Evaluating the Impact of Smart City Composite Index on Economic Performance Across Provincial Areas

Abstract

Urban management plays an important role in the transformation towards smart cities by improving resource efficiency and enhancing economic performance. This study examines the nonlinear relationship between smart city development and economic performance across 31 provinces of Iran by constructing a comprehensive smart city composite index (SCI) based on nine dimensions of the IESE Cities in Motion framework, addressing a key gap in the regional smart city literature. Methodologically, the study combines a Hicks-neutral technological progress framework with Hansen's log-threshold regression model to investigate how the impact of smart city development varies across different levels of urban ‘smartness,’ using cross-sectional spatial data. The empirical results reveal clear spatial disparities in smart city development. Tehran, Khorasan Razavi and Fars rank highest in terms of smartness, while Lorestan, Semnan and Kohgiluyeh and Boyer-Ahmad are positioned at the lower end of the distribution. The findings further show that the impact of the smart city index on economic performance is contingent on a threshold value of 0.0128. Below this threshold, a 1% increase in the SCI corresponds to a 0.496% higher GDP per capita. Above the threshold, the marginal effect declines, with a 1% increase in SCI associated with a 0.244% higher output. Overall, the results provide strong evidence of diminishing returns to smart infrastructure investment. While early stages of smart city development are associated with stronger relative economic performance in less-developed provinces, more advanced regions tend to experience saturation effects. These findings suggest that targeted investment in smart city infrastructure in lagging regions can yield higher marginal returns and contribute to reducing spatial inequality and promoting balanced regional development.