A Fuzzy Cognitive Mapping Approach for Housing Affordability Policy Modeling MARILENA-AURA DIN MARIA MOISE Department of IT, Statistics, and Mathematics Romanian American University of Bucharest 012101 Bucharest ROMANIA din.marilena.aura@profesor.rau.ro , maria.moise@rau.ro Abstract: - Considering the Fuzzy Cognitive Map‟s potential to be used in the policy modeling, this paper applies Fuzzy Cognitive Map (FCM) in the field of housing, in order to help policy maker to decide the best policy in supporting the Housing Affordability. FCMs are capable of participative process, mapping, analysis, modeling and scenarios in terms of significant events or factors, named concepts and their cause-effect relationships. Our approach is based on examining the perceptions of different stakeholders groups on housing affordability policy issues, in order to facilitate the development of a comprehensive housing policy modeling. Within this process, we propose to quantify the subjective perceptions of the different stakeholder groups, using FCM methodology, generally known as suitable tool for livelihood analysis. This paper presents a FCM approach used into FUPOL project (www.fupol.eu) financed by FP7 Program. The FUPOL project proposes a comprehensive new governance model to support the design of complex policies and their implementation, to further advance the research and development in simulation, urban policy process modeling, semantic analysis, visualization and integration of those technologies. Key-Words: - Housing policy modeling, Housing Affordability Policy, Fuzzy Cognitive Map (FCM), subjective perceptions, FUPOL. 1 Introduction 1.1 Housing Affordability Policy Model Research in housing planning ought to address the larger universe of affordable housing provided by actors across multiple sectors [1]. It is well known that local officials in city governments need to develop a comprehensive housing policy to guide their current and future housing–related decisions in the context of a specific community that often face different issues. Access to affordable housing is an essential prerequisite for any community based on humanitarian principles. Johnson [2] estimates structural parameters for math programming-based models for affordable housing design using statistical methods on observations provided by community-based nonprofit housing developers. Affordable Housing Institute believes that housing problems are global, but solutions are local: real change in housing ecosystems must be driven by local actors, according with the community perception. Local people and other stakeholders trust in the FCM scenario analysis process as being participants in the process. In order to identify and design policy directions for affordable housing it is necessary to understand how to relate the outputs generated by the FCM with different goals, such as: -to provide guidance regarding the type, number and location to build across the area -to help clients/households make relocation decisions, housing choice, etc. -to assign production levels for affordable housing and construction technology requirements regarding housing projects development -to optimize social impacts of affordable housing policy (social efficiency and equity measures) -to generate promising forecasting models for use at municipal/regional-level planning models for allocations or subsidized housing across a large study area -to better understand the nature of local housing markets Latest Advances in Information Science, Circuits and Systems ISBN: 978-1-61804-099-2 262