Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/27996
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBera, Anil Kumar-
dc.contributor.authorKangallı Uyar, Sinem Güler-
dc.date.accessioned2019-12-06T06:23:24Z-
dc.date.available2019-12-06T06:23:24Z-
dc.date.issued2019-08-
dc.identifier.urihttps://hdl.handle.net/11499/27996-
dc.identifier.urihttps://doi.org/10.1108/JERER-12-2018-0052-
dc.description.abstractPurpose – This paper presents a hedonic office rent model under the decentralized structure of Istanbul Office Market. The data set in the study includes 2,348 office spaces for the first quarter of 2018. This study aims to find determinants that affect the level of rent and examine whether the effects of office rent determinants are global or not. Design/methodology/approach – To consider both global and local effects, the paper uses mixed geographically weighted regression approach in hedonic office rent analysis. Findings – The empirical results indicate that office rent determinants such as physical, locational, neighborhood and market operational characteristics have significant impacts on the level of the rent. The findings also show that one of the office rent determinants has a global effect and the other determinants have local effects. According to the estimation results, local effects and statistical significances of these determinants vary from lower quartiles to upper quartiles. Originality/value – To the best of the authors’ knowledge, this is the first paper to consider global and local effects of office rent determinants on the level of rent, with mixed geographically weighted regression approach. The paper provides new insights into the hedonic valuation of commercial real estates, especially for decentralized office marketsen_US
dc.language.isoenen_US
dc.publisherJournal of European Real Estate Researchen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectIstanbulen_US
dc.subjectHedonic approachen_US
dc.subjectMixed geographically weighted regressionen_US
dc.subjectOffice renten_US
dc.subjectSpatial heterogeneityen_US
dc.titleLocal and global determinants of office rents in Istanbul: The mixed geographically weighted regression approachen_US
dc.typeArticleen_US
dc.identifier.volume12en_US
dc.identifier.issue2en_US
dc.identifier.startpage227en_US
dc.identifier.endpage249en_US
dc.authorid0000-0003-3694-150X-
dc.identifier.doi10.1108/JERER-12-2018-0052-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-85068052381en_US
dc.identifier.wosWOS:000485949300006en_US
dc.ownerPamukkale University-
item.languageiso639-1en-
item.openairetypeArticle-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.dept08.08. Econometrics-
Appears in Collections:İktisadi ve İdari Bilimler Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Files in This Item:
File Description SizeFormat 
Bera_KangalliUyar_2019.pdf52.99 kBAdobe PDFView/Open
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

5
checked on Jun 29, 2024

WEB OF SCIENCETM
Citations

6
checked on Jul 10, 2024

Page view(s)

42
checked on May 27, 2024

Download(s)

18
checked on May 27, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.