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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.04363 |
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| _version_ | 1866913640549974016 |
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| author | Donio, Shahaf Toch, Eran |
| author_facet | Donio, Shahaf Toch, Eran |
| contents | While local governments have invested heavily in smart city infrastructure, significant disparities in adopting these services remain in urban areas. The success of many user-facing smart city technologies requires understanding barriers to adoption, including persistent inequalities in urban areas. An analysis of a random sample telephone survey (n=489) in four neighborhoods of Tel Aviv merged with digital municipal services usage data found that neighborhood residency influences the reasons why residents adopt resident-facing smart city services, as well as individual-level factors. Structured Equation Modeling shows that neighborhood residency is related to digital proficiency and privacy perceptions beyond demographic factors and that those influence the adoption of smart-city services. We summarize the paper by discussing why and how place effects must be considered in further research in smart cities and the study and mitigation of digital inequality. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_04363 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Neighborhood Disparities in Smart City Service Adoption Donio, Shahaf Toch, Eran Human-Computer Interaction While local governments have invested heavily in smart city infrastructure, significant disparities in adopting these services remain in urban areas. The success of many user-facing smart city technologies requires understanding barriers to adoption, including persistent inequalities in urban areas. An analysis of a random sample telephone survey (n=489) in four neighborhoods of Tel Aviv merged with digital municipal services usage data found that neighborhood residency influences the reasons why residents adopt resident-facing smart city services, as well as individual-level factors. Structured Equation Modeling shows that neighborhood residency is related to digital proficiency and privacy perceptions beyond demographic factors and that those influence the adoption of smart-city services. We summarize the paper by discussing why and how place effects must be considered in further research in smart cities and the study and mitigation of digital inequality. |
| title | Neighborhood Disparities in Smart City Service Adoption |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2501.04363 |