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Areal Variation Measurement and Influencing Factor Decomposition of Carbon Emissions of Regional Logistics Ecosystems


Affiliations
1 Department of Business Management, Kunshan Dengyun College of Science and Technology, Suzhou 215300, India
2 Key Laboratory for Traffic and Transportation Security of Jiangsu Province, Huaiyin Institute of Technology, Huaian 223003, India
3 Key Laboratory for Traffic and Transportation Security of Jiangsu Province, Huaiyin Institute of Technology, Huaian 223003, China
 

Carbon emissions significantly affect the sustainable development of regional logistics ecosystems. However, the existing studies on logistics carbon emissions seldom consider the spatial inequality characteristic. A comprehensive approach to analyse the areal variations and the influencing factors of carbon emissions of regional logistics ecosystems accurately, was proposed in this study. The carbon emissions of regional logistics ecosystems were initially discussed and their areal variations were measured using Theil index model. Then, the key influencing factors of carbon emission change of regional logistics ecosystems, as well as the effects of these influencing factors were analysed. Finally, an empirical analysis was conducted considering Jiangsu province in China as an example. Results demonstrate the following: (1) The areal variations of carbon emissions of regional logistics ecosystems between regions and within regions can be measured objectively and scientifically with Theil index model, and the areal variation changes in carbon emissions can be accurately reflected. (2) The influencing factors of carbon emissions of regional logistics ecosystems can be classified into three factors, namely, energy structure, economic scale, and industrial structure, by using the logarithmic mean Divisia index decomposition approach. Moreover, the contributions of influencing factors to the carbon emission changes can be identified quantitatively. (3) Results of the empirical analysis show that the energy structure and economic scale in Jiangsu province positively affect the carbon emissions of regional logistics ecosystems. However, the industrial structure plays an adverse role. The study provides a new decision-making method to analyse quantitatively the areal variations in carbon emissions of regional logistics ecosystems, which can be used as a reference when designing differentiated measures and policies for low-carbon logistics development in different regions.

Keywords

Regional Logistics Ecosystem, Carbon Emission, Areal Variation, Factor Decomposition.
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  • Areal Variation Measurement and Influencing Factor Decomposition of Carbon Emissions of Regional Logistics Ecosystems

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Authors

Jie Wu
Department of Business Management, Kunshan Dengyun College of Science and Technology, Suzhou 215300, India
Lingyun Zhou
Key Laboratory for Traffic and Transportation Security of Jiangsu Province, Huaiyin Institute of Technology, Huaian 223003, India
Yachao Wu
Key Laboratory for Traffic and Transportation Security of Jiangsu Province, Huaiyin Institute of Technology, Huaian 223003, China

Abstract


Carbon emissions significantly affect the sustainable development of regional logistics ecosystems. However, the existing studies on logistics carbon emissions seldom consider the spatial inequality characteristic. A comprehensive approach to analyse the areal variations and the influencing factors of carbon emissions of regional logistics ecosystems accurately, was proposed in this study. The carbon emissions of regional logistics ecosystems were initially discussed and their areal variations were measured using Theil index model. Then, the key influencing factors of carbon emission change of regional logistics ecosystems, as well as the effects of these influencing factors were analysed. Finally, an empirical analysis was conducted considering Jiangsu province in China as an example. Results demonstrate the following: (1) The areal variations of carbon emissions of regional logistics ecosystems between regions and within regions can be measured objectively and scientifically with Theil index model, and the areal variation changes in carbon emissions can be accurately reflected. (2) The influencing factors of carbon emissions of regional logistics ecosystems can be classified into three factors, namely, energy structure, economic scale, and industrial structure, by using the logarithmic mean Divisia index decomposition approach. Moreover, the contributions of influencing factors to the carbon emission changes can be identified quantitatively. (3) Results of the empirical analysis show that the energy structure and economic scale in Jiangsu province positively affect the carbon emissions of regional logistics ecosystems. However, the industrial structure plays an adverse role. The study provides a new decision-making method to analyse quantitatively the areal variations in carbon emissions of regional logistics ecosystems, which can be used as a reference when designing differentiated measures and policies for low-carbon logistics development in different regions.

Keywords


Regional Logistics Ecosystem, Carbon Emission, Areal Variation, Factor Decomposition.

References