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Holy cities in India are seeing tremendous gentrification. This study aims to investigate the effect of the changing lifestyle of people towards spirituality and the changing lifestyle's impact on consumer buying behavior on properties in Indian holy cities which has not been studied anecdotally.

The research is exploratory in nature. A questionnaire has been sent to collect primary data through SurveyMonkey. Simple random sampling was used to collect a sample of 450 respondents which was also verified using G* software. The data were analyzed using descriptive statistics and partial least square–structured equation modeling (PLS-SEM).

Findings obtained through the structural model using bootstrapping technique suggest that intrinsic and extrinsic factors are attracting tourists leading to an increase in the demand for real estate in holy cities.

The research findings may vary as per the cultural differences and belief in spirituality, which is subject to perceptual biases in different holy cities.

The traditional determinants of property buying behavior are considered inadequate to attract real estate investments. The inclusion of these behavioral aspects – intrinsic and extrinsic factors may improve the investment inflows in India.

Spirituality connects to the concept of behavioral real estate, where the decision to buy property is largely affected by the emotional attachment of people.

This research adds value to fill the gap by finding out the latent determinant – emotional reasons impacting transnational gentrification in India.

The Chinese housing market has gone through rapid growth during the past decade, and house price forecasting has evolved to be a significant issue that draws enormous attention from investors, policy makers and researchers. This study investigates neural networks for composite property price index forecasting from ten major Chinese cities for the period of July 2005–April 2021.

The goal is to build simple and accurate neural network models that contribute to pure technical forecasts of composite property prices. To facilitate the analysis, the authors consider different model settings across algorithms, delays, hidden neurons and data spitting ratios.

The authors arrive at a pretty simple neural network with six delays and three hidden neurons, which generates rather stable performance of average relative root mean square errors across the ten cities below 1% for the training, validation and testing phases.

Results here could be utilized on a standalone basis or combined with fundamental forecasts to help form perspectives of composite property price trends and conduct policy analysis.

Sustainability has become an integral part of the real estate industry, alongside advancing globalization and demographic development. Due to real estate's influence on greenhouse gas emissions throughout its life cycle, both the regulatory and legal requirements concerning the sustainability of real estate are growing and, as a result of social responsibility, the interest of tenants and investors in sustainable real estate. However, criteria for measuring the ecological sustainability of a real estate investment in the purchase process in order to reduce the risk of including “stranded assets” in the portfolio are missing. This paper aims to address the need to integrate the issue of carbon stranding into existing sustainability rating tools.

Existing tools are examined based on defined criteria to determine whether they are suitable for purchasing a property before suitable tools for purchase are compared. Strengths and weaknesses are identified, which are to be remedied with the scoring tool. Taxonomy regulation is integrated into the existing valuation basis as a legal regulation.

The result is a scoring tool that enables real estate companies to measure and evaluate the ecological sustainability performance of a property during the acquisition process, taking into account the three aspects of sustainability and considering them when determining an appropriate purchase price in line with market conditions. Moreover, the developed tool helps to minimize the risk of acquiring a stranding asset.

The environmental, social and governance (ESG) framework employed in this study does not incorporate governance considerations. While the analysis extensively evaluates the building's environmental and social aspects, it does not extend to examining the governance practices of the companies involved. Thus, the assessment is confined solely to the physical attributes of the property without accounting for broader corporate governance factors.

The developed scoring tool represents a valuable tool for the real estate industry, offering insights into sustainability performance during property acquisitions and providing a structured framework for decision-making. By addressing both certification and taxonomy regulation requirements, the tool contributes to the industry's evolution toward more sustainable and environmentally responsible real estate practices.

In response to the growing importance of sustainability in the real estate industry, this paper introduces a novel scoring tool for evaluating the sustainability of real estate investments during the acquisition process.

The purpose of this paper is to examine whether mandatory disclosure of information accompanying the sale of real estate achieves its aim of informed purchasers.

