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This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.

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.

The aim of this article states that in each stage of the industrial revolution, only a few initiatives have been real game changers. In Industry 3.0, “Internet of Information” has transformed the business landscape via connectivity and communications. Enterprises could come together to spur innovation in a cooperative or competitive manner. In Industry 4.0, the “Internet of Value” has shown considerable benefits; and, blockchain technology is expected to touch all layers of a business ecosystem, and the construction industry is not an exception.

This study aims to answer the “How do enterprise blockchain solutions contribute to the vibrancy of the construction ecosystem from social, economic, and environmental aspects?” Following a comprehensive literature review, the Grey Ordinal Priority Approach (OPA-G) is employed in multiple criteria decision analysis (MCDA). OPA-G can select functionally rich enterprise blockchain solutions that meet the needs of the future construction industry, while there is uncertainty in the input data.

The results from the case study show that organization under observation welcomes an enterprise blockchain solution that delivers services related to “renewable energy certificates” in the context of “smart cities and built environment”. Employing high-ranked blockchain solutions brings vibracy and sustainability to construction ecosystem in terms of “C₆. decentralized finance and investment,” “C₃. multi-party and cross-industry collaboration,” and “C₈. data-driven value creation”.

At the micro level, blockchain solutions automate processes, streamline operations, and build new capacities on a new business model. At the macro level, blockchain creates a vibrant ecosystem based on transparency, decentralization, consensus-based democracy, interoperability, etc. Indeed, the capability of blockchain solutions at an enterprise scale (enterprise blockchain solutions) can shape a new construction ecosystem. The practical implications of current research are preparing executives for a fundamentally different next normal in construction.

This paper aims to examine the effects of investor sentiment on the development of the real estate corporate bond market in Vietnam.

The research uses an autoregressive distributed lag (ARDL) model with quarterly data. Additionally, the study employs Google Trends search data (GVSI) related to topics such as “Real Estate” and “Corporate Bond” to construct a sentiment index.

The empirical outcomes reveal that real estate market sentiment improves the growth of the real estate corporate bond market, while stock market sentiment reduces it. Also, there is evidence of a long-run negative effect of corporate bond market sentiment on the total value of real estate bond issuance. Further empirical research evidences the short-term effect of sentiment and economic factors on corporate bond development in the real estate industry.

Due to difficulties in collecting data, this paper has the limited sample of 54 valid quarterly observations. Moreover, the sentiment index based on Google search volume data only reflects the interest level of investors, not their attitudes.

These results yield important implications for policymakers in respect of strengthening the corporate bond market platform and maintaining stability in macroeconomic and monetary policies in order to promote efficient and sustainable market development.

The study offers some suggestions for regulators and governments to improve the real estate corporate bond market.

This is the first quantitative study to examine the effect of sentiment factors on real estate corporate bond development in Vietnam.

Many studies have analysed the impact of various variables on the ability of companies to raise capital. While most of these studies are sector-agnostic, literature on the effects of macroeconomic variables on sectors that established over the last 20 years like property technology and financial technology, is scarce. This study aims to identify macroeconomic factors that influence the ability of both sectors and is extended by real estate variables.

The impact of macroeconomic and real estate related factors is analysed using multiple linear regression and quantile regression. The sample covers 338 observations for PropTech and 595 for FinTech across 18 European countries and 5 deal types between 2000–2001 with each observation representing the capital invested per year for each deal type and country.

Besides confirming a significant impact of macroeconomic variables on the amount of capital invested, this study finds that additionally the real estate transaction volume positively impacts PropTech while the real estate yield-bond-gap negatively impacts FinTech.

For PropTech and FinTech companies and their investors it is critical to understand the dynamic with mac-ro variables and also the real estate industry. The direct connection identified in this paper is critical for a holistic understanding of the effects of measurable real estate variables on capital investments into both sectors.

The analysis fills the gap in the literature between variables affecting investment into firms and effects of the real estate industry on the investment activity into PropTech and FinTech.

Over a long period, even low inflation has an impact on portfolio value and households’ purchasing power. In such a context, inflation hedging should remain an important issue for investors. In particular, long-term investors, who are concerned with the protection of their wealth, seek to hold effective hedging assets. This study aims to demonstrate that residential assets in “Grand Paris” are a hedge against inflation and particularly against its unexpected component.

In this study, the physical residential markets in 127 communes in Paris and the Parisian first-ring suburbs are considered as potential asset classes. We simplified the analysis by clustering the 127 communes into five homogenous groups using ascending hierarchical classification (AHC). Then, we test the hedging ability of these groups within a mixed asset portfolios using both correlation and regression analysis.

This paper presents an analysis of the “Grand Paris” housing market and its inflation hedging ability with comparison to other financial asset classes. Results show that the five housing groups act as a highly positive hedge against unexpected inflation. Furthermore, cash and bonds seem to provide, respectively, a partial and an over hedge against unexpected inflation. Stocks act as a perverse hedge against unexpected inflation and provide no significant hedge against expected inflation. Also, indirect listed real estate demonstrates little correlation with inflation, which makes us reject its hedging ability contrary to physical residential real estate.

