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dc.contributorDepartment of Building and Real Estate-
dc.creatorChen, JHen_US
dc.creatorYang, LRen_US
dc.creatorAzzizi, VTen_US
dc.creatorChu, Een_US
dc.creatorWei, HHen_US
dc.publisherVilnius Gediminas Technical Universityen_US
dc.rightsCopyright © 2020 The Author(s). Published by VGTU Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.rightsThe following publication Chen, J. H., Yang, L. R., Azzizi, V. T., Chu, E., & Wei, H. H. (2020). Establishing dynamic impact function for house pricing based on surrending multi-attributes: evidence from Taipei city, Taiwan. International Journal of Strategic Property Management, 24(2), 119-129, is available at
dc.subjectFinancial engineeringen_US
dc.subjectHouse pricing theoryen_US
dc.subjectImpact functionen_US
dc.subjectProperty managementen_US
dc.titleEstablishing dynamic impact function for house pricing based on surrending multi-attributes : evidence from Taipei city, Taiwanen_US
dc.typeJournal/Magazine Articleen_US
dcterms.abstractThe objective of the research is aimed for a solution that is to establish the dynamic impact function of surrounding multi-attribute for house pricing. It is also able to measure the ripple effect and allows the hedonic parameter estimates to vary from point-to-point. A comprehensive literature review is carried out to obtain an adequate theoretical basis for the corresponding hypothesis and concepts. The proposed dynamic impact function for multi-attributes is then constructed based on the characteristics of surrounding facilities. Adopting the convenience sampling criteria of 95% confidence level on the data sampling and 10% limit of error in a 5−95% proportion, we collect the empirical data of 39 yearly house sales in the investigated urban areas of Taipei city focusing on housing prices and then utilize them for evaluating and adjusting the function. The actual house price and that of proposed function affected by Mass Rapid Transit (MRT) stations are analysed, resulting in the correlation coefficient at 0.946 (single attribute) and 0.944 (multi-attribute), respectively. The findings support that proposed function can highly represent the house pricing pattern and be an accurate tool for appraisers.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of strategic property management, 2020, v. 24, no. 2, p. 119-129en_US
dcterms.isPartOfInternational journal of strategic property managementen_US
dc.description.validate202006 bcma-
dc.description.oaVersion of Recorden_US
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