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© 2017 Elsevier Ltd The implementation of heating technologies based on renewable resources is an important part of Italy's energy policy. Yet, despite efforts to promote the uptake of such technologies, their diffusion is still limited while heating systems based on fossil fuels are still predominant. Theory suggests that beliefs and attitudes of individual consumers play a crucial role in the diffusion of innovative products. However, empirical studies corroborating such observations are still thin on the ground. We use a Choice Experiment and a Latent Class-Random Parameter model to analyze preferences of households in the Veneto region (North-East Italy) for key features of ambient heating systems. We evaluate the coherence of the underlying preference structure using as criteria psychological constructs from the Theory of Diffusion of Innovation by Rogers. Our results broadly support this theory by providing evidence of segmentation of the population consistent with the individuals’ propensity to adopt innovations. We found that preferences for heating systems and respondents’ willingness to pay for their key features vary across segments. These results enabled us to generate maps that show how willingness to pay estimates vary across the region and can guide local policy design aimed at stimulating adoption of sustainable solutions.

The project is located in the Binnengasthuis area In Amsterdam. This part of the city of Amsterdam houses a mixture of buildings and architecture styles, a rarity where many famous Amsterdam architects have contributed to. The spatial structure of this part of Amsterdam is unique, the location is the result of a layered construction in which the buildings have been fitted in combination with green structures ( courtyards, streets and squares ). The project is a renovation of 80s social housing building in the heart of the binnengasthuis area. With my design I wanted to create programmatic social diversity that could be also reflected in the architectural image through a variety of forms, materials and facade elements in a social housing block of the 1980s which is lacking of these qualities., Heritage & Architecture, Architecture, Architecture and The Built Environment

© 2016 by the authors. The estimation and policy use of spatially explicit discrete choice models has yet to receive serious attention from practitioners. In this study we aim to analyze how geographical variables influence individuals' sensitivity to key features of heating systems, namely investment cost and CO2 emissions. This is of particular policy interest as heating systems are strongly connected to two major current environmental issues: emissions of pollutants and increased use of renewable resources. We estimate a mixed logit model (MXL) to spatially characterize preference heterogeneity in the mountainous North East of Italy. Our results show that geographical variables are significant sources of variation of individual's sensitivity to the investigated attributes of the system. We generate maps to show how the willingness to pay to avoid CO2 emissions varies across the region and to validate our estimates ex-post. We discuss why this could be a promising approach to inform applied policy decisions.