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.
•Examining last-mile robots reveals their impact on user behavior; TTF model predicts acceptance factors.•Study identifies value-in-use and trust roles, linking to repeat usage and recommendations.•Practical insights enhance last-mile robot industry strategies effectively.•Chinese market insights underscore understanding user behavior in robotic services growth.•Study implications contribute to understanding user behavior in last-mile robot adoption.