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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 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.

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.

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 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.