The inflation topic: although several researches exist that question the hedging property of real estate, very few concentrate on physical residential assets and to the best of the authors’ knowledge, this study is the only one that targets the “Grand Paris” area. Residential assets of the “Grand Paris” communes are confirmed to be a hedge against inflation and particularly against its unexpected component thanks to its capital appreciation rather than income one. Also, we show that the listed real estate in France (Sociétés d’Investissement Immobilier Cotée) does not provide the same hedging properties contrary to the US real estate investment trusts (REITs) who demonstrate this ability. Listed real estate could thus not be used interchangeably with housing to protect from inflation in the French market.

Protection of investors against inflation and in particular in the face of its return to France in 2022. Reassuring promoters and investors of the interest of residential investment projects in “Greater Paris” and of the potential that this holds.

Inflation takes a chunk out of the purchasing power of money and thereby erodes the real value of people’s finance. Investors and households who seek protection from inflation erosion should invest in direct housing, and in particular within areas that are experiencing an effective metropolization process.

The originality of the study is precisely relative to the geographical area studied. The latter has experienced favorable economic conditions for several years and offers interesting fundamentals to explore and exploit in investment strategies that prove capable of protecting against imminent inflation. The database is specific to this project and has been built through the compilation of several sources and with the support of BNP Paribas Real Estate.

Foreign direct investment in the real estate (FDIRE) sector is required to bridge the gap between investment needed and domestic funds. Further, foreign direct investment is gaining importance because other sources of raising finance such as External Commercial Borrowing and foreign currency convertible bonds have been banned in the Indian real estate sector. Therefore, the objective of the study is to explore the determinants attracting foreign direct investment in real estate and to assess the impact of those variables on foreign direct investments in real estate.

Johansen cointegration test, vector error correction model along with variance decomposition and impulse response function are employed to understand the nexus of the relationship between various macroeconomic variables and foreign direct investment in real estate.

The results indicate that infrastructure, GDP and tourism act as drivers of foreign direct investment in real estate. However, interest rates act as a barrier.

This article aimed at exploring factors attracting FDIRE along with estimating the impact of identified variables on FDI in real estate. Unlike other studies, this study considers FDI in real estate instead of foreign real estate investments.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

This study attempts to find the response of the real estate market to economic changes by identifying cause-effect relationships between mortgage, residential investment, and Saudi employment.

A quantitative approach to analytically examine the relationship among the variables. To find out the impact of investment, mortgage and Saudi employment on the Saudi real estate growth from 1970 to 2019. All data sets were obtained from the General Authority for Statistics (GAST), Saudi Central Bank (SAMA) and World Bank Group.

This study reveals a positive relationship between the mortgage and GDP in the Saudi Arabian real estate market. The same results for employment and investment; both have a positive effect on the GDP of the real estate market.

Analyzing the impact of real estate financing on various industries and the extent to which it is related to employment and unemployment rates is essential for future research. Moreover, this research can be applied to different countries and compared based on similarities and differences in implementing mortgage-related policies.

The government must encourage investment in various ways and establish a stable structure that ensures market stability and finds a balance between supply and demand.

This study reflects the importance of real estate financing not only to individuals and governments but also to investors and business workers, and it is essential to analyze the impact of real estate financing on various industries, as well as the extent to which it is related to employment and unemployment rates. This research can be applied to different countries and compared based on similarities and differences in the implementation of mortgage-related policies.

This study contributes to testing this study’s hypothesis: that mortgage positively impacts the real estate market of Saudi Arabia.

This paper examines the main drives of encouraging Iranian investors in the Turkish real estate market, focusing on the interface between push factors and pull factors that drive them abroad.

This paper examines the main drives of encouraging Iranian investors in the Turkish real estate market, focusing on the interface between push factors and pull factors that drive them abroad. For this purpose, the trend of housing price growth in Iran and Turkey was compared. The review of the 11-year trend of rates shows that housing prices in both countries have been continuously rising, and these prices have undoubtedly experienced increasing shocks in Iran. For further analysis, 13 main variables leading to the repulsion of investment in Iran's housing market and 15 variables shaping the attractiveness of investment in Turkey were identified in this sector. Thirty experts subsequently ranked the significant variables based on a closed-end questionnaire using quantitative strategic planning matrix. Examining housing investment elasticity in Turkey also shows that “Turkey's economic stability compared to neighboring countries” and “acquiring Turkish citizenship through real estate investment” are among the most important variables. On the other hand, the pressure variables of housing investment in Iran were “decrease in the value of the Iranian currency in recent years,” “currency price fluctuations” and “severe fluctuations and instability in the Iranian housing market.”

Examining housing investment elasticity in Turkey also shows that “Turkey's economic stability compared to neighboring countries” and “acquiring Turkish citizenship through real estate investment” are among the most important variables. On the other hand, the pressure variables of housing investment in Iran were “decrease in the value of the Iranian currency in recent years,” “currency price fluctuations” and “severe fluctuations and instability in the Iranian housing market.”

From a theoretical standpoint, foreign investment is in support of Turkey and harmful to Iran because the Turkish government is bolstering investment attractiveness to bring increased capital inflows into this country. Practically speaking, Turkey has aimed to create a rational framework for investors by strengthening and changing its economic system, as well as amending existing constitutions in this domain. Nevertheless, Iran resists any changes in its economic system and legislation. Therefore, a wide range of attractiveness and repulsion variables has led to the migration of Iranian investors to Turkey. In the present study, such variables are illuminated.