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• W3120367925 abstract "Replacing combustion vehicles with electric vehicles has been promoted by the Chinese government as a viable policy to reduce fuel consumption and greenhouse gas emissions. The purpose of this study is to examine factors that influence Chinese taxi drivers’ adoption of electric vehicles for living. This study takes the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) as the theoretical framework and extends it to examine the influence of taxi drivers’ satisfaction over government’s invectives on their adoption of electric vehicles for living (i.e., adoption intention and use behavior). A questionnaire-based survey was conducted in Shenzhen and Guangzhou from November 2018 to April 2019, and 725 valid samples were collected. The model has good explanatory power, and its predictive validity accounts for about 89% of the variance in adoption intention and 50% in use behavior. The statistical results supported that such constructs as Satisfaction with Incentive Policies, Performance Expectancy, Effort Expectancy, Facilitating Conditions, Hedonic Motivation, Price Value, and Habit, are influencing factors on taxi drivers’ intention of using electric vehicles (i.e., behavior intention). These constructs, together with Social Influence but excluding Habit, are also influential to the actual use of electric vehicles by taxi drivers for living (i.e., use behavior). This study expands the existing theoretical modeling for characterizing the adoption of electrical vehicles. The study suggests policy makers further investigate taxi driver's satisfaction with different incentive policies, and electric vehicle manufacturers focus on improving hedonic motivation for taxi drivers, e.g., providing test-drive experiences." @default.
• W3120367925 created "2021-01-18" @default.
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• W3120367925 date "2021-02-01" @default.
• W3120367925 modified "2023-10-17" @default.
• W3120367925 title "Characterizing the motivational mechanism behind taxi driver’s adoption of electric vehicles for living: Insights from China" @default.
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• W3120367925 doi "https://doi.org/10.1016/j.tra.2021.01.001" @default.
• W3120367925 hasPublicationYear "2021" @default.
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