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.

摘要

搜索属性本质上是一个多准则空间决策。该决定主要基于三个高层标准，包括家庭需求，建筑设施和位置特征。位置选择受多种特征驱动；包括但不限于环境因素，交通，服务和社区的社会经济地位。本文旨在通过开发七要素分类工具和评估国际房地产网站，通过使用差距分析方法来确定在提供位置选择信息方面理论与实践之间的差距。尽管提供了数字地球数据，但结果表明，房地产网站在提供足够的位置信息以支持有效的空间决策方面表现不佳。根据爱尔兰都柏林的一个案例研究，我们发现尽管附近的数字地球数据可能随时可用于支持决策，但差距仍然存在。我们假设原因是双重的。首先，将位置数据转换为可用信息存在技术挑战。其次，市场可能不希望提供可能被认为是负面的位置信息。在本文的结尾，我们讨论了为房地产决策设计空间决策支持系统所需的关键问题。市场可能不希望提供可能被视为负面的位置信息。在本文的结尾，我们讨论了为房地产决策设计空间决策支持系统所需的关键问题。市场可能不希望提供可能被视为负面的位置信息。在本文的结尾，我们讨论了为房地产决策设计空间决策支持系统所需的关键问题。