The need for more sustainable cities has become a primary objective of urban strategies. The urgency for a radical transition towards sustainability in a long term-vision has brought with it several new concepts, such as smart urbanism, and models, such as smart city, eco-city, sustainable neighborhood, eco-district, etc. While these terms are fascinating and visionary, they often lack a clear definition both in terms of theoretical insight and empirical evidence. In this light, this contribution aims at defining a conceptual framework through which to further substantiate the blurred concept of eco-district and sustainable neighborhood. It does so by reviewing the concepts of smart urbanism and sustainable neighborhood/eco-districts in the literature, including also references to other well-known sustainability-oriented models of urban development. It then explores whether several indicators, emerging from the analysis of exemplary case studies of sustainable neighborhoods in Europe, can be used to clearly identify the characteristics of a sustainable approach at the district scale. The analysis, built on a review of existing literature, allows for both the clarification of several issues related to these fields of inquiry, as well as for the identification of the potential bridges to link these issues.

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Renewable energy resources and energy-efficient technologies, as well as building retrofitting, are only some of the possible strategies that can achieve more sustainable cities and reduce greenhouse gas emissions. Subsidies and incentives are often provided by governments to increase the number of people adopting these sustainable energy efficiency actions. However, actual sales of green products are currently not as high as would be desired. The present paper applies a hybrid agent-based model (ABM) integrated with a Geographic Information System (GIS) to simulate a complex socio-economic-architectural adaptive system to study the temporal diffusion and the willingness of inhabitants to adopt photovoltaic (PV) systems. The San Salvario neighborhood in Turin (Italy) is used as an exemplary case study for testing consumer behavior associated with this technology, integrating social network theories, opinion formation dynamics and an adaptation of the theory of planned behavior (TPB). Data/characteristics for both buildings and people are explicitly spatialized with the level of detail at the block scale. Particular attention is given to the comparison of the policy mix for supporting decision-makers and policymakers in the definition of the most efficient strategies for achieving a long-term vision of sustainable development. Both variables and outcomes accuracy of the model are validated with historical real-world data.

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