Integrating biodiversity considerations into urban development projects has become increasingly important for developers, as it contributes to ecosystem services and supports occupiers’ well-being. Moreover, despite the increasing regulation (ESG, EU Taxonomy, SDGs) there are very few successful projects because there is a lack of methods to effectively manage and integrate complex and diverse data from various sources, such as urban ecology, environmental impact assessments, biodiversity surveys or spatial planning data. Based on emerging technologies, a common data environment (CDE) can provide a solution to manage and integrate these data sets effectively. In this paper, we explore the potential of a CDE for biodiversity integration in a Swiss Real Estate Development project.

We employed a mixed-methods research approach, incorporating one case study, action research, and iterations to create a minimum viable product (MVP) for testing the technical solution. Additionally, we analysed the potential business case for a CDE in managing biodiversity data and supporting biodiversity integration in real estate projects.

Upon examination of the project documentation, it has been observed that the incorporation of biodiversity into real estate development projects is impeded by the insufficient specification of the data requirements, integration, and management of biodiversity. Additionally, the study found that the absence of a business case for developers that incorporates ecosystem services is a significant obstacle to the integration of biodiversity in urban development. This can be attributed to the lack of a business case for developers that incorporates ecosystem services. To address both issues, a collaborative data environment (CDE) can serve as a potential solution by enabling the sharing, collaboration, and management of biodiversity data. For this purpose, an Eco-Module was developed which contain enhanced ecological data such as animal species distribution, habitat and vegetation types as part of the ecological data requirements. Three GeoBIM technological solutions were explored and tested using a Minimum Viable Product (MVP) approach to integrate GIS-specific biodiversity data sets such as shapefiles and raster data with the BIM model. Furthermore, the study has investigated the added value for real estate owners/investors by recommending to further use the data to quantify the overall benefits of eco-services as a base for a solid business case.

The incorporation of ecosystem services in the business case for developers can incentivize biodiversity integration in real estate development. A common data environment can provide an effective solution for managing and integrating complex and diverse biodiversity data sets from different scales. The added value comes from the data analysis and ecological simulations such as habitat suitability and species distribution models. In addition, hydrological and climatic data can enrich the CDE. By implementing an ecologically enriched CDE with dedicated Eco-Modules, the platform can raise awareness during the lifecycle of the project on important ecological issues, showing the potential use of biodiversity information for landscape-architectural-urban design and concrete financial and environmental benefits to decision-makers.

The average lifetime of a building is only 39 years, with the most common reason for building demolition being functional obsolescence. At the same time buildings worldwide account for 40 percent of the world’s waste, 40 percent of material resource use and 33 percent of all human induced emissions. To cope with these environmental impacts and to extend the functional lifetime of buildings, adaptive reuse has become a well-established strategy in the field of architecture and the built environment. The decision-making process in adaptive reuse projects is often complex, due to the many stakeholders, and decision criteria involved. Multi-criteria decision making (MCDM) models have become increasingly popular in recent years for the evaluation of adaptive reuse projects, as they provide a structured approach to assess and compare alternative solutions, taking into account these multiple criteria. There is however no clear consensus on the decision criteria and the decision support tool when it comes to adaptive reuse. Many publications on decision making in adaptive reuse have focussed on specific areas of application within the AR process, but few have considered the full process as a whole. The lack of consensus on the decision criteria used for adaptive reuse, and the need to holistically approach the AR process as a whole, based on the different phases, provides a knowledge gap for this paper. An integrative literature review on the decision criteria for adaptive reuse was conducted using a systematic search approach. An comparative analysis was performed to find relationships and contrasts between decision criteria for adaptive reuse. Based on this analysis multiple lists of decision criteria for adaptive reuse were constructed, for the four main phases of the AR process (Pre-project, preparation, implementation, and post-completion phases). The findings of this paper contribute to the growing literature on Multi Criteria Decision Making for adaptive reuse by synthesizing the decision criteria according to the four phases of the AR process. Through this literature review, a further comprehension is provided on the decision criteria for adaptive reuse throughout the AR process, that can help stakeholders of adaptive reuse projects in structuring their decision making process.

To implement economic strategies that consider the entire life cycle of a property, criteria such as sustainability, agility, usability, safety, time, and cost are crucial.

The literature shows that real estate and facilities management researchers strive to develop agile and easy-to-use calculation methods to achieve CO2 reduction goals and better account for building life-cycle costs by choosing green and cost-effective solutions and strategies.

However, few tools can address these issues by providing an integrated IT solution to determine the life cycle cost-effectiveness of construction measures through an easy and performant calculation model.

For that reason, the research project on cost-benefit simulation with partners from the University of Applied Sciences Mainz and the “LBB” (State Office for Real Estate and Construction), owner of 1600 buildings in Germany, aims to develop a model for calculating the life-cycle costs, energy efficiency, and the environmental impact of buildings in monetary terms based on the “DIN” Standard Building Occupancy Costs (DIN 18960 2020-11).

This paper shows a case study calculated by the new tool “NUKOSI” (Use of cost calculator and simulation) based on the Filemaker platform developed by Claris. With this database solution, existing data from the planning phase use to determine the life cycle costs of a building and to establish an ecological balance.

It is, therefore, possible to carry out a study and statistical analysis of the updating of the supply variants (sale, construction, purchase, rent) and budget planning or portfolio management, which is performed easily or automatically by own or external staff.

These have efficient consequences, establishing a carbon footprint oriented on the construction elements, minimizing operating costs, providing modernization and maintenance planning, and maximizing value.

“NUKOSI” is used operationally by the “LBB” as an IT solution and has been tested, for example, in higher education, trade, real estate funds, and religious institutions.

The real estate sector is a rapidly growing sector considered the locomotive of economic development. However, besides rapid growth, unplanned urbanization has led to significant problems such as environmental pollution, degradation of natural vegetation and soil resources, reduction of water resources and drinking water, destruction of biodiversity and damage to the ozone layer, global warming, and climate change, as well as intensive waste problems. The building industry causes issues ranging from excessive consumption of natural resources to environmental pollution in building construction and use. For real estate markets to be characterized as sustainable, it is essential to leave livable areas for future generations and, at the same time to develop several economic, financial, and legal policies. The idea of sustainability is on the agenda of many organizations, such as the United Nations and the European Union Commission. The United Nations has listed 17 items within the scope of the 2030 Sustainable Development Goals: “sustainable cities and society”. Sustainability of societies and cities and leaving a livable world to future generations are the goals of developed countries. Therefore, supporting many environmental, legal, and political factors and providing economic development is necessary. While it is so crucial for the real estate sector to be sustainable, the concept of sustainability appears as an abstract concept. For this reason, studies to measure sustainability are extremely important. Within the scope of the research, a literature review was conducted on the measurement of sustainability in real estate markets. The review was taken advantage of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Using keywords that may be related to the real estate sector, 113 studies in the Web of Science database and 152 studies in the Scopus database were analyzed in detail. The studies were evaluated by combining them with content analysis. According to the results of the research, it is seen that sustainability in real estate markets is mostly investigated at the environmental level.

Real estate accounts for 61% of France's national net wealth. Housing is the largest item of  expenditure of French households. Indices that track real estate prices evolution are thus crucial  instruments for decision makers of all kinds: households, investors, the scientific community,  local governments, etc. Yet, the available public statistics fail to cope with the heterogeneity of  the housing prices dynamics across the country. 

In France, Notaire-Insee indices are considered as the reference, especially because their  methodology and indices are open source. Quarterly, the institute produces indices for  apartments and houses in big agglomerates. With 9 indices for house prices in France, the  division proposed by this methodology hides a lot of disparities. For instance, the “Province”  house index includes more than 25000 cities as diverse as Toulouse (450k inhabitants) and  Malroy (350 inhabitants), which represents 36% of the French housing stock. This indicator  does not make it possible to highlight the differences in dynamics between cities geographically  distinct and drived by different fundamentals due to different economic conditions. 

This work aims at producing a library of open data real estate price indices that track price  evolution at fine geographical scale. To do so we develop a methodology for real estate price  index computation, and then apply it on geographical clusters close to local markets. We want to be part of an open-source approach. Indeed, the methodology will be published, and  all the indices will be made available for free to all. 

The proposed method is applied on the fiscal database of real estate transactions DV3F,  containing all the transactions in France (except Alsace, Moselle and Mayotte) between 2010  and 2020. 

Our approach is based on classic hedonic price index methods. Each aspect and hypothesis of  the hedonic method have been justified to produce precise indices. 

Producing indices close to local markets requires working in a low data environment, and  increases the probability of encountering outliers. Hedonic methods being very sensitive to  outliers, we tackle this issue by testing the impact of different dynamics filters methods. To reduce the heteroscedasticity and improve the precision of the model, different forms and  combinations of the regression have been tested. 

This method is applied to 2 divisions of France: one for apartments, another for houses. In order  to produce indices close to local markets, a clusterization of cities of France is computed as  finely as possible and based on socio economic and local housing stock criteria. To preserve the  quality of indexes, all clusters respect constraints of minimum transaction volumes. This  division is based on a clusterization of urban areas thanks to Ascending Hierarchical  Classification and Kohonen algorithms. 

This clusterization resulted in the computation of 350 apartments and 400 houses indices. The  application of our approach on these geographical clusters reveals a great diversity of house  price dynamics. For instance, the “Province” index produced by Notaire-Insee is divided into  220 clusters, with variations between 2015 and 2020 of 2% and 29% respectively for the first  and ninth decile of these indices. 

By highlighting the plurality of real estate price dynamics in France and urban centers, our  approach emphasizes the need for indices to be computed on a local scale to be useful.

This study examines the connection between investor herding and house price bubbles in US metropolitan markets. Contrary to widely accepted theory on herding as a prime motivator for price bubbles, limited evidence is found to support this proposition. Rather, there is empirical support to suggest that price bubbles, proxied by excess returns, are in fact the motivator for investor herding. There are substantial time delays in the mechanism which are particularly relevant for discussions of market efficiency and persistence in behaviour. Furthermore, there is significant evidence of a relationship between reverse herding and price bubbles that is supported by a consideration of market structure and access to private information. The idiosyncratic impacts of price volatility on market dynamics are also included with a focus on constructing a leading indicator. Finally, the study assesses the relative impacts of local and national determinants on the extent of herding and price bubbles.

