iBuyer’s use of PropTech to make large-scale cash offers

Gespeichert in:

Autor*in:	Anderson, Jackson T. [verfasserIn] Fuerst, Franz [verfasserIn] Peiser, Richard B. [verfasserIn] Seiler, Michael J. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	brokerage experiment, regret aversion FinTech housing iBuyer pricing strategies PropTech

Übergeordnetes Werk:	Enthalten in: Journal of real estate research - London [u.a.] : Taylor & Francis, 1986, 46(2024), 1, Seite 114-135
Übergeordnetes Werk:	volume:46 ; year:2024 ; number:1 ; pages:114-135

Links:	Link aufrufen Link aufrufen

DOI / URN:	10.1080/08965803.2023.2214467

Katalog-ID:	1895966094

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allfields	10.1080/08965803.2023.2214467 doi (DE-627)1895966094 (DE-599)KXP1895966094 DE-627 ger DE-627 rda eng Anderson, Jackson T. verfasserin aut iBuyer’s use of PropTech to make large-scale cash offers Jackson T. Anderson, Franz Fuerst, Richard B. Peiser and Michael J. Seiler 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier brokerage (dpeaa)DE-206 experiment, regret aversion (dpeaa)DE-206 FinTech (dpeaa)DE-206 housing (dpeaa)DE-206 iBuyer (dpeaa)DE-206 pricing strategies (dpeaa)DE-206 PropTech (dpeaa)DE-206 Fuerst, Franz verfasserin (DE-588)1026297753 (DE-627)726434655 (DE-576)371608066 aut Peiser, Richard B. verfasserin (DE-588)170650294 (DE-627)060767979 (DE-576)131515233 aut Seiler, Michael J. verfasserin (DE-588)171534476 (DE-627)061745324 (DE-576)132321343 aut Enthalten in Journal of real estate research London [u.a.] : Taylor & Francis, 1986 46(2024), 1, Seite 114-135 Online-Ressource (DE-627)325570280 (DE-600)2037318-1 (DE-576)273895559 2691-1175 nnns volume:46 year:2024 number:1 pages:114-135 https://www.tandfonline.com/doi/pdf/10.1080/08965803.2023.2214467 Verlag lizenzpflichtig https://doi.org/10.1080/08965803.2023.2214467 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_39 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_224 GBV_ILN_285 GBV_ILN_370 GBV_ILN_374 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2107 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 46 2024 1 114-135 26 01 0206 4555075072 x1z 22-07-24 26 00 DE-206 The expansion of iBuyer's use of PropTech to major housing markets raises a series of questions for both buyers and sellers when making instant, all-cash offers. This study uses a sequence of experiments to identify the proper implementation of existing behavioral real estate concepts to improve the iBuying process, a burgeoning area of residential real estate. We find strong evidence of anchoring for all-cash offers in that sellers are nearly twice as likely to transact when they are first presented with the net proceeds offer price (market value minus costs) rather than starting with the higher gross market value offer price. After the sale, seller regret aversion becomes strong when the seller's house is subsequently sold for 10% or more than the all-cash buyer paid, but regret aversion is mitigated with communication of the improvements made to enhance the selling price. We further find that sellers do not know which all-cash buyer's Automated Valuation Model (AVM) is the most accurate and are therefore much more influenced by brand awareness than model sophistication. Finally, while the extant literature has examined offer price strategies for home sellers, this is the first investigation of buyer offer price strategies. In stark contrast to selling strategies, pricing strategies do not matter when making an offer to buy.
spelling	10.1080/08965803.2023.2214467 doi (DE-627)1895966094 (DE-599)KXP1895966094 DE-627 ger DE-627 rda eng Anderson, Jackson T. verfasserin aut iBuyer’s use of PropTech to make large-scale cash offers Jackson T. Anderson, Franz Fuerst, Richard B. Peiser and Michael J. Seiler 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier brokerage (dpeaa)DE-206 experiment, regret aversion (dpeaa)DE-206 FinTech (dpeaa)DE-206 housing (dpeaa)DE-206 iBuyer (dpeaa)DE-206 pricing strategies (dpeaa)DE-206 PropTech (dpeaa)DE-206 Fuerst, Franz verfasserin (DE-588)1026297753 (DE-627)726434655 (DE-576)371608066 aut Peiser, Richard B. verfasserin (DE-588)170650294 (DE-627)060767979 (DE-576)131515233 aut Seiler, Michael J. verfasserin (DE-588)171534476 (DE-627)061745324 (DE-576)132321343 aut Enthalten in Journal of real estate research London [u.a.] : Taylor & Francis, 1986 46(2024), 1, Seite 114-135 Online-Ressource (DE-627)325570280 (DE-600)2037318-1 (DE-576)273895559 2691-1175 nnns volume:46 year:2024 number:1 pages:114-135 https://www.tandfonline.com/doi/pdf/10.1080/08965803.2023.2214467 Verlag lizenzpflichtig https://doi.org/10.1080/08965803.2023.2214467 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_39 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_224 GBV_ILN_285 GBV_ILN_370 GBV_ILN_374 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2107 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 46 2024 1 114-135 26 01 0206 4555075072 x1z 22-07-24 26 00 DE-206 The expansion of iBuyer's use of PropTech to major housing markets raises a series of questions for both buyers and sellers when making instant, all-cash offers. This study uses a sequence of experiments to