| Title | Crowdsourcing Smart City: SmartTaipei Project |
|---|---|
| ID_Doc | 44964 |
| Authors | Liu, HK; Guo, YW; Chen, LY |
| Title | Crowdsourcing Smart City: SmartTaipei Project |
| Year | 2023 |
| Published | |
| Abstract | Increasingly governments engage the crowd through online platforms to generate innovation and utilize collaborative platforms for AI adoptions as a governance strategy. This study aims to investigate the factors associated with terminated and implemented smart city or AI related technologies projects through qualitative analysis. This study selected a setting based on the Taipei Smart City Industrial Field Experiment Pilot Program since 2016. We collected online achieved data of the smart city proposals from 2016 to April 2023 (N=295). Based on those achieved data with descriptions for termination and implementation, this paper discusses the opportunities, challenges, and suggestions for overcoming such challenges of the SmartTaipei Project. Given that governments do not provide financial support for smart city pilot projects, enterprises acquire opportunities to experiment with and thus improve their products or services. The successful experiment is conducive to research and development, business expansion, and even government procurement. However, despite the fact that the SmartTaipei proposals and projects have been discussed and modified several times before implementation, 41.7% of the projects were terminated due to several reasons. We classify the total number of AI technologies adopted across all projects. We also use the Technology Enactment Framework as the analysis framework to summarize the reason why nearly 41.7% of the project (N=123) were terminated. To address the challenges of building smart cities, this paper suggests that municipal governments (1) build up platforms for stakeholder participation and assess progressive results, (2) develop a comprehensive development strategy and enhance digital infrastructure, and (3) develop a convention for international exchange. |
| https://dl.acm.org/doi/pdf/10.1145/3598469.3598474 |
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