Quantifying the dynamic effects of smart city development enablers using structural equation modeling

In recent years, smart city projects have drawn significant attention as initiatives for enhancing urban development. Many studies have incorporated technical and non-technical enablers to better control the growth of smart cities. However, despite considerable achievements, the direct and indirect effects of smart city enablers on urban performances have not been quantified comprehensively. Thus, due to this lack of in-depth understanding, smart city leaders encounter difficulties in establishing proper development strategies. To address this issue, the present study has used Structural Equation Modeling (SEM) to identify the critical enablers of smart cities and to quantify their dynamic effects (i.e., direct and indirect effects) on the performances of such cities. More specifically, the authors applied SEM to test and estimate the relationships between four enabler clusters (i.e., technological infrastructure, open governance, intelligent community, and innovative economy) and four performance objectives (i.e., efficiency, sustainability, livability, and competitiveness) using the actual data of 50 smart cities. The statistical results demonstrated that non-technical enabler clusters, as well as the technical drivers, have significant impacts on the performances of smart cities with their highly interrelated, synergetic dynamics. Based on those findings, urban leaders can enhance strategic planning for smart city transitions through proper policy management.