Willingness to pay for automated taxis: a stated choice experiment to measure the impact of in-vehicle features and customer reviews

Hao Yin () and Elisabetta Cherchi ()
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Hao Yin: Newcastle University
Elisabetta Cherchi: Newcastle University

Transportation, 2024, vol. 51, issue 1, No 3, 72 pages

Abstract: Abstract This study aims to contribute to the limited empirical evidence on Automated Taxis (ATs) by analysing the in-vehicle features that ATs ought to have to satisfy taxi passengers requests that in a Normal Taxi (NT) are dealt with a direct communication between the passenger and the driver. Based on the results of focus groups and several pilots, two in-vehicle features are tested: change of destination and chat with an operator during the trip. The paper also contributes to the body of literature on the impact of social influence on the adoption of innovation by testing the impact of consumer reviews other than the typical measure of adoption and injunctive norms. A Stated Choice (SC) experiment was built putting particular effort in the definition and presentation of the new attributes tested. The study was applied in China among current users of NTs (i.e. with the driver). Hybrid choice models were estimated and a resampling technique was used to test the model sensitivity to the sample gathered. Results show that on average, Chinese taxi users are willing to pay 0.35 Euros to have the option to ‘change the destination’ and 0.78 Euros to be able to ‘chat with an operator’ inside the AT. Among the social influence attributes, the reviews from previous customers confirmed to be the most effective measure, users are willing to pay 1.58 Euros more to use a taxi that got good reviews for long trips (≥ 30 min) and 0.57 Euros for shorter trips. The Willingness to Pay (WTP) estimated are all significant at more than 95% and have a narrow confidence intervals.

Keywords: Automated taxis; Stated choice experiment; In-vehicle features; Social influences; Customer reviews; Willingness to pay (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11116-022-10319-3

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