Evgeny Antipov

Personal Details

First Name:	Evgeny
Middle Name:
Last Name:	Antipov
Suffix:
RePEc Short-ID:	pan259
	http://www.BusinessResearch.ru

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Elena Pokryshevskaya & Evgeny Antipov, 2013. "Importance-performance analysis for internet stores: a system based on publicly available panel data," HSE Working papers WP BRP 08/MAN/2013, National Research University Higher School of Economics.

   Cited by:

   1. Tontini, Gerson, 2016. "Identifying opportunities for improvement in online shopping sites," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 228-238.

2. Antipov, Evgeny & Pokryshevskaya, Elena, 2010. "Accounting for latent classes in movie box office modeling," MPRA Paper 27644, University Library of Munich, Germany.

   Cited by:

   1. Hofmann, Julian & Clement, Michel & Völckner, Franziska & Hennig-Thurau, Thorsten, 2017. "Empirical generalizations on the impact of stars on the economic success of movies," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 442-461.

3. Antipov, Evgeny & Pokryshevskaya, Elena, 2010. "Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics," MPRA Paper 27645, University Library of Munich, Germany.

   Cited by:

   1. Brano Glumac & Francois Des Rosiers, 2018. "Real estate and land property automated valuations systems: a taxonomy and conceptual model," ERES eres2018_148, European Real Estate Society (ERES).
      • GLUMAC Brano & DES ROSIERS François, 2018. "Real estate and land property automated valuation systems: A taxonomy and conceptual model," LISER Working Paper Series 2018-09, Luxembourg Institute of Socio-Economic Research (LISER).
   2. Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
   3. Michalis Doumpos & Dimitrios Papastamos & Dimitrios Andritsos & Constantin Zopounidis, 2021. "Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches," Annals of Operations Research, Springer, vol. 306(1), pages 415-433, November.
   4. Mehrbakhsh Nilashi & Shahla Asadi & Rabab Ali Abumalloh & Sarminah Samad & Fahad Ghabban & Eko Supriyanto & Reem Osman, 2021. "Sustainability Performance Assessment Using Self-Organizing Maps (SOM) and Classification and Ensembles of Regression Trees (CART)," Sustainability, MDPI, vol. 13(7), pages 1-24, March.
   5. Marco Locurcio & Pierluigi Morano & Francesco Tajani & Felicia Di Liddo, 2020. "An Innovative GIS-Based Territorial Information Tool for the Evaluation of Corporate Properties: An Application to the Italian Context," Sustainability, MDPI, vol. 12(14), pages 1-29, July.
   6. Vladimir Vargas-Calder'on & Jorge E. Camargo, 2020. "Towards robust and speculation-reduction real estate pricing models based on a data-driven strategy," Papers 2012.09115, arXiv.org.
   7. Daikun Wang & Victor Jing Li, 2019. "Mass Appraisal Models of Real Estate in the 21st Century: A Systematic Literature Review," Sustainability, MDPI, vol. 11(24), pages 1-14, December.
   8. Sebastian Gnat & Mariusz Doszyn, 2020. "Parametric and Non-parametric Methods in Mass Appraisal on Poorly Developed Real Estate Markets," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1230-1245.
   9. Jannet C. Bencure & Nitin K. Tripathi & Hiroyuki Miyazaki & Sarawut Ninsawat & Sohee Minsun Kim, 2019. "Development of an Innovative Land Valuation Model (iLVM) for Mass Appraisal Application in Sub-Urban Areas Using AHP: An Integration of Theoretical and Practical Approaches," Sustainability, MDPI, vol. 11(13), pages 1-17, July.
   10. Mahdieh Yazdani, 2021. "Machine Learning, Deep Learning, and Hedonic Methods for Real Estate Price Prediction," Papers 2110.07151, arXiv.org.
   11. Mohammad Mirbagherijam, 2021. "Housing Price Prediction Model Selection Based on Lorenz and Concentration Curves: Empirical Evidence from Tehran Housing Market," Papers 2112.06192, arXiv.org.
   12. Kokot Sebastian & Gnat Sebastian, 2019. "Simulative Verification of the Possibility of using Multiple Regression Models for Real Estate Appraisal," Real Estate Management and Valuation, Sciendo, vol. 27(3), pages 109-123, September.
   13. Jungsun Kim & Jaewoong Won & Hyeongsoon Kim & Joonghyeok Heo, 2021. "Machine-Learning-Based Prediction of Land Prices in Seoul, South Korea," Sustainability, MDPI, vol. 13(23), pages 1-14, November.
   14. Kristoffer B. Birkeland & Allan D. D'Silva & Roland Füss & Are Oust, 2021. "The Predictability of House Prices: "Human Against Machine"," International Real Estate Review, Global Social Science Institute, vol. 24(2), pages 139-183.
   15. Susanna Levantesi & Gabriella Piscopo, 2020. "The Importance of Economic Variables on London Real Estate Market: A Random Forest Approach," Risks, MDPI, vol. 8(4), pages 1-17, October.
   16. Sebastian Gnat, 2021. "Property Mass Valuation on Small Markets," Land, MDPI, vol. 10(4), pages 1-14, April.

4. Antipov, Evgeny & Pokryshevskaya, Elena, 2009. "Applying CHAID for logistic regression diagnostics and classification accuracy improvement," MPRA Paper 21499, University Library of Munich, Germany.

   Cited by:

   1. Celal Hakan Kagnicioglu & Mune Mogol, 2014. "Implementation of Chaid Algorithm: A Hotel Case," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 3(4), pages 42-51, October.
   2. Wöcke, Albert & Moodley, Terence, 2015. "Corporate political strategy and liability of foreignness: Similarities and differences between local and foreign firms in the South African Health Sector," International Business Review, Elsevier, vol. 24(4), pages 700-709.

Articles

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 5 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-ECM: Econometrics (2) 2011-01-03 2011-01-03
2. NEP-ICT: Information and Communication Technologies (2) 2013-11-29 2014-04-11
3. NEP-CIS: Confederation of Independent States (1) 2014-04-11
4. NEP-CMP: Computational Economics (1) 2011-01-03
5. NEP-COM: Industrial Competition (1) 2014-04-11
6. NEP-CUL: Cultural Economics (1) 2011-01-03
7. NEP-EFF: Efficiency and Productivity (1) 2013-11-29
8. NEP-GER: German Papers (1) 2014-04-11
9. NEP-MKT: Marketing (1) 2014-04-11
10. NEP-URE: Urban and Real Estate Economics (1) 2011-01-03

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