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Identifying Rental Stress Zones in Lisbon: A Spatial Rental Stress Index for Housing Affordability
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| 1.89 MB | Adobe PDF |
Orientador(es)
Resumo(s)
This study addresses the growing housing affordability crisis in Lisbon, where existing approaches to measuring rental stress often based on simple income-to-rent ratios, fail to reflect the influence of tourism pressure, urban amenities, and socio-spatial inequalities, limiting their usefulness for urban planning and policy-making. By developing a spatially explicit Rental Stress Index (RSI), this research seeks to provide a more comprehensive measure of rental market pressure. t In recent years, rising housing prices driven by tourism, real estate investment, and increased demand have widened the gap between rental costs and household income, intensifying intra-urban inequalities. To overcome the limitations of traditional affordability measures, this research adopts a Design Science Research Methodology (DSRM) to create a composite index integrating socioeconomic, housing, and spatial indicators. The RSI is computed at the parish level using multiple open data sources, including census data, rental prices, and geospatial data on short-term rentals and urban amenities. The results reveal a clear center–periphery pattern, with higher rental stress concentrated in central parishes, where elevated prices, tourism pressure, and urban attractiveness converge. Peripheral areas show comparatively lower stress levels. The findings demonstrate that rental stress is multidimensional, emerging from the interaction between housing market dynamics, socioeconomic vulnerability, and territorial characteristics. An interactive Power BI dashboard was developed to support the visualization and interpretation of results, enabling more informed decision-making. This study contributes a replicable, datadriven framework to support housing policy and promote more equitable urban development.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Business Intelligence
Palavras-chave
Rental Stress Housing Affordability Urban Analytics Composite Indicators Spatial Decision Support Short-Term Rentals