Determinants of intention-to-use first-/last-mile automated bus service

The successful adoption of a product or service by its target market or users relies on delivering a product or service in line with their needs and expectations. Failure to do so will likely result in a low rate of uptake or use of the product or service. This study sought to identify the criteria by which potential users of a first-/last-mile automated bus (AB) service would evaluate the service, and accordingly decide whether to use or disregard the service. This research investigated various explanatory factors affecting users’ perceptions of the service’s quality and utility, and which enhanced or diminished their intentions to use it. The data analysed in this study was collected from a survey conducted in February and March of 2018 in Stockholm, Sweden, during a trial operation of a first-/last-mile AB service. Three-factor theory analysis, commonly used to analyse services, was applied to this data in order to identify users’ core perceptions about the service, which in turn influence their intention-to-use the service. Structural equation modelling was used to identify the significant factors that influence the identified perceptions influencingthe intention-to-use the service. This study found that different subgroups of users prioritised different attributes. Prospective users (with no prior experience with the service) were most concerned with the frequency of service. Their intention-to-use the service greatly increased when the service frequency is comparable to the service frequency of a regular public bus service. Experienced users’ intentions to continue using the service greatly increased when the buses were made more comfortable. This study additionally found that users’ perceptions of the service’s quality were also influenced by numerous factors including the passenger’s age, income level, preferred mode of travel for daily trips, preferred mode of travel for first-/last-mile trips, being tech-savvy or not, and their level of familiarity with automated driving technology.

• Record URL:
  https://doi.org/10.1016/j.tra.2020.06.001
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0965856420306108
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
• Supplemental Notes:
  • © 2020 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Chee, Pei Nen Esther
  • Susilo, Yusak O
  • Wong, Yiik Diew
• Publication Date: 2020-9

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 350-375
• Serial:
  • Transportation Research Part A: Policy and Practice
  • Volume: 139
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0965-8564
  • Serial URL: http://www.sciencedirect.com/science/journal/09658564

Subject/Index Terms

• TRT Terms: Acceptance; Attitudes; Automated guided vehicle systems; Autonomous vehicles; Decision making; Quality of service; Structural equation modeling; Transit buses; Transit riders
• Subject Areas: Passenger Transportation; Planning and Forecasting; Public Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01751782
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 11 2020 5:31PM