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The purpose of this paper is to unveil how Johor Bahru resident’s conceptions are affected by various structural housing attributes. The determination of an appropriate combination of housing preferences requires a great deal of involvement to balance a complex interplay of factors. This is attributable to this fact that housing preferences involve multiple-criteria decision-making, as each element has its own perceived relative importance. Accordingly, this study examines the resident housing preferences of Johor Bahru located in southern Malaysia with specific emphasis on the priority of structural attributes of housing preferences.

Using data collected through the theoretical and conceptual framework of non-structural fuzzy decision support system (NSFDSS) applied to facilitate the priority setting process.

Priority lists of preferences for structural housing attributes showing the contribution of each factor within their respective level and not the contribution of that factor toward the overall housing preferences were established.

By providing primary information about how potential buyers of a new house prioritize the different elements of a house design, the obtained results can make a useful contribution to the knowledge of individuals engaged in the housing development industry.

While in examining consumers’ housing choice and preferences, most studies use the hedonic price framework studying the issue from several aspects, this is first study dedicated to establish a priority of housing attribute using NSFDSS.

Many of the existing senior living accommodation options in Malaysia are ill-suited to the needs and requirements of seniors as they age further. To establish best practice guidance to meet the housing needs for seniors, the purpose of this paper is to examine the effect of neighbourhood quality, locational and structural attributes on the likelihood of owning a retirement home among the young-old aged 60 to 74 years in Malaysia.

In this paper, 300 young-old retirees from Greater Kuala Lumpur, Malaysia were interviewed using purposive sampling. Only 240 were used for the analysis.

The results revealed that respondents are likely to own the retirement home which could support their overall health and well-being within a safe and supportive senior-friendly neighbourhood. Furthermore, respondents are willing to reside in the retirement home that is served with good access to amenities.

The likelihood of young-old seniors adjusting their housing disequilibrium situation is higher as long as the right housing attributes are incorporated into the retirement home.

The results of this paper would be very pertinent for the development of the physical planning guidelines on settlements and facilities for the elderly in Malaysia.

With the change in cultural values, the increasing life expectancy in senior adult population and improved household income in Malaysia, there is great potential for purpose-built senior housing projects for seniors who need help with activities of daily living, but desire to live as independently as possible.

This paper presents a procedure for considering interactions of neighbourhood quality and property specifics within hedonic models of housing price. It handles interactions between geographical factors and the marginal contribution of each property attribute for enhancing values assessment. Making use of simulation procedures, it is combining GIS technology and spatial statistics to define principal components of accessibility and socio‐economic census related to transaction prices of single‐family homes. An application to the housing market of the Quebec Urban Community (more than 3,600 bungalows transacted in 1990 and 1991) illustrates its usefulness for building spatial hedonic models, while controlling for multicollinearity, spatial autocorrelation and heteroskedasticity. Distance‐weighted averages of each property attribute in the neighbourhood and interactions of property attributes with each principal component are used to detect any spatial effect on sale price variations. This first‐stage spatial hedonic model approximates market prices, which are then used in order to compare “expected” and actual property tax amounts, which are added to obtain a second‐stage model incorporating fiscal effects on house values. Interactions between geographical factors and property specifics are computed using formulae avoiding multicollinearity problems, while considering several processes responsible for spatial variability. For each property attribute, they define sub‐models which can be used to map variations, across the city, of its marginal value, assessing the cross‐effect of geographical location (in terms of neighbourhood profiles and accessibility to services) and its own valuation parameters. Moreover, this procedure distinguishes property attributes, exerting a stable contribution to value (constant over the entire region) from those whose implicit price significantly varies over space.

Tobler's law of geography states that things that are close to one another tend to be more alike than things that are far apart. In this regard, the spatial pattern of price distribution is defined by the arrangement of individual entities in space and the geographic relationships among them. The purpose of this paper is to provide emerging findings of research analysing the salient factors which impact on the sale price of residential properties using a spatial regression approach.

