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• W2896714617 abstract "Abstract Taxis are the main contributor to the emissions of roadside pollutants and greenhouse gases. Many studies have shown that electrifying the taxi fleet is effective in reducing roadside pollution and carbon footprint. However, high ownership cost of electric taxis, limited driving range, and availability of chargers are constraining their deployment. Government subsidy has been sought for in many applications, yet the required amount can be enormous and remains infeasible in many jurisdictions. To address these issues, electric taxis are proposed to provide premium services and let all stakeholders share the financial input. That is, a higher fare will be charged to the taxi customers for a higher service quality. The taxi drivers with higher incomes will be able to pay more to rent the electric taxis. With an increase of rental income to the taxi owners, fewer financial incentives from the government will be required. This study aims to uncover the factors underpinning how taxi owners and drivers choose between conventional taxis and the proposed premium electric taxis. Stated-preference surveys were conducted in Hong Kong, and two separate binary logistic regression models were calibrated accordingly. It was found that the (subsidized) vehicle purchase price, rental income, and battery lifespan were influential to the owners, while fare income, the rental cost, the access time to chargers, and the range per charge significantly affected taxi drivers’ decisions. An equilibrium model with an iterative solution procedure is proposed to illustrate the interactions between the stakeholders and predict the changes in percentage-of-switch under different policy settings. Policy implications to improve taxi service and reduce roadside emissions and pollution are hence discussed." @default.
• W2896714617 created "2018-10-26" @default.
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• W2896714617 date "2018-12-01" @default.
• W2896714617 modified "2023-10-01" @default.
• W2896714617 title "Modeling the acceptance of taxi owners and drivers to operate premium electric taxis: Policy insights into improving taxi service quality and reducing air pollution" @default.
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• W2896714617 doi "https://doi.org/10.1016/j.tra.2018.10.011" @default.
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