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Approaches to Analysis of Factors Affecting the Residential Real Estate Bid Prices in Case of Open Data Use

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Electronic Governance and Open Society: Challenges in Eurasia (EGOSE 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1135))

Abstract

Determining the procedure and approaches to automating real estate appraisal is an important condition for improving e-government on the basis of one of the key economic sectors throughout the state. The paper discusses a set of approaches to the analysis of factors affecting the pricing of objects that offer in a market of residential real estate. The components of the process of working with source data on real estate objects in Russia are described. Ways of extraction a structured description of particular factors, source data geocoding, merging data from various sources with the subsequent normalization of data for some factors are suggested. Testing of the proposed solutions was carried out on the basis of data sets for the Volgograd region: downloads from the ad placement site for the period from January to December 2018, data from the ReformaGKH website, the OpenStreetMap mapping project and the depersonalized information of the Unified State Register of Real Estate. Approaches to the analysis of physical (year of completion, type of object by period of construction, area of premises, number of floors of a building and floor of an apartment) and spatial characteristics of real estate objects were proposed and tested. The location quality factor is taken into account in the form of an integrated assessment of the results of the analysis of the density map of social infrastructure objects location. In general, the work offers step-by-step instructions on the formation and analysis of the information base, indicating specific sources and methods for calculating valuations, applicable for any region of Russia.

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References

  1. Parygin, D.S., Sadovnikova, N.P., Shabalina, O.A.: Information and analytical support for city management tasks. Volgograd (2017). [In Russian]

    Google Scholar 

  2. Ustugova, S., Parygin, D., Sadovnikova, N., Yadav, V., Prikhodkova, I.: Geoanalytical system for support of urban processes management tasks. In: Kravets, A., Shcherbakov, M., Kultsova, M., Groumpos, P. (eds.) Communications in Computer and Information Science, CIT&DS 2017. Communications in Computer and Information Science, vol. 754, pp. 430–440. Springer Cham (2017). https://doi.org/10.1007/978-3-319-65551-2_31

    Google Scholar 

  3. Mashkova, A.L., Savina, O.A., Banchuk, Y.A., Mashkov, E.A.: Using open data for information support of simulation model of the Russian Federation spatial development. In: Chugunov, A., Misnikov, Y., Roshchin, E., Trutnev, D. (eds.) EGOSE 2018. CCIS, vol. 947, pp. 401–414. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-13283-5_30

    Chapter  Google Scholar 

  4. Ozerov, E.S.: Economic Analysis and Real Estate Valuation. Saint Petersburg (2007)

    Google Scholar 

  5. Sternik, G.M., Sternik, S.G.: Property Market Analysis for Professionals. Ekonomika Publishing, Moscow (2009). [In Russian]

    Google Scholar 

  6. Gryaznova, A.G., Fedotova, M.A.: Real estate valuation. Fin and Stat, Moscow (2008)

    Google Scholar 

  7. Mirzoyan, N.V.: Valuation of real estate. Moscow (2005). [In Russian]

    Google Scholar 

  8. Burinskienė, M., Rudzkiene, V., Venckauskaite, J.: Models of factors influencing the real estate price. In: 8th International Conference on Environmental Engineering (2011)

    Google Scholar 

  9. International Association of Assessing Officers. https://www.iaao.org/. Accessed 21 Apr 2019

  10. Kirzhner, E.: Big Data Applications in Real Estate Analysis. https://codeburst.io/big-data-applications-in-real-estate-analysis-502accc54dc8. Accessed 10 Jan 2019

  11. Sanina, L.V., Sherstyankina, N.P., Bergen, D.N., Dashkevich, P.M.: Modeling of the price for flats at the regional market of real estate (at the example of Irkutsk region). In: Proceedings of Universities Investment Construction Real estate, vol. 7, no. 3, pp. 27–41 (2017)

    Article  Google Scholar 

  12. Hill, R.J., Scholz, M.: Can geospatial data improve house price indexes? A hedonic imputation approach with splines. Rev. Income Wealth 64(4), 737–756 (2018)

    Article  Google Scholar 

  13. Chica-Olmo, J., Cano-Guervos, R., Chica-Rivas, M.: Estimation of housing price variations using spatio-temporal data. Sustainability 11(6), 1551 (2019)

    Article  Google Scholar 

  14. Housing price statistics - house price index. https://ec.europa.eu/eurostat/statistics-explained/index.php/Housing_price_statistics_-_house_price_index. Accessed 17 July 2019

  15. Constantinescu, M.: Machine-Learning Real Estate Valuation: Not Only a Data Affair. https://towardsdatascience.com/machine-learning-real-estate-valuation-not-only-a-data-affair-99d36c92d263. Accessed 14 July 2019

  16. Avito. https://www.avito.ru/. Accessed 18 Jan 2019

  17. Domofond.ru. https://www.domofond.ru/. Accessed 22 Nov 2018

  18. Public cadastral map. https://pkk5.rosreestr.ru/. Accessed 07 Nov 2018

  19. The official website of the Russian Federation for posting information on tendering. https://torgi.gov.ru/. Accessed 26 Feb 2019

  20. Federal Service for State Registration, Cadastre and Cartography. https://portal.rosreestr.ru/. Accessed 29 Nov 2018

  21. Federal State Statistics Service. http://www.gks.ru/. Accessed 25 May 2019

  22. Official statistics. https://fedstat.ru/. Accessed 19 Feb 2019

  23. Real Estate Website. https://regionalrealty.ru/. Accessed 14 Apr 2019

  24. Real Estate Market Indicators. https://www.irn.ru/. Accessed 20 Mar 2019

  25. Karyagin, M.E., Romanov, V.A.: Russian large cities’ open data: problems of innovative development. In: Proceedings of the International Conference on Electronic Governance and Open Society: Challenges in Eurasia (EGOSE 2016), pp. 120–125. ACM, New York (2016)