The commercial real estate sector is being transformed by technology and PropTech. Companies are increasingly looking for new alternatives and Blockchain has the potential to solve the issues about challenges, regarding liquidity and transparency by offering fresh alternatives for commercial real estate investors. The main problem examined is that the complexity of the leasing processes and the handling of the process with different actors make the whole process open to errors. Smart contracts using blockchain technology promise to solve this complexity in the contract process. Smart contracts are also claimed to form a structure where reliability and transparency are guaranteed. The purpose of smart contracts is to ensure that the lease agreement is signed, the rent is paid on time, and the contract termination is implemented in accordance with the terms. This research explores the application areas of smart contracts based on Blockchain technology and potential application innovations in the commercial property market and finds criteria for using smart contracts in property leasing. Smart contracts are an important example of the use of Blockchain technology in commercial real estate leasing. Therefore, it is essential to find criteria that allow the use of smart contracts in commercial property leasing. The criteria that smart contracts must meet in order to be preferable to the existing contract type are questioned and if these criteria are met, whether smart contracts can be used in the shopping center rental process has been researched. The criteria considered in the current lease agreement process, and the use of blockchain technology in the commercial real estate industry are explained. In commercial real estate contracts, the application areas of smart contracts are explored. The importance of the criteria in this process is determined through a survey of employees in commercial property leasing companies. The survey investigating the criteria for smart contracts to be used instead of existing lease contracts will be made to the target people and the survey results will be evaluated by a scoring method. The AHP method is used to integrate the criteria into the hierarchical structure and show which criteria are effective in the selection decision for the leasing contract process. The scoring system determines which criteria are more important than the others. Participants in the interview were asked which criterion they preferred over the others. The criteria that resulted from these surveys were scored using scoring matrices. The survey using the AHP method revealed the criteria and features that the leasing process must promise for the use of smart contracts. As a result, the opportunity for smart contracts to be integrated into the commercial property leasing process is being pursued.

This study attempts to propose ecosystem valuation approach for river by using contingent valuation. This study offers a thorough yet straightforward and useful framework for valuing ecosystem products and services. In addition, this study provides a survey based on contingent valuation methodology for estimating the non-use benefits of Malaysia's Johor River's improvement in ecosystem services. As far as the literature review is concerned this will be the first study of such kind in Malaysia. This study is also unique because it will utilise the freely available satellite data and advanced image classification technique of deep learning to classify different land use types. This study combineD economic valuation of ecosystem services to better highlight the importance of ecosystem services. The study findings on spatial and temporal distribution of ecosystem services can help guide future land-use policy i.e development of appropriate land use options and water resources management to enhance ecosystem services.

Over the last thirty years a large literature has developed that considered the investment opportunities that arise within the REIT (Real Estate Investment Trust) sector. This literature has considered an array of issues, including the relationship and diversification across different REIT sectors (e.g. Chong et al., 2012; Stevenson 2016), the role REITs can play in both real estate (e.g. Stevenson, 2001) and capital market (Liu & Mei, 1992; Lee & Stevenson, 2005) portfolios and also issues relating to international diversification in public real estate. Some papers have considered portfolio trading strategies within REITS (e.g. Cici et al., 2011; Feng et al., 2022; Zhou & Anderson, 2013) and also the analysis of Smart Beta strategies (Guidolin & Pedio, 2019) or the predictability of REIT returns (e.g. Akinsomi et al., 2016; Letdin et al., 2019; Ling et al., 2000; Li & Wang, 1995; Serrano & Hoesli, 2010, Stevenson, 2001). However, the majority of this literature has focused on relatively low-frequency data, on a monthly frequently or less. This paper takes a slightly different approach, focusing on both higher-frequency data, at a daily frequency, and more active trading strategies. The paper utilizes data obtained for the US Equity REIT sector and compares the performance of a variety of trading strategies commonly adopted by active traders. The analysis utilizes data source from Bloomberg and considers the viability of active trading strategies in the US Equity REIT sector. The strategies included consider approaches such as Relative Strength, Momentum and Mean Reversion over a variety of time horizons. The analysis also examines more fundamentally based measures, including Price to FFO (Funds from Operations).

Over the years, various forms of developer obligations have been considered in English planning and development policies. The most recent major addition to the developer applications was the Community Infrastructure Levy, which has been available for local planning authorities since 2010. The levy is a non-negotiable developer obligation that a local planning authority can, but does not have to, adopt. The levy is used in combination with negotiable developer obligations, which have a scaled-back scope after the adoption of the levy. Although there is a vast amount of literature focusing on developer obligations, the introduction of new developer obligations within the existing set of obligations has been studied much less. Our paper aims to fill this gap by studying the factors affecting the adoption likelihood of the community infrastructure levy as well as its impact on the housing supply. Our study can guide decision-makers regarding the design of the developer obligations framework. They also offer valuable insight into how new instruments will work within the existing developer obligations framework.

Purpose: We introduce state-of-the-art Machine Learning-based methods for key document processing procedures to support and accelerate the ever-growing digitalisation efforts in real estate as in other industries. We create a tool to divide any PDF containing multiple documents into their singular documents. This allows for an en-masse digitization of paper-based files instead of the standard one-by-one scan approach. Further, we present ML based methods for the automated classification of both digital and digitized documents.

Design/methodology/approach: The segmenting tool analyzes the different pages to determine the start and end of any document inside a mass scan. For that purpose, it extracts features from both the text and page design which includes fonts, layouts, existing page numbers etc. to correctly split any multi-document PDF. This forms the basis for the classification tool to sort the segmented documents into any real estate document classes.

Findings: The paper presents an overview of different Machine Learning methods to create these tools as well as their performance under different conditions, thereby offering insight into optimal solutions for processing documents in real estate on a case-by-case basis. The findings are the groundwork to this particular and novel problem. The methods, which are provided open source, serve as a basis for accelerating real estate document processing from scan or inbox to digital storage and ultimately machine-based information extraction.

Practical implications: The digital processing of documents requires enormous efforts especially when dealing with the typically large quantities of documents in real estate, whether paper-based, digitized or digital. Our approach simplifies this often time-consuming task and thereby encourages firms to open up to direly needed digitization. The methods presented are essential for the digitization of all areas in real estate management and can promote PropTech business cases.

Originality/value: This paper introduces effective methods for processing existing paperbased, digitized and digital files as well as Machine Learning models fitted to complement these methods specifically for real estate.

This paper studies the seller’s agency choice and the financial consequences of this decision. Specifically, at sale, sellers can choose to use either the agency they originally purchased the house from, or a different agency. Our empirical findings suggest that sellers choose agencies for house sales based on past purchase experience and current market shares of agencies. A premia analysis on pair sale transactions also suggests using the same agency is financially suboptimal, resulting in a 1.1--1.4% price discount. These results are consistent with agency theory--using the same agency with more information may not be financially in the interest of principals.

Knowledge of emission sources is essential to take measures in time to mitigate the subsequent effects on health and the environment. In general terms, substances that are harmful to health and the environment are called air pollutants. The World Health Organization (WHO 2022b) estimated ~ 37.000 premature deaths related to ambient air pollution in Germany in 2016. Air pollution is a concern for everyone, but its effects are not compensated, and the originator is not required to cover the costs. Several methods have been developed to determine these costs. In the context of air pollution, the revealed-preference method is considered as it "involves determining the value that consumers hold for an environmental good by observing their purchase of goods in the market that directly – or indirectly – relate to environmental quality". Based on a semiparametric hedonic regression this paper evaluates the impact of air quality on the asking rents in Berlin between 2018 and 2021. The rental income of apartments located in areas with low pollution was 2% higher than market average. Assets in areas with high pollution were offered at a discount between –2% and -6% in comparison with average assets.

This research considers how private and public entities across the African continent continue to perpetuate projects that are often refered to as African urban fantasies.  It suggests that although very few projects achieve  their urban visions, they continue to be marketed based on narratives that include urban concepts such as Eco-Cities , Smart cities, and the promise of sophisticated  urban lifestyles based on the principles of New Urbanism .  There is growing evidence indicating that these proposed large developments  have little relevance to their local context and are usually based on an unrealistic understanding of the market.  Moreover, these projects reflect a complicated interrelationships between the objectives of private and public sector players.  From a policy perspective it often includes the provision of financial incentives and urban Infrastructure. This research builds on existing reserach. It draws conclusions regarding the objectives, the institutional arrangements, and the challenges  that characterise such projects . The research develops a theoretical framework that could be used to better understand the development of large African Urban projects. 

This abstract discusses the increasing importance of Environmental, Social, and Governance (ESG) factors in the real estate industry in Asia and Malaysia, where many listed property companies have begun to adopt ESG practices. However, the effectiveness of these initiatives on company performance remains unclear. This problem statement aims to investigate the potential benefits of integrating ESG practices into the operations of listed real estate companies and to identify the specific ESG factors that are most important in driving performance. Previous studies have shown mixed results, and there is a need to investigate the specific ESG factors that are most important in driving the performance of listed real estate companies in Asia and Malaysia. While academic research has been supportive of the increased value of ESG in real estate investing, this research aims to examine major real estate challenges and topics such as climate change risk issues, energy efficiency, and decarbonization frameworks. The significance of ESG in real estate investment decision-making for real estate investors globally moving ahead has been established, notably around the topics of climate risk reduction, climate resilience, and zero-carbon initiatives.

Focussing on the agricultural land sales market this paper investigates the use of development overage provisions, also referred to as clawbacks, in land sales.  Land transaction data was collected from agents in the agricultural land agency sector and analysed to ascertain the extent of the use of overage provisions and the terms contained therein. The paper makes three contributions. Firstly, it identifies the wide spread use of overage provisions in agricultural land sales and seeks to determine whether the inclusion of an overage provision has an adverse impact on the final sale price.  Secondly it provides insight into common terms, trigger events and methods of security, particularly focusing in on the valuation mechanisms when the overage is triggered.  Thirdly it seeks to make a tentative step towards standardising valuation procedures for untriggered overage provisions by interpreting those currently in use. For the long term purpose of understanding whether there could be a market place for untriggered overage provisions, which could ultimately lead to the securitisation of these provisions, in order to create a new real estate investment product.  

This study examines the effects of investor sentiment on the price adjustment behaviors for real estate investment trust (REIT) and the stock prices by applying the threshold error correction (EC) model. We defined the regimes and estimated the endogenously threshold level by the five investor sentiment proxies: the VIX index, the VXO index, the put/call ratio, and two search volume indexes provided by Google Trends. The empirical results reveal that there are asymmetric effects of investor sentiment on the price adjustment behaviors for both the REIT and stock returns. The coefficients of price adjustment are significantly negative values under most regimes constructed by the different investor sentiment proxies. Moreover, the adjustment degree in upper regime is greater than that in lower regime. Thus, if market participants are strongly bearish or their attention level was high (i.e., in the upper regime), they will quickly adjust their portfolios in response to an economic shock. For all regimes, the efficiency of the price adjustment behavior is greater in the REIT market than in the stock market. The results also reveal the significant lead-lag relationships between the REIT and stock markets under the most regimes.