The research develops and formulates a geographically weighted regression (GWR) model to incorporate residential sales transactions within the Belfast Metropolitan Area over the course of 2010. Transaction data were sourced from the University of Ulster House Price Index survey (2010, Q1‐Q4). The GWR approach was then evaluated relative to a standard hedonic model to determine the spatial heterogeneity of residential property price within the Belfast Metropolitan Area.

This investigation finds that the GWR technique provides increased accuracy in predicting marginal price estimates, in comparison with traditional hedonic modelling, within the Belfast housing market.

This study is one of only a few investigations of spatial house price variation applying the GWR methodology within the confines of a UK housing market. In this respect it enhances applied based knowledge and understanding of geographically weighted regression.

This paper aims to construct rental housing indices and identify market segmentation for more effective property-management strategies.

The hedonic model was employed to construct the rental indices. Using the k-means++ and REDCAP (Regionalisation with Dynamically Constrained Agglomerative Clustering and Partitioning) approaches, the authors conducted clustering analysis and identified different market segmentation. The empirical study relied on the database of 80,212 actual rental transactions in Beijing, China, spanning 2016–2018.

Rental housing market segmentation may distribute across administrative boundaries. Properly segmented indices could provide a better account for the heterogeneity and spatial continuity of rental housing and as well be crucial for effective property management.

Residential rent might not only vary over space but also interplays with housing price. It would be worth studying how the rental market functions together with the owner-occupied sector in the future.

Residential rental indices are of great importance for policymakers to be able to evaluate housing policies and for property managers to implement competitive strategies in the rental market. Their constructions largely depend on the analysis of market segmentation, a trade-off between housing spatial heterogeneity and continuity.

This paper fills the gap in knowledge concerning segmented rental indices construction, particularly in China. The spatial constrained clustering approach (REDCAP) was also initially introduced to identify regionalised market segmentation due to its superior performance.

The housing/real estate sector is one of the most important sectors in any country. However, existing marketing literature on the home buying behavior and the decision-making process is still in the early stage of development. The purpose of this study is to examine the home buying behavior from the consumers’ perspective in a high-context culture, namely, Kyrgyzstan and its managerial and/or public policy implications to other countries which are at a similar level of socio-economic development as Kyrgyzstan.

Using a questionnaire, data for the study (n = 300) is collected from households in Bishkek, Kyrgyzstan. Personal interviews were used to collect data from the four administrative regions of Bishkek.

Results of this study show that the physical, environmental and financial dimensions of the homes influenced consumers’ home buying intentions. A few statistically significant differences in terms of preferences for the proximity of the property to schools and shopping districts, having public sewer and water connections, and safety characteristics of the neighborhood were found between the first-time homebuyers and the repeat homebuyers.

The most important limitation of the study is the use of convenience sampling. Although the sample size is reasonably large, the selection of the responses was done based on using convenience and connections. Representativeness of the results may be limited.

Along with the physical, environmental and financial dimensions of the homes, home buying is a high-involvement decision; it is not as much of an emotional purchase but rather a main residence and a good long-term value for Kyrgyz households. Both marketing and social stimuli did not have any statistically significant effect on purchase intentions. Therefore, housing and real estate developers should focus on understanding how their offering meets individual customers’ tangible and intangible expectations and assist them in their highly involved decision-making process.

To the best of the authors’ knowledge, this study is the first to conduct an empirical study to analyze the home buying decisions of Kyrgyz households. This study contributes to marketing literature by filling the existing gaps in understanding various facets of the high-context consumers’ home buying decision-making.

This paper aims to examine house price drivers in Dubai, addressing nonlinearity and heterogeneity.

The study applies a combination of linear and nonlinear, as well as quantile regression, specifications to address these concerns and better explain the real-world phenomenon.

The study shows the double-log quantile regression approach is an overarching description of house price drivers, confirming that not only the price of housing and its determinants are non-linearly related but also that their relationship is heterogeneous across house price quantiles. The findings reveal the prevalence of sub-market differentials in house price sensitivity to house attributes such as size (in square meters), location and type of house, as well as government laws. The study also identifies the peaks and deflation, as well as the rebounding nature of the house price bubble in Dubai.

