| Title | A Quantitative Model of Innovation Readiness in Urban Mobility: A Comparative Study of Smart Cities in the EU, Eastern Asia, and USA Regions |
|---|---|
| ID_Doc | 43866 |
| Authors | Ayfantopoulou, G; Touloumidis, D; Mallidis, I; Xenou, E |
| Title | A Quantitative Model of Innovation Readiness in Urban Mobility: A Comparative Study of Smart Cities in the EU, Eastern Asia, and USA Regions |
| Year | 2023 |
| Published | Smart Cities, 6, 6 |
| Abstract | The smart cities paradigm has gained significant attention as a tool to address the multifaceted challenges posed by contemporary urban mobility systems. While cities are eager to integrate cutting-edge technologies to evolve into digital and intelligent hubs, they often deal with infrastructure and governance bottlenecks that prevent the rapid adoption of industry-driven innovations. This study introduces a three-step methodological approach to forecast a city's innovation readiness in urban mobility, thus facilitating city-led innovation and identifying key areas within urban mobility systems that require attention. Initially, a comprehensive literature review was undertaken to ascertain the most impactful innovation indicators influencing a city's ability to embrace new technologies. Subsequently, Principal Component Analysis (PCA) was applied to identify these indicators, highlighting the primary markers of innovation for each city. The final step involved the application of both random and fixed-effects regression models to quantify the influence of distinct unobserved variables-such as economic, cultural, and political factors-on the innovation readiness of various cities. The methodology's effectiveness was tested using data from cities across diverse regions. The findings underscore that merely 7 out of 21 innovation indicators are critical for assessing a city's innovation readiness. Moreover, the random-effects model was identified as the most suitable for capturing the nuances of unobserved variables in the studied cities. The innovation readiness scores at the city level revealed a diverse range, with cities like Madrid, Gothenburg, and Mechelen demonstrating high readiness, while others like Kalisz and Datong showed lower scores. This research contributes to the strategic planning for smart cities, offering a robust framework for policymakers to enhance innovation readiness and foster sustainable urban development, with a newfound emphasis on city-specific analysis. |
| https://www.mdpi.com/2624-6511/6/6/148/pdf?version=1701251411 |
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