Search results

With access to the large-scale search data from Rightmove plc, the paper firstly indicated the possibility of using user-generated data from online property portals to predict housing market activities and secondly embraced a GIS approach to explore what people search for housing and what they chose and investigated the issue of mismatch between search patterns and revealed patterns. Based on the analysis, the paper contributes a visual GIS-based approach which may help planners and designers to make more informed decisions related to new housing supply, particularly where to build, what to build and how many to build.

The paper used the 2013 housing search data from Rightmove and the 2013 price data from Land Registry with transactions made after the search period and embraced a GIS approach to explore the potential housing demand patterns and the mismatch between searches and sales. In the analysis, the paper employed the K-means approach to group prices into five levels and used GIS software to draw maps based on these price levels. The paper also employed a simple analysis of linear regression based on the coefficient of determination to investigate the relationship between online property views and values of house sales.

The result indicated the strong relationship between online property views and the values of house sales, implying the possibility of using search data from online property portals to predict housing market activities. It then explore the spatial housing demand patterns based on searches and showed a mismatch between the spatial patterns of housing search and actual moves across submarkets. The findings may not be very surprising but the main objective of the paper is to open up a potentially useful methodological approach which could be extended in future research.

It is important to identify search patterns from people who search with the intention to buy houses and from people who search with no intention to purchase properties. Rightmove data do not adequately represent housing search activity, and therefore more attention should be paid to this issue. The analysis of housing search helps us have a better understanding of households' preferences to better estimate housing demand and develop search-based prediction models. It also helps us identify spatial and structural submarkets and examine the mismatches between current housing stock and housing demand in submarkets.

The GIS approach in this paper may help planners and designers better allocate land resources for new housing supply based on households' spatial and structural preferences by identifying high and low demand areas with high searches relative to low housing stocks. Furthermore, the analysis of housing search patterns helps identify areas with latent demand, and when combined with the analysis of transaction patterns, it is possible to realise the areas with a lack of housing supply relative to excess demand or a lack of latent demand relative to the housing stock.

The paper proves the usefulness of a GIS approach to investigate households' preferences and aspirations through search data from online property portals. The contribution of the paper is the visual GIS-based approach, and based on this approach the paper fills the international knowledge gap in exploring effective approaches to analysing user-generated search data and market outcome data in combination.

This paper aims to bring together research on housing market area, submarket and household migration into a systems approach that helps us gain a better understanding of the structure and dynamics of a housing market and identify housing problems for a large metropolitan area.

The paper uses a geographic information system (GIS)-based method with simple quantitative techniques, including spatial analysis, location analysis, house price clustering and cross-tabulation. The analysis is based on migration data from the 2011 Census, house price data from the Land Registry in 2011 for Greater Manchester at the ward level and the output areas level.

The results show that different submarkets and housing market areas had different patterns of spatial migration and connections with other areas. Through a systematic analysis of migration and house price in combination, it also found a close connection between destination submarkets and the ages of migrants and identified specific problematic patterns for a large metropolitan area.

The interactions between the owner-occupied sector and the social and private rented sectors are arguably an important omission from the analysis. Also, it is acknowledged that clustering ward units based on price differentials is subject to distortions in terms of specification, size and shape. Moreover, the use of the large samples may result in very small p-values, leading to the problem of the rejection of the predefined hypothesis.

A systematic analysis of migration and house price in combination may be used to gain a better understanding of the housing market dynamics and identify housing problems systematically for a large metropolitan. It may help to identify low-demand areas, high-demand areas and assist planners with decisions in allocating suitable land for new housing constructions.

The GIS-based method introduced in the paper could be considered as an effective approach to provide a better basis for determining policy interventions and public investment designed to allocate land resources effectively and improve transport systems to change existing problematic migration patterns.

This paper fills a gap in the international literature in relation to adopting a systems approach that analyses migration and house price data sets in combination to systematically explore migration patterns and linkages and identify housing problems for a large metropolitan area. This systems approach can be applied in any metropolitan area where migration and house price data are available.

A panel error correction model has been developed to investigate the spatial correlation patterns among house prices. This paper aims to identify a dominant housing market in the ripple down process.

