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This paper aims to explore the relationship between market pricing and design quality within the development industry. Currently, there is a lack of research that examines real estate at the property level. Development quality is widely believed to have diminished over the past decades, while many investors seem uninterested in the design process. The study aims to address these issues through a pricing model that integrates design attributes. It is hoped that empirical findings will invite broader stakeholder interest in the design process.

The research establishes a framework for assessing spatial compliance across residential developments within London. Compliance is assessed across ten boroughs, with technical space guidelines used as a proxy for design quality. Transaction prices and spatial assessments are aligned within a hedonic pricing model. Empirical findings are used to establish whether undermining spatial standards presents a significant development risk.

Findings suggest a relationship between sale time and unit size, with “compliant” units typically transacting earlier than “non-compliant” units. Almost half of the 1,600 apartments surveyed appear to undermine technical guidelines.

It is suggested that an array of design attributes be explored that extend beyond unit size. Additionally, future studies may consider the long-term implications of design quality via secondary transaction prices.

Practical implications include the development of a more scientific approach to design valuation. This may enhance the position of product design management within the development industry and architectural services.

Social implications may include improvement in residential design.

An innovative approach combines a thorough understanding of both design and economic principles.

The emergence of Covid-19 and its epidemic features have affected many people around the world. Regardless of the physical and psychological problems caused by it, people must isolate themselves from their surroundings. This problem is more intense in urban areas where people live in crowded apartments and high-rise buildings. During the lockdown, residents of such buildings suffered from disconnection from nature, in addition to the lack of communication with others. As most multi-story apartments and residential complexes do not have separate green spaces and do not provide a safe connection to nature for occupants, it is very tough for the residents of these buildings to endure the disease, and occupants are more vulnerable to disease. Accordingly, this study proposes the biophilic design as an effective approach to provide a secure connection with nature in residential complexes and high-rise apartments.

The questionnaire method was used in this study to analyze the raised hypotheses. Two types of residential zones were selected for the survey and comparing the results. One is apartment units without dedicated green space, and the other is villa houses with private green space. Size of the sample population include 300 people (150 residents of an apartment block and 150 residents of villa homes).

Strict restrictions during the pandemic have prevented people from connecting with nature, especially in urban areas, owing to the lack of separated and dedicated green spaces, whereas connection with nature can be healing and lead to relieving anxiety and stress in this era based on the approved research. Accordingly, applying a biophilic approach to the design process would be helpful.

The lack of a biophilic project to observe was one of the limitations of this study. Being an available biophilic project in the surroundings could be very helpful to observe and acquire comprehensive knowledge and experiences from the handlers and users of biophilic buildings.

This study can be beneficial for patients, individuals and occupants of apartments and residential complexes in urban areas who suffer from distance from nature and green spaces during the restrictions of pandemics such as Covid-19.

This study proposes the use of biophilic architecture in the design process of residential complexes and high-rise apartments to provide isolated and dedicated green spaces for occupants, especially during the lockdown when people have been deprived of parks and public green spaces.

This paper aims to assess the overall social housing development, point out factors affecting it and propose some policy implications for social housing development.

The research investigated investors, credit institutions and officials involved in social housing development. Bac Ninh province currently has 51 social housing projects that have been and are being implemented. The hypothetical regression model has seven latent variables and is tested by the criteria through the SPSS25.0 software.

There are 29 factors belonging to seven groups affecting housing development. Their impact rates range from 3.47% to 30.25%.

The study has only identified the factors affecting social housing development but has not undertaken an in-depth assessment of its development status and forecast for the future. Therefore, this gap needs to be further studied. The proposed research method could also be applied when researching social housing developments in other countries around the world.

To develop social housing to meet the needs of the real estate market, it is necessary to improve the policies that have the strongest impact first. Then, it is necessary to improve the factors with a smaller impact.

The study proposes policy implications for faster housing development for low-income people that improve their living standards.

To the best of the authors’ knowledge, the paper has studied for the first time social housing development and the factors affecting it. The paper also shows the level of their impact so that priority policies can be applied to each factor.

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 is the first article to apply a machine learning approach to the analysis of time on market on real estate markets.

The random survival forest approach is introduced to the real estate market. The most important predictors of time on market are revealed and it is analyzed how the survival probability of residential rental apartments responds to these major characteristics.

Results show that price, living area, construction year, year of listing and the distances to the next hairdresser, bakery and city center have the greatest impact on the marketing time of residential apartments. The time on market for an apartment in Munich is lowest at a price of 750 € per month, an area of 60 m2, built in 1985 and is in a range of 200–400 meters from the important amenities.

The findings might be interesting for private and institutional investors to derive real estate investment decisions and implications for portfolio management strategies and ultimately to minimize cash-flow failure.

Although machine learning algorithms have been applied frequently on the real estate market for the analysis of prices, its application for examining time on market is completely novel. This is the first paper to apply a machine learning approach to survival analysis on the real estate market.

This case is mainly about the development journey of Tujia, a unicorn in China's accommodations-sharing sector, as well as the development status of the sector. On December 1, 2011, Tujia.com—China's first medium- and high-end vacation apartment booking platform—was formally launched, and it announced the first round of capital injection in less than half a year after its launch. It completed D and D+ round of financing on August 3, 2015, securing $300 million with an estimated value exceeding $1 billion. The completion of this financing round meant that Tujia formally entered the $1 billion club composed of “unicorn” Internet companies. In June 2016, it announced the strategic M&A of Mayi; in October 2016, it announced its strategic agreement with Ctrip.com and Qunar.com for the M&A of their apartment and homestay businesses. The completion of these transactions manifested the matrix with the four major platforms Tujia, Mayi, Ctrip, and Qunar. Since then, Tujia has become the absolute pacesetter in China's online accommodations-sharing sector.

