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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.

This study examines the relationship between environmental building certification Building Research Establishment Environmental Assessment Method (BREEAM-NL) and office rents in the Dutch office market.

A hedonic price model was used to assess the impact of BREEAM certification on office rents. The study is based on 4,355 rent transactions in the period 2015 to mid-2022, in which 331 transactions took place in certified office buildings and 4,024 transactions in non-certified office buildings.

The results provide empirical evidence on quantitative economic benefits of BREEAM-certified offices in the Netherlands. After controlling for all important office rent determinants, the results show a rental premium for certified office buildings of 10.3% on average. The green premiums highly differ across submarkets and vary between 5.1 and 12.6% in the five largest Dutch cities. Additionally, the results show significant positive correlation between BREEAM-NL label score and rents, whereby better performing buildings generally command higher rents.

The study contributes to the current literature on green building economics by providing, as one of the first, empirical evidence on the existence of financial benefits for BREEAM-certified office buildings in the Dutch office market.

This study investigates information flow of market constituents and global indices at multi-frequencies.

The study’s findings were obtained using the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (I-CEEMDAN)-based cluster analysis executed for Rényi effective transfer entropy (RETE).

The authors find that significant negative information flows among sustainability equities (SEs) and conventional equities (CEs) at most multi-frequencies, which exacerbates diversification benefits. The information flows are mostly bi-directional, highlighting the importance of stock markets' constituents and their global indices in portfolio construction.

The authors advocate that both SE and CE markets are mostly heterogeneous, revealing some levels of markets inefficiencies.

The empirical literature on CEs is replete with several dynamics, revealing their returns behaviour for diversification purposes, leaving very little to know about the returns behaviour of SE. Wherein, an avalanche of several initiatives on Corporate Social Responsibility (CSR) enjoin firms to operate socially responsible, but investors need to have a clear reason to remain sustainable into the foreseeable future period. Accordingly, the humble desire of investors is the formation of a well-diversified portfolio and would highly demand stocks to the extent that they form a reliable portfolio, especially, amid SEs and/or CEs.

本研究擬審查多頻率的及為市場成份的信息流和全球指數。

研究人員使用基於改良完全集合經驗模態分解自適應噪聲(Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise)的聚類分析法,取得Rényi有效轉移熵,藉此得到研究結果。

我們發現、於大部份多頻率,在持續性股票和傳統股票間有顯著的負信息流動,這會增加多樣化的益處。這些信息流大部份是雙向的,這強調了股票市場成份及其全球指數在構建投資組合上的重要性。

我們認為持續性股票市場和傳統股票市場大多為異質市場,這顯示了市場的低效率,而且這低效率的程度頗大。

關於傳統股票的實證性文獻裡是充滿了變革動力的,這顯示了它們以多樣化為目的的回報行為。這使我們對關於持續性股票的回報行為、認識變得實在太少了。於此,大量的企業社會責任的新措施不斷提醒各公司、要本著企業社會責任的理念去營運;但投資者需清晰明白他們為何需在可見的將來保持可持續性。因此,他們卑微的願望是一個較好的多樣化投資組合得以形成,故此他們高度要求股票要有組成可靠投資組合的性質和能力,特別是在持續性股票和/或傳統股票當中。

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.

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 objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

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.

While most efforts to combat climate change are focussed on energy efficiency and substitution of fossil fuels, growth in the built environment remains largely unquestioned. Given the current climate emergency and increasing scarcity of global resources, it is imperative that we address this “blind spot” by finding ways to support required services with less resource consumption.

There is now long overdue recognition to greenhouse gas emissions “embodied” in the production of building materials and construction, and its importance in reaching targets of net zero carbon by 2050. However, there is a widespread belief that we can continue to “build big”, provided we incorporate energy saving measures and select “low carbon materials” – ignoring the fact that excessive volume and area of buildings may outweigh any carbon savings. This is especially the case with commercial real estate.

As the inception and planning phases of projects offer most potential for reduction in both operational and embodied carbon, we must turn our attention to previously overlooked options such as “build nothing” or “build less”. This involves challenging the root cause of the need, exploring alternative approaches to meet desired outcomes, and maximising the use of existing assets. If new build is required, this should be designed for adaptability, with increased stewardship, so the building stock of the future will be a more valuable and useable resource.

This points to the need for increased understanding and application of the principles of strategic asset management, hitherto largely ignored in sustainability circles, which emphasize a close alignment of assets with the services they support.

Arguably, as the built environment consumes more material resources and energy than any other sector, its future configuration may be critical to the future of people and the planet. In this regard, this paper seeks to break new ground for deeper exploration.

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.

The authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.

The results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.

To the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.

Technological change drives transformation in most sectors of the economy. Industry 4.0 technologies have been applied at different stages of a building’s lifecycle. However, limited studies exist on their application in real estate facilities management (REFM). This study aims to assess the existing knowledge on the topic to suggest further research directions.

Scopus-indexed literature from 2013 to 2023 was examined and visualised using VOSviewer software to output quantitative (descriptive) results. Content analysis was used to complement the quantitative findings.

Findings indicated a concentration of research in China, Norway and Italy. The knowledge areas included three clusters: lifecycle integration and management, data curation and management and organisational and management capabilities. The benefits, challenges and support strategies were highlighted.

More collaboration is needed across countries and territories on technology integration in REFM. Future research using alternative methodologies is recommended, with a focus on adopting and non-adopting REFM organisations. Further, implications for facility managers, employees, technology suppliers or vendors, training, organisations and management exist.

Further, implications for facility managers, employees, technology suppliers or vendors, training, organisations and management exist.

The study reveals the knowledge base on technology use in REFM. It adds to the evidence base on innovation and technology adoption in REFM.