In response to the pressing need for comprehensive urban development strategies, this study proposes the construction of a Smart Sustainable City Assessment Framework (SSCAF) that integrates cutting-edge methodologies. By leveraging the potential of big data analytics and the Analytic Network Process (ANP), the SSCAF aims to provide a holistic evaluation tool for urban planners and policymakers. Through a systematic approach, this framework incorporates environmental, societal, economic, and technological dimensions, ensuring a well-rounded assessment of smart sustainable cities. Ultimately, the SSCAF holds promise in facilitating the development of resilient, efficient, and livable cities in the face of rapid urbanization and environmental challenges. This integrated framework will provide a holistic perspective on urban development, ensuring that relevant assessment tools are constructed to effectively evaluate progress. Furthermore, the advancement of "Big Data" theory has revolutionized the way city planners interpret and utilize data from various sources. This data-driven approach ensures that the evaluation model is robust and reflective of the complex interplay between environmental, societal, economic, and technological factors in smart sustainable cities. The study will conduct model validation through city evaluations. The Fuzzy Delphi Technique (FDT) will be applied to select key indicators for the smart sustainable city. Additionally, Data Mining and the ANP will be utilized to predict future variance ratios of indicators and determine their weights based on anticipated future scenarios. Finally, an empirical analysis will assess the smart sustainable level of Taipei City and Singapore, aiming to validate the model and propose relevant suggestions.

Authors:
Wann-Ming Wey, National Taipei University, Taiwan

About the Presenter(s)
Dr. Wann-Ming Wey is Professor (Full) and Dean, Department of Real Estate and Built Environment and International College of Sustainability Innovations (ICSI) at National Taipei University, Taiwan.

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