Real Estate Research Articles

Virtual land in the metaverse? Exploring the dynamic correlation with physical real estate

Virtual land in the metaverse? Exploring the dynamic correlation with physical real estate

Financialization and vertical integration enhance renter-perceived property owner effectiveness

PurposeThis work examines the impact of financialization and vertical integration on renter-perceived property owner effectiveness.Design/methodology/approachBased on a sample of 1,186 renters in the US, the UK and Canada, the research addresses gaps in the literature regarding the implications of financialization and vertical integration on renters.FindingsIn contrast to previous work that shows the negative implications of financialization, the results indicate that financialization is positively correlated with renter-perceived property owner effectiveness, challenging the prevailing narrative that it strictly benefits shareholders and the financial elite. Vertical integration’s effect on renter-perceived property owner effectiveness was also shown to be positive and significant, enhancing the existing vertical integration literature that has not focused on real estate. A post-hoc interaction analysis revealed the benefits of vertical integration on renter sentiment are greater among highly financialized firms.Practical implicationsThe study offers managerial considerations for property owners seeking to enhance renter sentiment and satisfaction as well as contributes to real estate strategy and management literature.Originality/valueThese results are novel, as previous research has not empirically shown financialization to elicit benefits for broader stakeholder groups.

Smart Renting: Harnessing Urban Data with Statistical and Machine Learning Methods for Predicting Property Rental Prices from a Tenant’s Perspective

The real estate market plays a pivotal role in most nations’ economy, showcasing continuous growth. Particularly noteworthy is the rapid expansion of the digital real estate sector, marked by innovations like 3D visualization and streamlined online contractual processes, a momentum further accelerated by the aftermath of the Coronavirus Disease 2019 (COVID-19) pandemic. Amidst this transformative landscape, artificial intelligence emerges as a vital force, addressing consumer needs by harnessing data analytics for predicting and monitoring rental prices. While studies have demonstrated the efficacy of machine learning (ML) algorithms such as decision trees and neural networks in predicting house prices, there is a lack of research specifically focused on rental property prices, a significant sector in Brazil due to the prohibitive costs associated with property acquisition. This study fills this crucial gap by delving into the intricacies of rental pricing, using data from the city of São Carlos-SP, Brazil. The research aims to analyze, model, and predict rental prices, employing an approach that incorporates diverse ML models. Through this analysis, our work showcases the potential of ML algorithms in accurately predicting rental house prices. Moreover, it envisions the practical application of this research with the development of a user-friendly website. This platform could revolutionize the renting experience, empowering both tenants and real estate agencies with the ability to estimate rental values based on specific property attributes and have access to its statistics.

Regulation and Organisation of Housing Management Activities in Germany, Poland and Latvia

Abstract Multi-dwelling buildings are one of the essential infrastructural elements of a residential area. Therefore, qualitative and professional management of such real estate is of importance. The insufficient investment into maintenance and improvement of housing is stated in Latvian policy planning documents as one of the most significant problems, causing risks for achieving the goal of compliance of the housing fund with energy efficiency, construction, safety and amenity standards. The article examines the main aspects of management of residential buildings, identifies the related risks and offers solutions for their prevention. The article aims at emphasising the significance of building maintenance and exploring management processes of residential buildings in Latvia, Poland and Germany, making a comparison that helps to understand the housing management regulation and organisational approach in each country and identify their common and differing features. In the course of the research, the authors of the article review the sources on management activities of residential buildings, identify and assess the management process risks and make a comparative analysis of housing management processes in Latvia, Poland and Germany. Information regarding the housing management field of the countries examined in the article has been obtained by summarising and analysing the policy documents and regulatory enactments, as well as by interviewing Latvian, Polish and German experts. When analysing the obtained results, conclusions have been made with regards to political responsibility, legal regulation and professional competence requirements in the field of housing management.

Determinants of future anxiety across individual, household, and regional levels in South Korea using a social ecological model

This study is the first to examine the determinants of future anxiety in South Korea using the Social Ecological Model (SEM). It aimed to show that, beyond individual factors, mezzo- and macro-level aspects, particularly those related to housing, may influence anxiety. Utilizing 2018 data from the Korean Health Panel Survey, we employed a three-level multilevel analysis to investigate how these factors contribute to the perception of future anxiety among Koreans. Our findings reveal that future anxiety is influenced by a complex interplay of demographic and socio-economic factors, including gender, age, health status, economic stability, living conditions, and regional socio-economic indicators. Notably, the study highlights the significant role of household-level factors, such as income and housing status, in shaping individuals’ anxieties about the future. Additionally, regional characteristics like housing vacancy rates and suicide rates are found to have an impact, suggesting the importance of broader socio-economic and cultural contexts in understanding future anxiety. Given South Korea’s socio-economic challenges, including the real estate crisis and demographic shifts, our study underscores the need for targeted policies to alleviate future anxiety, enhance mental well-being, and promote a more equitable society.