identify the proper implementation of existing behavioral real estate concepts to improve the iBuying process, a burgeoning area of residential real estate. We find strong evidence of anchoring for all-cash offers in that sellers are nearly twice as likely to transact when they are first presented with the net proceeds offer price (market value minus costs) rather than starting with the higher gross market value offer price. After the sale, seller regret aversion becomes strong when the seller's house is subsequently sold for 10% or more than the all-cash buyer paid, but regret aversion is mitigated with communication of the improvements made to enhance the selling price. We further find that sellers do not know which all-cash buyer's Automated Valuation Model (AVM) is the most accurate and are therefore much more influenced by brand awareness than model sophistication. Finally, while the extant literature has examined offer price strategies for home sellers, this is the first investigation of buyer offer price strategies. In stark contrast to selling strategies, pricing strategies do not matter when making an offer to buy.
allfields_unstemmed	10.1080/08965803.2023.2214467 doi (DE-627)1895966094 (DE-599)KXP1895966094 DE-627 ger DE-627 rda eng Anderson, Jackson T. verfasserin aut iBuyer’s use of PropTech to make large-scale cash offers Jackson T. Anderson, Franz Fuerst, Richard B. Peiser and Michael J. Seiler 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier brokerage (dpeaa)DE-206 experiment, regret aversion (dpeaa)DE-206 FinTech (dpeaa)DE-206 housing (dpeaa)DE-206 iBuyer (dpeaa)DE-206 pricing strategies (dpeaa)DE-206 PropTech (dpeaa)DE-206 Fuerst, Franz verfasserin (DE-588)1026297753 (DE-627)726434655 (DE-576)371608066 aut Peiser, Richard B. verfasserin (DE-588)170650294 (DE-627)060767979 (DE-576)131515233 aut Seiler, Michael J. verfasserin (DE-588)171534476 (DE-627)061745324 (DE-576)132321343 aut Enthalten in Journal of real estate research London [u.a.] : Taylor & Francis, 1986 46(2024), 1, Seite 114-135 Online-Ressource (DE-627)325570280 (DE-600)2037318-1 (DE-576)273895559 2691-1175 nnns volume:46 year:2024 number:1 pages:114-135 https://www.tandfonline.com/doi/pdf/10.1080/08965803.2023.2214467 Verlag lizenzpflichtig https://doi.org/10.1080/08965803.2023.2214467 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_39 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_224 GBV_ILN_285 GBV_ILN_370 GBV_ILN_374 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2107 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 46 2024 1 114-135 26 01 0206 4555075072 x1z 22-07-24 26 00 DE-206 The expansion of iBuyer's use of PropTech to major housing markets raises a series of questions for both buyers and sellers when making instant, all-cash offers. This study uses a sequence of experiments to identify the proper implementation of existing behavioral real estate concepts to improve the iBuying process, a burgeoning area of residential real estate. We find strong evidence of anchoring for all-cash offers in that sellers are nearly twice as likely to transact when they are first presented with the net proceeds offer price (market value minus costs) rather than starting with the higher gross market value offer price. After the sale, seller regret aversion becomes strong when the seller's house is subsequently sold for 10% or more than the all-cash buyer paid, but regret aversion is mitigated with communication of the improvements made to enhance the selling price. We further find that sellers do not know which all-cash buyer's Automated Valuation Model (AVM) is the most accurate and are therefore much more influenced by brand awareness than model sophistication. Finally, while the extant literature has examined offer price strategies for home sellers, this is the first investigation of buyer offer price strategies. In stark contrast to selling strategies, pricing strategies do not matter when making an offer to buy.
allfieldsGer	10.1080/08965803.2023.2214467 doi (DE-627)1895966094 (DE-599)KXP1895966094 DE-627 ger DE-627 rda eng Anderson, Jackson T. verfasserin aut iBuyer’s use of PropTech to make large-scale cash offers Jackson T. Anderson, Franz Fuerst, Richard B. Peiser and Michael J. Seiler 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier brokerage (dpeaa)DE-206 experiment, regret aversion (dpeaa)DE-206 FinTech (dpeaa)DE-206 housing (dpeaa)DE-206 iBuyer (dpeaa)DE-206 pricing strategies (dpeaa)DE-206 PropTech (dpeaa)DE-206 Fuerst, Franz verfasserin (DE-588)1026297753 (DE-627)726434655 (DE-576)371608066 aut Peiser, Richard B. verfasserin (DE-588)170650294 (DE-627)060767979 (DE-576)131515233 aut Seiler, Michael J. verfasserin (DE-588)171534476 (DE-627)061745324 (DE-576)132321343 aut Enthalten in Journal of real estate research London [u.a.] : Taylor & Francis, 1986 46(2024), 1, Seite 114-135 Online-Ressource (DE-627)325570280 (DE-600)2037318-1 (DE-576)273895559 2691-1175 nnns volume:46 year:2024 number:1 pages:114-135 https://www.tandfonline.com/doi/pdf/10.1080/08965803.2023.2214467 Verlag lizenzpflichtig https://doi.org/10.1080/08965803.2023.2214467 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_39 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_224 