Predicting days on market to optimize real estate sales strategy

Castelli, Mauro (avtor), Dobreva, Maria (avtor), Henriques, Roberto (avtor), Vanneschi, Leonardo (avtor)

Irregularities and frauds are frequent in the real estate market in Bulgaria due to the substantial lack of rigorous legislation. For instance, agencies frequently publish unreal or unavailable apartment listings for a cheap price, as a method to attract the attention of unaware potential new customers. For this reason, systems able to identify unreal listings and improve the transparency of listings authenticity and availability are much on demand. Recent research has highlighted that the number of days a published listing remains online can have a strong correlation with the probability of a listing being unreal. For this reason, building an accurate predictive model for the number of days a published listing will be online can be very helpful to accomplish the task of identifying fake listings. In this paper, we investigate the use of four different machine learning algorithms for this task: Lasso, Ridge, Elastic Net, and Artificial Neural Networks. The results, obtained on a vast dataset made available by the Bulgarian company Homeheed, show the appropriateness of Lasso regression.

• Jezik: Angleški jezik
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: EF - Ekonomska fakulteta
• Različica publikacije: Objavljena publikacija
• Leto izida: 2020
• Št. strani: 22 str.
• Številčenje: Vol. 2020, art. 4603190
• PID: 20.500.12556/RUL-114724
• UDK: 659.2:004
• ISSN pri članku: 1099-0526
• DOI: 10.1155/2020/4603190
• COBISS.SI-ID: 25563110
• Datum objave v RUL: 06.03.2020

Gradivo je del revije

• Naslov: Complexity
• Skrajšan naslov: Complexity
• Založnik: Wiley
• COBISS.SI-ID: 18282279

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
• Začetek licenciranja: 06.03.2020

Projekti

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: P5-0410
• Naslov: Digitalizacija kot gonilo trajnostnega razvoja posameznika, organizacij in družbe