Sustainable development, the fight against climate change and the protection of biodiversity have become essential considerations in all the different business sectors. They particularly affect the construction and real estate sectors, which contribute to nearly 38% of all global carbon dioxide emissions (UNEP, 2023). Sustainable development has been transposed to real estate by the concept of sustainable or green building. Property asset managers must therefore adopt effective practices to comply with good sustainable building practices and to manage the social, economic, and environmental impacts generated by their buildings. Green building literature provides a clear framework on the range of practices, indicators, measures, and methods to assess the sustainable performance of a building (Nilashi et al. 2015; Zhao et al., 2019). However, scientific literature makes few distinctions between private and public sector buildings (Baird et al., 2022).

The purpose of this research is to paint a portrait of the practices used in 2022 by public sector property asset managers in Quebec, who are essential stakeholders to be mobilized to succeed in the transition to more sustainable buildings. They are indeed major owners of real estate portfolios, and they are called upon to demonstrate the State’s exemplarity.

Some 88 public sector property asset managers responded to a survey of 188 questions distributed in Quebec between December 2021 and March 2022 relating to: (1) the description of their organization and their real estate portfolio; (2) the practices operationalized by their organization in property management; (3) the practices to manage environmental impacts and (4) the practices to manage social impacts. 

The analysis of the responses to the survey shows that respondents consider themselves effective in terms of managing internal risks relating to their buildings without, however, concretely considering the impacts they generate on external stakeholders. Waste, water, and greenhouse gas (GHG) emissions management practices are given more priority than energy management practices. This is explained by the low cost of hydroelectricity in Quebec. These environmental impact management practices are, however, supplanted by the interest in practices for managing the health, safety, comfort, and well-being of internal building stakeholders, which can be explained by the consequences resulting from the COVID-19 crisis. To perform better, respondents point out that they would need training in sustainable building management and budgetary resources, particularly for the maintenance and upkeep of their assets. The sustainable development objectives pursued by the organizations of the respondents still need to be integrated into the contracts with the various suppliers. Finally, the fight against climate change and the development of resilience to natural disasters are not or hardly integrated into the management of their operations.

This research could be replicated in different parts of the world to compare these practices with those used in Quebec. It could also be taken up in Quebec to analyze the evolution in time of sustainable institutional building management practices.

Energy performance certificates (EPCs) exist for real estate objects in many countries around the world. These documents represent a rich source of real estate information for both residential and commercial properties.

Depending on the country, energy performance certificates provide detailed information on energy efficiency and pollutant emissions, as well as a wide variety of other useful data: Information on location, usage profile, year of construction, time of the last change (e.g., year of refurbishment), geometric information (lengths, areas, volumes), temperature-, climate-, heat- and ventilation-related information, information on energy generation and storage as well as information on the validity duration and the issuer.

For many applications, it would be desirable to have this data available in a structured, digital form for a large number of properties. For certain applications, for example, to meet legal requirements in the area of environmental, social, and governance (ESG), having this data is mandatory. Reading this data manually from energy performance certificates proves to be very time-consuming, expensive and error-prone: Hundreds of, e.g., numerical values may have to be read out and written down without errors over a period of hours.

In order to extract this data easily, quickly, cheaply and with high accuracy, DataScience Service GmbH (DSS), a real estate software company based in Vienna, Austria, has developed an application programming interface (API) that extracts all data of interest from EPCs automatically. Being able to make this data available quickly for a large number of properties opens up many possibilities for answering scientific and engineering questions in real estate economics, urban planning, energy & environmental science, and building physics, and also provides opportunities for developing practical applications in the real estate and energy industry.

In this talk, we will provide a brief introduction to the API we developed for the Austrian market, which can be readily extended to support EPCs of other countries depending on market demand.

Security deposit is a very important aspect of property management since it is based on liabilities which a tenant might leave behind when vacating a property. The property manager has roles to play and must demonstrate his skills and expertise in the application of security deposit. In countries such as United States of America, United Kingdom and Ireland, Korea, South Africa and some others, relevant laws guide the application of security deposit. However, there is a gap in extant literature with regard to application of security deposit in emerging economies. Therefore, this informs the aim of the study which is to examine the application of security deposit in residential properties in emerging economies such as the study area. The survey research design was adopted by the study. Data was obtained through primary sources using a sample size of 326 estate firms registered by Estate Surveyors and Valuers Registration Board of Nigeria (ESVARBON). The findings from the analysis using descriptive statistics indicated that the determination, collection and refund policies by estate firms where based on either their discretion, the landlords’ instruction or the agreement by the firms and the landlords, hence not guided by any legal framework or standardized security deposit policy by the government. These and other factors from the findings of the study, led to series of challenges faced by the estate firms in the application of security deposit in residential properties. Hence, the study proffered recommendations that would improve and strengthen the quality of security deposit application in these properties in Nigeria as well as help to reduce the challenges faced by the estate firms.

Most real estate decisions are multi-criteria by nature. The obvious means to support such decisions are multi-criteria models, developed in the field of operations research (OR) decades ago and applied in many industries ever since. But not in the real estate sector. Here, OR is still a foreign concept, confined to some exotic niches and academic circles. The aim of this paper is to demonstrate that mathematical decision models can be applied to practical real estate problems and can help to improve decision quality. We use OR for commercial portfolio transactions, which are particularly complex due to the exponential increase in the flow of information, which quickly exceeds the information processing capacity of humans.

The research design follows a mixed-methods approach. Based on literature research and interviews with industry experts, a decision model using Analytical Hierarchy Process (AHP) and Elimination Et Choix Traduisant La Realité (ELECTRE) is designed to prioritise properties from a target portfolio. The model architecture includes measures to reduce human decision-making biases, which is a requirement of Behavioral Operations Research (BOR). Then, data from a medium-sized portfolio transaction in Germany is used to test the model. The result is a list of properties ranked in the order of their alignment with the investment objectives, offering an entirely rational solution. Debriefing interviews with the decision-makers support the assumption that this solution is superior to most bounded rational solutions, which were discussed during the acquisition process.

Digital technologies are changing workplaces physically and functionally so much that working professionals need to develop digital skills to ensure that they do not become ‘physically present but functionally absent’ in the 21st Century business environment. Accordingly, the nature of the current business space makes digital skills fundamental requirements for a sustainable career in modern valuation practice despite the fact that the valuation profession traditionally does not demand digital literacy are a requirement for professional practice. This brief review examines the digital skills valuers currently have per their training to assess the skills which are relevant, and suggests which digital skills should be the focus of training programmes meant for building the capacities of present and prospective valuation professionals. From the review, the ability to carry out valuations using digital tools is no longer a brand of competitive advantage but increasingly becoming a valuable requirement in the digital era though many working professionals and job seekers lack basic digital skills. This article forecasts that this skills gap can be bridged through digital training in the universities for future professionals and through continuous professional development (CPD) programmes for working professionals at risk of displacement from the valuation profession. Consequently, communication, collaboration, creativity, critical thinking, information, and problem-solving skills (van Laara, et al., 2019) are general fundamental digital skills that valuation professionals should focus on acquiring rather than learning skills such as writing, reading, measured drawings, data entry and analysis, photography which are efficiently done by various digital tools.

We present an assessment of contemporary climate risk quantification tools utilized by the real estate industry. Given the escalating frequency and severity of extreme weather events, it is imperative for market participants to employ reliable and robust risk quantification methods to manage their portfolios. Our study evaluates the methods currently used against multiple criteria, including database quality, quantification methodology, transparency, actuality, scope, geographical suitability, and others. We employ publicly available information and the outcomes of a questionnaire sent to providers of risk quantification software. Furthermore, we calculate the physical climate risk for a pre-defined portfolio using the identified climate risk quantification methods. Our findings indicate that many of the available tools lack transparency in their methodology and that there are significant discrepancies in the physical risk quantifications. This paper contributes to the given objective in various ways. Specifically, it offers an overview of the available tools used by market participants, it defines criteria that can be employed to assess climate risk tools, with an emphasis on the real estate industry, and it identifies the weaknesses and strengths of the different approaches.

The use of Automated Valuation Models (AVMs) in the context of traditional real estate valuations and their performance has been discussed in the academic community for several decades. Most studies focus on finding which method is best suited for estimating property values. One aspect that has not yet been studied scientifically is the appropriate choice of the spatial training level. The published research on AVMs usually deals with a manually defined region and fails to test the methods used on different spatial levels. The aim of our research is thus to investigate the impact of training AVM algorithms at different spatial levels in terms of valuation accuracy. We use a dataset with about 1.2 million residential properties from Germany and test four different methods, namely Ordinary Least Square, Generalized Additive Models, eXtreme Gradient Boosting and Deep Neural Network. Our results show that the right choice of spatial training level can have a major impact on the model performance, and that this impact varies across the different methods.

We are contemporary real estate valuers who use daily tools of present value maths and discounted cash flow analysis. Endowed with those tools, we travel back to the 30's and analyse the origins of the dual leasehold rate, an appraisal technique that has been widely used -but contested- till our present times.

Following the journey of Mackmin (2008), we find that the original idea of Mackmin (1928) is based on a correct valuation principle, but the dual-rate formula advocated by Parry (1930) and others is wrong in terms of discounting. We correct the old formula and we take it back to the present. The corrected formula can then be further extended and adapted to different cases of contemporary leasehold valuations. We show through some numerical simulations to which extent the old dual-rate formula differs from the corrected version.

We reach a possibly different conclusion from the one of Mackmin (2008): a dual (or even triple) rate formula can still be useful to value leaseholds but it needs to be obtained by correct principles of discounted cash flow.

This research explores barriers to implementing sustainability measures in existing Central London Office spaces from different a Stakeholder’s perspective. Drawing on insights from the literature, this research identifies limitations of building assessment methods and environmental certification including Green Leases, EPCs and BREEAM In-Use. Data from 30 semi-structured interviews across four Stakeholder groups were utilised to extrapolate findings using both close and open-ended research questions which enabled a focused yet conversational interaction with the interviewee. The data analysis and preliminary findings highlight several themes from a Stakeholders perspective, which have so far been unexplored in literature enabling three objectives to be met. The three objectives focus on barriers to sustainability measures with a specific focus on BREEAM In-Use, value aspects brought about by good workspace design, Smart Building Technology, and its influence on Stakeholder’s communication and finally, difficulties of retrofitting existing office spaces with technology to enhance environmental performance and potential solutions. More attention should be given to mitigate issues associated with the BREEAM In-Use certification, specifically auditor integration which can affect innovation, communication, and costs. The degree of value aspects brought about by good workspace design varies according to specific Stakeholder category, nonetheless, all agree that value is brought about; SBT increases end-user control and of all the Stakeholder relationships, the Landlord & Tenant relationship is most positively impacted by using SBT. Despite the surge in demand for sustainable spaces, uptake of SBT is slow. SBT could be used as a complimentary technology alongside building assessments (such as BREEAM In-use) to ensure higher sustainability output of an existing office space is achieved and not hindered but only if the barriers associated with BREEAM In-Use integration are recognised by policy makers and there is a commitment or strategy in place to incentivise Landlords to retrofit existing spaces with SBT. Landlords’ incentives to uptake SBT.

