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, Marina Dabić

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Article number123242
JournalTechnological Forecasting and Social Change
Early online date2 Feb 2024
Publication statusE-pub ahead of print - 2 Feb 2024

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