No abstract

Culture, creativity and circularity are driving forces for the transition of cities towards sustainable development models. This contribution proposes a data-driven quantitative methodology to compute cultural performance indices of cities (C4 Index) and thus compare results derived by subjective and objective assessment methods within the case study of the Metropolitan City of Naples. After data processing with Machine-Learning (ML) algorithms, two methods for weighting the indicators were compared: principal component analysis (PCA) and geographically weighted linear combination (WLC) with budget allocation. The results highlight similar trends among higher performance in seaside cities and lower levels in the inner areas, although some divergences between rankings. The proposed methodology was addressed to fill the research gap in comparing results obtained with different aggregation methods, allowing a choice consistent with the decision-making environment.

Maritime transport technologies and infrastructures development fostering global economies since the second half of the 20th century, conditioning the reshaping of the territorial system in terms of social and spatial organisation, detaching port functions from urban ones and weakening their relationships. The reorganisation of the same activities, often within larger areas of the existing urban structure, has emphasised the so-called misalignment of the City-Port, given by dynamics having benefits at the regional scope and localised negative impacts. The European recommendations provided by both the Sustainable Development Goals (SDGs) framework and the Maritime Spatial Planning European Directive 2014/89, within the theoretical and methodological framework provided by Circular City Model (CCM) approach, define the context to reconsider City-Port dynamics, leading to a regeneration of both the port and the city. To identify sustainable design strategies’ portfolio for Naples City-Port, in Italy, as pivotal action to trigger the regenerative process, the selection of a suitable set of indicators, within a multidimensional and multi-scale decision support system, has been developed. The study is part of the Italian research Project of Relevant National Interest (PRIN, 2015), “Metropolitan cities: territorial economic strategies, financial constraints, and circular regeneration”, coordinated by the Polytechnic of Milan, Italy.

No abstract

No abstract