Seemingly unrelated regression estimators are adapted to deal with the contemporary correlations and heterogeneity across cities. Impulse response functions are subsequently implemented to simulate the spatial correlation patterns. The newly developed approach is then applied to the Australian capital city house price indices.

The results suggest that Melbourne should be recognised as the dominant housing market. Four levels were classified within the Australian house price interconnections, namely: Melbourne; Adelaide, Canberra, Perth and Sydney; Brisbane and Hobart; and Darwin.

This research develops a panel regression framework in addressing the spatial correlation patterns of house prices across cities. The ripple-down process of house price dynamics across cities was explored by capturing both the contemporary correlations and heterogeneity, and by identifying the dominant housing market.

This study aims at understanding the reasons causing the decline in the practice of traditional, regional architectural methods of creating house forms in the Khasia Punji at Jaflong, Sylhet area.

Two main types of traditional and modern house forms were identified and studied in order to document and analyze the aspects of changes in the construction method and material uses, while the interviews together with observational, qualitative and descriptive study formed an insight into the changing socio-cultural dynamics and evolving lifestyle of the tribe. Apart from physical surveys, the primary data on settlement patterns over twenty years' time were reviewed through satellite imaging while the characteristics of local house forms were also collected from tourist photographs through time recorded in Google database.

The findings of this research have pointed out that in the case of the Khasi tribe, the shift in temporal context, accompanied by a shift in technological, socio-cultural and economic aspects, is fueling the transformation in the formal expression, material and methods of the house building.

Limitations were posed in setting up more constructive and informative interview sessions with the Khasi people due to the coronavirus disease 2019 (COVID-19) situation which limited the survey outcomes in general.

The scope of this study is to understand the changes and advances in socio-cultural, technological aspects of a society and their impact on the intricate patterns of life and customs that are evidently reflected in the transformation of built environments.

This research attempts to understand the causes behind the transformation of vernacular house forms, taking place in the Khasi village of Jaflong, Sylhet.

This research introduces a hypothesis for establishing typologies and patterns for architectural plans based on their climate, culture and orientation. The repetition and reproduction of spaces in architectural plans are rooted in mathematical equations. Factorial and permutation formulae are the type of equations used as scientific tools to define typology. In addition, a new perspective on culture and privacy in line with the Arabic house is included to illustrate the practicality of restricted plans according to cultural needs.

To make the approach accessible, the theory is integrated into a software using C++ as the programming tool. Accordingly, all patterns and typologies are reproduced by inserting digits or numbers to simulate the process of using permutations and factorials for the creation of diagrammatic patterns and, subsequently, architectural plans.

The authors recommend that this method be integrated in future housing studies at earlier stages to obtain a high number of alternatives for architectural plans. The results of mathematical permutation of this study will help architects and designers to evolve their methods and processes through creating alternative patterns and culture (and climate)-specific typologies to provide more design possibilities.

This study is set to improve the adjacency diagram theory into the adjacency diagram with orientation theory, which accounts for the geographical orientation to obtain more comprehensive and climate-responsive patterns.

The purpose of this paper is to compare rural houses reconstructed by core housing method after the Manjil earthquake in 1990 and traditional housing. Also, other factors such as residential space needs of residents, the role of the used structure in building the core units and the role of climatic conditions in the expansion of residential units have been investigated.

Some rural houses which were reconstructed by using core housing method – 86 rural houses – in 20 different villages were investigated using quantity and quality method. Also, the rate of satisfaction of inhabitants with their reconstructed houses was evaluated.

Although rural houses were reconstructed with inhabitants' participation and with use of local technology and materials, those houses had some characteristics contrary to traditional houses. Another problem was in the gradual expansion of spaces, which led to disharmonious and unbalanced growth and converted the houses into a complex and closed entity. It caused trouble in privacy and connections of family members and in the use of spaces.

The paper reports research generally done on rural houses which were reconstructed after the Manjil earthquake in 1990 and shows that this reconstruction experience was done by using core housing method. Also, how the core units were expanded was analyzed and advantages and disadvantages of this reconstruction experience were extracted. These results can be useful in planning and designing shelters for survivors of future disasters.