Issues related to sustainability and climate change have widely generated the interest of both academics and practitioners. The negative impacts of climate change are now substantiated through scientific evidence. The built environment is one of the major carbon emitters in any economy that could have a clear impact towards the battle against climate change. Though much research has been initiated to reduce carbon emissions from the built environment or to make it more sustainable, it is not well known to what extent commercial property valuers are incorporating sustainability and climate change issues while valuing properties. Valuation advice produced by professional valuers are used by investors, occupiers and lender and therefore, if these advice lack in terms of sustainability, it could have far reached impacts within the built environment. Though some research has been initiated in Australia, in the UK research is scarce on valuers’ perception of sustainability. To understand that research was undertaken at the University of Reading as part of a PhD thesis using a mixed methods approach that included a Survey and 32 Interviews of valuers, investors, owner occupiers and lenders. Among other things, this research found some challenges faced by valuers in the UK that are working as barriers to incorporate sustainability in the valuation methodology. These include valuers’ reliance on third party for data such as EPC upgrade cost and environmental assessments, lack of data related to sustainability of the subject property as well as comparable property, lack of evidence for sustainability premiums or discounts, issues related to time constrains, fees, costs and client’s pressure, lack of education and training of valuers on sustainability and climate change issues as well as the use of traditional methodology to value properties. Addressing and working on these challenges are paramount to move forward for a more sustainable future.

Property rates, usually used in the income approach, can be determined in a reverse income approach model for every transaction where the net yield is known. The height of the property rates represents the risk of the asset that is traded. The height of the yield, therefore, depends on influencing parameters that can explain the risk. A classical approach to investigate these influences is a multiple linear regression model. In an inhomogeneous market, the investigation leads to bad results for the classic approach.

In this work, we will compare different parametric and non-parametric methods to model the height of the rates. Thus, we present the application of Artificial Neural Networks (ANN) as well as Random Forest Regression (RFR) as non-parametric methods and compare the results with parametric approaches like the classic multiple linear regression (MLR) as well as a Geographical Weighted Regression (GWR). The dataset consists of a submarket of mixed-use-buildings (residential and commercial) in the federal state of Lower Saxony (Germany).

The asset class of mixed-use is only traded 200 times per year in the federal state with more than 8 million inhabitants. Therefore, the investigated sample (including 5 years of data) comes from the official purchase price database. Beside the building characteristics (No. of floors, year of construction and average rent per sqm), locational parameters are considered (standard land value, population forecast, and population structure). 

Due to the inhomogeneous rural, urban and socio-demographic environment, the models can be complex. The evaluation of the different approaches led to inhomogeneous results. No perfect method can be determined for the dataset. Our goal is to understand and interpret the different results in the view of how the methods work. Therefore, we investigate the results by means of the used influencing parameters (model size), sample sizes and the influence/significance of the parameters on the result. The patterns found are discussed in comparison of methods and in the context of the data. We conclude our contribution by formulating the possibilities and limitations.

German and especially Berlin went through an interesting period within housing policy after unification neglecting the elasticity of the housing demand. After different forms of rent regulations and other restrictions to the supply side of the market, socialising large parts of the housing stocks is discussed as the next step to leave market economy in Berlin. This paper tells the story of Housing Policy in Berlin after unification. 

Bidding wars, whereby multiple buyers compete for a property and place bids in excess of the initial list price, have become increasingly common in residential real estate markets. However, there is only scarce empirical evidence on their causes and even less evidence on their direct and indirect effects. 

We link bidding behavior to shocks to local demand by leveraging quasi-experimental variation from a generous tax exemption policy in the Dutch housing market. In those local markets most affected by the policy, the share of transactions above list price increased significantly, compared to less exposed markets. 

Importantly, this impact of the tax exemption on transaction outcomes is not driven by treated buyers alone but spills over to other buyers, who also increase their bids. Both effects last well beyond the period in which the tax exemption policy exists. The policy also has important wealth effects that outweigh the original tax exemption. Finally, we show that the demand shock does not have a uniform effect, as it is most pronounced in markets that were relatively tight to begin with.

In order to do justice to climate change, the Paris Climate Agreement and social demands, the European Green Deal was concluded. Its goal is to make Europe climate-neutral by 2050. As part of this, the so-called Taxonomy Regulation came into force on 01.01.2022. In order to analyse how the Taxonomy Regulation affects sustainability efforts and corporate financing, especially green bonds, a survey was conducted among listed German real estate companies.

The focus was on three research questions: 

1. To what extent does the Taxonomy Regulation influence listed real estate companies and their financing?
2. What is the interaction between the Taxonomy Regulation and green bonds? 
3. How will this field of corporate financing develop in the future? 

The paper shows the results of the survey and analyses them.

The analysis of price fluctuations of real estate equity companies he been approached from different perspectives, such as region, investment type or regional focus. However, the capital market volatility of different business models of real estate equity companies has not been investigated so far. The aim of this paper is to gain a better understanding of how real estate equity companies’ business models can be quantified and distinguished in the first place. We use real estate equity companies´ turnover along the two dimensions “area of economic activity” and “asset class” to distinguish between business models and to quantify turnover fragmentation. How the fragmentation of each dimension impacts the capital market volatility is relevant for our understanding of how diversification is valued by capital markets. Additionally, different business models and associated stocks might respond differently to varying market phases and external shocks. An analysis of these reactions is therefore a research objective with potentially interesting insights in terms of resiliency during crisis such as the Covid-19 pandemic. Our analysis is based on a sample of 48 real estate equity companies from Germany and Austria from Q1/2016 up until Q3/2022 with a total market capitalization of €89bn. The turnover data was collected by analyzing the business reports and in a survey among the companies in 2022. We use hierarchical clustering after Ward (1963) and a silhouette index to derive compact clusters of real estate equity companies sharing a comparable turnover structure, which can be interpreted as groups of business models. Based on those results we firstly analyze the fragmentation of each business model in terms of turnover fragmentation using the Hirschman-Herfindahl index and the relation between fragmentation and capital market volatility. Secondly, we construct a stock market index for each business model and investigate the first and second moment as well as the correlations with macroeconomic variables and sentiment indicators. Thirdly, the indices are subjected to a change point analysis based on the Pruned Exact Linear Time (PELT) method to identify breaks in the volatility of the return series. From here the individual time frames of each index based on the identified breaks are subjected to analysis and specifically the pandemic period. In addition to a better understanding of the complexity and fragmentation of the business models pursued by real estate equity companies and their impact on capital market volatility, this paper provides a basis for a systematic benchmarking approach for investors and regulators based on the identified groups of business models, as well as a better understanding of the resiliency of different business models during different market phases.

Commercial real estate regeneration markets are analysed in the context of the debate over the role of institutional investors in financing regeneration development as a primary source of the sustainable funding. This research aims to explore whether urban policy fosters economic sustainability of the regeneration real estate market by strengthening the scope of its maturity, resilience and competitiveness with the influence of municipal planning instruments and political leadership through regeneration policies. The research design of this research is embedded in the structure of the conceptual framework on market sustainability. Two sets of the property indices constructed constitute the rental values of the regeneration properties and standing properties in Manchester city centre respectively during the period from 1967 to 2017. This approach aims to evaluate the performance of the regeneration property market against the performance of the mainstream property market in Manchester as well as to assess the quantitative movements of the market performance indicating the level of economic sustainability. The evidence of rental value movement between 1984 and 2017 shows that the regeneration market has become more mature particularly after 1998 with steadily stable trends. Within the timeframe of the three property cycles, it can be observed that the rental value of regeneration properties after 1997 became more closely aligned with that of non-regeneration properties indicating a sign of market maturity. The evidence indicates that the regeneration office market is less economically resilient due to the higher possibility of being exposed to greater investment risk. The regeneration office market in Manchester city centre demonstrates a positive stature in achieving economic sustainability enhanced by Manchester being an economically resilient city able to compete for investment.

Besides its structural and economic characteristics, the location of a property is probably one of the most important determinants of its underlying value. In contrast to property valuations, there are hardly any approaches to date that evaluate the quality of a real estate location in an automated manner. The reasons are the complexity, the number of interactions and the non-linearities underlying the quality specifications of a certain location. These are difficult to represent by traditional econometric models. The aim of this paper is thus to present a newly developed data-driven approach for the assessments of real estate locations. By combining a state-of-the-art machine learning algorithm and the local post-hoc model agnostic method of Shapley Additive Explanations, the newly developed SHAP location score is able to account for empirical complexities, especially for non-linearities and higher order interactions. The SHAP location score represents an intuitive and flexible approach based on econometric modeling techniques and the basic assumptions of hedonic pricing theory. The approach can be applied post-hoc to any common machine learning method and can be flexibly adapted to the respective needs. This constitutes a significant extension of traditional urban models and offers many advantages for a wide range of real estate players.

In a world subject to a higher frequency of extreme climatic events, migration appears as one adaptation strategy for households, so that demand for housing will change. While a large literature analyzes cross-country migration mechanisms linked to climatic events in developing countries, or focuses on specific case-study events in both developed or developing countries, the literature remains scarce with respect to the impact of climate risks on household location decisions and internal migration.

In this context, the goal of this paper is to determine the relationship between climate shocks and intra-country residential migration, for the case of France. We propose a response function that includes the nature of the climatic shocks combined with local geographical characteristics. Our empirical strategy exploits short-term extreme climatic events, such as floods or large fires, as information shocks that impact households’ beliefs. These shocks, combined with household-level panel data pertaining to housing search behavior, allows us to estimate how extreme climatic events (ECEs) shift household location decisions. In particular, we exploit a large database containing housing search for a specific household before and after a climate event on real estate online platforms in France. Specifically, we first use a database of listings consultations on SeLoger platform containing more than 16 Millions search observations. Second, we use a database of real estate estimations on the Meilleurs Agents platform containing more than 100 000 search observations. We combine these datasets with a dataset of climate-related extreme events and official risk maps. Both of these datasets are spatially disaggregated at the municipality level for the Metropolitan France.

