Multi-level differentiation of short-term rental properties: A deep learning-based analysis of aesthetic design

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dc.contributor.authorZhang, Huihuien
dc.contributor.authorZach, Florian J.en
dc.contributor.authorXiang, Zhengen
dc.date.accessioned2023-09-07T16:34:11Zen
dc.date.available2023-09-07T16:34:11Zen
dc.date.issued2023en
dc.date.updated2023-09-06T20:40:20Zen
dc.description.abstractThis study aims to test the effects of differentiation on short-term rental performance along the dimension of aesthetic design. Online platforms display listing cover photos as search results, thus making aesthetic design a key element of differentiation. We hypothesize opposite impacts in two geographical scopes, local- and city-level, which answers an important question in differentiation literature of whom to compare to. Based on the assumption that localized competition has asymmetric influences, we introduce competition intensity as moderator. Hypotheses are tested with 96,196 listings from April 2021 to March 2022 in the Texas Airbnb market. We quantify aesthetic design by probability distribution scores over four design styles predicted by a pre-trained machine learning model. This study identifies differentiation benefits at local-level but discounts at city-level. Furthermore, it shows market intensity strengthens benefits and mitigates discounts regardless of the geographic scope. Finally, implications for aesthetic design as a strategic tool are discussed.en
dc.description.versionAccepted versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1016/j.tourman.2023.104832en
dc.identifier.issn0261-5177en
dc.identifier.orcidZach, Florian [0000-0003-0243-4913]en
dc.identifier.urihttp://hdl.handle.net/10919/116235en
dc.identifier.volume100en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S0261517723001140en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectshort-term rentalen
dc.subjectaesthetic designen
dc.subjectdeep learningen
dc.subjectdifferentiationen
dc.subjectconformityen
dc.subjectlocalized competitionen
dc.subject3504 Commercial servicesen
dc.subject3508 Tourismen
dc.titleMulti-level differentiation of short-term rental properties: A deep learning-based analysis of aesthetic designen
dc.title.serialTourism Management: Research, Policies, Practiceen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dcterms.dateAccepted2023-08-22en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Pamplin College of Businessen
pubs.organisational-group/Virginia Tech/Pamplin College of Business/Hospitality and Tourism Managementen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Pamplin College of Business/PCOB T&R Facultyen

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