With an increasing number of smart cities initiatives in developed as well as developing nations, smart cities are seen as a catalyst for improving the quality of life for city residents. However, current understanding of the risks that may hamper successful implementation of smart city projects remains limited due to inadequate data, especially in developing nations. The recent Smart Cities Mission launched in India provides a unique opportunity to examine the type of risks, their likelihood, and impacts on smart city project implementation by providing risk description data for area-based (small-scale) development and pan-city (large-scale) development projects in the submitted smart city proposals. We used topic modeling and semantic analysis for risk classification, followed by risk likelihood–impact analysis for priority evaluation, and the keyword co-occurrence network method for risk association analysis. The risk classification results identify eight risk categories for both the area-based and pan-city projects, including (a) Financial, (b) Partnership and Resources, (c) Social, (d) Technology, (e) Scheduling and Execution, (f) Institutional, (g) Environmental, and (h) Political. Further, results show risks identified for area-based and pan-city projects differ in terms of risk priority distribution and co-occurrence associations. As a result, different risk mitigation measures need to be adopted to manage smart city projects across scales. Finally, the paper discusses the similarities and differences in risks found in developed and developing nations, resulting in potential mitigation measures for smart city projects in developing nations.
Small-Scale Public Rental Housing Development Using Modular Construction—Lessons learned from Case Studies in Seoul, Korea