Workplace collaboration, interdependent work, is an intellectually intense and highly social endeavor suggesting that some collaborative activities are more effective face-to-face ‘in person’, within the office environment.  To foster and enhance collaborative work, organisations have focused their efforts on creating collaborative workplaces, with the expectation that workplace management models combined with design features will encourage employees to build relationships and share their knowledge and expertise. Utilising team boundary theory the study looks at the paradox between proximity, the degree of physical closeness between employees and teams, and their need for privacy in an open-plan office that operates a combination workplace management strategy – allocated desks and hot-desking. The results reveal that boundary behaviours within-teams and across the six teams in the one business unit studied varied. The team with a highly specialised knowledge and skill base,  under constant pressure to mitigate information leakage in their business dealings, relied on within-team collaboration. They preferred to work together from clustered banks of allocated workstations in an area of the office that they considered to be ‘theirs’. The hot-desking arrangements for the three teams that had a shared knowledge base and complicated skill set did encourage knowledge sharing, mainly through brief interactions and impacted their perceptions of who is in the ‘team’. The results also highlight design features that make workspace fit-for-purpose and those that create barriers to collaboration.

In this article we analyze the dynamic returns of REITs and test multi-factor asset pricing models based on real estate specific risk exposure, including market risk, size, value momentum, cash flow volatility, leverage, investment growth, term risk, default risk, liquidity risk and common macroeconomic factors. We also focus on the role of idiosyncratic risk and higher moments and scrutinize their relative importance to explain the decomposition of listed property companies returns on U.S. financial markets. We suggest the use of a new parsimonious common factors model to improve REITs valuation and to define their cost of capital. Revisiting the previous literature devoted to the role of leverage in the real estate industry, our empirical (un-conditional and conditional) results shed new light on leverage risk and idiosyncratic risk for U.S. REITs returns over a long period (2000-2021) marked by important crises.

Virtual real estate investments are becoming an increasingly important investment instrument in terms of investing in virtual land assets in the Metaverse. In addition, when investment decisions in the Metaverse are analysed, it is observed that there are highly similar market movements with the real world. This situation can provide insight into real-world prediction when using traditional methods such as multiple linear regression (MLR) on very large databases. This paper analyses the correlation between the two worlds by obtaining statistical results using data mining algorithms.Purpose of the study is to identify the potential high-yielding ones among Istanbul neighborhoods with analyzes made for virtual lands, which are seen as a virtual real estate investment instrument, and to determine the relationship between them by comparative analysis of virtual land values and real estate values. In this context, Metaverse platform (overthereality.ai) where the world map is divided into virtual lands, was accessed with open access software to get the data of virtual lands traded in primary and secondary markets within the borders of Istanbul. At the same time, square meters prices data of residential units for sale were also accessed from the real estate site (sahibinden.com) with the highest sales volume in Turkey, and these data were converted into land values and statistically analyzed, together with virtual land values, specifically for Istanbul neighborhoods.

This study analyses the time-varying composition of real estate values by using an artificial neural network approach to identify whether and how certain indicators’ impacts on property values fluctuate over time. Therefore, cross-sectional property and macroeconomic data from the United States is applied, spanning a period from 1999 to 2021. In times of normal economic activity, property values are made up of two-thirds of physical attributes and one-third of the macroeconomic environment. During crises periods and times of high uncertainty, like the Global Financial Crisis, the share of the economies impact increases by roughly 5%, meaning that sudden economic changes have a higher impact on property values during crises periods versus normal times. However, these changes in the composition of real estate values varies even from one crisis to another, which confirms the dynamic relationship between the US macroeconomy and the housing market. Moreover, this study provides evidence that neural networks are capable of detecting non-linearities in property values especially during times of financial volatility.

Conditional geographical clustering is the strategy of grouping real estate properties within a contiguous region to exploit economies of scale through spatial proximity. We expect significant benefits from this strategy as a result of gains in local market expertise and cost reductions associated with improved operational performance from the efficient management of a portion of a Real Estate Investment Trust (REIT) property portfolio. This strategy differs from both geographical diversification and agglomeration strategies. Geographical diversification is the strategy of acquiring properties in distinct geographical markets as to take advantage of the diversification effect of the differing economic conditions in the multiple markets. However, managing a property portfolio that is geographically disperse may pose challenges such as lack of expertise in the multiple markets, difficulty in property monitoring, lower management efficiency, and higher agency costs.  Prior literature finds REIT geographical diversification either destroys firm value or has little to no benefit. Ambrose, Ehrlich, Hughes, and Wachter (2000), Capozza and Sequin (1998, 1999), Gyourko and Nelling (1996), and Demirci, Eichholtz, and Yonder (2020) find either no, or limited, evidence of economic benefits. Whereas, Campbell, Petrova, and Sirmans (2003), Cici, Corgel, and Gibson (2011), Cronqvist, Hogfeldt, and Nilsson (2001), and Hartzell, Sun, and Titman (2014) present results that indicate discounts in value for geographically diversified REITs. More recently, Feng, Pattanapanchai, Price and Sirmans (2019) find geographical diversification benefits arise for REITs with high levels of institutional ownership and which invest in core property types. Agglomeration, on the other hand, refers to the strategy of locating properties near concentrations of economic activity such as in areas of fast economic growth or areas where similar properties owned by other firms are located. Prior literature explains agglomeration economies benefits firm productivity and provides positive externalities (Henderson 1986; Henderson 2003; Rosenthal and Stranges 2008; Melo et al., 2009; Greenstone et al. 2010; Koster et al. 2014) which may explain the concentration of REIT properties in certain U.S. markets. However, agglomeration generally refers to the location of properties neighboring other properties that are not owned by the REIT.

In this paper, we examine the impact of conditional geographical clustering on REIT operations and firm value. Specifically, we test whether a strategy of property clustering translates into improved efficiency and performance that may impact REIT firm value and stock returns. That is, we explore channels through which conditioned geographical clustering contributes to REIT shareholder wealth. Such channels include operational efficiency, operational performance, and credit risk.

We contribute to the literature by measuring the optimal REIT cluster size (in terms of number of property units) and distance (in terms of amplitude of radii) by property-type specialization. This analysis provides REIT managers with indications of if property clustering is an effective strategy for all REIT specializations. Moreover, for those property-types for which clustering matters, our results provide guidance on the optimal proportion of the portfolio that should be clustered and the size of the cluster that will provide most benefit. The analysis by property-type specialization is of particular importance since each property sector has unique characteristics, distinct demand and supply drivers, and responds to economic factors in different ways. Each REIT asset class signifies a distinct business line with different economic sensitivities and which calls for a particular investment strategy that corresponds to the idiosyncrasies of the property type. Prior literature highlights the importance of property-type specialization segmentation in REIT studies finding, for example, that specialized REITs show varying degree of business cycle exposure, tend to have distinct levels of correlation with the economy, show markedly dissimilar capital structures, varying risk-return characteristics and deviations from net asset value, and are prone to different pricing anomalies (Wheaton, 1999; Reddy and Cho, 2018; Van Nieuwerburgh, 2019; Huerta et al., 2020).

This abstract discusses the concept of market-based consistent capitalisation rate, which is used to value assets and project market returns. The authors argue that in order to gain insight into pricing, it is necessary to explore the theory behind determining a discount rate, also known as the capitalisation rate. The capitalisation rate is used to discount the cash flow to calculate property value. Market pricing can be obtained by observing the value of the capitalisation rate, which has two applications: pricing other assets and diagnosing the drivers of capital growth. However, the authors raise concerns about inconsistent assumptions in the cash flow and their impact on comparable yields across markets. They propose an alternative approach of calculating a consistent capitalisation rate based on minimal assumptions in the explicit part of the cash flow or the flow valued in-perpetuity, which can then be used to calculate the impact of changes in market pricing on capital value and make price comparisons across markets.

The article aims to identify the revealed preferences of buyers in the secondary housing market in Warsaw. The study was conducted based on data on real estate transactions made in the secondary market in 2016-2020 in Warsaw. The data was supplemented with information from the land register (section II - ownership), the real estate cadastre and using Google Street View. Based on hedonic models and unique datasets covering more than 25,000 observations, preferences were investigated by gender, age and marital status.

We compare the performance of Markowitz’s mean-variance analysis based on Pearson correlation coefficients (PCC) and Partial-correlation coefficients (PACC); using monthly return data on 11 REIT sectors and the EREIT index, over the period from January 1994 to December 2022.  The results of the empirical analysis show a number of features of interest.  First, we find that the off-diagonal elements of the PCC matrix are significantly positive.  In contrast, the corresponding off-diagonal elements of the PACC matrix, conditioned on the EREIT index, are generally insignificantly different from zero and in a number of cases significantly negative.  Second, we find that PACC-based minimum-risk portfolios (MRPs) are more diversified than PCC-based portfolios.  While the PAC-based weights of the MRP change significantly from period to period, the MRP weights using PACC are very stable.  The stability of the PACC portfolio weights means that the weights in one period can be used in the next period, with very little increase in portfolio risk.  Therefore, the extent of rebalancing is limited in PACC portfolios, which will minimise transaction costs.  In contrast, the instability of the PCC-based portfolio weights means that holding the optimum weights of the MRP in one sub-period leads to portfolio risks that are on average 30% greater than with an MRP optimum solution in the next sub-period.  In other words, the MRPs estimated by the PACC method are substantially better than that by PCC-based methods.  We conclude, therefore that portfolios constructed by PACC are more useful and meaningful for risk management and optimal portfolio selection than Pearson correlation-based methods.

The post financial crisis tightening of mortgage conditions and changes in mortgage market regulation are the focus of this paper, considering variation across both UK regions and household types. The methodological approach employs a double hurdle model. A truncated regression and its empirical specification seek to reflect the presence of credit constraints, accounting for significant changes in financial regulatory regime. The econometric focus of the paper is the second hurdle (the demand for mortgage debt) in the double hurdle model, and the impact of mortgage type on this hurdle. Models employ Understanding Society Survey (USS) Data, covering newly originated mortgages for the period 2001-2018. The paper finds that since 2008 the North of England, Yorkshire, East Midlands, Wales, and Northern Ireland experience issues with access to both variable and fixed rate mortgage funds, while Scotland and the West Midlands had limited access to fixed rate mortgage credits. First-time buyers continue to be constrained by mortgage credit funds. Furthermore, we consider lenders’ profitability motives, constraining the supply of fixed rate funds for liquidity constrained (low income) households. Policy implications of this research include awareness of potential asymmetric responses to changing lending conditions within the mortgage market across regions which may assist in designing improved financial regulatory measures and housing affordability programs.

