Exploring the role of co-agglomeration of manufacturing and producer services on carbon productivity: An empirical study of 282 cities in China

Xu, Hui; Liu, Weijia; Zhang, Dawei

doi:10.1016/j.jclepro.2023.136674

Cited by 25 publications

(4 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Current studies on carbon productivity found that there are positive "U" [31], positive "N" [32], and other characteristics of carbon productivity. Xu and others [31] confirmed that the interplay between manufacturing and producer services, along with carbon productivity, exhibits "U" characteristics. Only a high level of synergies can promote carbon productivity.…”

Section: Manufacturing Dss and Carbon Productivitymentioning

confidence: 99%

Can the Synergy of Digitalization and Servitization Boost Carbon-Related Manufacturing Productivity? Evidence from China’s Provincial Panel Data

Li,

Chen,

Cheng

2024

Sustainability

View full text Add to dashboard Cite

With the goal of carbon peaking and neutrality, carbon productivity has become a means of sustainability in manufacturing, and the impact of the synergy of digitalization and servitization (DSS) on carbon productivity (CP) deserves in-depth study. Based on data with respect to manufacturing in 30 provinces in China from 2013 to 2020, a coupled coordination degree model is used to calculate the degree of manufacturing coordination. A regression effect model is used to explore the intrinsic mechanism of the impact of DSS on CP. The main results show the following: (1) The DSS in manufacturing positively contributes to enhancing CP, and there are non-linear features in both. (2) Technological innovation can contribute to the impact of DSS on CP, as does industry structure, and there is a mediating effect between the two. (3) When economic growth is used as the threshold, DSS and CP reflect a positive “U” relationship. Based on the above findings, policy recommendations are made to promote the sustainable development of manufacturing.

show abstract

Section: Manufacturing Dss and Carbon Productivitymentioning

confidence: 99%

Can the Synergy of Digitalization and Servitization Boost Carbon-Related Manufacturing Productivity? Evidence from China’s Provincial Panel Data

Li,

Chen,

Cheng

2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…On one hand, the industrial transformation and upgrading of resource-based cities often involve an adjustment of industrial structure, which is an important influencing factor in the changes of industrial spatial patterns [7,8]. On the other hand, by optimizing the industrial spatial pattern, it is possible to enhance the spatial competitiveness of enterprises, reduce production costs, and promote technological innovation, thereby driving the industries towards higher added value and technological content and achieving the transformation and upgrading of the industries [52,53]. Due to long-term development and renewal, the central region of Tangshan City has a relatively well-developed infrastructure and supporting facilities, serving as the commercial and residential center of the city.…”

Section: Effect Of the Spatial Pattern Change In Steel Plants On Land...mentioning

confidence: 99%

Exploring Relationships between Spatial Pattern Change in Steel Plants and Land Cover Change in Tangshan City

Ni,

Zhao,

et al. 2023

Sustainability

View full text Add to dashboard Cite

It is of great significance for the sustainable development of steel cities to explore the relationship between the spatial pattern change in steel plants and land cover change during the transformation of steel cities. To address the issue of unsatisfactory results for segmenting steel plants based on high-resolution remote sensing images, due to insufficient sample datasets and task complexity, we proposed a steel plant segmentation strategy that combines high-resolution remote sensing images, POI data, and OSM data. Additionally, we discussed the effect of POI data and OSM data on steel plant segmentation, analyzing the spatial pattern change in steel plants in Tangshan City during 2017–2022 and its relationship with land cover change. The results demonstrate that: (1) The proposed strategy can significantly improve the accuracy of steel plant segmentation. The introduction of POI data can significantly improve the precision of steel plant segmentation, however, it will to some extent reduce the recall of steel plant segmentation, and this phenomenon weakens as the distance threshold increases. The introduction of OSM data can effectively improve the effectiveness of steel plant segmentation, however, it has significant limitations. (2) During 2017–2022, the spatial distribution center of steel plants in Tangshan City moved obviously to the southeast, and the positive change in steel plants was mainly concentrated in the coastal regions of southern Tangshan City, while the negative change in steel plants was mainly concentrated in central Tangshan City. (3) There is a relatively strong spatial correlation between the positive change in steel plants and the transition from vegetation to built area, as well as the transition from cropland to built area.

show abstract

“…Regarding cost effect, industrial co-agglomeration can save enterprise cost not only in the trade of intermediate goods, but also in the flow of production factors. As for intermediate goods trade, due to the refinement of industrial division of labor, enterprises in demand and supply of intermediate goods based on input–output relationship will appear in the collaborative agglomeration area, which reduces the transaction cost of intermediate goods 59 . As for the flow of production factors, industrial co-agglomeration can attract lots of highly skilled talents, which reduces the cost of information collection and talent recruitment.…”

Section: Theoretical Analysis and Research Hypothesismentioning

confidence: 99%

The impact of industrial collaborative agglomeration on total factor carbon emission efficiency in China

Yuan,

Liu,

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities.

show abstract

Exploring the role of co-agglomeration of manufacturing and producer services on carbon productivity: An empirical study of 282 cities in China

Cited by 25 publications

References 40 publications

Can the Synergy of Digitalization and Servitization Boost Carbon-Related Manufacturing Productivity? Evidence from China’s Provincial Panel Data

Can the Synergy of Digitalization and Servitization Boost Carbon-Related Manufacturing Productivity? Evidence from China’s Provincial Panel Data

Exploring Relationships between Spatial Pattern Change in Steel Plants and Land Cover Change in Tangshan City

The impact of industrial collaborative agglomeration on total factor carbon emission efficiency in China

Contact Info

Product

Resources

About