Using a case study approach focused on mandatory disclosure in South Australia data was collected from interviews and focus groups with key personnel in the property industry involved in the production of information required to fulfil vendors’ disclosure obligations.

The authors found that purchasers are ill-served by a long and complex form of mandatory disclosure with a short time frame that prevents the use of the information provided. Without good form design and increased digital affordances provided by the cadastral and conveyancing systems, mandatory disclosure is insufficient to ensure minimisation of information asymmetry between vendor and purchaser.

To the best of the authors’ knowledge, this is the first Australian qualitative study that examines the utility of mandatory vendor disclosure in real estate sales and the first to consider the impact of the digitalisation of cadastral and conveyancing systems upon the efficacy of mandatory disclosure regimes.

ESG (Environment, Social, Governance) has taken on increased importance in recent years for all stakeholders, with the S dimension now taking on a stronger focus in the real estate space. This paper proposes a new metric to be used in the S space to assess improvements in aspects such as gender equality and cultural diversity in real estate. It adds to the S metrics currently available to see the more effective delivery of the S dimension into real estate investment decision-making.

A new S metric in ESG is proposed and validated. Using this metric, examples regarding gender equality and cultural diversity are assessed among leading real estate players in Australia. This S metric is assessed over a number of time periods to demonstrate the improvements in gender equality and cultural diversity in these major real estate players.

This new S metric is seen to be highly effective and robust in capturing the changes in various aspects of the S dimension in ESG in the real estate space today; particularly concerning gender equality and cultural diversity. It is clearly able to demonstrate the significant changes in increased participation of women at the more senior leadership levels by leading players in the real estate space.

With ESG becoming a critical issue in the real estate sector, issues involved in the S space will take on increased significance going forward. This is critical, as the elements of the S dimension such as gender equality and cultural diversity are important aspects for an effectively functioning real estate industry. The S metric developed in this paper can be used for benchmarking purposes over time, as well as between real estate players, between sub-sections within a real estate organisation, and comparing against other industry sectors. It is also relevant in all organisations, and is not just limited to the real estate sector. Additional metrics in the S space are an important development to further empirically assess the effective delivery of the S dimension of ESG in the real estate sector and more broadly.

This paper specifically proposes this new S metric in ESG in the real estate industry. This is a key issue for the real estate industry going forward at all levels, as it will facilitate a more diverse real estate industry and more effective real estate investment decision-making. This S metric is applicable in all organisational sectors where the S dimension of ESG is important.

This paper investigates the relationship between the sustainable finance disclosure regulation (SFDR) and the performance of unlisted real estate funds.

While existing literature has primarily focused on the impact of voluntary sustainability disclosure, such as certifications or reporting standards, this study addresses a significant research gap by constructing and analyzing the financial J-Curve of 40 funds under the SFDR. The authors employ a panel regression analysis to examine the effects of different SFDR categories on fund performance.

The findings reveal that funds categorized under Article 8 of the SFDR do not exhibit significantly poorer performance compared to funds categorized under Article 6 during the initial phase after launch. On average, Article 8 funds even demonstrate positive returns earlier than their peers. However, the panel regression analysis suggests that Article 8 funds slightly underperform when compared to Article 6 funds over time.

While investors may not anticipate lower initial returns when opting for higher SFDR categories, they should nevertheless be aware of the limitations inherent in the existing SFDR labeling system within the unlisted real estate sector.

To the best of our knowledge, this study represents the first quantitative examination of unlisted real estate fund performance under the SFDR. By providing unique insights into the J-Curves of funds, our research contributes to the existing body of knowledge on the impact of sustainability regulations in the financial sector.

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.

This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.

The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.

These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

These findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.

Using a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

The delay in real estate projects in India is pervasive. Organization and management (O&M) and project management (PM)-related challenges are argued to contribute to project delays. This study examined the O&M and PM factors that cause delays, the level of implementation of various O&M and PM aspects in real estate projects and how the challenges can be alleviated.

