Otwarty dostęp

The contribution of statistical models in the field of real estate valuation


Zacytuj

Abodoye B. E., Chan A. C. P., Abidoye A, Oshodi O. S. (2018/2019). Predicting property price index using artificial intelligence techniques. Evidence from Hong Kong. International journal of housing markets and analysis. DOI: 10.1108/IJHMA-11-2018-0095. Open DOISearch in Google Scholar

Abidoye B. R., Chan A. C. P., 2018. Hedonic valuation of reale estate properties in Nigeria. Journal of African Real Estate Research, Vol. 1(1), pp. 1 – 18. DOI: 10.1080/09599916.2017.1286366. Open DOISearch in Google Scholar

Abidoye B. R., Chan A. C. P.. 2016/2017. Modeling property values in Nigeria using artificial neural network. Journal of property research, Vol. 1(1), pp. 122 – 140. DOI: 10.15641/jarer.vlil.452. Open DOISearch in Google Scholar

Abidoye B. R., Chan A. C. P., 2016. Critical determinants of residential property value: professionals’ perspective. Journal of Facilities management, Vol. 14(3), pp. 283 – 300. DOI: 10.1108/JFM-02-2016-0003. Open DOISearch in Google Scholar

Abidoye B. R., Chan A. C. P., 2016. Artificial neural network in property valuation: application framework and research trend. Property Management, Vol. 35(5), pp. 554 – 571. DOI: 10.1108/PM-06-2016-0027. Open DOISearch in Google Scholar

Adair A. S., Berry J. N., McGreal W. S., 1991. Land availability, housing demand and the property market. Journal of property research, Vol. 8(1), pp. 59 - 69. DOI: 10.1080/09599919108724020. Open DOISearch in Google Scholar

Adair A., McGreal, 1988. The application of multiple regression analysis in property valuation. Journal of valuation, Vol. 6 (1), pp. 57 – 67. DOI: 10.1108/eb008002. Open DOISearch in Google Scholar

Adair A. S., Berry J. N., McGreal W. S., 1996. Hedonic modelling, housing submarkets and residential valuation. Journal of property research, Vol. 13, pp. 67 – 83. DOI: 10.1080/095999196368899. Open DOISearch in Google Scholar

Adair A., McGreal S., Smyth A., Cooper J., Ryley T., 2000. House price and accessibility: the testing of relationship within the Belfast urban area. Housing studies, 15(5), pp. 699-716. DOI: 10.1080/02673030050134565. Open DOISearch in Google Scholar

Arribas I., García F., Guijarro F., Oliver J., Tamošiūnirne R., 2016. Mass appraisal of residential real estate using multilevel modeling. International journal of strategic property management, Vol. 20(1), pp. 77-87. DOI: 10.3846/1648715X.2015.1134702. Open DOISearch in Google Scholar

Bao H. X. H., Wan A. T. K., 2004. On the use of Spline Smoothig in estimating hedonic housing price models: empirical evidence using Hong Kong data. Real estate economics, Vol. 32(3), pp. 487 – 507. DOI: 10.1111/j.1080-8620.2004.00100.x. Open DOISearch in Google Scholar

Benjamim J. D., Guttery R.S., Sirmans C.F., 2004. Mass appraisal: An introduction to Multiple Regression Analysis for real estate valuation. Journal of Real Estate Practice and Education, Vol. 7, No. 7, pp. 67-77.10.1080/10835547.2004.12091602 Search in Google Scholar

Bahia H. S. I., 2013. A data mininig model by using ANN for predicting real estate market: comparative study. International journal of intelligence science, Vol.3, pp. 162 – 169. DOI: 10.4246/ijis.2013.34017 Open DOISearch in Google Scholar

Borst R. A., 1991. Artificial neural networks. The next modelling/calibration technology for the assessment community. Property Tax Journal, Vol. 10, No.1, pp. 69 – 94. Search in Google Scholar

Božić B., Milićević D., Pejić M, Marošan S., 2013. The use of multiple linear regression in property valuation. Geonaukal, Vol. 1(1), pp. 41 - 45.10.14438/gn.2013.06 Search in Google Scholar

Brunson A. L., Buttimer R. J., Rutherford R. C. (1994), Neural Networks, nonlinear specifications, and industrial property values, University of Texas at Arkington, working paper series No., pp. 94-102. Search in Google Scholar

Calhoun A. C., 2001. Property valuation methods and data in the United States. Housing finance international, Vol. 16(2), pp. 12-23. Search in Google Scholar

Cechin A., Souto A., González A. M., 2000. Real estete value at porto alege city using artificial neural networks. Proceedings. Sixth Brazilian Symposium on Neural Networks, Vol. 1. DOI: 10.1109/SBRN.2000.889745. Open DOISearch in Google Scholar

