Search results

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.

The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies.

The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method.

The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach.

One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets.

The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City.

The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice.

The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.

The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.

This study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.

The model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.

Numerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.

The aim of this paper is to introduce a framework that helps to identify strategic themes on which real estate investors form their strategies. A holistic approach to strategic management in real estate management has enjoyed popularity in corporate real estate research, while similar research has been lacking from the investor-based real estate management.

The research design consists of two main parts: 1) formulating propositions based on existing literature and 2) attempting to validate the propositions through a qualitative interview study with major real estate owners in Finland.

The main finding is that the current real estate investors reflect the transient nature of competitive advantages and assess their strategies accordingly. The companies consider the traditional profitability and revenue growth aspects of their business but also a more long-term future growth dimension. As an outcome, the investors base their strategies on eight strategic themes which are “Innovation”, “ESG”, “Marketing and sales”, “Financial management”, “Leasing management and tenant satisfaction”, “Competitive environment and portfolio management”, “Outsourcing and strategic partnerships” and “Cost and operation optimization”.

This paper opens opportunities for future research concerning different strategies in real estate investment business and their impacts.

The presented framework provides support for real estate investors to create real estate management strategy or to evaluate their current strategy and to recognize operational actions and decisions that are relevant for their strategy.

This paper provides an extension to corporate real estate (CRE) literature by showing that the CRE theories are adaptable to real estate investment and provide value for their strategic management. This paper also contributes to real estate investment literature by providing a well-founded and empirically contested strategic management framework, the IREM framework, for identifying strategic themes on which real estate investors form their strategies.

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.

The purpose of this paper is to study the user experiences of the futures wheel method to investigate its suitability to advance futures thinking in the real estate field.

The user experiences of the futures wheel method are investigated through questionnaire answers of 114 master’s level students and real estate experts taking part in future wheel workshops.

The futures wheel method could enhance future-oriented thinking and decision-making in the real estate field. The respondents see futures thinking as an important skill and recognize several advantages concerning the method.

The futures wheel method bears great potential to be used in the real estate sector and it could be a fruitful addition to the curriculums at different education levels in real estate studies.

Futures thinking is essential when aiming for sustainable decisions in the real estate field which again would benefit the whole surrounding society.

This paper is the first published paper concentrating on the user experiences of the future wheel method in the real estate sector. The benefits and the disadvantages of the method are investigated but also the attitudes indicating the potential of the method to be successfully adopted in the field are analyzed.

This study aims to investigate the impact of international diversification on the value and operating efficiency of European real estate firms.

The study is conducted using a panel fixed effects regression model to estimate the relationship of international diversification with firm value and operating efficiency. International diversification is mainly measured via the negative of the Herfindahl–Hirschman Index (HHI) using property-level data. Firm value and operating efficiency are proxied by financial ratios observed annually from 2002 to 2021 at the firm level.

The results demonstrate that international diversification has a negative effect on firm value. Additionally, it lowers operating efficiency by weakening a firm's ability to generate operating earnings from its assets. By examining whether the reduction in operating efficiency is due to the rental income channel or the capital gains channel, the authors find strong statistical evidence that international diversification negatively impacts capital gains. International diversification is negatively associated with net gains from property valuations (unrealized capital gains) and net profits from property disposals (realized capital gains).

The empirical analysis is limited to Europe.

This paper extends the geographical diversification literature. While existing literature focuses on domestic diversification within the United States, this paper explores the effects of international diversification on European real estate firms. To the extent of the authors' knowledge, this is the first paper to examine the impact of geographical diversification on capital gains.

Real estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. The purpose of this paper is to investigate how real estate firms use big four auditors to signal quality.

The authors use Swedish firm level data containing all limited liability real estate companies in the country to determine the determinants of big four auditors. The data set consists of 34,306 observations and is analyzed through logit regressions.

The results show that big four companies are primarily contracted by large and mature companies, rather than new firms or firms with volatile financial records, although the latter could be expected to have a large need to signal quality. The authors also find that firms listed on the stock market and firms targeting public use real estate are more inclined to use big four companies.

Real estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. No prior study of this area has been detected.

Previous research on automation and job disruption is only marginally related to the real estate industry and its characteristics. This study investigates the effects of digitization on jobs in German real estate sector, in order to assess the proportion of jobs threatened to be replaced by automation. Since Germany is the largest EU economy insights for the German real estate market allow a first approximation for Europe.

An extensive database of the German Federal Employment Agency containing job definitions and occupation titles is matched with real estate criteria to create a subset with the relevant real estate occupations. This data is combined with a database of the German Institute of Employment Research reflecting to what extent tasks within jobs can be automated by current technical capabilities.

For the 286 identified occupations within the real estate sector a weighted average of 47 percent substitution probability through current technological capabilities is derived for tasks within the examined occupations.

This contribution indicates the extent of the structural change the real estate sector has to face due to digitization: One out of two real estate jobs will have to be re-created.

This research quantifies the magnitude of the job killer aspect of digitization in the real estate sector.

Corporate governance principles are living a positive momentum in light of the megatrends reshaping the world. An effective company based on sound governance principles can prevent issues and corporate scandals as the company ensures greater transparency and accountability. Accordingly, this paper aims to investigate the relationship between shareholder-oriented corporate governance mechanisms, value and performances in the real estate sector.

This paper investigates the relationship between corporate governance mechanisms, performance and value in a sample of 111 USA real estate firms. After collecting data from 2014 to 2018, this paper tests the research hypothesis using the linear fixed-effect model.

The results demonstrate a positive impact of shareholder-oriented corporate governance mechanisms on performance and value. In particular, firms with no chief executive officer (CEO) duality and staggered board mechanisms and recognizing excess variable compensation to the firms' executive have a significantly higher Tobin's Q, return on assets (ROA) and price-to-book performance.

The implications are twofold: on the one hand, this motivates shareholders to establish new corporate control mechanisms to maximize value, attract more capital and improve operating performance. On the other hand, this allows investors to direct the investors' resources toward real estate firms with effective corporate governance mechanisms that may return higher performance and value.

Focusing on the real estate industry, where governance is expected to have a lower impact due to solid regulation, especially in real estate investment trusts (REITs), the research allows the formulation of industry-specific inferences that may be generalized for the general market.