Perception surveys among the consumers and relevant stakeholders engaged in real estate projects in the Bhubaneswar and Cuttack regions of India were conducted to collect data on the factors of delay and implementation of the O&M and PM aspects. Relevant statistical methods and structural equation modeling (SEM) were used for data analysis.

Findings suggest that from the O&M point of view, poor decision-making, mishandling of finance, concurrent execution of many projects, diversion and misuse of finance for unrelated activities, lack of PM personnel and poor management contribute to the delay. Further, although the project initiation is satisfactorily done, most of the PM principles are not largely used, thus leading to delay.

The study does have limitations, including its reliance on a perception survey of consumers and stakeholders, a limited sample size and a restricted number of projects. Nevertheless, the study highlights the need to address poor O&M and the insufficient application of PM principles to combat project delays in the Indian real estate sector.

Proper O&M and adequate application of PM will enable professional management of the projects and avoid delay.

Proper O&M and the application of adequate PM would reduce delays in real estate projects. Consequently, conflicts between the companies and consumers might be reduced and housing and infrastructure demands might be met.

The study manifested that the lack of adequate implementation of O&M and PM aspects leads to delays. So, it is theorized that O&M and PM play critical roles in the success of real estate projects. Appropriate implementation of the principles and best practices linked to these aspects might alleviate the challenges of delay in real estate projects in India.

This study aims to study the sensitivity of nonlisted real estate investment companies’ accounting earnings to house prices. This study evaluates whether house price changes determined these companies’ return on equity (ROE) or if other factors influenced the industry’s profitability beyond house price growth.

The authors collected a ten-year sample with the aggregate ROE of Portugal’s real estate investment companies, split by regions, and data on house prices and the per capita gross domestic product as a control variable. The authors ran a national-level time series with the canonical cointegrating regression estimator, which is robust to a small sample size; the authors also performed a regression on regional-level panel data with the common correlated effects mean group estimator, thus allowing slope coefficient heterogeneity and controlling for cross-sectional dependence. The authors also ran ordinary least squares regressions as a means of comparison.

This study found that an increase in the house price is not translated into an increase in the aggregate ROE. The results are robust with a reduced survivorship-biased sample, meaning that even the best-succeeded real estate investment companies do not have their accounting ROE dependent on house price growth.

The sample size is small and specific to one country. This paper did not study the housing market structure to verify whether it operates under monopolistic competition, which could further explain the attained results.

Policy decision-makers should know that there are no excess profits in the real estate investment companies’ industry because of house price growth that could be subject to windfall taxes.

To the best of the authors’ knowledge, the connections between house prices and real estate investment companies’ accounting earnings have never been studied.

Many town centres in England exhibit high retail property vacancies and require regeneration. Several alternatives for the replacement of town centre retail (TCR) have been suggested, one of which is healthcare. The healthcare sector in England is in distress, with the National Health Service (NHS) tackling extensive patient waiting lists, whilst operating from an ageing estate. This paper is an introductory study that uses seven carefully selected personalised surveys to raise academic awareness of the importance and potential of integrating healthcare into town centres and calls for large-scale research to establish the statistical validity of the reported observations.

This study is developed from an interpretative standpoint. Through semi-structured interviews with key stakeholders specific to retail-to-healthcare conversions, this study reports stakeholders' perspectives on opportunities and limitations for such conversions to give direction for large statistical research in the future.

All participants support the integration of healthcare into town centres and agreed that diagnostic services, mental health support and primary care services are appropriate for provision within town centres. The participants advocate large-scale change in town centres in England, with integrated healthcare co-located with complementary services to fit with wider regeneration plans. Participants prefer adaptation of existing buildings where technically feasible and emphasise the importance of obtaining the buy-in of other stakeholders whilst expressing concerns about the uncertainty of capital funding availability.

This is the first study to analyse the practice of retail-to-healthcare conversions in town centres. These are still rare in England and projects are complex. The market experience is limited, and thus, the literature is scarce. This study fills this void and provides a starting point for future quantitative research in this area and informs the new town-planning policies.