| Title |
Factors that determine residents' acceptance of smart city technologies |
| ID_Doc |
45406 |
| Authors |
Habib, A; Alsmadi, D; Prybutok, VR |
| Title |
Factors that determine residents' acceptance of smart city technologies |
| Year |
2020 |
| Published |
Behaviour & Information Technology, 39, 6 |
| DOI |
10.1080/0144929X.2019.1693629 |
| Abstract |
While some cities attempt to determine their residents' demand for smart-city technologies, others simply move forward with smart-related strategies and projects. This study is among the first to empirically determine which factors most affect residents' and public servants' intention to use smart-city services. A Smart Cities Stakeholders Adoption Model (SSA), based on Unified Theory of Acceptance and Use of Technology (UTAUT2), is developed and tested on a mid-size U.S. city as a case study. A questionnaire was administered in order to determine the influence of seven factors - effort expectancy, self-efficacy, perceived privacy, perceived security, trust in technology, price value and trust in government - on behaviour intention, specifically the decision to adopt smart-city technologies. Results show that each of these factors significantly influenced citizen intention to use smart-city services. They also reveal perceived security and perceived privacy to be strong determinants of trust in technology, and price value a determinant of trust in government. In turn, both types of trust are shown to increase user intention to both adopt and use smart-city services. These findings offer city officials an approach to gauging residential intention to use smart-city services, as well as identify those factors critical to developing a successful smart-city strategy. |
| Author Keywords |
Smart-city; e-government; trust in government; trust in technology; structural Equation model (SEM); survey |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000497633000001 |
| WoS Category |
Computer Science, Cybernetics; Ergonomics |
| Research Area |
Computer Science; Engineering |
| PDF |
|