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Communication Dans Un Congrès Année : 2011

Understanding the challenge of housing refurbishment using decision trees

Résumé

Climate change and oil depletion appear to be among the most important challenges for today and future societies. In order to mitigate possible harmful effects, a radical reduction of energy consumption and greenhouse gas emission is necessary in the so-called developed countries. To achieve a low carbon society, the energy system must be reconsidered in all energy consuming sectors and particularly in existing buildings. Unfortunately, if the final objective is known, the road from policy to action is complex and depends on varying processes and factors of success. A large number of actors are involved in the different steps of housing refurbishment projects. Every actor has a role in this chessboard and each of their actions can influence the target objective. Those influences can work as a lever or a barrier with respect to the final objective and impact the efficiency of the actors' strategy. Understanding the actors' strategy and the dynamics of barriers and levers that draw the road to energy efficiency may help to develop best practices and improve their effectiveness. This paper presents the first results of a survey performed on actors of housing refurbishment in France and on social housing occupants in the Loire Department, France. Using a particular decision tree type, called success tree, the way that could lead to the French energy objective in the building sector will be analyzed. Four types of barriers and levers were identified within refurbishment projects (financial, behavioural, technical and political and normative). This approach may help to better understand the project dynamics that will be necessary to take up the challenge of energy efficiency in this sector.
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Dates et versions

emse-00633639 , version 1 (19-10-2011)

Identifiants

  • HAL Id : emse-00633639 , version 1

Citer

Jonathan Villot, Natacha Gondran, Valérie Laforest. Understanding the challenge of housing refurbishment using decision trees. ECEEE 2011 summer study, Jun 2011, Belambra Presqu'île de Giens, France. pp.1125-1132. ⟨emse-00633639⟩
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