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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.

This study aims to examine the impact of some real variables such as real effective exchange rates, real mortgage rates, real money supply, real construction cost index and housing sales on the real housing prices.

This study uses a nonlinear autoregressive distributed lag (NARDL) model in the monthly period of 2010:1–2021:10.

The real effective exchange rate has a positive and symmetric effect. The decreasing effect of negative changes in real money supply on real housing prices is higher than the increasing effect of positive changes. Only positive changes in the real construction cost index have an increasing and statistically significant effect on real house prices, while only negative changes in housing sales have a small negative sign and a small increasing effect on housing prices. The fact that the positive and negative changes in real mortgage rates are negative and positive, respectively, indicates that both have a reducing effect on real housing prices.

This study suggests the first NARDL model that investigates the asymmetric effects on real housing prices instead of nominal housing prices for Turkey. In addition, the study is the first, to the best of the authors’ knowledge, to examine the effects of the five real variables on real housing prices.

This study aims to merge the world’s proven ways of housing finance, including musharakah mutanaqisah, housing cooperatives and real estate crowdfunding, to present an alternative housing unaffordability solution based on the Islamic finance principle. It is intended to reduce the burden of funding for both sides (consumers and developers) and create win–win chances for all stakeholders, including intermediaries. By moving away from debt financing and merging the features of crowdfunding and cooperative, it is hopeful that the burden of home ownership will no longer be the case.

This paper presents the opinions of potential Chinese homebuyers (minority Muslims and most non-Muslims) and a few industry experts toward the proposed model via a mixed research method.

According to the findings, the majority of respondents agreed with the proposed paradigm. Just concerned that China’s lack of community culture and trust could pose a major threat to implementation. However, this paper argues that Chinese local governments may perform pilot testing in places where Islamic culture is prevalent. Their unique community culture and fundamental understanding of Shariah law may affect the viability of the proposed model.

The proposed model would increase the applicability of Islamic finance as a way of protecting the social order of communities in the spirit of upholding justice and fairness. A new type of housing loan based on musharakah mutanaqisah may squeeze out the real estate bubble and provide stakeholders with a multidimensional investment channel. In particular, the study identifies the impact of Chinese Islamic financing on government and cultural needs. It presents possible challenges for implementing the proposed model in reality and helps bridge the gap between theory and practice.

The purpose of this study is to examine the buyers’ preferences influencing the purchase of privately developed affordable housing in Kolkata and to determine whether unsold houses result from misalignment with these preferences.

The literature review and user-opinion survey identified 119 independent variables that indicate buyers’ preferences. A questionnaire survey of 383 households in affordable housing units from 32 housing complexes in Kolkata recorded buyers’ preferences and satisfaction against the independent variables grouped under five levels of characteristics. The product weights of variables derived from the rank sum method and percentage satisfaction give the Utility Score. Multivariate regression and univariate linear regressions were conducted to determine the significance of each Level of characteristics and each variable, identifying the significant variables that would affect the sale of affordable houses.

The multivariate regression analysis has indicated that 68.56% of the variation in the percentage of unsold houses was explained by the five utility scores, which affirms that misalignment with buyers’ preferences significantly affects the sale of privately developed affordable houses. Furthermore, building and neighbourhood-level utility show the highest significance as predictors, while city-level and miscellaneous utility have moderate significance, but housing complex-level utility lacks statistical significance.

This study addresses a research gap in privately developed affordable housing in Kolkata, enhancing understanding of buyer preferences in this segment.

This study aims to present the variations of optimal seismic control of reinforced cement concrete (RCC) structure using different structural systems. Different third-dimensional mathematical models are used to examine the responses of multistory flexibly connected frames subjected to earthquake excitations.

This paper examined a G + 50 multi-storied high-rise structure, which is analyzed using different combinations of moment resistant frames, shear walls, seismic outrigger systems and seismic dampers to observe the effectiveness during ground motion against soft soil conditions. The damping coefficients of added dampers, providing both upper and lower levels are taken into consideration. A finite element modeling and analysis is generated. Then the nature of the structure exposed to ground motion is captured with response spectrum analysis, using BNBC-2020 for four different seismic zones in Bangladesh.

