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This study aims to explore the spatial externalities of apartment vacancy rates on housing rent by considering multiple vacancy durations.

This research uses smart meter data to measure unobservable vacant houses. This study made a significant contribution by applying building-level smart meter data to housing market analysis. It examined whether vacancy duration significantly affected apartment rent and whether the relationship between apartment rent and vacancy rate differed depending on the level of housing rent.

The primary finding indicates that there is a significant negative correlation between apartment rent and vacancy duration. Considering the spatial externalities of apartment vacancy rates, the apartment vacancy rates of surrounding buildings did not show any statistical significance. Moreover, quantile regression results indicate that although the bottom 10% of apartment rent levels showed a negative correlation with all vacancy durations, the top 10% showed no statistical significance related to vacancies.

This study measures the extent of spatial externalities that can differentiate taxation based on housing vacancies.

The findings indicate that landlords have asymmetric information about their buildings compared with the surrounding buildings, and the extent to which price adjusts for long-term vacancies differs depending on the level of apartment rent.

This paper aims to explore factors influencing apartment price volatility in the two biggest cities in Vietnam, Hanoi and Ho Chi Minh City.

The study uses the supply and demand approach and provides a literature review of previous studies to develop four main hypotheses using four determinants of apartment price volatility in Vietnam: gross domestic product (GDP), inflation rate, lending interest rate and construction cost. Subsequently, the Vector Error Correction Model (VECM) is used to analyze a monthly data sample of 117.

The research highlights the important role of construction costs in apartment price volatility in the two largest cities. Moreover, there are significant differences in how all four determinants affect apartment price volatility in the two cities. In addition, there is a long-run relationship between the determinants and apartment price volatility in both Hanoi and Ho Chi Minh City.

Limitations related to data transparency of the real estate industry in Vietnam lead to three main limitations of this paper, including: this paper only collects a sample of 117 valid monthly observations; apartment price volatility is calculated by changes in the apartment price index instead of apartment price standard deviation; and this paper is limited by only four determinants, those being GDP, inflation rate, lending interest rate and construction cost.

The study provides evidence of differences in how the above determinants affect apartment price volatility in Hanoi and Ho Chi Minh City, which helps investors and policymakers to make informed decisions relating to the real estate market in the two biggest cities in Vietnam.

This paper makes several recommendations to policymakers and investors in Vietnam to ensure a stable real estate market, contributing to the stability of the national economy.

This paper provides a new approach using VECM to analyze both long-run and short-run relationships between macroeconomic and sectoral independent variables and apartment price volatility in the two biggest cities in Vietnam.

The purpose of this paper is to analyze the social and functional features of micro-apartment and, based on the findings, to demonstrate the projects of modern micro-apartment designed for one or two people, which are implemented in the experimental design.

Based on the analysis of the study of theoretical scientific works on the research topic and from the standpoint of an interdisciplinary discourse the social and economic prerequisites for the demand for such a dwelling are determined and the categories of citizens for whom a micro-apartment is an advantage are identified. Particular attention is paid to the typological boundaries of the study, the generalization and synthesis of sources which is reflected in identifying the features of the functional zoning of a micro-apartment in connection with the needs of residents and determining modern ways to improve the comfort of living.

At the examples of experimental design of micro-apartment for the city of Almaty we substantiated the expanding the existing typology of residential buildings by adding a new type of urban dwelling – a micro-apartment which occupies a niche between apartment housing for permanent residence and traditional hotels.

The content of the study is devoted to the analysis of a micro-apartment as a new type of modern urban dwelling for a single and small-family population. Urban residents’ interest in economical, affordable small-area dwellings as well as the need to study and design micro format dwellings for the modern urban environment is a topical issue.

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.

To achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).

Results of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R² of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.

Therefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.

By adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

The paper employs a unique online user-generated housing search dataset and introduces a novel measure for housing demand, namely “contacts per listing” as explained by hedonic, geographic and socioeconomic variables.

The authors explore housing demand by employing an extensive Internet search dataset from a German housing market platform. The authors apply state-of-the-art artificial intelligence, the eXtreme Gradient Boosting, to quantify factors that lead an apartment to be in demand.

The authors compare the results to alternative parametric models and find evidence of the superiority of the nonparametric model. The authors use eXplainable artificial intelligence (XAI) techniques to show economic meanings and inferences of the results. The results suggest that hedonic, socioeconomic and spatial aspects influence search intensity. The authors further find differences in temporal dynamics and geographical variations.

To the best of the authors’ knowledge, it is the first study of its kind. The statistical model of housing search draws on insights from decision theory, AI and qualitative studies on housing search. The econometric approach employed is new as it considers standard regression models and an eXtreme Gradient Boosting (XGB or XGBoost) approach followed by a model-agnostic interpretation of the underlying effects.

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.