Chaphalkar N. B., Sandbhor S., 2013. Use of Artificial Intelligence in real property valuation. International journal of engineerin and technology, Vol. 5(3), pp. 2334 – 2337. Search in Google Scholar

Chiarazzo V., Caggiani L., Marinelli M., Ottomanelli M., 2014. A Neural Network based model for real estate price estimation considering environmental quality of property location. Transportation research procedia, Vol. , pp. 810 – 817. DOI: 10.1016/j.trpro.2014.10.067. Open DOISearch in Google Scholar

Cohen J., Cohen P., West G. S., Aiken L.S. Applied multiple regression/correlation analysis for the behavioral sciences, 3rd edition, Mahwah, NJ: Lawrence Erlbaum Associates, 2003. Search in Google Scholar

Curry B., Morgan P., Silver M., 2002. Neural networks and non-liniear statistical methods: an application to the modelling of price-quality relationships. Computers & operations research, vol. 29, pp. 951 – 969. DOI: 10.1016/S0305-0548(00)00096-4. Open DOISearch in Google Scholar

Deaconu A., Diagnosticul și evaluarea întreprinderii. Editura Economică, București, 2019. Search in Google Scholar

Din A., Hoesli M., Bender A., 2001. Enviromental variables and real estate prices. Urban Studies, Vol. 38 (11), pp. 1989 – 2000.10.1080/00420980120080899 Search in Google Scholar

Do Q., Grudnitski G., 1992. A neural network approach to residential property appraisal. The real Estate Appraisel, December, pp. 8-45.10.1080/10835547.1993.12090712 Search in Google Scholar

Do Q., Grudnitski G., 1993. A neura network analysis of the effect of age on housing values. The Journal of Real estate Research, Spring, pp. 253 – 264.10.1080/10835547.1993.12090712 Search in Google Scholar

D’amato M., 2004. A comparison between mra and rough set theory for mass appraisal. A case in bari. International journal of strategic property management, Vol. 8, pp. 205 – 217. IBBN: 1648-715x.10.3846/1648715X.2004.9637518 Search in Google Scholar

Fletcher M., Mangan J., Raeburn E., 2004.Comparing hedonic models for estimating and forcasting house prices. Property management, Vol. 22(3), pp. 189 – 200. DOI: 10,1108/026374704105448986. Open DOISearch in Google Scholar

Foryś I., Gaca R., 2016. Theoretical and practical aspects of qualitative variable descriptions of residential property valuation multiple regression models. The 10th Professor Aleksander Zelias International Conference on modelling and forcasting of socio-economics phenomena. Search in Google Scholar

García N., Gámez M., Alfaro E., 2008. ANN + GIS: An automated system for property valuation. Neurocomputering, Vol 71, pp. 733 – 742. DOI: 10.1016/j.neucom.2007.07.031. Open DOISearch in Google Scholar

González S. A. M., Formoso T. C., 2006. Mass appraisal with genetic fuzzy rule-based systems. Property management, Vol. 24(1), pp. 20-30. DOI: 10.1108/02637470610643092. Open DOISearch in Google Scholar

Goodman A. C.,1978. Hedonic prices, price indices and housing markets. Journal of urban economics, Vol. 5(4), pp. 471 – 484. DOI: 10.1016/0094-1190(78)90004-9. Open DOISearch in Google Scholar

Goodman A. C., 1978. Andrew Court and the invention of hednic price analysis. Journal of urban economics, Vol. 44, pp. 291-298. DOI: 10.1016/0094-1190(78)90004-9. Open DOISearch in Google Scholar

Hu L., He S., Han Z., Xiao H., Su S., Weng M., Cai Z., 2018. Monitoring housing rental prices based on social media: an integrated approach of machine-learning algorithms and hedonic mdeling to inform equitable housing policies. Land use policy, Vol. 82, pp. 657 – 673. DOI: 10.1016/j,landusepol.2018.12.030. Open DOISearch in Google Scholar

Isakson H. R., 1998. The review of real estate appraisals using multiple regression analysis. Journal of real estate research, Vol. 15(1/2), pp. 177 – 190. DOI: 10.1080/10835547.1998.12090922. Open DOISearch in Google Scholar

James G., Witten D., Hastie T., Tibshirani R., 2013, An introduction to statistical learning with Applications in R. Springer texts in statistics.10.1007/978-1-4614-7138-7 Search in Google Scholar

Kathmann R. M., 1993. Neural network for the mass appraisal of real estate. Computers, environment and urban systems, Vol. 17(4), pp. 373 – 384. , DOI: 10.1016/0198-9715(93)90034-3. Open DOISearch in Google Scholar