GBV_ILN_285 GBV_ILN_370 GBV_ILN_374 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2107 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 46 2024 1 114-135 26 01 0206 4555075072 x1z 22-07-24 26 00 DE-206 The expansion of iBuyer's use of PropTech to major housing markets raises a series of questions for both buyers and sellers when making instant, all-cash offers. This study uses a sequence of experiments to identify the proper implementation of existing behavioral real estate concepts to improve the iBuying process, a burgeoning area of residential real estate. We find strong evidence of anchoring for all-cash offers in that sellers are nearly twice as likely to transact when they are first presented with the net proceeds offer price (market value minus costs) rather than starting with the higher gross market value offer price. After the sale, seller regret aversion becomes strong when the seller's house is subsequently sold for 10% or more than the all-cash buyer paid, but regret aversion is mitigated with communication of the improvements made to enhance the selling price. We further find that sellers do not know which all-cash buyer's Automated Valuation Model (AVM) is the most accurate and are therefore much more influenced by brand awareness than model sophistication. Finally, while the extant literature has examined offer price strategies for home sellers, this is the first investigation of buyer offer price strategies. In stark contrast to selling strategies, pricing strategies do not matter when making an offer to buy.
allfieldsSound	10.1080/08965803.2023.2214467 doi (DE-627)1895966094 (DE-599)KXP1895966094 DE-627 ger DE-627 rda eng Anderson, Jackson T. verfasserin aut iBuyer’s use of PropTech to make large-scale cash offers Jackson T. Anderson, Franz Fuerst, Richard B. Peiser and Michael J. Seiler 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier brokerage (dpeaa)DE-206 experiment, regret aversion (dpeaa)DE-206 FinTech (dpeaa)DE-206 housing (dpeaa)DE-206 iBuyer (dpeaa)DE-206 pricing strategies (dpeaa)DE-206 PropTech (dpeaa)DE-206 Fuerst, Franz verfasserin (DE-588)1026297753 (DE-627)726434655 (DE-576)371608066 aut Peiser, Richard B. verfasserin (DE-588)170650294 (DE-627)060767979 (DE-576)131515233 aut Seiler, Michael J. verfasserin (DE-588)171534476 (DE-627)061745324 (DE-576)132321343 aut Enthalten in Journal of real estate research London [u.a.] : Taylor & Francis, 1986 46(2024), 1, Seite 114-135 Online-Ressource (DE-627)325570280 (DE-600)2037318-1 (DE-576)273895559 2691-1175 nnns volume:46 year:2024 number:1 pages:114-135 https://www.tandfonline.com/doi/pdf/10.1080/08965803.2023.2214467 Verlag lizenzpflichtig https://doi.org/10.1080/08965803.2023.2214467 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_39 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_224 GBV_ILN_285 GBV_ILN_370 GBV_ILN_374 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2107 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 46 2024 1 114-135 26 01 0206 4555075072 x1z 22-07-24 26 00 DE-206 The expansion of iBuyer's use of PropTech to major housing markets raises a series of questions for both buyers and sellers when making instant, all-cash offers. This study uses a sequence of experiments to identify the proper implementation of existing behavioral real estate concepts to improve the iBuying process, a burgeoning area of residential real estate. We find strong evidence of anchoring for all-cash offers in that sellers are nearly twice as likely to transact when they are first presented with the net proceeds offer price (market value minus costs) rather than starting with the higher gross market value offer price. After the sale, seller regret aversion becomes strong when the seller's house is subsequently sold for 10% or more than the all-cash buyer paid, but regret aversion is mitigated with communication of the improvements made to enhance the selling price. We further find that sellers do not know which all-cash buyer's Automated Valuation Model (AVM) is the most accurate and are therefore much more influenced by brand awareness than model sophistication. Finally, while the extant literature has examined offer price strategies for home sellers, this is the first investigation of buyer offer price strategies. In stark contrast to selling strategies, pricing strategies do not matter when making an offer to buy.
language	English
source	Enthalten in Journal of real estate research 46(2024), 1, Seite 114-135 volume:46 year:2024 number:1 pages:114-135
sourceStr	Enthalten in Journal of real estate research 46(2024), 1, Seite 114-135 volume:46 year:2024 number:1 pages:114-135
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authorswithroles_txt_mv	Anderson, Jackson T. @@aut@@ Fuerst, Franz @@aut@@ Peiser, Richard B. @@aut@@ Seiler, Michael J. @@aut@@
