TY - JOUR
T1 - Out of the way, human! Understanding post-adoption of last-mile delivery robots
AU - Lim, Xin-Jean
AU - Chang, Jennifer Yee-Shan
AU - Cheah, Jun-Hwa
AU - Lim, Weng Marc
AU - Kraus, Sascha
AU - Dabić, Marina
N1 - Acknowledgment: This research was financially supported by the Slovenian Research Agency (www.arrs.gov.si) within the research program P5–0441. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Data availability: The data that has been used is confidential.
PY - 2024/4
Y1 - 2024/4
N2 - 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.
AB - 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.
U2 - 10.1016/j.techfore.2024.123242
DO - 10.1016/j.techfore.2024.123242
M3 - Article
VL - 201
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
SN - 0040-1625
M1 - 123242
ER -