Acceptance of Autonomous Delivery Vehicles for Last-Mile Delivery in Germany – Extending UTAUT2 with Risk Perceptions

Sebastian Kapser, Mahmoud Abdelrahman

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)
11 Downloads (Pure)

Abstract

The inevitable need to develop new delivery practices in last-mile logistics arises from the enormously growing business to consumer (B2C) e-commerce and the associated challenges for logistics service providers. Autonomous delivery vehicles (ADVs) are believed to have the potential to revolutionise last-mile delivery in a way that is more sustainable and customer focused. However, if not widely accepted, the introduction of ADVs as a delivery option can be a substantial waste of resources. At present, the research on consumers’ receptivity of innovations in last-mile delivery, such as ADVs, is limited. This study is the first that investigates the users’ acceptance of ADVs in Germany by utilising an extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and adapted it to the context of ADVs in last-mile delivery. Quantitative data was collected through an online survey approach (n=501) and structural equation modelling was undertaken. The results indicate that price sensitivity is the strongest predictor of behavioural intention (i.e., user acceptance), followed by performance expectancy, hedonic motivation, perceived risk, social influence and facilitating conditions, whereas no effect could be found for effort expectancy. These findings have important theoretical and practical contributions in the areas of technology acceptance and last-mile delivery.
Original languageEnglish
Pages (from-to)210-225
Number of pages16
JournalTransportation Research Part C: Emerging Technologies
Volume111
Early online date6 Jan 2020
DOIs
Publication statusPublished - 1 Feb 2020

Fingerprint

Dive into the research topics of 'Acceptance of Autonomous Delivery Vehicles for Last-Mile Delivery in Germany – Extending UTAUT2 with Risk Perceptions'. Together they form a unique fingerprint.

Cite this