Increasing carbon efficiency is a key path to sustainable development, and information and communication technology (ICT) may help realize a win-win situation for the economy and the environment. However, the existing literature on the impact of ICT on carbon efficiency is relatively shallow. Using a database of Chinese cities, this study empirically explores the role of ICT in carbon efficiency from the aspects of direct impact, mediation effect, and threshold effect. Results show that ICT significantly improves the carbon efficiency represented by single-factor and total-factor carbon efficiency. The mediation effect indicates that technological innovation, industrial structure upgrading, and external openness are effective ways for ICT to play its role. The threshold model shows that the promoting effect between the two depends on the local institutional environment. Further heterogeneity analysis shows that ICT plays a more remarkable role in promoting carbon efficiency in eastern regions. This study provides evidence for aggressively digitizing economies to shift towards a low-carbon economy. Policymakers are encouraged to consider better integrating ICTs into sustainable development strategies.
GaoDLiYYangQ. Can pollution charges reform promote industrial SO2 emissions reduction—evidence from 189 China’s cities. Energy Environ2021; 32: 96–112.
2.
WenHLeeCCSongZ. Digitalization and environment: how does ICT affect enterprise environmental performance. Environ Sci Pollut Res2021; 28: 54826–54841.
3.
XuQZhongMCaoM. Does digital investment affect carbon efficiency? Spatial effect and mechanism discussion. Sci Total Environ2022; 827: 154321.
4.
Danish. Effects of information and communication technology and real income on CO2 emissions: the experience of countries along belt and road. Telemat Inform2019; 45: 101300.
5.
WangEZLeeCC. The impact of information communication technology on energy demand: Some international evidence. Int Rev Econ Finance2022; 81: 128–146.
6.
ZhongMRCaoMYZouH. The carbon reduction effect of ICT: a perspective of factor substitution. Technol Forecast Soc Change2022; 181: 121754.
7.
AngBW. Is the energy intensity a less useful indicator than the carbon factor in the study of climate change?Energy Policy1999; 27: 943–946.
8.
ZhouPAngBWWangH. Energy and CO2 emission performance in electricity generation: a non-radial directional distance function approach. Eur J Oper Res2012; 221: 625–635.
9.
ChandraSShirishASrivastavaSC. Theorizing technological spatial intrusion for ICT enabled employee innovation: the mediating role of perceived usefulness. Technol Forecast Soc Change2020; 161: 120320.
10.
XuLFanMYangL, et al.Heterogeneous green innovations and carbon emission performance: evidence at China’s city level. Energy Economics2021; 99: 105269.
11.
SongWMaoHHanX. The two-sided effects of foreign direct investment on carbon emissions performance in China. Sci Total Environ2021; 791: 148331.
12.
AcheampongAOAmponsahMBoatengE. Does financial development mitigate carbon emissions? Evidence from heterogeneous financial economies. Energy Economics2020; 88: 104768.
13.
WangKWuMSunY, et al.Resource abundance, industrial structure, and regional carbon emissions efficiency in China. Resour Policy2019; 60: 203–214.
14.
WuHHaoYRenS, et al.Does internet development improve green total factor energy efficiency? Evidence from China. Energy Policy2021; 153: 112247.
15.
GaoDLiGYuJ. Does digitization improve green total factor energy efficiency? Evidence from Chinese 213 cities. Energy2022; 247: 123395.
16.
UsmanAOzturkIHassanA, et al.The effect of ICT on energy consumption and economic growth in South Asian economies: an empirical analysis. Telemat Inform2021; 58: 101537.
17.
HiltyLM. Information technology and sustainability: Essays on the relationship between information technology and sustainable development. BoD–Books on Demand2011.
18.
ZhangJChengMYuN. Internet use and lower life satisfaction: the mediating effect of environmental quality perception. Ecol Econ2020; 176: 106725.
19.
ShabaniZDShahnaziR. Energy consumption, carbon dioxide emissions, information and communications technology, and gross domestic product in Iranian economic sectors: a panel causality analysis. Energy2019; 169: 1064–1078.
20.
OzcanBApergisN. The impact of internet use on air pollution: evidence from emerging countries. Environ Sci Pollut Res2018; 25: 4174–4189.
21.
SadorskyP. Information communication technology and electricity consumption in emerging economies. Energy Policy2012; 48: 130–136.
22.
SalahuddinMAlamK. Information and communication technology, electricity consumption and economic growth in OECD countries: a panel data analysis. Int J Electr Power Energy Syst2016; 76: 185–193.
23.
BelkhirLElmeligiA. Assessing ICT global emissions footprint: trends to 2040 & recommendations. J Cleaner Prod2018; 177: 448–463.
24.
ParkYMengFBalochMA. The effect of ICT, financial development, growth, and trade openness on CO2 emissions: an empirical analysis. Environ Sci Pollut Res2018; 25: 30708–30719.
25.
LangeSPohlJSantariusT. Digitalization and energy consumption. Does ICT reduce energy demand. Ecol Econ2020; 176: 106760.
26.
LinBZhouY. Does the internet development affect energy and carbon emission performance. Sustain Prod Consump2021; 28: 1–10.
