| dc.description.abstract | In recent years, the research and discussion of energy or environmental issues have become a global forum. In the face of the threat of mobile pollution sources to the environment and health, countries around the world have invested resources to advocate carbon reduction and air pollution reduction. The impact of fuel vehicles on the environment has been Inevitable issues, the rise of the green economy has changed the industrial structure. The development and evolution of the ocomotive industry technology, Taiwan′s electric motorcycles compete with fuel motorcycles from technical research and development to product quality. In particular, the speel limit, riding distance and charging convenience that consumers value have been significantly improved. For accelerate the replacement of old fuel motorcycles , the central and local governments continue to purchase car subsidies. This study takes the electric vehicle model data from 2016 to the present and the number of Taiwan electric vehicle subsidies as a research sample, refers to the literature of electric vehicle technology and market characteristics in the past to discuss and construct this research framework.
The hedonic price analysis of electric motorcycles adopts the Ordinary Least Square model (OLS). Research that motorcycle horsepower is the basic key factor of electric motorcycles . Safety performance and upgrade specifications are the key factors affecting the price of heavy motorcycles . The duration and grade slope are key factor affecting price for Light(small) motorcycles.
The empirical analysis of car purchase subsidies is based on the Panel Data Two-way fixed effect model. The research resylts confirm that the difference in the impact of the car purchase subsidy policy on the number of electric vehicles, the replacement of the old replacement subsidy is better than the new purchase subsidy program, the higher the education level, and the higher the acceptance of electric vehicles in counties and cities, in the Air Quality Index (QAI) data There is no significant impact. | en_US |