[
Aliyev, K., Amiraslanova, M., Bakirova, N., & Eynizada, N. (2019). Determinants of housing prices in Baku: empirical analyses. International Journal of Housing Markets and Analysis, 12(2), 281-297.
]Search in Google Scholar
[
Bourassa, S., Cantoni, E., & Hoesli, M. (2010). Predicting house prices with spatial dependence: a comparison of alternative methods. Journal of Real Estate Research, 32(2), 139-160.
]Search in Google Scholar
[
Choong, W. C. (2018). Statistical Analysis Of Housing Prices In Petaling District Using Linear Functional Model (Doctoral dissertation, UTAR).
]Search in Google Scholar
[
Cuc, L. D., Rad, D., Manațe, D., Szentesi, S. G., Dicu, A., Pantea, M. F., ... & Bâtcă-Dumitru, G. C. (2023). Representations of the Smart Green Concept and the Intention to Implement IoT in Romanian Real Estate Development. Sustainability, 15(10), 7777.
]Search in Google Scholar
[
Ding, X. (2022). Macroeconomic Factors Affecting Housing Prices: Take the United States as an Example. In 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) (pp. 2335-2339). Atlantis Press.
]Search in Google Scholar
[
Ebekozien, A., Abdul-Aziz, A. R., & Jaafar, M. (2019). Housing finance inaccessibility for low-income earners in Malaysia: Factors and solutions. Habitat International, 87, 27-35.
]Search in Google Scholar
[
Hong, T., Koo, C., Kim, D., Lee, M., & Kim, J. (2015). An estimation methodology for the dynamic operational rating of a new residential building using the advanced case-based reasoning and stochastic approaches. Applied Energy, 150, 308-322.
]Search in Google Scholar
[
Hoxha, V., Hoxha, D., & Hoxha, J. (2022). Study of factors influencing apartment prices in Prishtina, Kosovo. International Journal of Housing Markets and Analysis, 15(5), 1242-1258.
]Search in Google Scholar
[
Jafari, A., & Akhavian, R. (2019). Driving forces for the US residential housing price: a predictive analysis. Built Environment Project and Asset Management, 9(4), 515-529.
]Search in Google Scholar
[
Jim, C. Y., & Chen, W. Y. (2006). Impacts of urban environmental elements on residential housing prices in Guangzhou (China). Landscape and urban planning, 78(4), 422-434.
]Search in Google Scholar
[
Kim, J., Lee, Y., Lee, M. H., & Hong, S. Y. (2022). A comparative study of machine learning and spatial interpolation methods for predicting house prices. Sustainability, 14(15), 9056.
]Search in Google Scholar
[
Li, L., & Chu, K. H. (2017). Prediction of real estate price variation based on economic parameters. In 2017 International Conference on Applied System Innovation (ICASI) (pp. 87-90). IEEE.
]Search in Google Scholar
[
Lu, S., Li, Z., Qin, Z., Yang, X., & Goh, R. S. M. (2017). A hybrid regression technique for house prices prediction. In 2017 IEEE international conference on industrial engineering and engineering management (IEEM) (pp. 319-323). IEEE.
]Search in Google Scholar
[
Manate, D., Lile, R., Rad, D., Szentesi, S. G., & Cuc, L. D. (2023). An analysis of the concept of green buildings in Romania in the context of the energy paradigm change in the EU. Transformations in Business & Economics, 22(1).
]Search in Google Scholar
[
Rutskiy, V., García, D. S., Denisova, E., Alina, F., Okashev, N., Devederkin, I., Bystrova, N., Elisseva, E., & Tsarev, R. (2023). Modeling the Well-Being of the Population and Its Factors Using the Well-Being Index. In Computer Science On-line Conference (pp. 605-614). Cham: Springer International Publishing.
]Search in Google Scholar
[
Ryan, S. (1999). Property values and transportation facilities: Finding the transportation-land use connection. Journal of planning literature, 13(4), 412-427.
]Search in Google Scholar
[
Sharma, A., & Poongodi, T. (2023). Prediction of Real-Time Estate Pricing using Train-Test Splitting Techniques. In 2023 4th International Conference on Intelligent Engineering and Management (ICIEM) (pp. 1-6). IEEE.
]Search in Google Scholar
[
Sundrani, D. M. (2018). Factors influencing home-purchase decision of buyers of different types of apartments in India. International Journal of Housing Markets and Analysis, 11(4), 609-631.
]Search in Google Scholar
[
Wang, P. Y., Chen, C. T., Su, J. W., Wang, T. Y., & Huang, S. H. (2021). Deep learning model for house price prediction using heterogeneous data analysis along with joint self-attention mechanism. IEEE Access, 9, 55244-55259.
]Search in Google Scholar
[
Wooldridge, J. M. (2009). Introductory econometrics: A modern approach. Mason, OH: South Western, Cengage Learning. Speziell S. 271-276.
]Search in Google Scholar
[
World Green Building Council (2014). Health, wellbeing & productivity in offices. Retrieved from:https://worldgbc.org/wpcontent/uploads/2022/03/compressed_WorldGBC_Health_Wellbeing__Productivity_Full_Report_Dbl_Med_Res_Feb_2015-1.pdf
]Search in Google Scholar
[
Yazdani, M. (2021). Machine learning, deep learning, and hedonic methods for real estate price prediction. arXiv preprint arXiv:2110.07151.
]Search in Google Scholar