Speaker
Description
In metropolitan areas with large populations, university students suffer from spatial inequalities due to inadequate housing supply and uneven distribution of housing environment elements, leading to stress, instability, and insecurity (Sotomayor et al., 2022; Fang and van Liempt, 2021). Since students are a vulnerable group with limited housing choices, an over-reliance on market distribution fails to address student housing inadequacies and inequalities (Pillai et al., 2024). Decision-makers should investigate the factors shaping students' housing preferences and implement supportive policies to address the housing needs of students. However, existing research predominantly adopts a top-down perspective, analyzing the student housing distribution as an outcome of policies and emphasizing the impact of existing environments on housing choices (Poku-Boansi et al., 2023). Few studies explore the mechanisms underlying the deviation between students’ housing preferences and actual choices, limiting the potential of policies to mitigate spatial and systemic constraints on housing equality for students.
Our research addresses this gap by analyzing the correlation between students' housing preferences and choices from a humanistic perspective, exploring the influential mechanism of economic, social, and physical factors in students' housing decisions and the discrepancies between their subjective values and actual solutions. This analysis provides insights into the underlying causes of spatial inequality of housing distribution among students. Based on these insights, we propose targeted housing distribution strategies that align with students' needs, considering the existing urban environment across different districts to promote equitable allocation of urban transportation, services, and communities.
The study focuses on Berlin, a metropolis with severe student housing shortages. Through semi-structured interviews, university students were asked to rate the importance of five key factors—rent price, transportation convenience, room type, service density, and community safety—contributing to their ideal housing. These preference data were used for clustering analysis, dividing the respondents into groups with distinct housing preferences and spatial distribution patterns. Furthermore, the economic, social, and physical environment indicators corresponding to these five factors were measured and examined for their correlation with students' subjective preferences, using postal code areas as the unit of analysis. This approach reveals the alignment or deviation between students' housing preferences and the actual environment of their selected housing, forming the basis for proposing housing distribution strategies that account for the preferences of this vulnerable group in metropolitan areas.
The results demonstrate that students are distinctly categorized into three groups based on their housing preferences. Groups 1 and 3 prioritize rent price, with the former placing transportation convenience as the second priority, while the latter considers service density equally important. In contrast, Group 2, which prioritizes room type, places less emphasis on low rent. A comparison between preference scores and actual housing environments reveals a high degree of alignment regarding transportation factors. Students who prioritize transportation convenience tend to select housing within a 30-minute commute from their university, whereas the other two groups do not. Conversely, preferences for service density do not exhibit a strong positive correlation with the actual distribution of chosen housing, reflecting the uncertainty of service density as a guiding factor in students' housing decisions.
These findings reveal the group differences in housing preferences among students, from which we unveil the varying degrees of influence exerted by environmental factors on their subjective values and actual decisions on housing. These influencing mechanism investigations in our research not only assist governments and planning departments in optimizing student housing distribution, but also provide more targeted references for urban renewal and land use policy development from a humanistic perspective. This contributes to more effectively addressing the actual needs of the student population at the policy level and mitigating housing inequality.
References
Fang, C., van Liempt, I. (2021) “We prefer our Dutch”: International students’ housing experiences in the Netherlands. Housing Studies, 36, 822–842.
Pillai, A.K., Vieta, M.A., Sotomayor, L. (2024) University Student Housing as Business Proposition and Entrepreneurial Activity: The Canadian Case. Housing Policy Debate, 34, 644–667.
Poku-Boansi, M., Tetteh, N., Adarkwa, K.K. (2023) Preferences for rental housing in urban Ghana: A discrete choice experiment. Habitat International, 138, 102853.
Sotomayor, L., Tarhan, D., Vieta, M., McCartney, S., Mas, A. (2022) When students are house-poor: Urban universities, student marginality, and the hidden curriculum of student housing. Cities, 124, 103572.
| Keywords | Student housing; Housing preference; Housing environment; Spatial inequality; Data-driven planning |
|---|---|
| Best Congress Paper Award | Yes |