Many people living in and around Mumbai face space scarcity within homes, an issue exacerbated for families with members having differing and conflicting spatial requirements. By investigating how families live in existing residential environments, planners and designers can enable families to cope better with space scarcity.

A case study approach is used to examine four small home settings in and around Mumbai, followed by a thematic analysis of the data collected.

This study contributes a framework for studying small homes in and around Mumbai wherein they are characterized by five categories of information: internal zoning pattern, expansion pattern, spatial specialization and stratification pattern, outdoor space appropriation pattern and household adjustment pattern. Analysis through this framework gives insight into how small home settings are used by residents.

To the best of the authors’ knowledge, this is the first study offering in-depth comparative analysis of small home typologies in India.

The paper sets out a conceptualisation of the housing cycle centring on households' desire to upgrade their housing consumption.

The paper begins by studying house price trends and cycles in OECD countries since 2000 to identify housing cycle patterns. It then assesses existing theories partly in relation to these patterns. It then proposes a new conceptualisation of the housing cycle.

The paper finds the central role of supply lags in housing cycles is not warranted. Instead, a demand cycle generated by upgrading desires better explains an initial boom followed by a slow recovery.

The paper challenges existing orthodoxy on housing cycle dynamics and proposes an alternative perspective.

Understandings of house prices and their interrelationships have undoubtedly drawn a great amount of attention from various market participants. This study aims to investigate the monthly newly-built residential house price indices of seventy Chinese cities during a 10-year period spanning January 2011–December 2020 for understandings of issues related to their interdependence and synchronizations.

Analysis here is facilitated through network analysis together with topological and hierarchical characterizations of price comovements.

This study determines eight sectoral groups of cities whose house price indices are directly connected and the price synchronization within each group is higher than that at the national level, although each shows rather idiosyncratic patterns. Degrees of house price comovements are generally lower starting from 2018 at the national level and for the eight sectoral groups. Similarly, this study finds that the synchronization intensity associated with the house price index of each city generally switches to a lower level starting from early 2019.

Results here should be of use to policy design and analysis aiming at housing market evaluations and monitoring.

This paper focusses on analysing the impact of crime on the housing market in Los Angeles (LA) County. By looking at different types of crime instead of general crime measures and controlling by spatial dimension of prices and crime as well as endogeneity, a model is developed that allows for the understanding of how a specific crime impacts the housing market transaction price. To perform the analysis, the paper merges different data sets (crime, housing transaction and census data) and then computes the distances to crucial transport modes to control the accessibility features affecting housing prices. The latter allows estimating the association of housing prices and crime in the distance and estimating the impact on housing depending on it.

This paper focusses on the following crimes: aggravated assault, burglary (property crime), narcotics, non-aggravated assault and vandalism. The paper shows firstly how incidents of reported crime are distributed across space and how they are related to each other – thus highlighting crime models with spatial influences. Secondly, the research utilises instrumental variables within the methodology to estimate house prices using spatial analysis techniques while controlling for endogeneity. Thirdly, it estimates the direct impact of crime on house prices and explores the impact of housing and neighbourhood features.

Results suggest that house transaction prices and crime are closely correlated in two senses. Housing prices are endogenously negatively associated with the levels of narcotics and aggravated assaults. For narcotics, the impact of distance is shorter (1,000 m). However, for burglary, vandalism and non-aggravated assaults, the price reaction suggests a positive association: the further away the crime occurs, the higher the prices. The paper also shows the large spatial association of different crimes suggesting that they occur together and that their accumulation would make negative externalities appear affecting the whole neighbourhood.

The use of a huge database allows interesting findings, but one limitation can be to not have longer time observations to identify the crime evolution and its impact on housing prices.

Large implications as the relationship identified in this paper allow defining precise policies to avoid crime in different areas in LA. In addition, crime has significant but quantitative small effects on LA housing transaction prices suggesting that the effect depends on the spatial scale as well as lack on information about where the crimes are committed. Lack on information suggests low transparency in the market, affecting the transaction decision-taken process, affecting the risk perception and with relevant implications over household welfare.

This paper relates the spatial association among crimes defining the hotspots and their impacts on housing transaction prices.