Autonomous Delivery Robots for Urban Last-mile Logistics Operations: a modified UTAUT framework

Interest in autonomous deliveries among logistics service providers (LSP) is growing. This is due to pressure regarding emission reduction regulations, driving bans inside cities, and growing service demands. Autonomous Delivery Robots (ADR) can form a solution and help to optimize current logistics operations. This work investigates factors that might influence the behavioural intention to use ADR. Focus is on decision-makers of LSP. Data was collected through an online survey. The questionnaire is based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Results provide insights concerning factors shaping the acceptance of ADR for last-mile logistics operations. The factors performance expectancy, facilitating conditions, experience, trust, and perceived risk were found to affect the behavioural intention.

• Record URL:
  • https://doi.org/10.1016/j.trpro.2023.11.658
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2352146523009560
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
• Supplemental Notes:
  • © 2023 The Author(s). Published by Elsevier B.V. Abstract reprinted with permission of Elsevier.
• Authors:
  • Engesser, Valeska
  • Rombaut, Evy
  • Vanhaverbeke, Lieselot
  • Lebeau, Philippe
• Conference:
  • Transport Research Arena Conference (TRA Lisbon 2022)
  • Location: Lisbon , Portugal
  • Date: 2022-11-14 to 2022-11-17
• Publication Date: 2023

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 1816-1823
• Serial:
  • Transportation Research Procedia
  • Volume: 72
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2352-1465
  • Serial URL: http://www.sciencedirect.com/science/journal/23521465/
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Decision making; Delivery vehicles; First mile and last mile; Perception; Supply chain management
• Geographic Terms: Belgium
• Subject Areas: Data and Information Technology; Economics; Freight Transportation; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01912776
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 21 2024 5:05PM