Preference Gaps Between Developers and Millennials in Landed Housing in Yogyakarta Urban Agglomeration
DOI:
https://doi.org/10.12928/jampe.v5i1.12998Keywords:
Affordability gap, Developer decision making , Millennial housing preferences , Urban agglomeration, Yogyakarta housing marketAbstract
The increasing urbanization in Yogyakarta Urban Agglomeration has
driven rapid residential development, especially in landed housing. This
study analyzes the gap between property developers' preferences and
millennial consumers' expectations in housing provision. Utilizing
mixed methods, primary data were collected from 54 property
practitioners through structured questionnaires and in-depth
interviews. Quantitative analysis included Exploratory Factor Analysis
(EFA), Pearson Correlation, and K-Means Clustering to identify
dominant developer preferences. Qualitative phenomenological
analysis confirmed market trends and millennial preferences. The
findings reveal that developers prioritize factors such as land position,
house type, and land shape, while millennial consumers emphasize
affordability, accessibility, and neighborhood comfort. A comparative
analysis using Principal Component Analysis (PCA) and independent t
tests revealed significant preference misalignments, particularly in
access to main roads and environmental quality. The study highlights
the necessity for coordinated policy intervention and developer
adaptation to align housing supply with millennial demands, proposing
the integration of public facility proximity and price affordability into
future residential planning strategies. This research contributes by
highlighting the mismatch in housing value perceptions between
stakeholders and consumers. Practically, these insights provide
policymakers and developers with a framework for designing housing
policies and projects that better integrate affordability, accessibility, and
livability, ensuring that they meet the housing needs of millennials.
References
Abidoye, R. B., Puspitasari, G., Sunindijo, R., & Adabre, M. (2021). Young adults and homeownership in Jakarta, Indonesia. International Journal of Housing Markets and Analysis, 14(2), 333–350. https://doi.org/10.1108/IJHMA-03-2020-0030
Adachi, K. (2016). Exploratory factor analysis in Matrix-based introduction to multivariate data analysis. Springer, Singapore. https://doi.org/10.1007/978-981-10-2341-5_12
Alasmari, F. (2025). Affordability, Preferences, and Barriers to Multifamily Housing for Young Families in Riyadh, Saudi Arabia. Buildings, 16(1), 167. https://doi.org/10.3390/buildings16010167
Bourassa, S. C., & Hoesli, M. (2022). Hedonic, residual, and matching methods for residential land valuation. Journal of Housing Economics, 58, 101870. https://doi.org/10.1016/j.jhe.2022.101870
Carozzi, F., Hilber, C. A. L., & Yu, X. (2024). On the economic impacts of mortgage credit expansion policies: Evidence from Help to Buy. Journal of Urban Economics, 139. https://doi.org/10.1016/j.jue.2023.103611
Carmona, M., Gabrieli, T., & Bento, J. (2023). Bridging the design / finance divide: adding ‘design strings’ to the finance of urban development. Journal of Urban Design, 28(6), 597–622. https://doi.org/10.1080/13574809.2023.2206549
Choi, J., Kee, D., Lee, J., & Kim, J. J. (2023). Understanding heterogeneous consumer preferences for residential zero-energy buildings (ZEBs) in South Korea: A latent class approach. Sustainable Cities and Society, 97, 104747. https://doi.org/10.1016/j.scs.2023.104747
Diaz-Serrano, L. (2009). Disentangling the housing satisfaction puzzle: Does homeownership really matter? Journal of Economic Psychology, 30(5), 745–755. https://doi.org/10.1016/j.joep.2009.06.006
