TY - JOUR
T1 - Can smart transportation inhibit carbon lock-in? The case of China
AU - Dong, Kangyin
AU - Jia, Rongwen
AU - Zhao, Congyu
AU - Wang, Kun
N1 - Funding Information:
This article has been sponsored by the National Social Science Foundation of China (Grant Nos. 2020VGQ003 and 22VMG013). Social Science Foundation of Ministry of Education of China (19YJC630061).
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/10
Y1 - 2023/10
N2 - A thorough understanding of carbon lock-in is an essential precondition for the effective design and continuous improvement of climate policy. Based on a balanced panel dataset of 30 provinces in China during the period 2002–2021, we explore the nexus between smart transportation and carbon lock-in using the System-Generalized Method of Moments (SYS-GMM) model. We also investigate the heterogeneous, asymmetric, and threshold effects among the above two issues, and examine three internal impact mechanisms. We thus arrive at the following four main conclusions: (1) Smart transportation significantly reduces carbon lock-in, highlighting its importance in eradicating carbon lock-in. (2) Smart transportation has the most pronounced impact on carbon lock-in in the central region, and can effectively mitigate all aspects of carbon lock-in, especially industry lock-in and institution lock-in. (3) Smart transportation is more effective in alleviating carbon lock-in in provinces with a higher level of carbon lock-in. Moreover, a threshold of environmental regulation exists between smart transportation and carbon lock-in, with stricter environmental regulation leading to a stronger carbon lock-in reduction effect of smart transportation. (4) Smart transportation indirectly influences carbon lock-in through three channels of economic scale, industrial structure upgrading, and technological innovation. Based on these findings, we propose some policy recommendations for smart transportation development and carbon lock-in mitigation.
AB - A thorough understanding of carbon lock-in is an essential precondition for the effective design and continuous improvement of climate policy. Based on a balanced panel dataset of 30 provinces in China during the period 2002–2021, we explore the nexus between smart transportation and carbon lock-in using the System-Generalized Method of Moments (SYS-GMM) model. We also investigate the heterogeneous, asymmetric, and threshold effects among the above two issues, and examine three internal impact mechanisms. We thus arrive at the following four main conclusions: (1) Smart transportation significantly reduces carbon lock-in, highlighting its importance in eradicating carbon lock-in. (2) Smart transportation has the most pronounced impact on carbon lock-in in the central region, and can effectively mitigate all aspects of carbon lock-in, especially industry lock-in and institution lock-in. (3) Smart transportation is more effective in alleviating carbon lock-in in provinces with a higher level of carbon lock-in. Moreover, a threshold of environmental regulation exists between smart transportation and carbon lock-in, with stricter environmental regulation leading to a stronger carbon lock-in reduction effect of smart transportation. (4) Smart transportation indirectly influences carbon lock-in through three channels of economic scale, industrial structure upgrading, and technological innovation. Based on these findings, we propose some policy recommendations for smart transportation development and carbon lock-in mitigation.
KW - Carbon lock-in
KW - China
KW - Mediating effect model
KW - Smart transportation
KW - Threshold effect model
UR - http://www.scopus.com/inward/record.url?scp=85168773498&partnerID=8YFLogxK
U2 - 10.1016/j.tranpol.2023.08.003
DO - 10.1016/j.tranpol.2023.08.003
M3 - Journal article
AN - SCOPUS:85168773498
SN - 0967-070X
VL - 142
SP - 59
EP - 69
JO - Transport Policy
JF - Transport Policy
ER -