Work

Trust transfer in the adoption of autonomous last mile services toward digital urban system

Year: 2024

Type: article

Abstract: Last mile connectivity is crucial in transporting people from a transportation hub to a destination. Government-supported autonomous last-mile service (ALMS) is a cutting-edge solution to this problem, providing on-demand public transportation that connects to the primary mode of transportation and is automatically operated through the use of autonomous vehicles and other complementary technologies. However, the implementation of ALMS poses several challenges. Trust is an essential factor in enabling users to overcome their concerns about risk and uncertainty. Although trust can be developed towards various entities, existing studies have only explored trust in autonomous vehicles, without addressing overall trust in the ALMS. Furthermore, ALMS is a sophisticated social-technological transportation service, consisting of multiple components that could trigger distinct trust beliefs. Our research aims to understand the factors influencing trust in ALMS and identify ways to promote trust and overcome potential obstacles to adoption. The results showed that trust in ALMS mediated the influence of both trust in public transportation and trust in supporting technologies on ALMS use intention. The research also identified key factors driving trust, including the reputation of technology companies and government, public transportation satisfaction, and cost-benefit calculation of supporting technologies. Additionally, cost-benefit analysis was found to be a second-order construct consisting of seven dimensions, including availability, data privacy, cybersecurity, technology reliability, service quality, usability, and environmental impact.

Source: Digital engineering.

DOI: 10.1016/j.dte.2024.100030

Authors: Shengbin Wang, Ziyue Huang

Institution: The College of New Jersey

Language: English

Topic: Transportation and Mobility Innovations

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $1,700