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Modelling the factors that affect the intention to adopt emerging digital technologies for a sustainable smart world city

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  • Teng, Qiuling
  • Bai, Xiaoyu
  • Apuke, Oberiri Destiny

Abstract

All over the world, urbanization's problems are forcing governments to look for innovative ways to run contemporary cities and as such, solving urban problems has become a hot topic. The implementation of smart city technology is one of the most sought-after solutions. However, research on the variables that influence individuals' intentions to use smart city services is still in its infancy, particularly in developing countries. This research looked at what influences people's decisions to utilize or embrace smart city services in on Asian country. It extended the Unified Theory of Acceptance and Use of Technology (UTAUT2) model by adding trust in technology, trust in government, perceived security concern and perceived privacy concern. Using a simple random sampling technique, data were collected from 470 participants across three major cities in one Asian country. The biggest predictor of the desire to use smart city services, according to our research, is the facilitating condition. Other elements include social influence, hedonic drive, performance expectancy, effort expectancy, and trust in the government. The inclination to use smart city services was shown to be inversely correlated with privacy and security concerns. Trust in smart city services had nothing to do with its usage intention. Finally, gender and age did not act as moderators of the hypothesized relationships in our model. This outcome established strong theoretical and practical implications as discussed in this article.

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  • Teng, Qiuling & Bai, Xiaoyu & Apuke, Oberiri Destiny, 2024. "Modelling the factors that affect the intention to adopt emerging digital technologies for a sustainable smart world city," Technology in Society, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:teinso:v:78:y:2024:i:c:s0160791x24001519
    DOI: 10.1016/j.techsoc.2024.102603
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    1. Yucen Zhou & Zhong Wang & Lifeng Liu & Yanran Peng & Beatrice Ihimbazwe, 2025. "The Impact of Digitization on Urban Social–Ecological Resilience: Evidence from Big Data Policy Pilots in China," Sustainability, MDPI, vol. 17(2), pages 1-27, January.
    2. Lu, Hang, 2024. "Exploring the predictors of public acceptance of artificial intelligence-based resurrection technologies," Technology in Society, Elsevier, vol. 78(C).

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