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Abstract

This study examines the transformative impact of artificial intelligence-enhanced smart eco-city management paradigms on spatial value assessment and housing price formation mechanisms. Through sophisticated mixed-methods analysis of 320 neighborhoods across five urban areas, employing advanced machine learning algorithms for pattern recognition, the research identifies significant synergistic relationships between digital infrastructure and environmental quality that profoundly influence housing valuations. Empirical evidence demonstrates that neighborhoods exhibiting high levels of both digital connectivity and environmental amenities command substantial price premiums of 60-100% above baseline areas, markedly exceeding the combined individual effects of digital (25-45%) and environmental (15-40%) factors alone. The strength of this synergistic relationship manifests in robust correlations between combined Digital-Environmental indices and housing prices (r = 0.83), with AI-driven predictive models achieving exceptional accuracy in forecasting spatial value shifts (R²=0.861). The study contributes a multidimensional analytical framework linking technological innovation, artificial intelligence applications, environmental governance, and housing market dynamics. Policy implications suggest the necessity for integrated governance approaches spanning digital and environmental planning spheres, with particular attention to algorithmic equity considerations given the widening price gaps between digitally-enabled and analog neighborhoods. Effective development of smart eco-cities necessitates the implementation of comprehensive strategies that not only create value through AI optimization but also ensure its equitable distribution across diverse urban communities.

Keywords

Artificial intelligence Digital-ecological integration Smart eco-city governance Spatial economics of housing Value synergy

Article Details

Author Biographies

Ping Li, Universiti Tun Abdul Razak, Wisma Unirazak, 195A, Jln Tun Razak, Hampshire Park, Kuala Lumpur, 50450, Malaysia

Ping Li is currently pursuing her PhD at UNIRAZAK Business School. Her research interests are in real estate markets and macroeconomic policies.

Cheok Mui Yee, Universiti Tun Abdul Razak, Wisma Unirazak, 195A, Jln Tun Razak, Hampshire Park, Kuala Lumpur, 50450, Malaysia

Cheok Mui Yee is currently a teacher at the UNIRAZAK School of Business. Her research interests are in Financial Management; Research Data Analysis; Accounting; Management.

Wanyi He, The National University of Malaysia, Lingkungan Johan, 43600 Bandar Baru Bangi,Selangor, Malaysia；

Wanyi He is PhD candidate in Sociology of Education, Faculty of Education, Universiti Kebangsaan Malaysia. Her research interests are in the areas of students' social well-being, educational tracking and social stratification.

Lijuan Lu, Universiti Tun Abdul Razak, Wisma Unirazak, 195A, Jln Tun Razak, Hampshire Park, Kuala Lumpur, 50450, Malaysia

Lijuan Lu is currently pursuing her master at UNIRAZAK Business School. Research direction: Analyzing the operational efficiency of China's online retail industry

Kaizhou Qin, Universiti Tun Abdul Razak, Wisma Unirazak, 195A, Jln Tun Razak, Hampshire Park, Kuala Lumpur, 50450, Malaysia

Kaizhou Qin is currently pursuing his master at UNIRAZAK Business School.His research interests arethe multi-dimensional impact mechanism of chain store data resources, technical services, and construction investment on management innovation system

How to Cite
Li, P., Mui Yee, C., He, W., Lu, L., & Qin, K. (2025). AI-enhanced spatial value reassessment in digital transformation: impacts of smart eco-city management paradigms on housing price formation mechanisms. Future Technology, 4(3), 239–250. Retrieved from https://fupubco.com/futech/article/view/379
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