Kestens Y., Thériault M., Rosiers F. D., 2006. Heterogeneity in hedonic modelling of house prices: looking at buyer’s household profiles. J Geograph syst, Vol. 8, pp. 61 – 96. DOI: 10.1007/s10109-005-0011-8. Open DOISearch in Google Scholar

Knopf J. W. 2006. Doing a literature review. PS. Political Science & Politics, vol. 39 (1), pp. 127 – 132. Search in Google Scholar

Kuburik M., Tomić H., Mastelić Ivić S., 2012. Use of Multicriteria Valuation of Spatial Units in a System of Mass Real Estate Valuation. Prelliminary Communicationâ KiG, Vol. 11(17), pp. 759-774. Search in Google Scholar

Lenk M. M., Worzala M. E., Silva A., 1997. High-tech valuation: should artificial neural network bypass the human valuer? Jurnal of Property valuation Investment, Vol. 15 (1), pp. 8-26. DOI: 10.1108/14635789710163775. Open DOISearch in Google Scholar

Lin C. C., Mohan B. S., 201. Effectiveness comparison of the residential property mass appraisal methodologies in the USA. International Journal of Housing Market and Analysis, Vol. 4 No. , 2011, pp. 224-243.10.1108/17538271111153013 Search in Google Scholar

Limsombuchai V., Gan C., Lee M., 2004. House Price Prediction: Hedonic Price Model vs. Artificial Neural Network. American Journal of Applied Science, Vol.1 (3), pp. 193 – 201.10.3844/ajassp.2004.193.201 Search in Google Scholar

Lin C. C., Mohan A. B., 2011. Effectiveness comparison of the residential property mass appraisal methodologies in the USA. International journal of housing markets and analysis, Vol. 4(3), pp. 224 – 243. DOI: 10.1108/17538271111153013. Open DOISearch in Google Scholar

Liu J. G., Zhang X. L., Wu W. P., Application of Fuzzy Neural Network of Real Estate Prediction, Spring-Verlang Berlin Heidelberg, pp. 1187 – 1191.10.1007/11760191_173 Search in Google Scholar

Malpezzi S., 2002. Hedonic pricing models: a selective and applied review. Housing economics and public policy, Ch.5. DOI: https://doi.org/10.1002/9780470690680.ch510.1002/9780470690680.ch5 Search in Google Scholar

McClusey J. W., Borst A. R., 2011. Detecting and validating residential housing submarkets. A geostatistical approach for use in mass appraisal. International journal of housing markets and analysis, Vol. 4(3), pp. 290 – 318. DOI: 10.1108/175382711111530400. Open DOISearch in Google Scholar

McCluskey W.m Davis P., Haran M., CcCord M., McIlhatton D., 2012, The potential of artificial neural networks in mass apparaisal: the case revisited. Journal od financial management of property and construction, Vol. 17(3), pp. 274 – 292. DOI: 10.1108/1366431211274371. Open DOISearch in Google Scholar

McCluskey J. W., McCord M., Davis T. p., Haran M., McIlhatton D., 2013. Prediction accuracy in mass appraisal: a comparison of modern approaches. Journal of property research, Vol. 30 (4), pp. 239 – 265. DOI: 10.1080/09299916.2013.781204. Open DOISearch in Google Scholar

Munakata T., Fundamentals of the New Artificial Intelligence, Springer, New York, 1998. Search in Google Scholar

Nghiep N., Al C., 2001. Predicting housing value: a comparison of multiple regression analysis and artificial neural networks. Journal of real estate research, Vol. 22(3), pp. 313 – 336. DOI: 10.1080/10835547.2001.12091068. Open DOISearch in Google Scholar

Ogwang T., Wang B., 2003. A hedonic price function for a northern BC community. Social indicators research, Vol. 61, pp. 285 – 296. DOI: 10.1023/A:1021905518866. Open DOISearch in Google Scholar

Pagourtzi E., Assimakopoulos V., Hatzichristos T., French N., 2003. Real appraisal: a review of valuation methods.Journal of property investment & finance, Vol. 21(4), pp. 383 – 401. DOI: 10.1108/14635780310483656 Open DOISearch in Google Scholar

Pontus N., 2019. Prediction of residential real estate selling prices using neural networks. KTH Royal Institute of Thenology School of Electrical Engineering and computer science, Stockholm, Sweden. Search in Google Scholar

Rahman A. N. S., Maimun A. H. N., Razali M. N. M., Ismail S., 2019. The artificial neural network model (ANN) for Malayesian housing market analysis. Journal of the Malayisian institute of planners, Vol. 17(1), pp. 1-9.10.21837/pmjournal.v17.i9.581 Search in Google Scholar

Rossini P., 1997. Artificial Neural Networks versus Multiple Regression in the Valuation of Residential Property. Australia Land Economics Review, 3(1), pp. 1-12. Search in Google Scholar

