Rapid urbanization has become a defining feature of global development in the twenty-first century, bringing both economic opportunities and significant governance challenges for cities. In developing countries, accelerated urban growth often places considerable pressure on urban infrastructure, public services, and institutional capacity. Indonesia is currently experiencing a rapid pace of urbanization, which has not always been matched by improvements in urban planning, governance quality, and equitable service delivery. In response, the Indonesian government has promoted the smart city agenda as a policy approach to enhance urban management through digitalization, data-driven governance, and innovation in public service delivery. However, existing smart city practices and studies in Indonesia largely emphasize technological solutions, while the role of smart city initiatives as instruments of urban governance and institutional capacity building remains underexplored. This study addresses this gap by examining smart city development in Indonesia through a comparative perspective with Singapore’s Smart Nation initiative. Singapore represents a contrasting governance model characterized by strong central coordination and high institutional capacity. Using an urban governance and institutional capacity framework, this study analyzes how different governance structures shape the ability of smart city policies to respond to urbanization pressures. The findings suggest that while Indonesia’s decentralized approach enables policy adaptation to local contexts, limitations in coordination and institutional capacity constrain the effectiveness of smart city initiatives. In contrast, Singapore’s centralized and integrated governance framework facilitates more coherent policy implementation and strategic use of digital technologies. The study concludes that strengthening institutional capacity and governance integration is essential for smart city policies to effectively manage urbanization, particularly in developing country contexts.
Copyrights © 2026