Factors that influence adoption intentions toward smart city services among users

Abstract

While smart cities have been initiated by various city governments around the world in recent years, digital transformations with regard to services have become essential for a city to be smart. Nonetheless, few previous studies have explored the adoption intentions toward smart city services, especially from a perspective of social learning. This study aims to investigate the factors that influence the adoption intentions toward smart city services among users. Based on social learning theory, this study develops a research model that integrates adoption intentions and five factors: perceived usefulness, perceived ease of use, trust, social influence, and government support. This study examined this model via survey data from 940 respondents in Taiwan. The results reveal that perceived usefulness, perceived ease of use, and trust have positive effects on adoption intentions and that social influence and government support have impacts on adoption intentions through trust. The results offer a useful reference for other countries in the early stages of smart city initiatives, and they have significant theoretical implications for researchers in the areas of smart cities and innovative service adoption.