27.
LeeCCYuanZWangQ. How does information and communication technology affect energy security? International evidence. Energy Economics2022; 109: 105969.
28.
TianXBaiFJiaJ, et al.Realizing low-carbon development in a developing and industrializing region: impacts of industrial structure change on CO2 emissions in southwest China. J Environ Manage2019; 233: 728–738.
29.
AvomDNkengfackHFotioHK, et al.ICT and environmental quality in Sub-Saharan Africa: effects and transmission channels. Technol Forecast Soc Change2020; 155: 120028.
30.
HausmannRRodrikD. Economic development as self-discovery. J Dev Econ2003; 72: 603–633.
31.
BaronRMKennyDA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol1986; 51: 1173.
32.
HansenBE. Sample splitting and threshold estimation. Econometrica2000; 68: 575–603.
33.
LiGGaoDLiY. Dynamic environmental regulation threshold effect of technical progress on green total factor energy efficiency: evidence from China. Environ Sci Pollut Res2022; 29: 8804–8815.
34.
AlamMMMuradMW. The impacts of economic growth, trade openness and technological progress on renewable energy use in organization for economic cooperation and development countries. Renew Energy2020; 145: 382–390.
35.
DuKLiJ. Towards a green world: how do green technology innovations affect total-factor carbon productivity. Energy Policy2019; 131: 240–250.
36.
XiongSMaXJiJ. The impact of industrial structure efficiency on provincial industrial energy efficiency in China. J Cleaner Prod2019; 215: 952–962.
37.
LuJWSongYShanM. Social trust in subnational regions and foreign subsidiary performance: evidence from foreign investments in China. J Int Bus Stud2018; 49: 761–773.
38.
WangXLFanGHuLP. Marketisation index report by province in China (2018). Beijing[M]Economic Sciences Press, 2019; 1-22. in Chinese.
39.
AdamsSKloboduEKM. Financial development and environmental degradation: does political regime matter?J Cleaner Prod2018; 197: 1472–1479.
40.
WangQWangXLiR. Does urbanization redefine the environmental Kuznets curve? An empirical analysis of 134 countries. Sustain Cities Society2022; 76: 103382.
41.
ShaoSLiXCaoJH. Urbanization promotion and haze pollution governance in China. Economic Reserch2019; 2: 148–165. in Chinese.
42.
DémurgerS. Infrastructure development and economic growth: an explanation for regional disparities in China. J Comp Econ2001; 29: 95–117.
43.
LiRLiLWangQ. The impact of energy efficiency on carbon emissions: evidence from the transportation sector in Chinese 30 provinces. Sustain Cities Soc2022; 82: 103880.
44.
ChengZLiLLiuJ. Natural resource abundance, resource industry dependence and economic green growth in China. Resour Policy2020; 68: 101734.
45.
RazaAGholamiRMeiyuG, et al.A review on the natural gas potential of Pakistan for the transition to a low-carbon future. Energy Sources Part A2019; 41: 1149–1159.
46.
PisanoPPirontiMRiepleA. Identify innovative business models: can innovative business models enable players to react to ongoing or unpredictable trends. Entrepreneur Res Journal2015; 5: 181–199.
47.
WangQWangLLiR. Renewable energy and economic growth revisited: the dual roles of resource dependence and anticorruption regulation. J Cleaner Prod2022; 337: 130514.
48.
LeeCCYuanYWenH. Can digital economy alleviate CO2 emissions in the transport sector? Evidence from provincial panel data in China[C]. Nat Resour ForumOxford: Blackwell Publishing Ltd, 2022; 46: 289–310.
49.
HuangQYuYZhangS. Can smart city construction reduce environmental pollution. China Ind Econ2019; 8: 5–23. in Chinese.
50.
NunnNQianN. US food aid and civil conflict. Am Econ Rev 2014; 104: 1630–1666.
51.
ShiDDingHWeiP, et al.Can smart city construction reduce environmental pollution. China Ind Econ2018; 6: 117–135. in Chinese.
52.
HamidIAlamMSKanwalA, et al.Decarbonization pathways: the roles of foreign direct investments, governance, democracy, economic growth, and renewable energy transition. Environ Sci Pollut Res2022; 29(33): 49816–49831.
53.
MujtabaAJenaPKBekunFV, et al.Symmetric and asymmetric impact of economic growth, capital formation, renewable and non-renewable energy consumption on environment in OECD countries. Renew Sustain Energy Rev2022; 160: 112300.
54.
MujtabaAJenaPKMishraBR, et al.Do economic growth, energy consumption and population damage the environmental quality? Evidence from five regions using the nonlinear ARDL approach. Environ Challenges2022; 8: 100554.
55.
LiRWangQLiuY, et al.Per-capita carbon emissions in 147 countries: the effect of economic, energy, social, and trade structural changes. Sustain Prod Consump2021; 27: 1149–1164.
56.
JenaPKMujtabaAJoshiDPP, et al.Exploring the nature of EKC hypothesis in Asia’s top emitters: role of human capital, renewable and non-renewable energy consumption. Environ Sci Pollut Research2022; 29: 88557–88576.
