in China. Core cities such as Beijing, Shanghai, and Guangzhou have higher levels of energy efficiency, and peripheral cities such as Tangshan, Changzhou and Huizhou have lower energy efficiency (Chen et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, we further evaluate our results by changing the measurement of energy efficiency and the mediating variables. We use the total-factor energy efficiency based on the SFA model to measure energy efficiency (Zou et al, 2019); Theil index (Gan et al, 2011) to represent the industrial structure (replacing the proportion of the added value of the secondary and tertiary industries in GDP), and the number of accepted patent applications (Yuan et al, 2012) to represent technological innovation (replacing the number of authorized patent applications). As noted previously, only the optimal GMM estimation is used.…”
Section: Robustness Testmentioning
confidence: 99%