Rosen S., 1974. Hedonic prices and implicit markets: product differentiation in pure competition. Journal of political economy, Vol. 8(1), pp. 34 – 55.10.1086/260169 Search in Google Scholar

Rossini P., 1998. Improving the results of artificial neural network models for residential valuation. Fourth annual Pacific-Rim real estate society conference, Perth, Western Australia, pp. 1-18. Search in Google Scholar

Samaha A. S., Kamakura A. W., 2008. Assessing the market value of real estate property with a geographically weighted stochastic frontier model. Real estate economics, Vol. 36(4), pp. 717 – 751. DOI: 10.1111/j.1540-6229.2008.00228.x. Open DOISearch in Google Scholar

Sarip G. A., Hafez B. M., Daud N. M., 2016. Application of fuzzy regression model for real estate price prediction. Malaysian journal of computer science. Vol, 29(1), pp. 15 – 27.10.22452/mjcs.vol29no1.2 Search in Google Scholar

Selim H., 2009. Determinants of house in Turkey: Hedonic regression versus artificial neural network. Expert system with applications, Vol. 36(2), part 2, pp. 2843 2852. DOI: 10.1016/j.eswa.2008.01.044. Open DOISearch in Google Scholar

Şipoș C., Crivii A., 2008. Modelul regresiei liniare pentru evaluarea proprietăţilor imobiliares. Revista de evaluare, 2(5). Search in Google Scholar

Steverson S., 2004. New empirical evidence on heteroscedasticity in hedonic housing models. Journal of housing economics, Vol. 13(2), pp. 136 – 153. DOI: 10.1016/j.jhe.2004.04.004. Open DOISearch in Google Scholar

Stoean R., 2008. Reţele neuronale. Neural networks (NN). http://inf.ucv.ro/~rstoean Search in Google Scholar

Tay D. P. H., Ho D. K. K., 1992. Artificial Inteligenc and the Mass Appraisal of residencial Apartment, Jurnal of Property Valuation & Investment, 10:525-540.10.1108/14635789210031181 Search in Google Scholar

Trippi, R.R., Turban, E., 1992. Neural Networks in Finance and Investing: Using Artificial Intelligence to improve real world performance. Chicago, IL, Probus Publishing. Search in Google Scholar

Tothăzan H. F., Deaconu A. 2020. Neural Network Artificial Model for Real Estate Appraisal: Logic, controversies, and utility for the Ramanian context. “Ovidius” University Annals, Economic Sciences Series, Vol. XX(22), pp. 1093-1100. Search in Google Scholar

Tudorel A., Régis B., 2008. Econometrie. București, Editura Economica. Search in Google Scholar

Watkins C., 1999. Property valuation and the structure of urban housing markets. Journal of property investment & finance, Vol. 17(2), pp. 157-175. Academic paper.10.1108/14635789910258543 Search in Google Scholar

Wilkowski W., Budzyński T., 2006. Application of Neural Networks for Real Estate Valuation. TS86 – Valuations Methods, XXIII FIG Congress, Munich, Germany, October 8-1, 2006. Search in Google Scholar

Worzala E. M., Lenk M. M., Silva A., 1995, An explanation of neural networks and its application to real estate valuation, Journal of Real Estate Research, Vol. 10, No. 2, pp. 185-202.10.1080/10835547.1995.12090782 Search in Google Scholar

Yalpir S., 2014a. Forecasting residential realpago estate valees with AHP method and integrated GIS. In conference proceedings of people, Building and Enviroment 2014, Czech Republic, pp. 694 – 706. Search in Google Scholar

Yalpir S., Durduran S. S., Unel F. B., Yolcu M., 2014b. Creating A Valuation Map In GIS Through Artificial Neural Network Methodology: A Case Study. Acta Montanistica Slovaca, Vol. 19(2), p79-89. Search in Google Scholar

Yilmazer S., Kocaman S., 2020, A mass appraisal assestment study using machine learning based on multiple regression and random forest. Land use popicy, Vol. 90, pp. 1-11. DOI: 10.1016/j.landusepol.2020.104889. Open DOISearch in Google Scholar

Zhou G., Ji Yicheng, Chen X., Zhang F., 2018. Artificial neural Networks and the mass appraisal of real estate. International Journal of online engineering (iJOE), Vol. 1(3), pp. 180 – 187.10.3991/ijoe.v14i03.8420 Search in Google Scholar

Zurada J., Levitan S. A., Guan J., 2011. A comparison of regression and Artificial Intelligence methods in a mass appraisal context.10.1080/10835547.2011.12091311 Search in Google Scholar

eISSN:
2286-0991
Język:
Angielski