Pandemic-driven acceptance of urban drone deliveries

Kum Fai Yuen, Lanhui Cai, Shaun Chuin Kit Wee, Xueqin Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The objective of this study is to investigate the factors affecting the adoption of urban drone delivery as an infection prevention measure from a health-centric perspective. To this end, a theoretical model is developed, using the protection motivation theory as the backbone, with constructs from fear appeal theory and perceived value theory incorporated into the model. Subsequently, an online survey was administered to 450 participants living in Singapore. The results were analysed using structural equation modelling, revealing that perceived severity positively and significantly influences fear of COVID-19. The results also show that perceived vulnerability and fear of COVID-19, response efficacy and self-efficacy of drone deliveries positively and significantly impact perceived utility, while response cost has a significant negative impact on perceived utility. Both fear and perceived utility have a direct, positive and significant influence on the adoption intention of drone deliveries, with the overall most significant factor being fear of COVID-19. With these findings, this study has contributed to the understanding drone delivery adoption during pandemics. In this regard, the insights may assist logistics companies and transport policymakers in understanding concerns and motivations regarding drone deliveries.

Original languageEnglish
Pages (from-to)356-370
Number of pages15
JournalTransport Policy
Volume146
DOIs
Publication statusPublished - Feb 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

ASJC Scopus Subject Areas

  • Geography, Planning and Development
  • Transportation
  • Law

Keywords

  • COVID-19
  • Drone delivery
  • Fear appeal theory
  • Perceived value theory
  • Protection motivation theory
  • Structural equation modelling

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