The sharing economy enables apartment owners to generate income from their assets. “Agoda Homes” is an online travel agent (OTA) that directly competes with Airbnb. A destination has to discover its competitiveness, but few studies have provided an overview of accommodation attributes in each destination, which are crucial to shaping its brand image. This paper aims to illustrate firm-generated content or attributes that apartment owners list about their properties on an OTA platform to comprehend factual information about apartments in each destination with various star ratings and user ratings and to formulate a research model for future studies.

Informational content and accommodation attributes for apartments are automatically collected using a Web scraping tool (the Data Miner). Descriptive statistics and text analysis (word cloud and word frequency) are used to analyze data.

Findings reveal the primary location, facilities, cleanliness and safety attributes for all apartments in each destination, along with star ratings and user ratings. A research framework for scholars is also suggested. Guidelines for stakeholders in the tourism industry are additionally furnished.

This work concentrates on apartments, which have received less attention in the tourism literature. The study gathers factual data from a website to mitigate respondent bias issues inherent in the traditional survey methods.

This paper aims to study the Zabdah housing project residents’ satisfaction on both dwelling and neighborhood levels. In addition, the determinants of residents’ satisfaction are studied.

A mixed methodology approach was used, merging quantitative and qualitative methods. The questionnaire was developed and filled out through structured interviews. Descriptive statistics and multiple linear regression were used to understand the residents’ satisfaction levels. In addition, the chi-square test of independence was used to determine whether demographics and dwelling type were related to residents’ satisfaction.

It was found that the residents’ satisfaction level with Zabdah housing was moderate on both dwelling and neighborhood levels. On the dwelling level, the tiny dwelling areas were a fundamental problem. On the neighborhood level, good neighborhood services were crucial to the success of this project, while the lack of green spaces negatively affected the quality of life of its residents. In addition, the number of family members and dwelling types were critical determinants of residents’ satisfaction.

The findings can be developed into guidelines to govern the creation of better affordable residential environments. Furthermore, the successful dwelling typologies in this project can be modified to be adopted in the future.

To the best of the authors’ knowledge, this is the first study of its kind to explore the relationship of demographics and dwelling type with residents’ satisfaction in affordable housing in Jordan.

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 study aims to evaluate the efficiency of various techniques for enhancing indoor air quality (IAQ) in construction. It analyzed the alterations in the concentration of indoor air pollutants over time for each product employed in controlling pollution sources and removing it, which included eco-friendly substances and adsorbents. The study will provide more precise and dependable data on the effectiveness of these control methods, ultimately supporting the creation of more efficient and sustainable approaches for managing indoor air pollution in buildings.

The research investigates the impact of eco-friendly materials and adsorbents on improving indoor air quality (IAQ) in Dubai's tall apartment buildings. Field experiments were conducted in six units of The Gate Tower, comparing the IAQ of three units built with “excellent” grade eco-friendly materials with three built with “good” grade materials. Another experiment evaluated two adsorbent products (H and Z) in the Majestic Tower over six months. Results indicate that “excellent” grade materials significantly reduced toluene emissions. Adsorbent product Z showed promising results in pollutant reduction, but there is concern about the long-term behavior of adsorbed chemicals. The study emphasizes further research on household pollutant management.

The research studied the effects of eco-friendly materials and adsorbents on indoor air quality in Dubai's new apartments. It found that apartments using “excellent” eco-friendly materials had significantly better air quality, particularly reduced toluene concentrations, compared to those using “good” materials. However, high formaldehyde (HCHO) emissions were observed from wood products. While certain construction materials led to increased ethylbenzene and xylene levels, adsorbent product Z showed promise in reducing pollutants. Yet, there is a potential concern about the long-term rerelease of these trapped chemicals. The study emphasizes the need for ongoing research in indoor pollutant management.

The research, while extensive, faced limitations in assessing the long-term behavior of adsorbed chemicals, particularly the potential for rereleasing trapped pollutants over time. Despite the study spanning a considerable period, indoor air pollutant concentrations in target households did not stabilize, making it challenging to determine definitive improvement effects and reduction rates among products. Comparisons were primarily relative between target units, and the rapid rise in pollutants during furniture introduction warrants further examination. Consequently, while the research provides essential insights, it underscores the need for more prolonged and comprehensive evaluations to fully understand the materials' and adsorbents' impacts on indoor air quality.

The research underscores the importance of choosing eco-friendly materials in new apartment constructions for better IAQ. Specifically, using “excellent” graded materials can significantly reduce harmful pollutants like toluene. However, the study also highlights that certain construction activities, such as introducing furniture, can rapidly elevate pollutant levels. Moreover, while adsorbents like product Z showed promise in reducing pollutants, there is potential for adsorbed chemicals to be rereleased over time. For practical implementation, prioritizing higher-grade eco-friendly materials and further investigation into furniture emissions and long-term behavior of adsorbents can lead to healthier indoor environments in newly built apartments.

The research offers a unique empirical assessment of eco-friendly materials' impact on indoor air quality within Dubai's rapidly constructed apartment buildings. Through field experiments, it directly compares different material grades, providing concrete data on pollutant levels in newly built environments. Additionally, it explores the efficacy of specific adsorbents, which is of high value to the construction and public health sectors. The findings shed light on how construction choices can influence indoor air pollution, offering valuable insights to builders, policymakers and residents aiming to promote public health and safety in urban living spaces.