Classifying Smart City Startups: The Smart City Index - Maaike Hermse; Imke Nijland; Martina Picari; Mark Sanders (Utrecht University, Utrecht University School of Economics (U.S.E.), 2021)
In this paper we present an index for coding new ventures, projects and firms as "smart-city" or not. The index is based on a systematic assessment of some 70+ definitions of the concept from the literature. Based on this analysis, we propose a 7-item coding scheme based on venture descriptions that are commonly available from public data sources. We identified two necessary and 5 "intensity" items and propose an algorithm that translates these items into a single smartc-city index (SCI) that expresses the degree to which an activity is contributing to smart city development in a score between 1 and 5. We then show the results of coding 759 new ventures in different datasets to illustrate that our index gives sensible results. Some 90 (11%) of these ventures could be classified as "smart city" in our sample, scoring an average of about 3.3, with significant variation around these averages that make intuitive sense. Our index can be used in a broad range of applications.
Keywords: 330; Urban Development; Smart City; Entrepreneurship; Innovation; DataCollection