Finch, W. H. (2013). Exploratory factor analysis. In T. Teo (Ed.), Handbook of quantitative methods for educational research. SensePublishers, Rotterdam. https://doi.org/10.1007/978-94-6209-404-8_8
Gamal, A., Alsoufi, M. S. & Hamid, S. A. (2023). Housing preferences shifting under the COVID-19 pandemic: A case study of Cairo, Egypt. Journal of Urban Management, 12(3), 268-283. https://doi.org/10.1016/j.jum.2023.05.002
Grimes, A., Smith, C., O’Sullivan, K., Howden-Chapman, P., Gros, L. L., & Dohig, R. K. (2024). Housing tenure and subjective wellbeing: The importance of public housing. Applied Research in Quality of Life. https://doi.org/10.1007/s11482-024-10369-y
Hwang, J. H., & Lim, H. (2023). University students’ lifestyle and opinions for university-affiliated public housing: Focusing on auxiliary welfare facilities and residential services. Sustainability, 15(6), 5519. https://doi.org/10.3390/su15065519
Israel, G. D. (1992). Determining sample size. University of Florida Cooperative Extension Service. https://www.tarleton.edu/academicassessment/documents/Sample_Size.pdf
Kauko, T. (2006). Expressions of Housing Consumer Preferences: Proposition for a Research Agenda. Housing, Theory and Society, 23(2), 92–108. https://doi.org/10.1080/14036090600773097
Kim, J. (2024). Aging, housing prices, and young adults’ homeownership. Cities, 149. https://doi.org/10.1016/j.cities.2024.104914
Kim, S., Ryu, S., Kim, Y. S., & Lee, M. H. (2023). How housing welfare policies impact housing cost burdens: An analysis of housing welfare policy efficacy and household characteristics. Habitat International, 140, 1-8. https://doi.org/10.1016/j.habitatint.2023.102923
Lai, L. X., Wong, P. F., & Yong, F. Y. Y. (2023). Investigating the influence of homebuyers’ sociodemographic factors on preferences of sustainable affordable housing. International Journal of Strategic Property Management, 27(4), 261-274. https://doi.org/10.3846/ijspm.2023.20200
Lee, P. H., Han, Q., de Vries, B., & Juan, Y. K. (2024). Heterogeneities in willingness to pay for circular affordable housing: insight from young users. Housing Studies, 40(11), 450-2480. https://doi.org/10.1080/02673037.2024.2404063
Li, S., & Wong, S. K. (2024). Information asymmetry in the housing market: Evidence from Hong Kong. Journal of Real Estate Finance and Economics, 68, 138-159. https://doi.org/10.1007/s11146-023-09939-y
Marshall, M., & Zhang, M. L. (2025). Evaluating the effect of grant on affordable housing supply in England using a quasi-experiment. International Journal of Housing Policy, 1-24. https://doi.org/10.1080/19491247.2025.2482212
Marwal, A., & Silva, E. A. (2023). City affordability and residential location choice: A demonstration using agent based model. Habitat International, 136, 102816 https://doi.org/10.1016/j.habitatint.2023.102816
Matějková, J., & Tichá, A. (2025). Housing Market Trends and Affordability in Central Europe: Insights from the Czech Republic, Slovakia, Austria, and Poland. Buildings, 15(10), 1729. https://doi.org/10.3390/buildings15101729
Mohd Aini, A., Adediran, A. O., & Seng, Y. R. C. (2025;), "The influence of buyers’ aesthetic preferences for building facade colors on the pricing of high-rise residential properties: a hedonic pricing model analysis". International Journal of Housing Markets and Analysis,. 02. https://doi.org/10.1108/IJHMA-02-2025-0032
Mulliner, E. & Algrans, M. (2018). Preferences for housing attributes in Saudi Arabia: A comparison between consumers' and property practitioners' views. Cities, 83, 152-164. https://doi.org/10.1016/j.cities.2018.06.018.