The consequences of regulatory reform in emerging countries: the special case of real estate regulation in India

The consequences of regulatory reform in emerging countries: the special case of real estate regulation in India

Analiza zgodności danych opisowych ewidencji gruntów i budynku z księgami wieczystymi na wybranym przykładzie

There are currently two basic public registers concerning real estate in Poland: the Land and Building Register (EGiB) and the Land and Mortgage Register (KW). The descriptive data in the Land and Building Register includes information on registered plots of land, buildings and premises, while the Land and Mortgage Register presents information on the legal status of the property. These systems operate independently, as they are maintained by different public administration bodies. However, the data contained in the Land and Building Register form the basis for the designation of the property in the Land and Mortgage Register, and thus both registers are interconnected and should contain consistent information. It is crucial that the information repetitively reported in both the EGiB and KW are identical. Consistency of data attribute values contained in both registers provides technical and organisational opportunities for harmonisation and integration of data from both sets. It is also an important factor for conducting investment activities on real estate. Previous analyses by researchers indicate that data on plots in the real estate registers are not sufficiently consistent. The aim of the article is to review the current situation with regard to the consistency of the basic data on land plots contained in the Land and Building Register and Land and Mortgage Registers on a selected example. The analysis by the comparative method was supplemented with the determination of the Jaccard index and the Russel-Rao coefficient. These are indices allowing to determine the degree of similarity between sets containing the same attributes.

FRACTAL ANALYSIS IN ALTERNATIVE INVESTMENTS: UNVEILING DYNAMICS AND DIVERSIFICATION BENEFITS

The realm of alternative investments, comprising commodities, real estate, private equity, and other non-traditional asset classes, presents a rich landscape for investors seeking diversification and enhanced returns. Amidst the complexities of these markets, fractal analysis emerges as a powerful tool for unraveling the intricate dynamics and exploring diversification benefits. This paper delves into the application of fractal theory in alternative investments, assessing its efficacy in analyzing asset price movements, correlations, and portfolio diversification. Through a comprehensive review of the literature and empirical evidence, we elucidate how fractal analysis techniques can deepen our understanding of alternative investment markets and inform strategic decision-making. Key findings highlight the ability of fractal analysis to capture nonlinear dependencies, self-similarity, and multi-scale dynamics across various asset classes. The study demonstrates how these insights enhance portfolio resilience, optimize asset allocation, and improve risk-adjusted returns. Additionally, this research contributes novel perspectives on integrating fractal methods with portfolio management and risk diversification strategies.

Increasing the Market Value of Buildings Through Energy Retrofitting: A Comparison of Actual Retrofit Costs and Perceived Values

This study investigates how energy retrofitting measures contribute to increasing the market value of multi-family residential buildings within the European real estate market. It examines how energy efficiency improvements, driven by EU decarbonization strategies, enhance the actual and perceived value of these properties. The research employs a dual-methodology approach, integrating the Cost Approach to estimate the financial impact of retrofitting with the Contingent Valuation Method (CVM) to evaluate consumer willingness-to-pay (WTP) for energy-efficient properties. Two real case studies are considered to evaluate the methodology and how the monetary value of buildings is affected by their energy efficiency. The results revealed that buildings subjected to deep energy retrofitting are more attractive to potential buyers, who are willing to pay a premium of 13.5% over properties in pre-retrofit conditions. This underscores the tangible market value increment attributed to energy efficiency enhancements. This study bridges the gap between the quantifiable costs of energy retrofitting and the market valuation, offering a dual perspective by integrating both actual cost analysis and perceived market value. Moreover, this work highlights the correlation between energy retrofit investments and increased market value in the European real estate sector.

An ivory statuette depicting the god Thanatos discovered near Tomis (Moesia Inferior)

In recent years, real estate developments in Constanța prompted a series of preventive archaeological investigations, leading to the discovery of rich archaeological material. These finds include a bone statuette found in the Palazu Mare district of Constanța. In this context, the nucleus of habitation, previously inferred from various archaeological finds from the Roman period, has been identified. Numerous surveys and preventive archaeological investigations have allowed for a clearer delimitation of the archaeological site of Palazu Mare. Regarding chronology, the settlement (possibly a vicus) can be dated from the 2nd–3rd centuries to the early decades of the 4th century AD. The statuette in question was carved out of ivory, measuring 6 cm in height and 1.7 cm in width. It was made as a representation of the god Thanatos, the personification of the Angel of Death in Greek and Roman mythology. Unfortunately, the statuette is incomplete; the left hand and parts of the legs are missing, along with the wings originally located on its back. The closest analogy for our representation comes from Northern France, where a small bronze statue was discovered in a villa rustica in Salouël, a commune located on the outskirts of Amiens. Due to the uncertainty surrounding the function of the object to which the statue pertains, we classify it as instrumentum domesticum, a category that includes a variety of objects that were part of everyday Roman life. The discoveries made here are considered quite rare due to the material of the statuette, and the context in which it was found. Based on previous observations, it can be said that Thanatos is typically a characteristic of funerary art and is therefore rarely found in domestic contexts. Ivory statues are particularly uncommon in the Dobrudja region of Moesia Inferior.

