Out of the way, human! Understanding post-adoption of last-mile delivery robots

Xin-Jean Lim, Jennifer Yee-Shan Chang, Jun-Hwa Cheah, Weng Marc Lim, Sascha Kraus and Marina Dabic ()

Technological Forecasting and Social Change, 2024, vol. 201, issue C

Abstract: The pace of technological development is exceeding expectations and transforming the landscape of last-mile delivery. This study investigates how users' post-adoption behavior in using delivery robots is formed. Based on the task-technology fit (TTF) model, we present a research model that includes both direct and indirect factors that have been previously overlooked in the literature. We collected data from 550 users of delivery robots. Our structural equation modelling results show that two hedonic- (i.e., gratification and anthropomorphism) and three utilitarian- (i.e., service quality experience, delivery task requirements, and user-facing technology performance) driven factors predict perceived TTF in using delivery robots. Value-in-use and trust have sequential mediating effects that connect perceived TTF and service reuse likelihood and word-of-mouth recommendation. Our findings suggest ways to improve last-mile delivery robot strategies and provide practical implications for the industry.

Keywords: Delivery robot; Last-mile delivery; Task-technology fit model (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:201:y:2024:i:c:s0040162524000386

DOI: 10.1016/j.techfore.2024.123242

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