The development of the internet is of great significance for carbon reduction in the transportation sector. Drawing on panel data from 31 provinces in China spanning 2011 to 2021, we present novel evidence from the transportation sector. We construct an internet development assessment system comprising 18 indicators and compute an internet development index from four dimensions. Employing OLS, mediation analysis, and dynamic threshold panel models, we validate the relationship between the internet development index and carbon emissions in the transportation sector. Results indicate a significant increase in transportation sector carbon emissions with internet development, with a 0.072% rise in emissions for every 1% increase in the internet development index. This is primarily attributed to the influence of internet development on increasing internet shopping, vehicle ownership, and travel scale. Importantly, in regions with higher transportation sector carbon emissions, such as Shanghai, internet development may also lead to emission reductions. Thus, the Chinese government should pay particular attention to strategically employing internet technology in different regions, leveraging its technical advantages to promote carbon emission reduction strategies in the transportation sector.
AlataşS. Do environmental technologies help to reduce transport sector CO2 emissions? Evidence from the EU15 countries. Res Transp Econ2022; 91: 101047.
3.
BaiCZhouLXiaM, et al.Analysis of the spatial association network structure of China’s transportation carbon emissions and its driving factors. J Environ Manage2020; 253: 109765.
4.
GasparatosAEl-HaramMHornerM. A longitudinal analysis of the UK transport sector, 1970–2010. Energy Policy2009; 37: 623–632.
5.
LiuYFengC. Decouple transport CO2 emissions from China’s economic expansion: a temporal-spatial analysis. Transp Res D, Transp Environ2020; 79: 102225.
6.
KrautzbergerLWetzelH. Transport and CO2: productivity growth and carbon dioxide emissions in the European commercial transport industry. Environ Resour Econ2012; 53: 435–454.
7.
LiuMZhangXZhangM, et al.Influencing factors of carbon emissions in transportation industry based on CD function and LMDI decomposition model: China as an example. Environ Impact Assess Rev2021; 90: 106623.
8.
GaoCGeHLuY, et al.Decoupling of provincial energy-related CO2 emissions from economic growth in China and its convergence from 1995 to 2017. J Clean Prod2021; 297: 126627.
9.
HuangYZhuHZhangZ. The heterogeneous effect of driving factors on carbon emission intensity in the Chinese transport sector: evidence from dynamic panel quantile regression. Sci Total Environ2020; 727: 138578.
10.
HuangYHuMXuJ, et al.Digital transformation and carbon intensity reduction in transportation industry: empirical evidence from a global perspective. J Environ Manage2023; 344: 118541.
LinBZhouY. Does the internet development affect energy and carbon emission performance?Sustain Prod Consump2021; 28: 1–10.
13.
SalahuddinMAlamK. Internet usage, electricity consumption and economic growth in Australia: a time series evidence. Telemat Inform2015; 32: 862–878.
14.
ZhaoZ. Crossover administration of internet plus: perspective of creative destruction. China Ind Econ2015; 10: 146–160.
15.
ChenYYangWHuY. Internet development, consumption upgrading and carbon emissions—an empirical study from China. Int J Environ Res Public Health2022; 20: 65.
16.
HuangQYuYZhangS. Internet development and productivity growth in manufacturing industry: internal mechanism and China experiences. China Ind Econ2019; 8: 5–23.
17.
PanMZhaoXLvK, et al.Internet development and carbon emission-reduction in the era of digitalization: where will resource-based cities go?Resour Policy2023; 81: 103345.
18.
BrynjolfssonEHittLM. Beyond computation: information technology, organizational transformation and business performance. J Econ Perspect2000; 14: 23–48.
19.
KhanMXuXDouW, et al.OSaas: online shopping as a service to escalate E-commerce in developing countries. 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 1402–1409. https://ieeexplore.ieee.org/abstract/document/7828541/. 2016
SuiDZRejeskiDW. Environmental impacts of the emerging digital economy: the E-for-environment E-commerce?Environ Manage2002; 29: 155–163.
22.
HallASParsonsJ. Internet addiction: college student case study using best practices in cognitive behavior therapy. J Ment Health Couns2001; 23: 312.
23.
NieNErbringL. Internet and society. a preliminary report. IT&Society2002; 1: 275–283.
24.
HongJMcArthurDP. How does internet usage influence young Travelers’ choices?J Plan Educ Res2019; 39: 155–165.
25.
HongJMcArthurDPLivingstonM. Can accessing the internet while travelling encourage commuters to use public transport regardless of their attitude?Sustainability2019; 11: 3281.
26.
ZhaoCWangKDongX, et al.Is smart transportation associated with reduced carbon emissions? The case of China. Energy Econ2022; 105: 105715.
27.
