Understanding the Nonlinear Impact of Information and Communication Technology on Carbon Emissions in the Logistics Industry of China

Geng Peng, Yixuan Tang () and Kaiyou Tian
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Geng Peng: School of Economics, Jiangsu University of Technology, Changzhou 213001, China
Yixuan Tang: College of Architectural Science and Engineering, Yangzhou University, Yangzhou 225127, China
Kaiyou Tian: Shiliang Law School, Changzhou University, Changzhou 213164, China

Sustainability, 2023, vol. 15, issue 18, 1-22

Abstract: Information and communication technology (ICT) has broken the boundaries of traditional geographical space, and thus substantially promoted the development of the logistics industry. However, the effect of ICT on the carbon emissions of the logistics industry (CELI) has not been systematically explained. With Chinese provincial data from 2000 to 2018, this paper uses static and dynamic panel models and three robustness test methods to unveil the nonlinear impact of ICT (taking Internet usage as a proxy) on CELI. Some significant findings are concluded in this paper. (1) The relationship between Internet usage and CELI is inverted U-shaped, with the curve’s inflection point emerging in 2015. (2) The formation of the inverted U-shaped relationship is determined by the different roles of total factor productivity (TFP) and the express delivery business of the logistics industry. Specifically, Internet usage plays a positive role in TFP, which reduces carbon emissions but simultaneously increases carbon emissions by promoting the development of express delivery business. (3) The relationship between Internet usage and CELI is an inverted U-shape in the eastern and western regions, while in the central region, the relationship is linear. According to the findings, some policies at country, region and enterprise levels are highlighted in order for policymakers to utilize ICT to achieve reductions in carbon emissions.

Keywords: carbon emissions; logistics industry; information and communication technology; internet penetration rate; inverted U-shaped relationship (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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