Unlike many other major asset classes, when buying a physical asset like real estate, the legal date of the transfer of ownership is typically somewhere after the date of purchase. Using residential real estate as an example, we hypothesize that this period, the time-to-close, has a positive impact on transactions prices as a seller wants to be compensated by the buyer for the expected losses in terms of foregone house price appreciation, interest payments of a bridge loan, and any short-term rental costs over the time-to-close period. We show corroborative empirical evidence using a combination of administrative and realtor data from the Netherlands. Our results imply that the time-to-close is a fundamental part of the transaction process of physical assets and, as such, plays an important role in the price determination of such assets.

In the yearly United Nations Climate Change Conferences the participating countries have agreed to establish legally binding obligations to reduce greenhouse gas emissions. The climate change reduction measures as set out in the Paris Agreement are translated for the various countries into specific regulatory requirements by the nationally determined contributions – NDCs. The necessary reductions in greenhouse gas emissions until the year 2050 are split up for the various sectors like buildings, energy, industry, transport, agriculture or waste management. The building sector is decisive to limit global warming stemming from the increase in CO2 emissions. If the maximum temperature rise due to CO2 emission should be really kept to 2.0% (or even 1.5%) how much does the building stock has to decarbonize by when? Is this achievable for Europe? Seventy-five per cent of buildings in Europe are energy inefficient. Most of today’s buildings will still be in use in 2050. The annual renovation rate is only around 1.2 per cent. Investments in higher energy efficiency in real estate are often seen as low return and high risk. The perception of high risk is related to unclear investment costs, uncertain financing options and payback periods that are considered long. It is examined how the required route to net-zero for the real estate sector according to the nationally determined contributions match the present circumstances of the existing building stock in Europe.

Real estate price dynamics are well described at a large scale, but it suffers from a poor understanding of the fundamentals behind these dynamics, especially locally. Indeed, many indicators produced by different actors describe the fluctuations of prices well but fail to explain the mechanisms driving these changes at a local scale. This work aims at measuring the relevancy and the explanatory power of a set of potential economic, demographic and financial fundamentals on the housing price evolutions at a local scale, covering all France. The main objectives are to highlight the underlying factors of sub-markets in France and quantify their relative influence. The determinants of the housing markets have been studied in several papers at a country scale or for specific big cities. Indeed, some work focused on the Europe scale (Banerji, A., Shi, H., Hilbers, M. P. L. C., & Hoffmaister, M. A. W. (2008), Égert, B., & Mihaljek, D. (2007)), the country scale (​​Bessone, A. J., Heitz, B., & Boissinot, J. (2005)), or directly in specific cities (Baroni, M., Barthélémy, F., & Mokrane, M. (2008)). If some economic or financial variables like the interest rates or the average disposable income of a household seem to be designated as key factors explaining the fluctuations in prices, the relative influence of each of these variables on housing prices might be different in all sub-markets in France.

In this work, the influence of a set of potential determinants is measured thanks to statistical methods which are regularly used for this kind of purpose, such as simple linear regression, panel VAR methods, or cointegration measures. These methods have been tested on a database of indices covering all France. This study is based on a set of more than 800 indices built on a regionalization of France based on socio-demographic and economic data. These indices offer a good representation of house price evolutions at a local scale by construction of regions as fine as the available data allows. The fundamentals tested for this work are a set of time series data of economic, demographic, and financial variables covering the entire period 2010-2020 and are retrieved at the finest geographical scale. These variables were chosen among the more often cited in academic literature as potential underlying factors of real estate dynamics. The fundamentals tested are the following : long term interest rates, short term interest rates, unemployment rates, evolutions of population, inflation, new built construction, income evolution, savings rates, disposal income.

The contribution of this paper is twofold. First, we are, to our knowledge, the first to systematically test for the impacts of potential determinants of the evolution of housing prices, over a whole country, at a local scale. From a methodological perspective, it forces us to introduce a new custom econometric approach in order to produce meaningful and intelligible results. Second, we measure significant differences in the role played by the drop of long term interest rates in the price dynamics among local markets. In our opinion this is a proof of the asymmetric transmission of the accommodating monetary policy decided by the European Central Bank from 2015.

Corporate bonds are an important source of funding for real estate investment trusts (REITs). The outstanding unsecured debt of U.S. equity REITs, which is an approximation for outstanding bond debt, was $450 billion in 2022, while REIT net asset value was $1.1 trillion in the same year. This highlights the importance of corporate bonds for U.S. REITs. However, the literature on bond risk premia focuses only on corporate bonds in general and neglects the specific structure and functioning of issuing REITs. Specifically, U.S. REITs must distribute 90% of their taxable income to shareholders, which prevents them from building capital internally through retained earnings. Since corporate bonds represent a general claim on corporate assets and cash in the case of default, we hypothesize that the drivers of REIT bond risk premia differ from those of the general corporate bond market. Therefore, this paper aims to fill this gap by examining yield spreads, which are the difference between the yield on a REIT bond and the U.S. Treasury yield having the same maturity. Based on findings in the empirical asset pricing literature on the superior performance of artificial neural networks in the adjacent fields of stock and bond return prediction, this paper applies an artificial neural network to predict REIT bond yield spreads. We use a data set of 27,014 monthly U.S. REIT bond transactions from 2010 to 2021 and 33 explanatory variables including bond characteristics, equity and bond market variables, macroeconomic indicators, and, as a novelty, REIT balance sheet data, REIT type, and direct real estate market total return. Preliminary results show that the neural network predicts REIT bond yield spreads with an out-of-sample mean R2 of 36.3%. Feature importance analysis using explainable machine learning methods shows that default risk, captured by REIT size, economy-wide default risk spread, and interest rate volatility, is highly relevant to the prediction of REIT bond yield spreads. We also find evidence for tax and illiquidity risk premia. Interestingly, equity market-related variables are only important in times of economic recession. Real estate market return is an important feature and is negatively related to the predictions of REIT bond yield spreads. These findings underline that bond risk premia for REITs have additional drivers compared to those in the general corporate bond market.

Models to be established in large geographies or for multiple location selections should be as dynamic as the urban area itself. As much as the feature selection of the variables to be used for site selection models, the accuracy of the catchment areas will make important differences in the right location decisions. With the study, methods to adjust the catchment area by using the features of the facility to be positioned and the differences of the geography will investigate.

In general, facility location models are static models that evaluate demand and environmental conditions in a specific period. However, cities are dynamic and the demand and environmental conditions that will occur in cities are changing.  Therefore, it is not efficient or applicable to use access areas determined by the literature in each site selection study. In addition, as the demographic variables focused on each sector and geography may change, the catchment area should be redefined according to the geography and sector.

The study will focus on a location selection model that can be applied in a vast geography for a function that requires many locations to be determined. There are two questions that the study is designed to answer. First, how can the correct reach or area of attraction be determined for a large geography? Second, is it possible to produce dynamic site selection models by adjusting the catchment areas determined in the literature according to the characteristics of the geography?

The method will be one of the most critical decisions in the study. There are two prescribed methods for determining the correct distance. First, according to the details of the fieldwork, a variable related to distance will be generated and it is assumed that this variable will pass through feature selection. Another method can be to perform a consistency test with segments produced for different reach distances. The findings of this study will be supported by further analysis for example case studies with different dependent variable data such as the number of users and/or sales data. In addition, the outputs of this study may support researchers to develop new adjustment methods for facilities that are not studied before.

The NSW Crown Land Estate (CLE) consists of over 500,000 parcels of land, totalling over 300,000 square kilometres in area and valued in excess of $A13b (£7.3b).  Of this, a substantial portion is Crown Leases which can relatively easily be valued on a capitalisation basis.

This paper will focus on the General Category of land in the CLE, consisting of over 120,000 parcels of land (over 22,000 sq kilometres) and valued in excess of $A10b (£5.6b).  As such, this section of the CLE is over 2.5% of the area of the State and represents a considerable portion of the State’s assets.  For the General Category of land, a sales comparison approach is the most appropriate valuation methodology.

Annual valuations are required for the CLE and a mass valuation approach is necessary.  There are a number of issues in designing such a mass valuation process, the main concerns being that the portfolio is quite clustered and the distribution of the sizes and value of land parcels is skewed in the extreme.

The development of a 3-year cyclical mass valuation process will be discussed.  This process identifies suitable submarkets (strata) and a benchmarking process in each submarket.  A simple model is used which takes account of the extreme skew in parcel areas.  This permits the valuation of individual parcels of land while the main focus is on the valuation of the portfolio including estimates of the “error” in portfolio valuation.

Digital technologies has transformed human experience in the virtual world. Metaverse work as a network of 3-D virtual worlds where human can interact, carry out business, and build connections through their ‘avatars’ or digital identity. These would also grant an access to digital ecosystem through its own currency, property and possessions. In the metaverse, disruptive technologies (such as AR and VR, Blockchain, AI, 3D reconstruction and IoT) support the trading of digital real estate assets (such as sales and purchase of virtual lands) in the form of Non-Fungible Tokens (NFTs). Investment in real estate metaverse is currently experiencing a great return. Presently, real estate sales in the metaverse have been concentrated on the 'Big Four' — Sandbox, Decentraland, Cryptovoxels and Somnium. Therefore, investment in digital real estate assets require some degree of skills and competencies in the metaverse. The concept of digital intelligence is a set of skills needed by investors to meet digital technologies' demand in trading of digital real estate assets and the virtual world's challenges. This paper therefore explore the need for digital intelligence in investing in digital real estate assets in the metaverse from a theoretical perspective. Review of relevant literature in the subject area was adopted for this study. This paper outlined the major benefits of digital intelligence in the purchase of digital real estate assets as identifying the virtual land with the highest traffic, understanding the digital footprints in a geospatial context among others. This paper provide policy implication on the need for investors in digital real estate assets to acquire necessary digital skills (such as digital: identity, rights, security, safety etc.) for a successful business transactions (sales and purchase of digital assets) in the metaverse.

Purpose – The Delft University of Technology adapted their sustainable mission and wants to apply it also to the corporate real estate management. To allow decision making based upon a more integral approach in a long term perspective a choice is made for total cost of ownership. The benevolent project managers, asset managers, facility managers and financial account managers then ask for data, where they actually need a compass to interpret that data. The purpose of this paper is to find that compass. 

Design/methodology/approach – A theory-practice oriented approach is followed. Literature review is conducted to identify the need for a new economy that distances itself from the outdated neo-liberal models and gives space to a material-driven circular economy on the one hand and the more pragmatic life-cycle cost (total cost of ownership) approach on the other.

Findings – It seems that the donut economy offers the compass that the practice currently needs. It offers scope for making assumptions in a period in which people know which way things are going and at the same time want to have 'hard data'.

Quality/value – The study has the potential to support the university real estate management in its aim to meet their sustainable mission and to set a general approach. It will contribute to a larger research on this topic.

