Development and Application of Smart SPIN Model: Measuring the Spectrum, Penetration, Impact and Network of Smart City Industries in South Korea

• Published in: Buildings (Basel) 2022-07, Vol.12 (7), p.973
• Main Authors: Jo, Sungsu, Lee, Sangho
• Format: Article
• Language: English
• Subjects: Analytical methods; Business services; Case studies; Cities; Classification; Cluster analysis; Clustering; Communication; Construction industry; Ecology; Economic impact; Economics; Ecosystems; Factories; impact; industrial ecosystem; Infrastructure; Internet of Things; Mathematical models; network; Network analysis; Parameters; Penetration; Sensors; Smart cities; smart city industry; spectrum; Value chain
• ISSN: 2075-5309; 2075-5309
• DOI: 10.3390/buildings12070973

The research agenda on smart cities has increasingly extended not only on perspectives of social–economic relations between technologies and cities but also on the industrial economic ecosystem. The purpose of this study is to focus on an analytical method for the characteristics of a smart city’s ecology and industry. With that thought, we have developed a smart SPIN (Spectrum, Penetration, Impact and Network) model and applied it to analyze the ecology of the Korean smart city industry in general. This model consists of smart spectrum model, smart penetration model, smart impact path model and smart network clustering model. The smart SPIN model shows great potential as an analytical method for the smart city industry ecosystem. As a source of data for analyses from 1960, 1985 and 2015 via input–output table, we revised these data into 25 and 8 industries related to the smart city ecosystem. Additionally, we applied the 2015 GDP deflator. The results of analysis are as follows: First, spectrum, the number of smart industries is increasing. This means that the smart city industry scope and area are expanding. Second, analysis of the smart penetration model and smart ecological industry can be applied into other industries. In other words, traditional industries can crossover and utilize smart technology. Third, with the results of our analysis of the smart impact path model, production paths are increasing while parameter paths did not show a triple parameter path. This means the value chain of the smart city industry is highly divested, but the structure of the industry is weakening. Fourth, smart network analysis shows important clusters to be centered on traditional industries: the clusters do not appear in smart industry centers. This means the impact of the smart city is not strong. Our analysis shows that, today, the Korean industrial ecosystem of smart cities is interacting with existing industries and raising it to a more intelligent and smarter level. Thus, there is a need for this kind of analysis study in order to find optimized smart city industry ecosystem.