Growth of urban areas and abandonment of rural areas are phenomena that increase quickly. The main consequences of urbanization are pollution, consumption of resources and energy, waste dumps, and junk yards. These aspects require a better planning and design of European urban metropolitan areas, considering benefits, opportunities, costs and risks (B.O.C.R.), derivable by urban transformations and available resources. The paper consists of five parts. The first part contains some reflections on consequences of urban sprawl. In the second part, some possible kinds of cities are discussed (sustainable city, smart city, and compact city). The third part briefly describes a multicriteria decision-making approach known as the ‘analytic hierarchy process’ to deal with complex decisions. In the fourth part, alternative city models are analyzed (compact city, elevated city, green house city, and water city). Finally, in the fifth part, the criteria selected for the planning and design of the alternative city models are used for the prioritization of some European cities.

The COVID-19 (also called “SARS‑CoV‑2”) pandemic is causing a dramatic reduction in consumption, with a further drop in prices and a decrease in workers’ per capita income. To this will be added an increase in unemployment, which will further depress consumption. The real estate market, as for other productive and commercial sectors, in the short and mid-run, will not tend to move independently from the context of the aforementioned economic variables. The effect of pandemics or health emergencies on housing markets is an unexplored topic in international literature. For this reason, firstly, the few specific studies found are reported and, by analogy, studies on the effects of terrorism attacks and natural disasters on real estate prices are examined too. Subsequently, beginning from the real estate dynamics and economic indicators of the Campania region before the COVID-19 emergency, the current COVID-19 scenario is defined (focusing on unemployment, personal and household income, real estate judicial execution, real estate dynamics). Finally, a real estate pricing model is developed, evaluating the short and mid-run COVID-19 effects on housing prices. To predict possible changes in the mid-run of real estate judicial execution and real estate dynamics, the economic model of Lotka–Volterra (also known as the “prey–predator” model) was applied. Results of the model indicate a housing prices drop of 4.16% in the short-run and 6.49% in the mid-run (late 2020–early 2021).

This paper proposes a theoretical model of evaluation of environmental externalities based on the analysis of real estate prices. This issue is included in regional planning policies which include activities and interventions that produce economic and non-economic effects. The monetary assessment of economic and non-economic effects can be expressed as a forecast (ex ante) and/or following (ex post) such activities and interventions. The assessment of the economic impact, with particular reference to interventions and infrastructure work, is widely based on procedures which make use of market prices. The proposed model was applied to an actual case, considering the effects of noise pollution, produced by traffic from the Naples Beltway, on residential property.

The main aim of this paper is the interpretation of the existing relationship between real estate rental prices and geographical location of housing units in a central urban area of Naples (Santa Lucia and Riviera of Chiaia neighborhoods). Genetic algorithms (GA) are used for this purpose. Also, to verify the reliability of genetic algorithms for real estate appraisals and, at the same time, to show the forecasting potentialities of these techniques in the analysis of housing markets, a multiple regression analysis (MRA) was applied comparing results of GA and MRA.

The evaluation of real estate assets is currently one of the main focal points addressed by territorial marketing strategies, with the view of developing high-performing or competitive cities. Given the complexity of the driving forces that determine the behavior of actors in a real estate market, it is necessary to identify a priori the factors that determine the competitive capacity of a city, to attract investments. The decision support system allows taking into account the key factors that determine the “attractiveness” of real estate investments in competitive urban contexts. This study proposes an integrated complex evaluation model that is able to map out and encapsulate the multidimensional spectrum of factors that shape the attractiveness of alternative real estate options. The conceptual–methodological approach is illustrated by an application of the model to a real-world case study of investment choice in the residential sector of Naples.

This study concerns the determination of empirical evidence of a real estate market premium for Green Buildings and of an aware role of the private real estate market as driver to foster-up urban and architectural sustainability and energy efficiency. In real estate markets, there is growing relevance of Green Buildings, especially in cities where the greater part of residential buildings is built before the first regulations on energy performance. Through policies oriented towards sustainable practices, a twofold goal can be achieved: energy consumption mitigation respecting the historical value for existing buildings, direct economic impacts on real estate values. In some metropolitan or urban contexts, the “green premium” for buildings can be understood as a real “gold premium”. This result has been highlighted and quantified with a real estate market analysis developed for a central area of an Italian mid-size city, pursued through the innovative tool of Evolutionary Polynomial Regression (EPR). The study highlighted a higher sale price for properties characterized by the best ecological characteristics and energy efficiency (+41.52%).