Transforming urban spaces for 15-min city implementation: a two-stage SEM-ANN approach to enhancing quality of life

• Published in: Discover Computing Vol. 28; no. 1; pp. 137 - 16
• Main Authors: Agrawal, Swati, Jadon, Sanjay Singh
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 03.07.2025; Springer Nature B.V; Springer
• Subjects: 15-Min city framework; Artificial neural networks; Cities; Computer Science; Data Mining and Knowledge Discovery; Data Structures and Information Theory; Hypotheses; Information Storage and Retrieval; Infrastructure; Land use; Literature reviews; Modelling; Natural Language Processing (NLP); Neighborhoods; Outdoor air quality; Pattern Recognition; Quality of life; Recreation; Socioeconomic factors; Socioeconomic status; Spatial accessibility to amenities; Sustainability; Urban areas; Urban environments; Urban planning; Urban spatial restructuring; Well being; India; 15-Min city framework; Spatial accessibility to amenities; Socioeconomic status; Urban spatial restructuring; Quality of life
• ISSN: 2948-2992; 1386-4564; 2948-2992; 1573-7659
• DOI: 10.1007/s10791-025-09620-3

This study employs a two-staged structural equation modeling-artificial neural network (SEM-ANN) approach to examine the necessity of urban spatial restructuring (USR) for implementing the 15-Min City (15MC) framework and its impact on quality of life (QoL) in Gwalior, a Tier Two Indian city. Data collected from 457 respondents reveals that USR significantly enhances the implementation of the 15MC framework and QoL. The results highlight that spatial accessibility to amenities (SAA) mediates these relationships, underscoring the importance of proximity to essential services in improving urban living standards. Socioeconomic status (SS) moderates these relationships, with higher SS amplifying the positive impacts of USR and 15MC on QoL. The study demonstrates the utility of combining linear and non-linear modeling techniques to provide a comprehensive understanding of factors influencing QoL in urban areas. By identifying key drivers of livable urban environments, this research contributes to evidence-based decision-making for sustainable urban development.