Housing is one of the three basic needs of man alongside food and clothing. Housing is globally recognized as a fundamental human right. Housing has a positive impact on man’s welfare, health, efficiency, social behavior, satisfaction, and employment opportunities etc. Man’s access to housing can be frustrated by discrimination, and this discrimination occurs on various grounds. This study reviewed extant literatures on housing discrimination with the aim of revealing key findings, and gaps in literatures so as to set up future research agenda. The study made use of literatures extracted from Google scholar. . This study found that the housing discrimination occurs along the line of gender, race, ethnicity, religion, language, age, marital status, disabilities, income level, occupation, immigration status, family size, sexual orientation, nationality, color of skin, gender identity, victims of domestic violence, and ex-offenders. Most studies on housing discrimination has been carried out in United States, Germany, and Canada. This study found that there is paucity of study on housing discrimination in Nigeria, and there is need to fill this gap in literature.

Institutional investors, such as insurance companies and funds, can increase the risk-adjusted return of their real estate portfolio by directly or indirectly granting real estate loans. This is the central finding of our study. Real estate loans, also known as real estate private debt (REPD), which are not issued through bonds but are granted directly by banks and institutional investors, are an ideal addition to a real estate portfolio, according to the study.

Contrary to its relevance, this topic has received little attention in the literature so far, so that there are currently no comparable studies. Within the scope of the work, the diversification potentials that can be achieved in this way were examined. For the US market, the Giliberto Levy Commercial Mortgage Performance Index (GLCMPI) provides publicly accessible data for an analysis of the performance of REPD. The "NCREIF Property Index" (NPI) was used as a benchmark for the property portfolio to be diversified. Portfolio theory formed the theoretical foundation of the study. The indices were evaluated over the largest possible observation period from 1978 – 2021.

The COVID-19 pandemic that started in early 2020 and the refugee crisis related to the Russian invasion on Ukraine in February 2022 have been the source of shocks to the housing rental market. It has been particularly visible in Poland, where the market reacted to the changing environment through multiple channels, out of which two are the areas of interest of this paper. First of those is the rent-setting factors channel as it may be hypothesized that in response to those shocks the preferences of market participants have changed. Secondly, the drastic changes of demand and its structure resulted in an unprecedented variation of rent levels. Based on the hedonic model of the market of Poznan (Poland) it has been documented, that the pandemic influenced revealed preferences of market participants towards certain housing characteristics, such as the number of rooms, proximity to green areas and proximity to city center, leaving the price elasticity of presence of balcony unchanged. As for the impact of  the refugee crisis on the rent-setting factors, it has been shown that it has affected the tenants’ attitudes towards apartment furnishing, its type of heating and the type of building in which the apartment is located. Moreover, the quality-adjusted hedonic rent indices have been obtained using OLS, quantile regression and Spatial Autoregressive Model (SAR). Their goal has been to quantify the rent change of the market in years 2019-2023 but also to discuss the sensitivity of the rent indices to the rent-setting factors changes. The analysis has been conducted on the unique (in terms of the number of housing characteristics and their completeness) dataset of rental listings. However, in order to prove the validity of the results the comparison of some transactional and listings data has been provided. The early results show that the coefficients of the models built on the possessed dataset of apartment listings go in line with the ones obtained on the transactional data. Thus, running the analysis of the rent-setting factors on the listing data may be considered justified.

We examine the performance and interaction between earnings momentum and Google search attention using a global sample of 368 property-holding companies from 2005:1 to 2019:9 in the FTSE EPRA/NAREIT Global Real Estate Index. The portfolio returns are analyzed on a risk-adjusted basis employing a Carhart four-factor model. First, we show that high earnings REITs and REITs with high levels of unexpected Google search volume outperform in the subsequent month followed by a long-term reversal. Second, we find that unexpected Google search attention intensifies the earn- ings momentum. Third, we find that the attention-based momentum Granger causes the earnings momentum.

Research on ESG and real estate suggests that the industry can contribute to mitigating climate change by improving the “sustainability” of their property portfolio while also gaining better financial performance. However, the challenges of sustainable property investments (SPI) still exist due to the diffused causal chain between the high initial costs of investment and the resultant benefits in the long run. The aim of this study is to identify and model the impacts of SPI on the credit rating of Real Estate Investment Trusts (REITs), providing insight into the motivating factors that influence investors’ decisions to invest in properties with sustainability characters. The study was based on the panel data of 84 US equity REITs over 2014–2021. The regression analysis demonstrates a significant positive correlation between the sustainability of REITs’ property portfolio and their credit ratings, and that the advantages of SPI overshadow saving operational expenditures alone. The sub-period analysis also indicates that the marginal benefits of SPI may diminish over time, which, however, needs the support of further research. For robustness check, the type-year average of portfolio sustainability is used as an instrument variable in a two-stage model, and the results support previous findings. In short, this study supports the outlook that ESG-related investments are crucial parts of rating agencies’ assessment of REITs’ creditworthiness, and can enhance corporate financial performance through lowering firms’ debt financing costs.

Participants of an online Luxembourgish study are presented fake real-estate advertisements and tasked to make an offer to the shown properties. A random subset is also shown sellers' names that are strongly framed to signal their origins. Our randomised procedure allows us to conclude that, keeping everything else constant, sellers with African-sounding surnames are systematically offered lower prices. Our most conservative estimates suggest that the average racial penalty stemming from the demand-side of the housing market is equal to 22,000 euros. Last, we show that this penalty hides important differences across respondents: it is null for the youngest and most educated ones as well as those without any personal ties to an African diaspora, but can amount up to around 65,000 euros for those above 40 years of age and without post-secondary education.

Holistic real estate strategies have to fulfill different interests and demands. Not only do qualitative and quantitative goals have to be reconciled, but also conflicting goals have to be resolved. This paper investigates how to create a real estate rating that captures the dynamic developments of real estate over its life cycle. A proprietary model is presented that is based on a dynamically evolving utility analysis and takes into account both changes in condition and the changing requirements of user groups. This dynamic model for a real estate rating therefore not only offers the possibility of depicting future developments of a property, but also has the potential to derive correspondingly comprehensible and needs-based real estate strategies. A dynamized utility analysis, especially in combination with a system dynamic modeling, offers the potential to develop needs-based real estate strategies over the entire life cycle of real estate. The developed model is applied to a simulation and evaluated by experts from the real estate industry. As a result, a needs-based real estate strategy is derived.

This research investigates integration between housing and stock markets across 11 countries. Using total return indices over 1870 to 2015, results around the globe consistently show that stock and housing markets are integrated with a bilateral causal relationship. Our results have important implications for  portfolio diversification strategy and capital-switching effect hypothesis.

In recent years, Berlin has been the scene of various government interventions in the local real estate market, especially in the residential sector. Alongside measures like the "Mietpreisbremse" (rent brake) and the "Mietendeckel" (rent cap), the establishment of so-called "Erhaltungsgebiete" (urban preservation areas) is one of the most dominant state interventions in the Berlin real estate market. In Germany, urban preservation area statutes are regulations that can be enacted by the municipalities based on the special urban development law according to the German Building Code (BauGB). Since 1995, Berlin has established 74 urban preservation areas to preserve the composition of the local residential population and to avoid segregation and gentrification. This study provides insights into how the designation of urban preservation areas affects local housing prices and whether the objectives pursued by the regulator are achieved. Therefore, a unique data set, including 370,000 apartment transactions between 1984 and 2020, is analyzed. In combination with spatial data, a staggered difference-in-difference approach is used to investigate the real estate price development before and after the implementation of the respective regulation in comparison to non-regulated properties.

In Malaysia, the concept of land leasing onto land title has been extended to the strata title of a multi-story building, known as the strata lease scheme. This case study aims to provide, firstly, an overview of strata lease schemes in Malaysia and, secondly, a discussion of how the intention of developing strata lease schemes led to the creation of a new township. Data were obtained through interviews and document reviews from a single case study named Bandar Baru Farlim in the State of Penang, Malaysia. This study highlights best practices in property development initiatives toward sustainable housing delivery. 

MEES is a measure to improve buildings’ energy efficiency. However, whether this legislation will achieve its goals is not certain. Since the implementation of MEES, limited evidence of possible impact and effectiveness has been published, especially there is no post-implementation evidence. In this paper, we investigate whether price differentials exist between the EPC-labeled office buildings and nonlabelled buildings; then we further investigate whether the premiums/discount are affected by the level of rating if the price differentials exist, especially for the ones below MEES. We use a much larger sample of office buildings across England and Wales. We use the data of the office buildings, their hedonic features, and the rents from Costar. The EPCs are from data from the Ministry of Housing, Communities and Local Government with which the EPC assessment and rating reports are registered. The proportion of energy performance-certified buildings in our sample has increased significantly to above 50% of the total sample.   12,514 investment office buildings with the full information at the end of 2021 are included in the study, among them, 55% of the office buildings have valid EPC  ratings. This is the first study of UK commercial real estate with such a large sample to examine the effect of the EPC on commercial real estate value and provide some post-implementation evidence of the effectiveness of the MEES regulation.

This paper assesses the role of local greenness in attracting ESG capital into infrastructure deals in the US. Local greenness refers to state-level policies and incentives to increase energy efficiency, local capabilities to develop green assets, and local citizen’s green ideology. We identify ESG investors as infrastructure private equity (PE) fund management firms who have signed the United Nations Principles for Responsible Investment (UN PRI). We find that in states with higher greenness, ESG PE investors are more likely to be involved in an infrastructure deal. We show that green policies and incentives contribute to a boost in green capabilities and green ideology thus reducing political and regulatory risk for ESG investors interested in low-risk-low-return way of “greenifying” their portfolio. 

In the last three years the world has been moved from one crisis to the other one. There are so many factors that had crashed the stability in previous paradigms. The level of uncertainty is growing in all countries.  The purpose of this paper is defining the movements on Estonian housing market and trying to evaluate the possible impact of COVID- 19 crises. Does the COVID crisis had an impact and how significant the impact is/was to the movements on the housing market. 

Firstly, the article describes economic background and trends before COVID crises. Secondly, the analysis the activity and dynamics of housing market transactions and prices in pre and during the COVID-19 time. Trying to find an answer does the COVID time change the preferences of homeowners to change the living space from city to the countryside. There is obviously an impact of energy crises and problem with rising maintain costs, but there is a need for future research. 

Finally, there is still in air the geopolitical risk, that seems to have not an impact to the housing market yet.

