Research on Enhancing the Efficiency and Quality of Urban Water Information Management under Modern Innovative Management Models

Jing Meng, Jun He () and Peng Liu
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Jing Meng: Oxibridge College, Kunming University of Science and Technology
Jun He: Suan Suandha Rajabhat University
Peng Liu: Oxibridge College, Kunming University of Science and Technology

A chapter in Proceedings of the 2025 Seminar on Modern Property Management Talent Training Enabling New Productive Forces (MPMTT 2025), 2025, pp 133-139 from Springer

Abstract: Abstract This research investigates the application of modern innovative management models in enhancing the efficiency and quality of urban water management, with a particular focus on the role of information technology in this domain. Through literature review and case analysis, this paper examines the current status of urban water information management, the application of innovative management models, and the challenges faced along with corresponding strategies. The findings reveal that the application of big data, the Internet of Things (IoT), and artificial intelligence (AI) has significantly improved the efficiency and quality of water management. However, data security, technical standards, and talent shortages remain major challenges. In response to these issues, this paper proposes strategies such as improving policies and regulations, strengthening technological innovation, and enhancing talent cultivation. The results of this research hold significant theoretical and practical implications for advancing the modernization of urban water management in China.

Keywords: Urban Water Management; Informationization; Innovative Management Models; Efficiency Improvement; Quality Control (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-778-6_17

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DOI: 10.2991/978-94-6463-778-6_17

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