HouSI: Heuristic for delimitation of housing submarkets and price homogeneous areas

Royuela, Vicente; Duque, Juan Carlos

doi:10.1016/j.compenvurbsys.2012.04.005

Cited by 20 publications

(9 citation statements)

References 81 publications

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“…On the other hand, smaller entrepreneurs and valuers, in particular, may also benefit from this study. Specifically, on the basis of the segmentation carried out, appraisers can easily identify similar housing markets to ensure the accuracy of their estimates when valuing residential properties (Royuela and Duque, 2013).…”

Section: Research Implicationsmentioning

confidence: 99%

Housing market heterogeneity and cluster formation: evidence from Poland

Tomal

2021

IJHMA

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Purpose This study aims to identify clusters amongst the county housing markets in Poland, taking into account the criteria of size and quality of the housing stock, as well as price level. In addition, this work is intended to detect the socio-economic factors driving the cluster formation. Design/methodology/approach To group the studied housing markets into homogeneous clusters, this analysis uses a proprietary algorithm based on taxonomic and k-means++ methods. In turn, the generalised ordered logit (gologit) model was used to explore factors influencing the cluster formation. Findings The results obtained revealed that Polish county housing markets can be classified into three or four homogeneous clusters in terms of the size and quality of the housing stock and price level. Furthermore, the results of the estimation of the gologit models indicated that population density, number of business entities and the level of crime mainly determine the membership of a given housing market in a given cluster. Originality/value In contrast to previous studies, this is the first to examine the existence of homogeneous clusters amongst the county housing markets in Poland, taking into account the criteria of size and quality of the housing stock, as well as price level simultaneously. Moreover, this work is the first to identify the driving forces behind the formation of clusters amongst the surveyed housing markets.

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Section: Research Implicationsmentioning

confidence: 99%

Housing market heterogeneity and cluster formation: evidence from Poland

Tomal

2021

IJHMA

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“…Work on the fundamental theory of how best to conduct regionalization analyses, in general, is active and ongoing (Folch and Spielman, 2014;Laura et al, 2015;Kim et al, 2016;She et al, 2017). Although regions are sometimes required purely for statistical purposes (Openshaw, 1977;Spielman and Folch, 2015), regions are often used to model urban residential markets (Royuela and Duque, 2013), social communities (Hipp, 2010;Hipp et al, 2012, political communities (Morrill, 1976;Guo, 2008;Pang et al, 2010;Tam Cho and Liu, 2016;Magleby and Mosesson, 2018), disease clusters (Assuncao et al, 2006), and transit zones (Guo and Bhat, 2007;Li et al, 2014;Chen et al, 2015). 3 Depending on the social process under study and the frame of analysis, these may be larger or smaller than other common notions of how "large" a neighborhood is from the perspective of the expressive literature (Spielman and Singleton, 2015).…”

Section: Fully-exclusive Regionalizations: Bounding the Neighbourhoodmentioning

confidence: 99%

The Dynamics of Urban Neighborhoods: A Survey of Approaches for Modeling Socio-Spatial Structure

Knaap¹,

Wolf²,

Rey³

et al. 2019

Preprint

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For close to a century, researchers from across the disciplines of Urban Studies have developed empirical models for understanding the spatial extent and social composition of urban neighborhoods--and how these dimensions change over time. Unfortunately, however, these techniques have often been developed within disciplinary silos and without broad exposure to other potentially interested constituencies. In this paper, we traverse the literatures of social science, computer science, and statistics to examine a variety of modeling techniques for understanding neighborhood dynamics. We begin our review by examining early concepts of spatial structure first outlined in the Chicago School and discuss how the notions of social ecology and quantitative neighborhood analysis permeated the urban studies for several decades to come. Our survey continues by reviewing contemporary statistical approaches for identifying urban neighborhoods, culminating with the state of the art in subfields known as `geodemographics' and `regionalization'. Following this review, we offer insight into the field's persistent conceptual issues, identify areas ripe for additional research, and highlight newly-developed computational methods that can inform more just and socially equitable public policy, community development, and accountable governance.

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“…Bozkaya et al (2011) have proposed a decision support system including multi-criteria mathematical model, tabu search and geographical information system to design the electoral district design for the city of Edmonton. Royuela and Duque (2013) have considered the identification of housing market segmentation and proposed a spatially constrained clustering heuristic for the problem. This heuristic includes the problem specific initial solution construction procedure and tabu search as a local search procedure.…”

Section: Districting Problemmentioning

confidence: 99%

District Design and Route Planning for Customer-Related Field Operations of Natural Gas Distribution Systems: A Case Study

Atasagun¹,

Akhüseyin²,

Kara³

et al. 2018

Scitech

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Approximately 24% of the world energy requirement is supplied by natural gas. A natural gas distribution system in a city consists of four main processes, i.e. construction, operating, internal installations, and customer services, which are connected to each other. In this study, customer services processes of the distribution system which are directly related to customers is considered. Mathematical formulations are presented for customer services processes such as district design, route planning and mobile team workload assignment, and applied on one of the authorized natural gas distribution company in Turkey. Performance of the proposed formulations is compared with the current system by means of the number of mobile teams and amount of workloads. The computational studies show that the number of mobile teams of the proposed system is 37% lower than the current system.

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HouSI: Heuristic for delimitation of housing submarkets and price homogeneous areas

Cited by 20 publications

References 81 publications

Housing market heterogeneity and cluster formation: evidence from Poland

Housing market heterogeneity and cluster formation: evidence from Poland

The Dynamics of Urban Neighborhoods: A Survey of Approaches for Modeling Socio-Spatial Structure

District Design and Route Planning for Customer-Related Field Operations of Natural Gas Distribution Systems: A Case Study

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