Despite the quantity of collaborations, the vocational network of the housing production in Ankara during its first five years (1923–1928) remains dispersed. The aim of this study is to identify all the actors of housing production and their collaborations which shaped Ankara's urban development as the new capital city.

The study engages with the literature and archival documents to identify the actors of the housing production, i.e. architects, master-builders, public institutions, private companies, contractors and entrepreneurs, and their resultant vocational network in the housing production in Ankara during 1923–1928.

Due to different agendas, such as speculation, financial interests or patriotism, the construction industry in Ankara had become an arena where many paths intersected, forming an intertwined vocational network. The profession of contractor became popular, and local architects, engineers and even individuals of various other professions began to work as mediators for foreign companies and public institutions, which required support especially in large-scale projects.

The dispersed information revealed that the actors of the housing production remained mostly anonymous, or only the famous architects were commemorated; however, others could be found within the lines of the established literature on Ankara and/or in archival documents. This research not only focuses on “salient” actors but also highlights the “silent” actors of the housing production and prepares charts to clarify the vocational network in Ankara during its first five years to contribute to the future studies on Ankara and its housing.

As an important indicator of the quality of life of individuals, residential environments are continuing to evolve, due to the rapidly changing production–consumption relations. However, in this evolving process, the effect of the differentiated residential environments on the individuals' residential satisfaction remains unclear. This paper aims to measure the effects of the varying residential environments on the overall quality of urban life (QoUL) in Kayseri, one of the most developed cities in Central Anatolia.

It is based on empirical data on the quality of life in the different residential environments of Kayseri. The research method used stratified purposeful sampling, and the household survey data were analyzed using factor analysis, multiple regression and ANOVA statistical methods.

The most influential factors on the overall QoUL of individuals living in different Kayseri residential neighborhoods were satisfaction with neighborhood and city-level urban services, neighborhood relations and belonging factor groups. The critical finding obtained in this study is that residential satisfaction in low-rise and compact form housing areas in Kayseri is higher compared to residential satisfaction in high-rise neighborhoods. This result reveals that the high-rise building typology that is dominant in Turkey's big cities should be seriously questioned, and urban development policies should be re-evaluated.

The study was designed to produce baseline data so that future changes in residential conditions as perceived by the residents of Kayseri could be monitored to support decisions for residential areas.

Comparative case studies, particularly on low-rise versus high-rise environments, are scarce. As a result, this research contributes to the field of comparative studies on residential environments.

This paper aims to provide an exemplary application of an indicative post-occupancy evaluation (POE) on an organizational multistorey residential apartment building.

This research comprises of mixed qualitative and quantitative approaches. The methodology commences with a review of the recent literature, identification of performance elements, conduct of walk-through, distribution and collection of users' surveys and the development of short and long-term recommendations, where an adequate sample of users were approached for conducting a focus group interview session.

The research identifies 74 performance elements that were clustered into technical, namely (thermal, acoustic and visual comforts, indoor air quality and safety and security), functional, namely (design adequacy, finishing, furnishing, fittings and equipment and building surroundings) dimensions and behavioral, namely (apartment building attributes and managerial and logistical support). The questionnaire survey aimed to solicit users' opinions upon the occupied case study residential facility.

The research identifies areas of occupants' satisfaction and dissatisfaction in a typical multistorey residential building, as a part of a community housings for a mega organization, located in Saudi Arabia. The identification of these areas serves as a lesson learned for future developments, design considerations and implications. Hence, improving the well-being and comfort of its employees.

House price fluctuations send vital signals to many parts of the economy, and long-term predictions of house prices are of great interest to governments and property developers. Although predictive models based on economic fundamentals are widely used, the common requirement for such studies is that underlying data are stationary. This paper aims to demonstrate the usefulness of alternative filtering methods for forecasting house prices.

We specifically focus on exponential smoothing with trend adjustment and multiplicative decomposition using median house prices for Sydney from Q3 1994 to Q1 2017. The model performance is evaluated using out-of-sample forecasting techniques and a robustness check against secondary data sources.

Multiplicative decomposition outperforms exponential smoothing at forecasting accuracy. The superior decomposition model suggests that seasonal and cyclical components provide important additional information for predicting house prices. The forecasts for 2017–2028 suggest that prices will slowly increase, going past 2016 levels by 2020 in the apartment market and by 2022/2023 in the detached housing market.

We demonstrate that filtering models are simple (univariate models that only require historical house prices), easy to implement (with no condition of stationarity) and widely used in financial trading, sports betting and other fields where producing accurate forecasts is more important than explaining the drivers of change. The paper puts forward a case for the inclusion of filtering models within the forecasting toolkit as a useful reference point for comparing forecasts from alternative models.

To the best of the authors’ knowledge, this paper undertakes the first systematic comparison of two filtering models for the Sydney housing market.