    Google Scholar 

  26. Parygin, D.S., Malikov, V.P., Golubev, A.V., Sadovnikova, N.P., Petrova, T.M., Finogeev, A.G.: Categorical data processing for real estate objects valuation using statistical analysis. J. Phys.: Conf. Ser. 1015(032102) (2018). IOP Publishing

    Google Scholar 

  27. Tomita-parser. https://tech.yandex.ru/tomita/. Accessed 17 Nov 2018

  28. Geocoder. https://tech.yandex.ru/maps/geocoder/. Accessed 30 Jan 2019

  29. Housing and Communal Services Reform Fund. https://www.reformagkh.ru/. Accessed 04 May 2019

  30. OpenStreetMap. https://www.openstreetmap.org/. Accessed 03 June 2019

  31. Yandex.Maps. https://yandex.ru/maps/. Accessed 11 Mar 2019

  32. Google Maps. https://www.google.ru/maps/. Accessed 01 June 2019

  33. GIS. https://2gis.ru/. Accessed 29 May 2019

  34. Federal Information Address System. https://fias.nalog.ru/. Accessed 08 Apr 2019

  35. Ferlan, N., Bastic, M., Psunder, I.: Influential factors on the market value of residential properties. Eng. Econ. [Инжeнepнaя экoнoмикa] 28(2), 135–144 (2017)

    Google Scholar 

  36. Treece, K.: Comparative Market Analysis. https://fitsmallbusiness.com/comparative-market-analysis/. Accessed 16 Mar 2019

  37. Goodwin, K.: Location: Physical and Environmental Factors in Real Estate. https://www.propertymetrics.com/blog/2017/12/12/location-physical-and-environmental-factors/. Accessed 27 Dec 2018

  38. Punshon, B.: What influences a property’s value?. https://www.finder.com.au/what-influences-a-propertys-value. Accessed 11 Apr 2019

  39. Set of rules 54.13330.2011 “Residential apartment buildings”. http://docs.cntd.ru/document/1200084096. Accessed 31 Mar 2019

  40. Alonso, W.: Location and Land Use: Towards a General Theory of Land Rent. Cambridge University Press, Cambridge (1964)

    Book  Google Scholar 

  41. Bertaud, A., Renaud, B.: Cities without land markets: location and land use in a socialist city. http://alainbertaud.com/wp-content/uploads/2013/06/Cities_without_Land_Markets_Russian_Version.pdf. Accessed 15 Feb 2019

  42. Parygin, D., Sadovnikova, N., Kalinkina, M., Potapova, T., Finogeev, A.: Visualization of data about events in the urban environment for the decision support of the city services actions coordination. In: SMART-2016, Proceedings of the 5th International Conference on System Modeling & Advancement in Research Trends, pp. 283–290. IEEE (2016)

    Google Scholar 

  43. Cherkesov, V., Malikov, V., Golubev, A., Parygin, D., Smykovskaya, T.: Parsing of data on real estate objects from network resource. In: Proceedings of the IV International Research Conference “Information Technologies in Science, Management, Social sphere and Medicine” (ITSMSSM 2017), vol. 72, pp. 385–388. Atlantis Press (2017)

    Google Scholar 

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Acknowledgments

The reported study was funded by Russian Foundation for Basic Research according to the research project No. 18-37-20066_mol_a_ved. The authors express gratitude to colleagues from UCLab involved in the development of OS.UrbanBasis.com project.

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Authors and Affiliations

  1. GeoClever, Barrikadnaya Str. 1B, 400074, Volgograd, Russia

    Dmitry Boiko

  2. Volgograd State Technical University, Lenina Ave. 28, 400005, Volgograd, Russia

    Danila Parygin, Oksana Savina, Alexey Golubev & Ilya Zelenskiy

  3. ITMO University, Birzhevaya line 14, 199034, Saint Petersburg, Russia

    Sergey Mityagin

Authors
  1. Dmitry Boiko
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  2. Danila Parygin
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  3. Oksana Savina
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  4. Alexey Golubev
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  5. Ilya Zelenskiy
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  6. Sergey Mityagin
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Corresponding author

Correspondence to Danila Parygin .

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Editors and Affiliations

  1. ITMO University, St. Petersburg, Russia

    Andrei Chugunov

  2. Russian Academy of National Economy and Public Administration, St. Petersburg, Russia

    Igor Khodachek

  3. University of Leeds, Leeds, UK

    Yuri Misnikov

  4. ITMO University, St. Petersburg, Russia

    Dmitrii Trutnev

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Boiko, D., Parygin, D., Savina, O., Golubev, A., Zelenskiy, I., Mityagin, S. (2020). Approaches to Analysis of Factors Affecting the Residential Real Estate Bid Prices in Case of Open Data Use. In: Chugunov, A., Khodachek, I., Misnikov, Y., Trutnev, D. (eds) Electronic Governance and Open Society: Challenges in Eurasia. EGOSE 2019. Communications in Computer and Information Science, vol 1135. Springer, Cham. https://doi.org/10.1007/978-3-030-39296-3_27

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  • DOI: https://doi.org/10.1007/978-3-030-39296-3_27

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-39296-3

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