Competitività in sostenibilità urbana e territoriale. L’Emilia Romagna, regione d’Europa

The thesis in Urban and Regional Geography titled “URBAN AND TERRITORIAL COMPETITIVENESS IN SUSTAINABILITY. EMILIA-ROMAGNA, REGION OF EUROPE” is divided into two sections. Section one is additionally composed by two chapters (chap. 1 and 2) and deals with theoretical and gnosiological issues. Section two, of two more chapters (chap. 3 and 4), provides practical contributions: these issues give explanatory patterns to interpret the performances of emiliano-romagnoli urban systems. Chapter one is an introductory chapter. It analyzes globalization that involves a larger and larger number of cities, rich or poor. It also considers the so called “digital divide” either as one of the major phenomena of this unhomogeneous development or as an interesting gnosiological and practical challenge of geography. Globalization is now involving all the cities, large or small, but the small ones have higher risks of exclusion: it depends on their more fragile socio-economic, cultural, and environmental urban structure. That’s why European Union (chapter two) promotes policies and endows politics to sustain cities, because urban systems are the basis for the territorial development. So, European, national and local Institutions are firmly interested in promoting urban and local interventions and projects. Section two deals with economic-geography methods, which consists on collecting indicators and the benchmarking methodology. It also specifically analyzes the urban systems of Emilia-Romagna. Consequences of the globalization on the cities are interpreted with a study of their local resources, intended as potentials for their development. The STeMA approach, proposed by Professor Maria Prezioso (University of Roma, “Tor Vergata”) and used by the ESPON (European Spatial Program Observation Network) project, describes the main “determinants” of the territorial and urban development. These are easily comparable to one another (similar or better performing). This approach achieves two goals. On one hand, it is possible to analyze every urban system in its all main characteristics and to preserve its historical and cultural factors. On another hand, each city is “knowable” and “understandable” by all scholars, as it is objectively comparable. So, urban planners can propose specific “multi-level” and “multi-varied” programs of governance. These will face globalization by exalting local empowerment.

Spatial Disparity and Dynamic Trajectory of Convergence in China: Construction and Application of a Composite Index of Regional Development

China is a large country characterized by remarkable growth and distinct regional diversity. Spatial disparity has always been a hot issue since China has been struggling to follow a balanced growth path but still confronting with unprecedented pressures and challenges. To better understand the inequality level benchmarking spatial distributions of Chinese provinces and municipalities and estimate dynamic trajectory of sustainable development in China, I constructed the Composite Index of Regional Development (CIRD) with five sub pillars/dimensions involving Macroeconomic Index (MEI), Science and Innovation Index (SCI), Environmental Sustainability Index (ESI), Human Capital Index (HCI) and Public Facilities Index (PFI), endeavoring to cover various fields of regional socioeconomic development. Ranking reports on the five sub dimensions and aggregated CIRD were provided in order to better measure the developmental degrees of 31 or 30 Chinese provinces and municipalities over 13 years from 1998 to 2010 as the time interval of three “Five-year Plans”. Further empirical applications of this CIRD focused on clustering and convergence estimation, attempting to fill up the gap in quantifying the developmental levels of regional comprehensive socioeconomics and estimating the dynamic convergence trajectory of regional sustainable development in a long run. Four clusters were benchmarked geographically-oriented in the map on the basis of cluster analysis, and club-convergence was observed in the Chinese provinces and municipalities based on stochastic kernel density estimation.