NiuZChenJXuL, et al.Application of the environmental internet of things on monitoring PM 2.5 at a coastal site in the urbanizing region of southeast China. Int J Sustain Dev World Ecol2013; 20: 231–237.
28.
ErdoğanSYıldırımSYıldırımDÇ, et al.The effects of innovation on sectoral carbon emissions: evidence from G20 countries. J Environ Manage2020; 267: 110637.
29.
KhanANEnXRazaMY, et al.Sectorial study of technological progress and CO2 emission: insights from a developing economy. Technol Forecast Soc Change2020; 151: 119862.
30.
SorrellS. Jevons’ paradox revisited: the evidence for backfire from improved energy efficiency. Energy Policy2009; 37: 1456–1469.
LeeCYuanYWenH. Can digital economy alleviate CO 2 emissions in the transport sector? Evidence from provincial panel data in China. Nat Resour Forum2022; 46: 289–310.
33.
AlshehryASBelloumiM. Study of the environmental Kuznets curve for transport carbon dioxide emissions in Saudi Arabia. Renew Sustain Energy Rev2017; 75: 1339–1347.
LeeIKimJChoiB, et al.Measurement development for cultural characteristics of mobile Internet users at the individual level. Comput Human Behav2010; 26: 1355–1368.
39.
WangSTongF. Impact of internet development on carbon emissions in Jiangsu, China. Int J Environ Res Public Health2022; 19: 16681.
40.
WuHXueYHaoY, et al.How does internet development affect energy-saving and emission reduction? Evidence from China. Energy Econ2021; 103: 105577.
41.
YiMLiuYShengMS, et al.Effects of digital economy on carbon emission reduction: new evidence from China. Energy Policy2022; 171: 113271.
42.
GrossmanGMKruegerAB. Economic growth and the environment. Q J Econ1995; 110: 353–377.
43.
SchotJSteinmuellerWE. Three frames for innovation policy: r&D, systems of innovation and transformative change. Res Policy2018; 47: 1554–1567.
44.
ZhongWYuanWLiSX, et al.The performance evaluation of regional R&D investments in China: an application of DEA based on the first official China economic census data. Omega2011; 39: 447–455.
45.
BaronRMKennyDA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol1986; 51: 1173–1182.
46.
HansenBE. Threshold effects in non-dynamic panels: estimation, testing, and inference. J Econom1999; 93: 345–368.
47.
Kos-ŁabędowiczJUrbanekA. Do information and communications technologies influence transport demand? An exploratory study in the European union. Transp Res Proc2017; 25: 2660–2676.
48.
WeltevredenJWRotem-MindaliO. Mobility effects of b2c and c2c e-commerce in The Netherlands: a quantitative assessment. J Transp Geogr2009; 17: 83–92.
49.
LyonsGUrryJ. Travel time use in the information age. Transp Res Part A Policy Pract2005; 39: 257–276.
50.
DehdashtiYRatchfordBTNaminA. Who searches where? A new car buyer study. J Mark Anal2018; 6: 44–52.
51.
LiDLiMHanG, et al.A combined deep learning method for internet car evaluation. Neural Comput Appl2021; 33: 4623–4637.
Canals CasalsLMartinez-LasernaEAmante GarcíaB, et al.Sustainability analysis of the electric vehicle use in Europe for CO2 emissions reduction. J Clean Prod2016; 127: 425–437.
54.
LiY. Economic competitiveness and environmental implications of hydrogen energy and fuel cell electric vehicles in ASEAN countries: The current and future scenarios. Energy Policy2021; 148: 111980.
55.
BiresseliogluMEDemirbag KaplanMYilmazBK. Electric mobility in Europe: a comprehensive review of motivators and barriers in decision making processes. Transp Res Part A, Policy Pract2018; 109: 1–13.
56.
WangS. Predicting consumers’ intention to adopt hybrid electric vehicles: Using an extended version of the theory of planned behavior model. 2016.
57.
WangSLiJZhaoD. The impact of policy measures on consumer intention to adopt electric vehicles: evidence from China. Transp Res Part A, Policy Pract2017; 105: 14–26.
58.
HossainMSFangYRMaT, et al.The role of electric vehicles in decarbonizing India’s road passenger toward carbon neutrality and clean air: a state-level analysis. Energy2023; 273: 127218.
59.
NguyenTTPhamTATTramHTX. Role of information and communication technologies and innovation in driving carbon emissions and economic growth in selected G-20 countries. J Environ Manage2020; 261: 110162.
60.
WangJZhaoJDongK, et al.How does the internet economy affect CO 2 emissions? Evidence from China. Appl Econ2023; 55: 447–466.
61.
AuC-CHendersonJV. Are Chinese cities too small?Rev Econ Stud2006; 73: 549–576.
62.
NunnNQianN. US Food aid and civil conflict. Am Econ Rev2014; 104: 1630–1666.
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