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A Trust-Based Model for the Adoption of Smart City Technologies in Australian Regional Cities

doi: 10.3390/su13169316
This paper explores the role of stakeholders’ trust in the adoption of smart city technologies, leading to the identification of the critical determinants for adopting smart city technologies in Australian regional cities. A comprehensive review of the related literature has been conducted. Such a review leads to the development of a trust-based research model for investigating the importance of trust in technology and its adoption. This model is then tested and validated with the use of a structural equation modeling technique on the survey data collected from ICT professionals in Australian regional cities. The study results show that perceived usefulness, perceived external pressure and perceived information security influence trust in smart city technologies. Further analysis highlights the significant relationship between stakeholders’ trust and their intention to adopt smart city technologies. This study is unique, as it is one of a few studies that focus on exploring stakeholders’ trust in the adoption of smart city technologies from the perspective of ICT professionals in Australia. The study results can be used by the government agencies to formulate appropriate policies to enhance the use of smart city technologies in the active pursuit of smart city development in Australia.
- Central Queensland University Australia
- RMIT University Australia
- RMIT University Australia
- Central Queensland University Australia
smart cities, Environmental effects of industries and plants, Australia, TJ807-830, trust, TD194-195, Renewable energy sources, Environmental sciences, technology, adoption intention, GE1-350
smart cities, Environmental effects of industries and plants, Australia, TJ807-830, trust, TD194-195, Renewable energy sources, Environmental sciences, technology, adoption intention, GE1-350
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).24 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
