Nowadays, many public administrations have abandoned and underused heritage buildings due to a lack of public resources, although the effective contribution of cultural heritage as a driver and enabler of sustainable development is strongly recognized. Currently, investments in cultural heritage have multidimensional impacts (social, economic, historical, and cultural) and can contribute to increasing overall local productivity; improving the wellbeing of inhabitants; and attracting funding from the public, private, and private–social sectors. Lack of public resources has pushed local administrations to favor new forms of valorization of public property that can promote the “adaptive reuse” of historic buildings in order to preserve their social, historical, and cultural values. At the same time, administrations seek to stimulate the experimentation of new circular business, financing, and governance models in heritage conservation, creating synergies between multiple actors; reducing the use of resources; and regenerating values, knowledge, and capital. The objective of this paper is to propose an integrated evaluation model, based on multicriteria analysis, and a financial model to support the choice of an alternative reuse of an ancient monastery in the municipality of Mugnano in the Campania region in order to define a “shared strategy” based on a “bottom-up” approach. This starts from the needs of the local community but does not neglect the historical and cultural values of the heritage building, as well as the economic and financial feasibility. The positive results obtained show that the model proposed can be a useful decision support tool in environments characterized by high complexity such as cultural heritage sites, where the objective is to precisely highlight the elements that influence the dynamics of choice for building shared bottom-up development strategies.

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.

Contingency management, in particular the management of unanticipated events outside the control of an ordinary planning system, has in the last 50 years become an important and f'requently debated issue in the scientifïc literature on complex systems management under risk conditions. The urban system can be regarded as such an open complex system where extemal events, not always foreseeable with a closed system's model, may strongly impact on the intemal dynamics of an urban area. Conventionally, planning the future presupposes collecting information and analyzing it rationally in order to control for unexpected contingency events. But it is an important question in the field of urban planning, how proper strategies can be developed to deal with extemal uncertainty and shocks that transcend the imagination of policy-makers. How should decision-makers respond to such unforeseen jumps in a system? The aim of this paper is to present and apply a new scient$c decision support method based on the future studies literature, with the aim to help decision-makers in the strategie management of uncertainty and risk in order "to anticipate the extraordinary events correctly in order to act more effeively" (Godet, 1987). In particular, we wil1 deploy here the scenario methodology in combination with multicriteria analysis and mzzy set theory, as a useful leaming tool for the govemance of complex dynamic systems. In current debates on policy-makers' possible reactions to uncertainty (e.g., in the context of sustainability strategies), very often the so-called "no-regret" principle is advocated. The validity of this approach is tested, in the context of the present paper, on real-world threats in the Vesuvio volcanic area in the vicinity of the densely populated city of Naples, Italy. Four different policy scenarios wil1 be developed with the purpose to examine, control and reduce the risk for the people concemed in case of a future volcanic eruption and to lay, at the same time, the foundation for a drastic rehabilitation of the entire metropolitan area. PNO 11 FTGC

The need for renewal of disused urban area is widespread in many context of south Italy where the lack of public funds make difficult the management and maintenance of sites that often have considerable historical and architecture values.The choice of functions that can represent elements of attraction for the economic and social regeneration of these disused sites is a complex problem, given the multiplicity of interests involved and the uncertain factor determined by the non-typical conditions of real estate market, both from the demand and the supply side.In the present paper we propose to implement a choice model, based on the integration of multicriteria analysis and random utility model (referred to McFadden theory), able to support a participatory decision process of selecting alternative scenarios of requalification of an urban disused area located in a small village near the city of Naples, in the south of Italy.The positive results obtained show that the model proposed can be a useful decision support tool in environments characterized by high complexity, where the objective is precisely to highlight the elements that influence the dynamics of choice for building shared “bottom up” development strategies.