The effects of motivated consumer innovativeness on consumer acceptance of autonomous delivery robots

This research aimed to examine the impacts of motivated consumer innovativeness on customers' acceptance of autonomous delivery robots (ADRs) using the privacy calculus theory (PCT) and motivated consumer innovativeness theory (MCI). It was suggested that this impact was mediated by perceived risks and perceived cooperativeness. Four hundred and fifty survey responses were gathered through a stratified random sampling approach to effectively represent the population of Singapore, ensuring the sample's representativeness. The acquired data underwent analysis via structural equation modelling, uncovering that motivated consumer innovativeness (MCI) (i.e. functional MCI, hedonic MCI, cognitive MCI, and social MCI) influences the perceived (privacy) risks of using ADRs. In addition, the perceived risks influence the perceived cooperativeness of ADRs. Furthermore, the perceived risks and perceived cooperativeness both influence the consumers' acceptance of ADRs. The combination of theories is highly effective in explaining consumers' acceptance of ADRs, accounting for a substantial 78.3% of the variance. These findings highlight the significant impact of enhancing perceptions of ADR cooperativeness and transparent communication about privacy and safety on consumer acceptance. This, in turn, informs effective policy and strategic decisions for ADR development and deployment.