Gap analysis in decision support systems for real-estate in the era of the digital earth

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Title: Gap analysis in decision support systems for real-estate in the era of the digital earth
Authors: Rabiei-Dastjerdi, HamidrezaMcArdle, GavinMatthews, Stephen A.Keenan, Peter
Permanent link: http://hdl.handle.net/10197/12630
Date: 2021
Online since: 2021-11-11T14:25:22Z
Abstract: Searching for a property is inherently a multicriteria spatial decision. The decision is primarily based on three high-level criteria composed of household needs, building facilities, and location characteristics. Location choice is driven by diverse characteristics; including but not limited to environmental factors, access, services, and the socioeconomic status of a neighbourhood. This article aims to identify the gap between theory and practice in presenting information on location choice by using a gap analysis methodology through the development of a seven-factor classification tool and an assessment of international property websites. Despite the availability of digital earth data, the results suggest that real-estate websites are poor at providing sufficient location information to support efficient spatial decision making. Based on a case study in Dublin, Ireland, we find that although neighbourhood digital earth data may be readily available to support decision making, the gap persists. We hypothesise that the reason is two-fold. Firstly, there is a technical challenge to transform location data into usable information. Secondly, the market may not wish to provide location information which can be perceived as negative. We conclude this article with a discussion of critical issues necessary for designing a spatial decision support system for real-estate decision making.
Funding Details: European Commission
European Commission Horizon 2020
Type of material: Journal Article
Publisher: Taylor & Francis
Journal: International Journal of Digital Earth
Volume: 14
Issue: 1
Start page: 121
End page: 138
Keywords: Gap analysisDigital earthSpatial decision support systems (SDSS)Spatial dataReal estateDublinResidential choiceSocioeconomic statusHousing pricesAccessibilityNeighborhoodWalkabilityMobility
DOI: 10.1080/17538947.2020.1808719
Language: en
Status of Item: Peer reviewed
ISSN: 1753-8947
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science Research Collection
Business Research Collection

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