Spatial Automated Valuation Model (sAVM) – From the Notion of Space to the Design of an Evaluation Tool

João Lourenço Marques*, Paulo Batista, Eduardo Anselmo Castro, Arnab Bhattacharjee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
124 Downloads (Pure)

Abstract

Assuming that it is not possible to detach a dwelling from its location, this article highlights the relevance of space in the context of housing market analysis and the challenge of capturing the key elements of spatial structure in an automated valuation model: location attributes, heterogeneity, dependence and scale. Thus, the aim is to present a spatial automated valuation model (sAVM) prototype, which uses spatial econometric models to determine the value of a residential property, based on identification of eight housing characteristics (seven are physical attributes of a dwelling, and one is its location; once this spatial data is known, dozens of new variables are automatically associated with the model, producing new and valuable information to estimate the price of a housing unit). This prototype was developed in a successful cooperation between an academic institution (University of Aveiro) and a business company (PrimeYield SA), resulting the Prime AVM & Analytics product/service. This collaboration has provided an opportunity to materialize some of fundamental knowledge and research produced in the field of spatial econometric models over the last 15 years into decision support tools.

Original languageEnglish
Title of host publicationComputational Science and Its Applications. ICCSA 2021
PublisherSpringer
Pages75-90
Number of pages16
ISBN (Electronic)9783030869731
ISBN (Print)9783030869724
DOIs
Publication statusPublished - 11 Sept 2021
Event21st International Conference on Computational Science and Its Applications 2021 - Virtual, Online
Duration: 13 Sept 202116 Sept 2021

Publication series

NameLecture Notes in Computer Science
Volume12952
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Computational Science and Its Applications 2021
Abbreviated titleICCSA 2021
CityVirtual, Online
Period13/09/2116/09/21

Keywords

  • Housing market analysis
  • Spatial automated valuation model
  • Spatial econometric models

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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