The response of the structure is investigated according to the amplitude of the displacements, drifts, base shear, stiffness and torsion. The numerical results indicate that adding dampers at the base level can be the most effective against seismic control. However, placing an outrigger bracing system at the middle and top end with shear wall can be the most effective for controlling displacements and drifts.

The response of high-rise structures to seismic forces in Bangladesh’s soft soil conditions is examined at various levels in this study. This study is an original research which contributes to the knowledge to build earthquake resisting high-rises in Bangladesh.

Over the years, the significance of retrofitting has gained much attention with the unveiling of its different applications, such as energy retrofit and deep retrofit, to enhance the climate-resilience of buildings. However, no single study comprehensively assesses the climate-resilience of retrofitting. The purpose of this study is to address this gap via a systematic literature review.

Quality journal studies were selected using the PRISMA method and analysed manually and using scientometrics. Three dimensions of climate-resilience, such as robustness, withstanding and recovery, were used to evaluate the contribution of retrofit measures for achieving climate-resilient houses across four climate zones: tropical, arid, temperate and cold.

Most passive measures can enhance the robustness of residential buildings but cannot verify for withstanding against immediate shocks and timely recovery. However, some passive measures, such as night-time ventilation, show excellent performance over all four climate zones. Active measures such as heating, ventilation and air conditioning and mechanical ventilation with heat recovery, can ensure climate-resilience in all three dimensions in the short-term but contribute to greenhouse gas emissions, further exacerbating the long-term climate. Integrating renewable energy sources can defeat this issue. Thus, all three retrofit strategies should appropriately be adopted together to achieve climate-resilient houses.

Since the research is limited to secondary data, retrofit measures recommended in this research should be further investigated before application.

This review contributes to the knowledge domain of retrofitting by assessing the contribution of different retrofit measures to climate-resilience.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

The purpose of this paper is to understand if and how industrialized house building (IHB) could support productivity developments for housebuilding on project and industry levels. The take is that fragmentation of construction is one explanation for the lack of productivity growth, and that IHB could be an integrating method of overcoming horizontal and vertical fragmentation.

Singe-factor productivity measures are calculated based on data reported by IHB companies and compared to official produced and published research data. The survey covers the years 2013–2020 for IHB companies building multi-storey houses in timber. Generalization is sought through descriptive statistics by contrasting the data samples to the used means to control vertical and horizontal fragmentation formulated as three theoretical propositions.

According to the results, IHB in timber is on average more productive than conventional housebuilding at the company level, project level, in absolute and in growth terms over the eight-year period. On the company level, the labour productivity was on average 10% higher for IHB compared to general construction and positioned between general construction and general manufacturing. On the project level, IHB displayed an average cost productivity growth of 19% for an employed prefabrication degree of about 45%.

Empirical evidence is presented quantifying so far perceived advantages of IHB. By providing analysis of actual cost and project data derived from IHB companies, the article quantifies previous research that IHB is not only about prefabrication. The observed positive productivity growth in relation to the employed prefabrication degree indicates that off-site production is not a sufficient mean for reaching high productivity and productivity growth. Instead, the capabilities to integrate the operative logic of conventional housebuilding together with logic of IHB platform development and use is a probable explanation of the observed positive productivity growth.

Community centers play a socio-economic and urban role of combining different communal necessities, that serve inhabitants, at different neighborhoods in cities. Their role emerged in importance as being a hub for improving and customizing quality of life experiences of the public. This research presents a code-based risk assessment tool for evaluating fire safety measures that can be adapted in the context of community centers. It also provides an exemplary case study to demonstrate its application.

The study identified the factors that render community centers as a high-risk type of facilities in fire events. Various fire codes and standards were reviewed to describe the relevant fire safety measures. A code-based fire risk assessment tool was developed and implemented, through a case study. A set of recommendations were developed to improve the fire safety conditions of the case study facility.

Several violations to fire safety were identified in the case study building. The findings led to identifying a set of recommendations to improve its fire safety conditions.

This research introduced a systematic approach to raise awareness about fire incidences and consequences in community centers, and provides facilities managers with a tool, to assess compliance based on international fire code requirements.

In fire events, community centers are considered as high-risk facilities that may lead to significant losses of human lives and damages to assets. It is significant to study the causes of fire, for ensuring effective prevention and safe operations.