In recent years, active efforts to implement smart cities have increased worldwide. In smart cities, a large amount of personal information is captured, and urban development is based on these data. In Japan, implementations of smart cities continue to gain momentum, but the issue of social acceptance has become apparent, as smart cities are not fully accepted by citizens because of concerns about data leaks and misuse of personal information. This study examines the social acceptance of collecting and utilizing personal information in smart cities in relation to a variety of factors such as trust and perceptions of risk, justice, benefit, and necessity. An online survey was conducted wherein participants (N = 568) were presented with a vignette depicting an overview of a typical smart city. The results of structural equation modeling showed that perceived justice was positively related to trust and trust was negatively related to perceived risk and positively related to perceived benefit and necessity. Trust, perceived benefit, and perceived necessity were significantly related to social acceptance, with trust having the greatest relationship. The model obtained in this study contributes to practical efforts for the implementation of smart cities, and future directions are discussed.

In smart city services, large volumes of personal information are generally captured, and urban development is based on that data. However, people do not always have accepting attitudes toward smart city services. The purpose of this study was to identify the expectations and anxieties that people have toward five typical services in smart cities (social credit, artificial intelligence (AI) cameras, health information, garbage collection, and automatic vehicles) by using mainly open-ended questions. An online survey was conducted with Japanese participants by presenting them with one of the five vignettes about the services described above. The results showed that the participants’ expectations from each service were distinctly different between the vignettes. Anxieties about the leakage of personal information were found for the vignettes of social credit and health information. For the vignettes of AI cameras and garbage collection, anxieties that privacy would not be sufficiently ensured and that people would be involved in a surveillance society were noted. Additionally, the participants tended to exhibit lower accepting attitudes toward services considered to capture a large amount of personal information. We believe that our findings are meaningful to operators leading smart city projects and researchers in urban planning and psychology.

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In recent years, smart health (s-Health) services have gained momentum worldwide. The s-Health services obtain personal information and aim to provide efficient health and medical services based on these data. In Japan, active efforts to implement these services have increased, but there is a lack of social acceptance. This study examined social acceptance concerning various factors such as trust in the city government, perceived benefits, perceived necessity, perceived risk, and concern about interventions for individuals. An online survey was conducted, and Japanese participants (N = 720) were presented with a vignette depicting a typical s-Health service overview. The results of structural equation modeling showed that trust was positively related to perceived benefit and necessity and negatively related to perceived risk and concern about interventions for individuals. Perceived benefit and trust were positively related to social acceptance, and perceived risk was negatively related to acceptance. The model obtained in this study can help implement s-Health services in public. Empirical studies that contribute to improving public health by investigating the social acceptance of s-Health services should be conducted in the future.

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