Method of the corrected distance for the valuation of real estate: a theoretical proposal in development

This article presents a novel valuation model by market comparison that requires a minimum application of criteria by the appraiser, thus seeking the highest degree of objectivity possible. The premise that supports the model is that the price differences observed between comparable assets of the same market must be proportional to the dissimilarities (distances) between those same assets, but it shows that not every distance implies a price gap, so a corrected distance is used. As a validation, the results of applying the method to a fictitious case, as well as to two real data sets from the commune of Providencia, in the city of Santiago, Chile, are evaluated. The solution of the model requires the use of non-linear programming, and the examples show that the results are very similar to those obtained by applying Goal Programming, which is another optimization method applicable to the valuation of real estate.

Dynamic Causality Between the Housing Boom and Technological Innovation in China: A Sub-Sample Rolling-Window Analysis

This paper employs bootstrap rolling-window tests to investigate the dynamic causal relationship between the housing boom (HB) and technological innovation (TI) in China. Through sub-sample analysis, we reveal the dual impact of the HB on TI: during periods dominated by the liquidity effect, the HB exerts a positive influence on TI, whereas during periods dominated by the crowding-out effect, the HB negatively affects TI. Furthermore, this study identifies the significant positive effect of TI on the HB, suggesting that TI serves as a predictor of real estate development trends. This research not only provides empirical evidence on the bidirectional interaction between the HB and TI, but also offers valuable insights for policymakers in terms of balancing the development of the real estate market and TI.

Fake advertisements detection using automated multimodal learning: a case study for Vietnamese real estate data

The popularity of e-commerce has given rise to fake advertisements that can expose users to financial and data risks while damaging the reputation of these e-commerce platforms. For these reasons, detecting and removing such fake advertisements are important for the success of e-commerce websites. In this paper, we propose FADAML, a novel end-to-end machine learning system to detect and filter out fake online advertisements. Our system combines techniques in multimodal machine learning and automated machine learning to achieve a high detection rate. As a case study, we apply FADAML to detect fake advertisements on popular Vietnamese real estate websites. Our experiments show that we can achieve 91.5% detection accuracy, which significantly outperforms three different state-of-the-art fake news detection systems.

A wavelet analysis of monetary policy transmission channels in Morocco

PurposeThis paper examines the effects of monetary policy and the interdependencies between the real economy, the financial sector and monetary variables.Design/methodology/approachThe authors employ the continuous wavelet transform to examine how the relationship between the variables in question evolves over time and across various frequencies.FindingsThe results underscore the ineffectiveness of the exchange rate channel. Despite monetary policy consistently leading long-term interest rates, its limited impact on investment suggests the interest rate channel may be less operational. Conversely, the study presents evidence supporting the credit channel’s effectiveness, not only in low market volatility but also during economic downturns. Finally, the examination of the asset prices channel uncovers that the stock market was influenced by monetary policy during its brisk ascent, while real estate led monetary policy.Practical implicationsThe study yields several practical implications. It emphasizes employing advanced mathematical methods to capture the dynamic relationships between monetary policy and economic variables. It highlights the importance of a resilient banking sector given its significant role in the economic advancement of the country. It underscores the need to develop a more inclusive and dynamic financial system and diversify funding alternatives for the private sector to make asset prices a pivotal channel for achieving monetary policy objectives. And with Morocco’s transition to an inflation targeting framework and a flexible exchange rate regime, assessing the effectiveness of the interest rate and exchange rate channels becomes crucial. While the innovative use of wavelet coherence methodology sets a precedent for evaluating monetary policy transmission channels in developing countries, urging researchers and policymakers to explore novel quantitative approaches.Originality/valueThis article stands out as one of the few to employ the wavelet coherence methodology to investigate monetary policy transmission across multiple channels, specifically within the context of a developing country.

