Merging economic development with clusters theory and environmental sustainability

The aim of the present study was to investigate the linkages between local economic development, economic clusters, and environmental sustainability inside urban areas. Can the interaction of these three phenomena affect the improvement of the quality of life inside urban areas? This research question comes from the consideration that usually these three phenomena are considered sources of conflict in shaping the livability of urban areas. The objective was to design an index - the “SustaIn-Led” - to capture and connect levels of environmental sustainability, quality of life, and economic development together with the competitiveness of the innovation processes, activated by the knowledge economy, and social balance, triggered by the redistribution of the competitive advantages. The study takes into consideration the 53 largest U.S. metropolitan areas with a population over 1 million with a time series from the years 2000 through 2015. The first part of the present study has carried out the identification of the variables to represent and significantly explain the phenomena – local economic development, innovation, and environmental sustainability – linked to the design of the SustaIn-LED index. The structure of the thesis is articulated in two parts, divided into chapters accordingly. The first part was the deepening of the three aforementioned phenomena. This constitutes the rational analytical framework of the model with the choice of the variables/indicators as the information base. Particularly, innovation is explicated by means of the Cluster theory of Porter, as an expression of the modern economy aimed at the use and production of innovation. The environmental sustainability topic in urban areas is explained by means of the Air Quality Index (AQI), while local economic development is represented synthetically by means of the number of workers. In order to support the definition of a solid theoretical framework of the variables/indicators, several studies from literature have been reviewed to influence the choice of the panel data utilized to define the SustaIn-LED index. The second part was the development of the SustaIn-LED model, by means of the correlation testing between the number of workers, used as an indicator for economic development, and two explanatory variables, namely, the air quality, taken as an environmental sustainability indicator, and the number of patents, utilized as an indicator for innovation. Correlation and multiple regression analyses were conducted in order to examine the relationship between the three indicators. The multiple regressions for the year 2015 produced a low p-value, indicating that the predictors are significant in the regression analysis. Similar results of p-value are shown in all the years from 2000 to 2013, so for every year, changes in the number of patents and air quality are related to changes in the number of workers. For 2015 data, the results showed that part of the variance in the measure of total workers of the metropolitan areas could be predicted by measures of innovation and air quality. Higher R² values have been registered for the years from 2000 through 2013. The SustaIn-LED index is composed of six quantitative indicators. Such indicators have been divided into six thematic categories: sustainable transportation, pollution, economic development, innovation, social inclusion, and renting price in relation to median income. The SustaIn-LED index could be utilized in the urban regeneration processes to define the design parameters in the framework of compensation-equalization processes in urban planning and to support innovation policies activated with Smart Specialization Strategies by means of a better comprehension of environmental implications. The Air Quality Index represents the first limitation, since it shows a certain correlation with the number of workers, but it does not perfectly match the hypothesis, since it says the more polluted a metropolitan area is, the more workers. This is a logical consequence of the pollution in urban areas, since today too many people still utilize their own automobile for commuting to work every day. Conversely, in the SustaIn-LED model, I hypothesized an effect of environmental sustainability policies on the economic development of the urban area. Therefore, a negative correlation between the AQI and the number of workers in a determined metropolitan area has been traced (remembering that the higher the AQI, the more polluted the area). The choice of a better indicator representing environmental sustainability, such as the Green City Index, could improve the model with a higher correlation with the number of jobs and the number of patents.