| Abstract |
While many studies have tried to measure the magnitude of smart cities, they have not highlighted the degree of smartness and the interaction between smartness and the urban economy across all regions in the country. This study highlights them by employing a new 5Ic smart city index (Information, communication, and technology, Innovation, Intelligence, Infrastructure, and Inflow) based on all US Metropolitan Statistical Areas (MSAs) by employing the Seemingly Unrelated Regression (SUR) model. This study finds that New York, NY is the highest smart MSA, followed by Los Angeles, CA and San Francisco, CA. Second, the innovation and inflow indices and the GDP positively interact with each other (innovation -> GDP: 0.006 and GDP -> innovation: 0.018 and inflow -> GDP: 0.031 and GDP -> inflow: 0.028) when other important variables are controlled. Third, the SUR model is a better model than the OLS model since some smart city indices are associated with the GDP. Therefore, governments and urban planners should develop their smart city strategies based on the magnitude of smartness and the interaction between smartness and the urban economy in their regions.HighlightsThis study highlights the degree of smartness by employing a new 5Ic smart city index (Information, communication, and technology, Innovation, Intelligence, Infrastructure, and Inflow).This study employs the Seemingly Unrelated Regression model based on all US Metropolitan Statistical Areas.New York is the highest smart Metropolitan Statistical Area, followed by Los Angeles and San Francisco.The innovation and inflow indices and the Gross Domestic Product positively interact with each other. |