A Study on Bid Decision Factors for Non-Performing Real Estate Project Financing and the Valuation Basis

A Study on Bid Decision Factors for Non-Performing Real Estate Project Financing and the Valuation Basis

A systematic literature review on digital transformation in real estate: challenges and opportunities

PurposeThis study identifies key challenges to adopting smart real estate (SRE) technologies and offers insights and recommendations to enhance decision-making for stakeholders, including buyers and property investors.Design/methodology/approachTo achieve the aim of the study, a rigorous research approach was employed, conducting an in-depth analysis of 41 academic papers utilising PRISMA guidelines and checklists. The chosen methodology also applies a PEST (Political, Economic, Social and Technological) framework to identify factors influencing technology adoption in the real estate sector.FindingsThe study uncovers critical challenges to adopting smart real estate technologies, such as regulatory ambiguity, high implementation costs, and societal resistance. PEST analysis reveals that unclear standards and guidelines, coupled with the high financial burden of technology implementation, are significant obstacles. Socially, resistance to change and difficulties in integrating new technologies are prevalent. The study also underscores the potential of artificial intelligence (AI) for predictive analytics and blockchain for secure transactions and records, though their adoption is currently hindered by inadequate infrastructure and regulatory challenges. These findings underscore the need for strategic interventions to address these challenges and facilitate the effective integration of advanced technologies in the real estate sector, thereby enhancing industry innovation and competitiveness.Practical implicationsThe study offers insights for real estate stakeholders to embrace technology effectively, with a conceptual framework contributing to industry advancements.Originality/valueThe study’s key contribution is offering real estate stakeholders execution tactics and recommendations to navigate challenges and utilise technology, thereby driving industry innovation and enhancing competitiveness.

Pengaruh Return On Asset, Leverage, Dan Ukuran Perusahaan Terhadap Penghindaran Pajak Pada Perusahaan Real Estate Dan Property Yang Terdaftar Pada Bursa Efek Indonesia (BEI) Tahun 2019-2023

This research aims to empirically test the influence of Return on Assets, Leverage, and Company Size on Tax Avoidance in Real Estate and Property companies listed on the Indonesia Stock Exchange (2019-2023). This research includes quantitative research. The data used in this research is in the form of annual financial reports for real estate and property listed on the Indonesia Stock Exchange 2018-2022. The population in this study was 92 companies. The sample that meets the criteria is 17 companies. The number of observation samples was 85 data obtained using purposive sampling techniques. The analysis technique used is multiple linear regression using SPSS version 29. The results of the research show that the variable Return On Assets partially has a significant effect on company value with a significance value of 0.001, the Leverage variable partially has no significant effect on company value with a significance value. amounting to 0.108, and the Company Size variable partially has no significant effect on company value with a significance value of 0.617. The research results show that the variables Return On Assets, Leverage and Company Size simultaneously have a significant effect on Tax Avoidance with a significance value of 0.001.

Analysis of the Causes of Baolong Real Estate Bond Default

The real estate industry, as a pillar industry of China's national economy, plays an important role in the development of the economy and society. However, in recent years, due to the impact of the epidemic and the tightening of industry regulation, credit risks in the real estate industry have begun to accelerate exposure. Since 2021, there have been frequent defaults on real estate company bonds, and the scale of defaults has rapidly climbed to the top of the industry. Therefore, in-depth analysis of the reasons behind the wave of defaults by real estate companies has become an important issue that urgently needs to be addressed. This article takes Baolong Real Estate as the research object to explore the causes of its bond default. Research has found that: The fundamental reason for the default of Baolong Real Estate bonds lies in the company's operational strategy mistakes and neglect of debt management. The company's heavy holdings in the third and fourth tier real estate markets, coupled with an increase in commercial real estate, have weakened the company's profitability and operational capabilities. In addition, the company's asset liability ratio is too high and there is a problem of mismatched debt maturity. After entering the centralized redemption period, under the dual pressure of tightened external financing environment and hindered internal sales collection, bond defaults ultimately occurred.

Determinants of Earnings Management: The Moderating Role of Firm Size

This study aims to provide empirical evidence on the impact of financial distress, financial ratios, and corporate governance on earnings management, using company size as a moderating variable. This study focuses on real estate, construction, and property companies listed on the Indonesia Stock Exchange (IDX) between 2020 and 2022, with a sample of 54 companies selected through purposive sampling. Data analysis was conducted using multiple linear regression to test the direct effect of independent variables on earnings management and interaction test to evaluate the moderating role of firm size. The research findings show that financial distress affects earnings management, which suggests that companies under financial stress are more likely to rely on earnings management to present favorable earnings performance. In contrast, financial ratios do not affect earnings management, which suggests that well-performing firms are less likely to engage in the practice. Good corporate governance, represented by the proportion of independent directors, audit committee and managerial ownership, also affects earnings management. In addition, firm size moderates the relationship between financial distress and earnings management, with larger firms showing a greater tendency towards earnings management when facing financial challenges. These results underscore the importance of considering financial conditions and firm size when monitoring earnings management, as larger firms may be more prone to earnings management practices under certain conditions.

Investor Networks and Fund Performance in Private Equity Real Estate Funds

Investor Networks and Fund Performance in Private Equity Real Estate Funds