Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/220322
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dc.titleEXPLORING THE DETERMINANTS AND PRICING SCHEMES OF MIXED-­USE PROPERTY DEVELOPMENTS IN SINGAPORE
dc.contributor.authorTAN YING ZHEN SAMANTHA
dc.date.accessioned2017-05-17T07:28:46Z
dc.date.accessioned2022-04-22T15:59:28Z
dc.date.available2019-09-26T14:13:55Z
dc.date.available2022-04-22T15:59:28Z
dc.date.issued2017-05-17
dc.identifier.citationTAN YING ZHEN SAMANTHA (2017-05-17). EXPLORING THE DETERMINANTS AND PRICING SCHEMES OF MIXED-­USE PROPERTY DEVELOPMENTS IN SINGAPORE. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/220322
dc.description.abstractSingapore’s projected population of 6.9 million in 2030 poses the great challenge of managing land scarcity, as the commodity of land becomes increasingly valuable. In recent years, the approach of optimising land use with mixed-­use developments has become the leading solution. This dissertation embarks to understand and predict the pricing schemes of Singapore’s growing number of mixed-­use developments. This dissertation seeks to: 1. Analyse the impact of mixed-­use developments on residential property prices; 2. Compare the difference in pricing for the structural and locational attributes of both mixed-­use and non mixed-­use developments; 3. Examine the determinants of a mixed-­use development and identify their critical success factors; and 4. Derive pricing schemes for mixed-­use developments. Mixed-­use developments with at least a retail component (shopping mall) and a residential component (private residential development) were considered for study. Hedonic pricing models and out-­of-­sample tests revealed that: 1. Residential units in residential-­retail and residential-­retail-­office developments command premiums of 13.66% and 9.31% respectively; 2. Homebuyers price attributes of mixed-­use and non mixed-­use developments differently; 3. The critical success factors of a mixed-­use development include its scale, office component and eco-­friendly features; and 4. The prices of mixed-­use developments in the suburban area and Orchard district are most accurately predicted using the regression model for non mixed-­ use developments while the prices of mixed-­use developments in the CBD are best predicted using the mixed-­use developments with determinants regression model. It is worth noting that there are different pricing schemes for the different configurations of mixed-­use. These are important considerations for both developers and homebuyers in the context of a growing market for mixed-­use developments.
dc.language.isoen
dc.sourcehttps://lib.sde.nus.edu.sg/dspace/handle/sde/3690
dc.subjectReal Estate
dc.subjectRE
dc.subjectTu Yong
dc.subject2016/2017 RE
dc.subjectMixed-use Development
dc.subjectRegression Model
dc.subjectSingapore
dc.typeDissertation
dc.contributor.departmentREAL ESTATE
dc.contributor.supervisorTU YONG
dc.description.degreeBachelor's
dc.description.degreeconferredBACHELOR OF SCIENCE (REAL ESTATE)
dc.embargo.terms2017-05-30
Appears in Collections:Bachelor's Theses

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