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housing markets raises a series of questions for both buyers and sellers when making instant, all-cash offers. This study uses a sequence of experiments to identify the proper implementation of existing behavioral real estate concepts to improve the iBuying process, a burgeoning area of residential real estate. We find strong evidence of anchoring for all-cash offers in that sellers are nearly twice as likely to transact when they are first presented with the net proceeds offer price (market value minus costs) rather than starting with the higher gross market value offer price. After the sale, seller regret aversion becomes strong when the seller's house is subsequently sold for 10% or more than the all-cash buyer paid, but regret aversion is mitigated with communication of the improvements made to enhance the selling price. We further find that sellers do not know which all-cash buyer's Automated Valuation Model (AVM) is the most accurate and are therefore much more influenced by brand awareness than model sophistication. 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author	Anderson, Jackson T.
spellingShingle	Anderson, Jackson T. misc brokerage misc experiment, regret aversion misc FinTech misc housing misc iBuyer misc pricing strategies misc PropTech iBuyer’s use of PropTech to make large-scale cash offers
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topic_title	26 00 DE-206 The expansion of iBuyer's use of PropTech to major housing markets raises a series of questions for both buyers and sellers when making instant, all-cash offers. This study uses a sequence of experiments to identify the proper implementation of existing behavioral real estate concepts to improve the iBuying process, a burgeoning area of residential real estate. We find strong evidence of anchoring for all-cash offers in that sellers are nearly twice as likely to transact when they are first presented with the net proceeds offer price (market value minus costs) rather than starting with the higher gross market value offer price. After the sale, seller regret aversion becomes strong when the seller's house is subsequently sold for 10% or more than the all-cash buyer paid, but regret aversion is mitigated with communication of the improvements made to enhance the selling price. We further find that sellers do not know which all-cash buyer's Automated Valuation Model (AVM) is the most accurate and are therefore much more influenced by brand awareness than model sophistication. Finally, while the extant literature has examined offer price strategies for home sellers, this is the first investigation of buyer offer price strategies. In stark contrast to selling strategies, pricing strategies do not matter when making an offer to buy iBuyer’s use of PropTech to make large-scale cash offers Jackson T. Anderson, Franz Fuerst, Richard B. Peiser and Michael J. Seiler brokerage (dpeaa)DE-206 experiment, regret aversion (dpeaa)DE-206 FinTech (dpeaa)DE-206 housing (dpeaa)DE-206 iBuyer (dpeaa)DE-206 pricing strategies (dpeaa)DE-206 PropTech (dpeaa)DE-206
topic	misc brokerage misc experiment, regret aversion misc FinTech misc housing misc iBuyer misc pricing strategies misc PropTech
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title_full	iBuyer’s use of PropTech to make large-scale cash offers Jackson T. Anderson, Franz Fuerst, Richard B. Peiser and Michael J. Seiler
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code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4346</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">46</subfield><subfield code="j">2024</subfield><subfield code="e">1</subfield><subfield code="h">114-135</subfield></datafield><datafield tag="980" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">01</subfield><subfield code="x">0206</subfield><subfield code="b">4555075072</subfield><subfield code="y">x1z</subfield><subfield code="z">22-07-24</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="b">The expansion of iBuyer's use of PropTech to major housing markets raises a series of questions for both buyers and sellers when making instant, all-cash offers. This study uses a sequence of experiments to identify the proper implementation of existing behavioral real estate concepts to improve the iBuying process, a burgeoning area of residential real estate. We find strong evidence of anchoring for all-cash offers in that sellers are nearly twice as likely to transact when they are first presented with the net proceeds offer price (market value minus costs) rather than starting with the higher gross market value offer price. After the sale, seller regret aversion becomes strong when the seller's house is subsequently sold for 10% or more than the all-cash buyer paid, but regret aversion is mitigated with communication of the improvements made to enhance the selling price. We further find that sellers do not know which all-cash buyer's Automated Valuation Model (AVM) is the most accurate and are therefore much more influenced by brand awareness than model sophistication. Finally, while the extant literature has examined offer price strategies for home sellers, this is the first investigation of buyer offer price strategies. In stark contrast to selling strategies, pricing strategies do not matter when making an offer to buy.</subfield></datafield></record></collection>
score	7.4010878

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iBuyer’s use of PropTech to make large-scale cash offers

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