Oluleye, I. B., Oyetunji, A. K., Ogunleye, B. M., & Olukolajo, M. A. (2021). Real estate developers insight on the critical barriers to sustainable housing delivery. Real Estate Management and Valuation, 29(2), 84-96. https://doi.org/10.2478/remav-2021-0015
Poku-Boansi, M., Tetteh, N., & Adarkwa, K. K. (2023). Preferences for rental housing in urban Ghana: A discrete choice experiment. Habitat International, 138, 02853. https://doi.org/10.1016/j.habitatint.2023.102853
Pratama, R. A., & Idajati, H. (2022). Housing attribute preferences in Bandung City: A comparison between Generation X, Y, Z. DimensiArsitektur, 50(2), 113–124. https://doi.org/10.9744/dimensi.51.1.8-16
Prativi, F., Yuniarti, N. A., & Kamara, I. S. (2024). Millennial generation (Gen-Y) preferences towards landed house ownership in Yogyakarta urban agglomeration using logistic regression. Journal of Asset Management and Public Economy, 3(1), 31–43. https://doi.org/10.12928/jampe.v3i1.9078
Rahadi, R. A., Wiryono, S. K., Koesrindartoto, D. P., & Syamwil, I. R. (2015). Attributes influencing housing product value and price in the Jakarta Metropolitan Region. International Journal of Housing Markets and Analysis, 8(2), 169–188. https://doi.org/10.1108/IJHMA-05-2014-0013
Rey-Blanco, D., Zofío, J. L., & González-Arias, J. (2024). Improving hedonic housing price models by integrating optimal accessibility indices into regression and random forest analyses. Expert Systems with Applications, 235, 121059. https://doi.org/10.1016/j.eswa.2023.121059
Schultheiss, M. E., Pattaroni, L., & Kaufmann, V. (2024). Planning urban proximities: An empirical analysis of how residential preferences conflict with the urban morphologies and residential practices. Cities, 152, 105215. https://doi.org/10.1016/j.cities.2024.105215
Sebastián, J. J., & Severino, M. J. S. (2025). Real Estate Owners’ Early Thoughts on Lean IPD Implementation in Spain. Buildings, 15(4), 626. https://doi.org/10.3390/buildings15040626
Shafaay, M., Alqahtani, F. K., Alsharef, A., & Chen, G. (2025). Modeling construction cost overrun risks at the FEED stage for mining projects using PLS-SEM. Journal of Asian Architecture and Building Engineering, 1-17. https://doi.org/10.1080/13467581.2025.2481242
Soltani, A., Pettit, C. J., Heydari, M., & Aghaei, F. (2021). Housing price variations using spatio-temporal data mining techniques. Journal of Housing and the Built Environment, 36(3), 1199-1227. https://doi.org/10.1007/s10901-020-09811-y
Subagyo, A., Syari’udin, A., & Yunani, A. (2023). Determinant residential real estate of millennial generation in adapting housing microfinance case Indonesia chapter. International Journal of Housing Markets and Analysis, 16(5), 1007-1020. https://doi.org/10.1108/IJHMA-04-2022-0063
Teklemariam, N., Idowu, O. A., Dickes, L., & Owolabi, A. O. (2025). Land-Use Policy for Affordable Housing Goals: A Case Study of a Rapidly Growing Mid-Sized City in the United States. Land, 14(5), 1108. https://doi.org/10.3390/land14051108
Toșa, C., Sato, H., Miwa, T., & Mitrea, A. (2025). Beyond the bloc(k): unpacking residential choices in the Bucharest-Ilfov metropolitan area. European Planning Studies, 33(12),. https://doi.org/10.1080/09654313.2025.2571440
Tripathi, S., & Mahey, K. (2017). Urbanization and economic growth in Punjab (India): An empirical analysis. Urban Research & Practice, 10(4), 379–402. https://doi.org/10.1080/17535069.2016.1227875
Wan, H., Chowdhury, P. K. R., Yoon, J., Bhaduri, P., Srikrishnan, V., Judi, D., & Daniel, B. (2025). Explaining drivers of housing prices with nonlinear hedonic regressions. Machine Learning with Applications, 21, 100707. https://doi.org/10.1016/j.mlwa.2025.100707
Wang, Y., Zhang, J., Jiao, J., & Li, X. (2025). Residential rental decisions under perceived landscape environments: The role of audio-visual elements. Habitat International, 155, 103250. https://doi.org/10.1016/j.habitatint.2024.103250
World Bank Institute. (2015). Module: City strategy and governance. Retrieved from http://info.worldbank.org/etools/docs/library/166856/UCMP/UCMP/session1-2_strategy_governance.htm
Zamri, N. E. M. M., Yaacob, M. 'A., & Suki, N. M. (2021). Assessing housing preferences of young civil servants in Malaysia: do location, financial capability and neighbourhood really matter?. International Journal of Housing Markets and Analysis, 15(3), 579-591. https://doi.org/10.1108/IJHMA-02-2021-0012
Zhang, Y., & Miller, E. J. (2025). Location choice of residential housing supply: An application of the multiple discrete-continuous extreme value (MDCEV) model. Journal of Choice Modelling, 54, 100535. https://doi.org/10.1016/j.jocm.2024.100535
Zhang, Y., & Miller, E. J. (2024). Analyzing housing supply location choice: a comparative study of the modelling frameworks. Scientific Reports, 14, 1435. https://doi.org/10.1038/s41598-024-51754-9
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Fatima Putri Prativia, Bagaskara, Anisa Nurpita, Nurisqi Amalia, Anas Usman Bello
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
