Acceptance of Smart-City Technologies: Some Evidence on the Role of Perceptions and Demographics from a Municipality of Athens, Greece

The rise of the smart city reflects a transformative shift in urban development, defined by the integration of advanced technologies and data-driven solutions seeking to address rapid urbanization, environmental externalities, and the ever-increasing pressing need for optimal resource use. Nevertheless, a better understanding of the factors that shape citizens’ behavioral intentions towards smart-city living is becoming a sheer necessity. This study is among the first to empirically examine determinants describing the propensity to use smart-city services in an urban setting of south-eastern Europe. In this regard, we employ the smart-city stakeholders’ adoption (SSA) model in order to shed light on smart-city technology acceptance, further focusing on the underlying impact of demographics in shaping citizen attitudes and perceptions. Findings suggest that key predictors of acceptance (latent variables describing self-efficacy, price value, and trust in technology), all positively affect behavioral intention while the non-significance of effort expectancy contradicts the relevant results of previous studies and warrants further investigation. Furthermore, the analysis supports the theorized indirect effects of the model, whereas perceived privacy and perceived security both influence behavioral intention via trust in technology, while price value mediates the effect of citizen’s trust in government. The role of demographics was examined for potential moderating effects and was found to be significant, particularly in the case of age and education. Even though the demographic moderators we opted for do not substantially affect the explanatory power of the model, they seem to improve its specificity, particularly regarding perceptions on effort expectancy across the different demographic groups. Such results offer actionable insights on the relevance of smart-city acceptance models to the different demographic groups and in tailoring policies according to demographic segmentation groups with common characteristics.