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Regional Sustainability

Abstract

Speeding up the promotion of new energy vehicles is an important measure to optimize the energy structure, promote energy conservation and emission reduction, and develop the economy sustainability. The research uses a questionnaire survey to analyze the residents’ willingness to purchase new energy vehicles in Jinan City of China, and utilizes the binomial logistic regression model and Global Moran’s I to explain the impact of three factors (including respondents’ personal characteristics and subjective cognition, products, and social environment) on the purchase willingness of new energy vehicles. According to the survey, 75.12% of the respondents consider buying new energy vehicles in the future, but only 11.66% of the respondents know new energy vehicles well. It can be seen that the respondents in Jinan City generally have an insufficient understanding of new energy vehicles. It may lead to a decline in residents’ trust in new energy vehicles, which will in turn affect their purchase willingness. Based on the survey, we find that women who live far from the city center enjoy high incomes and have a low-carbon awareness, generally exhibit a higher willingness to purchase new energy vehicles. Spatial distribution of the purchase willingness has certain aggregation characteristics, showing a positive spatial correlation pattern. Purchase willingness has a certain positive diffusion effect in space, and areas with a higher purchase willingness have a positive driving effect on their surrounding regions. Spatial distribution of the purchase willingness can be used as one of the breakthroughs in promoting new energy vehicles. In addition, safety, price, after-sales service, and infrastructure of new energy vehicles are important determinants of people’s purchase willingness. Among the types of subsidies, financial subsidy is most effective on the residents’ purchase willingness. Our research provides an important information for the promotion of new energy vehicles in the region.

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