The data used are limited, in that information on only a few house attributes was available. Future research should include data on other house attributes such as house quality, zip codes and composition.

The findings of this study are expected to suggest results with significant ramifications for researchers, practitioners and policy makers. From a policy perspective, there is an obvious interest in understanding whether the price of housing is affected by different attributes differently along its distribution.

This study allows policy makers, developers and buyers of higher-priced houses to behave differently from buyers of lower-priced or medium-priced houses.

Methodologically, it demonstrates alternative linear and nonlinear, as well as quantile regression, specifications to address two increasing concerns in the house price literature: nonlinearity and heterogeneity. Unlike most other studies, this study used a rich data (140,039 day-to-day transactions of 10 years’ pooled data). The Dubai housing market presents an interesting case. UAE (Dubai, in particular) is named as the second-hottest marketplace for global residential property investors, ahead of Singapore, the UK and Hong Kong (Savills plc, 2015).

This paper aims to develop a house price forecasting model to investigate the impact of neighbourhood effect on property value.

Multi-level modelling (MLM) method is used to develop the house price forecasting models. The neighbourhood effects, that is, socio-economic conditions that exist in various locations, are included in this study. Data from the local government area in Greater Sydney, Australia, has been collected to test the developed model.

Results show that the multi-level models can account for the neighbourhood effects and provide accurate forecasting results.

It is believed that the impacts on specific households may be different because of the price differences in various geographic areas. The “neighbourhood” is an important consideration in housing purchase decisions.

While increasing housing supply provisions to match the housing demand, governments may consider improving the quality of neighbourhood conditions such as transportation, surrounding environment and public space security.

The demand and supply of housing in different locations have not behaved uniformly over time, that is, they demonstrate spatial heterogeneity. The use of MLM extends the standard hedonic model to incorporate physical characteristics and socio-economic variables to estimate dwelling prices.

While interior public space can be one of the most important criteria in designing high-rise residential buildings in urban environments in practitioners’ opinion, this study aims at investigating the importance of this criterion from consumers’ lifestyle standpoint. In particular, this study aims to examine the effects of different lifestyle orientations on consumers’ preference for this housing feature. Three relevant lifestyles are investigated including independence, family-orientation and homebody.

Survey data were collected from 331 owners of high-rise apartments in three residential buildings in urban areas.

The research results revealed significant and positive effects of independence and homebody lifestyle orientations on consumers’ preference for interior public spaces. Interestingly, a family-oriented lifestyle was found to negatively moderate the effect of a homebody lifestyle on the preference, providing evidence for possible exclusive impacts of different lifestyle orientations on the preference.

This study emphasizes the exclusive impacts of different lifestyles on consumers’ preference for housing features that need to be considered by developers and marketers when designing consumer positions and marketing strategies.

The purpose of this paper is to construct a hedonic property price index in the segmented housing market.

Three different research questions are investigated. The first considers how to identify separate local housing markets, with the use of a regression‐tree approach, and the second concerns when it is possible to update a price index, with a recursive regression approach. Finally, the question about seasonal adjustment is investigated.

Overall, the hedonic approach is the best method to use. Moreover, the County of Stockholm is not one market in the sense that the market can be represented by only one property price index. It can be best described as a number of different sub‐markets where the property prices grow differently. The results suggest that there exist at least five different price indexes in the County of Stockholm. The results also support that recursive regressions are two appropriate methods to answer the research questions. Here, the empirical analysis suggests that the parameter estimates converge relatively fast toward the estimate using all observations.

The paper illustrates how to derive sub‐markets in the construction of a price index and when to update a price index series.

The introduction of new financial products, such as property derivatives, to the market has made the construction and quality of property price indexes more important. High quality price indexes are vital when it comes to, for example, pricing property derivatives. The paper facilitates this.