National Models of Smart City Development: A Multivariate Perspective on Urban Innovation and Sustainability

Enrico Ivaldi (), Tiziano Pavanini, Tommaso Filì and Enrico Musso
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Enrico Ivaldi: Department of Humanistic Studies, Faculty of Communication, IULM University, 20143 Milan, Italy
Tiziano Pavanini: Department of Architecture and Urbanism (DAStU), Politecnico di Milano, 20133 Milan, Italy
Tommaso Filì: Italian Centre of Excellence in Logistics, Transport and Infrastructures, University of Genoa, 16126 Genoa, Italy
Enrico Musso: Italian Centre of Excellence in Logistics, Transport and Infrastructures, University of Genoa, 16126 Genoa, Italy

Sustainability, 2025, vol. 17, issue 16, 1-16

Abstract: This study examines the extent to which smart cities are expressions of nationally homogeneous development trends by way of an analysis of their structural characteristics from a multivariate viewpoint. Drawing on data from the International Institute for Management Development IMD Smart City Index 2024, we find a sample of 102 cities across the world clustering along six key dimensions of smartness: mobility, environment, government, economy, people, and living. The aim is to examine if cities within a country have similar profiles and, if so, to what degree such similarity translates to other macro-level institutional, political, and cultural conditions. Our results verify a tight correspondence between city profiles and national contexts, implying that macro-level governance arrangements, policy coordination, and institutional capacity are pivotal in influencing local smart city development. Planned centralised countries possess more uniform city characteristics, while decentralised nations possess more variant urban policies. This study contributes to international debate regarding smart cities by empirically identifying national directions of urban innovation. It offers pragmatic inputs for policymakers that aim to align local efforts with overall sustainable development agendas. Moreover, this study introduces a novel application of Linear Discriminant Analysis (LDA) to classify smart city profiles based on national models. While the analysis yields high classification accuracy, it is important to note that the sample is skewed toward cities from the Global North, potentially limiting the generalisability of the results.

Keywords: smart cities; national urban models; urban innovation; multivariate analysis; urban governance models; sustainable development (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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