Public Acceptance of Last-Mile Shuttle Bus Services with Automation and Electrification in Cold-Climate Environments

Naihui Wang, Yulong Pei () and Hao Fu
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Naihui Wang: School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China
Yulong Pei: School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China
Hao Fu: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China

Sustainability, 2022, vol. 14, issue 21, 1-16

Abstract: The last-mile shuttle bus service with automation and electrification has emerged to fill gaps in on-demand transportation systems and its goals are to satisfy the door-to-door mobility needs of residents. It could help to enhance the happiness of public travel in cold-climate environments, which is also considered a pro-social public transportation service. Although it has the potential to promote sustainable and environmentally friendly mobility systems, the successful implementation of last-mile shuttle bus services with automation and electrification highly depends on individuals’ willingness to accept. In this paper, a theoretical acceptance model for last-mile shuttle bus services with automation and electrification is proposed. Partial least squares structural equation modeling is employed to examine research model in accordance with 986 valid questionnaires answered by public in snow and ice environments. The outcomes show that the proposed model accounts for 73.4% of the variance in behavioral intention to utilize last-mile shuttle bus services with automation and electrification. The strongest determinants of behavior intention are attitude and perceived usefulness. In addition, perceived risk negatively affects behavioral intention. We also provide theoretical findings and practical suggestions for developing last-mile shuttle bus services with automation and electrification based on the results and our analysis.

Keywords: shuttle bus; last-mile transportation service; cold-climate environments; automated vehicle; electric vehicle; acceptance model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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