 Direct network effects in electric vehicle adoptionXiang Zhang, Xiaoming Hu, Liang Qi and Taosheng Jin Technological Forecasting and Social Change, 2024, vol. 209, issue C Abstract: Direct network effects (DNEs) are important market rules that influence the diffusion of electric vehicles (EVs). However, there is little empirical evidence on the role of DNEs in promoting EVs. We aim to reveal how the DNEs of EVs change with external shocks (e.g. the termination of subsidies and the outbreak of COVID-19) and further affect EV adoption. Using monthly panel data on EV adoption from 132 Chinese cities, we find that DNEs are larger during the subsidy period, decrease after the subsidy ends, and are not significantly affected by the pandemic. Cities that previously had local subsidies have larger DNEs, which have a multiplier effect that further reinforces the positive role of subsidies. Furthermore, we find that the removal of subsidies has a larger negative impact on EV adoption than the negative impact of the pandemic. Implications for policy makers and managers are proposed based on our findings. Keywords: Direct network effects; Subsidy cessation; The COVID-19 pandemic; Electric vehicle adoption (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:209:y:2024:i:c:s0040162524005687 DOI: 10.1016/j.techfore.2024.123770 Access Statistics for this article Technological Forecasting and Social Change is currently edited by Fred Phillips More articles in Technological Forecasting and Social Change from Elsevier |
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