Consumers' intention to use delivery robots in Iran: An integration of NAM, DOI, and TAM

This study seeks to identify factors influencing the adoption of sidewalk autonomous delivery robots (SADRs) as a green delivery method by shoppers. Accordingly, this study proposes a comprehensive model based on a combination of the norm activation model (NAM), diffusion of innovation (DOI) theory, and technology acceptance model (TAM). The data were collected from 463 Iranian buyers through an online questionnaire. The partial least square (PLS) results revealed that relative advantage, compatibility, and observability positively affected the attitude toward using delivery robots, while complexity negatively impacted this attitude. The observations indicated that problem awareness, ascribed responsibility, and environmental concern positively influenced personal norm. Finally, it was found that personal norm and attitudes toward using delivery robots positively affected the intention to use them. The results of the present work not only provide theoretical contributions to the literature but also can be practically helpful to policymakers.

• Record URL:
  • https://doi.org/10.1016/j.cstp.2023.101024
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2213624X23000780
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/2213624X
• Supplemental Notes:
  • © 2023 World Conference on Transport Research Society. Published by Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Ganjipour, Houmaan
  • Edrisi, Ali
• Publication Date: 2023-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 101024
• Serial:
  • Case Studies on Transport Policy
  • Volume: 13
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2213-624X
  • Serial URL: http://www.sciencedirect.com/science/journal/2213624X

Subject/Index Terms

• TRT Terms: Acceptance; Consumers; Delivery vehicles; Mobile robots; Technological innovations
• Geographic Terms: Iran
• Subject Areas: Data and Information Technology; Freight Transportation; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01886492
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 28 2023 4:57PM