I conduct an empirical analysis of household living space consumption based on microdata from the German Socio-Economic Panel. At the stage of the family life-cycle when children launch from home, frequently, no adjustment of living space takes place by the parental household, the then so-called empty nest household. In many cases, this doesn't happen due to market frictions like political interventions which lower the mobility of elderly households. I claim that a better utilization of this space would improve housing markets suffering from a lack of dwellings. Supplying this space to the market can substitute new dwelling construction and prevent related environmental harm. Thus, I quantify the total amount of excess living space in Germany related to this life-cycle effect using a multiply linear regression model to approximate the potential of living space creation by comparing empty nest households to a control group. On average, empty nest households consume 11 m2 more than the control group. Further, the application of a fixed effects model shows that if empty nest households move, they downsize significantly by about 16 m2. Moreover, I estimate environmental effects related to the substitution of housing construction. In short, my results show that there is a significant amount of vacant space in so-called empty nest households. Thus, measurements which support older households with freeing-up living space would ease tight housing markets and prevent environmental harm.

A better understanding of the behaviour of housing systems is essential for being able to develop planning policy interventions that can improve matching households with appropriate homes. Thus, understanding individual housing aspirations is crucial because these aspirations have a significant impact on housing systems. This paper examines generational differences in housing aspirations in light of demographics, lifestyles, and socioeconomic and political factors. It develops and evaluates probit models to a data set comprising 3407 responses in Turkey, an emergent market context. The results suggest that economic factors and lifestyle are affecting individuals’ housing aspirations.

The recent accelerated growth in PropTech and real estate innovation has created enormous opportunities for investors and entrepreneurs. Data from Unissu (2022) reveals that in 2010, PropTech attracted an investment capital of approximately $900 million and by 2021, the PropTech sector attracted approximately $18 bn. As expected, PropTech investment capital flow has been uneven across world economies. A huge proportion of this capital is concentrated in North American, Western European and core Asian economies, suggesting an uneven distribution of PropTech capital across world regions and economies. 

Research has shown that macroeconomic, demographic, geopolitical, institutional, and legal factors influence real estate capital flow. However, the impact of these factors on PropTech capital flow has not been explored. This research, therefore, aims to explore some of the key factors that attract PropTech investors to various countries and world regions. The study uses OLS models to explore core PropTech investment pull forces and further uses machine learning algorithms to forecast future PropTech capital concentration.

Purpose: The purpose of this study is to determine the weight of factors such as façade orientation, view, floor location, and daylight access that affect the value of the housing unit, and to measure whether the weights of these factors change depending on the users of the different types of housing units.

Study design/methodology/approach: The weights of the factors influencing the value of units in housing projects were determined in this study using the AHP model. The AHP model is presented as a survey to the residents of the housing projects. The results of AHP are analyzed using statistical tests.

Findings: According to the results, view and daylight are important factors for all types of housing units. Looking at sub criteria, we see that park view and middle floor are highly preferred for all apartment types. This is followed by a south view and main street view. The results suggest that there are certain preferences and trends in housing selection among residents with preferences varying based on factors such as unit size.

Originality: This study is a novel in terms of focusing on internal factors that affect housing value and weighting these factors according to different housing types.

Research limitations/implications: Only the physical factors that affect the architectural form and layout were examined in this study. Many factors such as financial, social, and environmental factors affect the value of housing units and those that do not affect the architectural form and layout of the building are excluded in this study.

Practical implications: The findings of this study will enable developers to better understand the needs of home buyers and design projects that meet those needs.

Aim: The aim of this research is to explore the influence of communication technologies on student social connectedness in the hybrid university learning environment (HULE). The importance of this research has emerged following the digitalisation of universities and introduction of the HULE. It is indicated by industry level research that student social connectedness is not only changing in these environments but being negatively impacted in these environments. Since it has been shown that there is a significant link between student social connectedness and the learning process, these findings are concerning. However, there has been little peer-reviewed research to help understand these new digitally orientated learning environments for the benefit of student social connectedness. Despite new communication technologies being continually developed and tested often for the benefit of the HULE (for instance, ‘the meeting Owl’), there is no real understanding of how they might: 1) improve student social connectedness in relation to other forms of existing communications technologies (for instance, ‘WhatsApp’), or 2) whether students engage with these technologies in the ways expected. Subsequently, the aim of this study is to expand the understanding of how student social connectedness is altered in the HULE with a focus on the communication technologies used in the HULE. 

Methodology: This empirical study adopts a perspective that centres on people-place relations to explore the relationship between student social connectedness, communication technologies, and the HULE. It applies theories of placemaking and socio-materiality to understand how students’ self-reported and observed perceptions of social connectedness are shaped by the communication technologies they engage with and the environment they located in. The study explores the case study of a Swiss university that has various campuses and actively engages with a hybrid-style learning approach. Qualitative data collection and analysis are being undertaken, comprising of focus groups, interviews, and questionnaire data. The study sample predominantly focuses on students at the undergraduate and master’s levels and the research target between 50-100 students in different classes and subject fields. Data collection began in the beginning of the autumn semester 2022 and aims to continue until the end of the spring semester 2023. 

Results: The findings are expected to indicate that students find it challenging to develop or maintain social connectedness in the liminal ‘in-between’ space of the HULE (for example, on the journey to class or waiting for a class to begin). Further, it is expected that their experiences with a place as an integrated aspect of social connectedness are also altered in the HULE, depending on their engagement with various communication technologies. It is expected that students will favour the ability to co-design their learning space to enable various communication technologies to be used, but certain guidance or ‘nudges’ could be useful to help students make more effective co-designing decisions. These findings will form part of a larger doctorate research project and expand on previously collected preliminary data to offer a larger basis for further research to be developed. It is expected to offer an innovative perspective on the HULE based on student social connectedness using perspectives from architecture and social geography, which aims to impact existing pedagogic approaches for university courses.

A fine spatial scale is essential to the widely applied omitted variable bias (OVB) treatment of small-area fixed-effects (FEs) in Hedonic Pricing (HP). However, environmental amenity valuation is subsumed into the FEs when amenities vary at a coarser spatial scale. To recover amenity valuation while retaining the OVB treatment, we derive a novel “Differenced-Price-Peers” (DPP) specification by integrating HP and the prices and attributes of spatiotemporal peers. The close equivalence between small-area-FE-HP and DPP for spatial OVB treatment and amenity capitalization is demonstrated in a rich data context for the distance to the city center. Further evidence shows DPP to successfully recover aviation noise capitalization in a context of sparse housing data and anisotropic noise pollution where small-area-fixed-effects-HP fails. The noise discount of house prices is -0.71% per decibel in DPP, which is about 70% higher than the magnitude of the non-FEs HP suggesting potential undervaluation due to spatial OVB.

Inflation is corrosive to real estate values. The performance resilience of real estate is directly linked to the ability to react to expected and non-expected changes in inflation. The degree of protection of the income component to higher-than-expected inflation is directly related to the ability of leases to consider CPI-escalation clauses. From the capital return perspective, assets with inflation-linked rental contracts are expected to provide higher protection due to more resilient real capital values. In order to assess the impact of inflation and interest rate hikes on the performance components of institutional real estate we merge MSCI performance data with macroeconomic fundamentals from Oxford Economics and estimate a semiparametric dynamic model. The results confirm that in an environment with +8% inflation, an economic growth of at least 2.5% is required in order for the income returns not to fall below long-term averages, whilst capital returns are not substantially affected in a recession with 4% inflation.

Real estate investment trusts (REITs) are widely used as a part of investment diversification opportunities of physical assets among investors. A number of studies on macroeconomic determinants suggest certain commonalities in commercial property market returns, which are driven by macroeconomic factors. This paper extends the range of common macroeconomic factors of REITs introduced by the existing literature. This paper outspreads the perspective of REITs analysis by employing up to 17 indicators in total that include not only usually used variables (GDP growth, CPI, equity markets indicators) but also new ones (among them with more significant relationships: business cycle, bond yields, PPI, industry production, credit for the private sector, hourly earnings for manufacturing, construction volumes, and building permits). We combine OLS regression (including time lags) with Granger causality and ARDL analysis to obtain more robust results. In the latter case, we identify the short and long-run relationship between EPRA and extended macro drivers. Our results confirm well-established relationships between EPRA, equity price growth, CPI, bond yields, and GDP. They also suggest the countercyclical behavior of EPRA, its negative relationship with PPI, industry variables, credit for the private sector and hourly earnings for manufacturing. However, it demonstrates a positive correlation between construction and residential building permits. The same results are obtained for short- and long-term perspectives. Furthermore, we demonstrate that including these new variables in the model increases its forecasting accuracy. Overall, our research contributes to an existing methodology of forecasting REITs' performance broadening the list of important macroeconomic variables that should be included in estimation of REIT’s performance.

Global developments have led to a fundamental change in the views and interests of consumers, especially regarding housing. Consumers have new demands for the housing of the future caused by complex circumstances. On the one hand, the use of sustainable building materials and renewable energies has increased due to rising energy costs and people’s growing concern for the environment. There has also been a massive increase in the desire for autocracy in housing. On the other hand, the socio-demographic developments, which show similar tendencies within the European Union, have changed the population’s mindset. An ageing society and the decreasing ability to act in old age are giving rise to new forms of housing. Therefore, there is an enormous desire for flexible living space that can be adapted to different stages of life. At the same time, these developments require digitalisation in housing. Digitisation is a necessary prerequisite for creating a new comfortable living environment and is an additional benefit for the residents. Thus, fast digital infrastructure and smart homes are coming into focus. The three megatrends - sustainability, socio-demographic developments and digitalisation - have an influence on future housing and are therefore focused on in this study.

Against this background, the study itself consists of two parts. First, it will examine which aspects affiliated with the three megatrends are changing housing from the perspective of private households. Then the different demands for housing will be analysed, according to various identified subgroups.

An extensive literature research forms the basis of the survey conducted with n= 962 private households in Germany. To achieve the research objectives, we conducted an experimental study that used the best-worst scaling method. The best-worst scaling method measures the individual strength of the respondents' perception of how a certain aspect will change future housing. Subsequently, a regression analysis is used to show the differences in perception of different subgroups.

The results of this study show that sustainable aspects are particularly relevant for home buyers. Considering the current environmental developments and similar socio-demographic developments within Europe, the results provide valuable insights that can also be transferred to foreign real estate markets. Thus, the present results provide important impulses for housing industry practice and point out important paths for further research.

The prevalent use of gifts, gratuities, and hospitality in the alternative real estate lending markets as part of business development practices has been observed, with the nature, scale, and type of such offerings varying significantly. With no formal regulation of the market, and a sole reliance on the U.K. Bribery Act (2010) alongside a handful of industry bodies, it begs the question of whether such offers may lead to market inefficiencies and unfair treatment of borrowers in the industry, resulting from the principal-agent problem arising. There has been substantial research demonstrating the benefits of including gifts, gratuities, and hospitality offers within any business development strategy as such practices lead to an increased number of real sales for the offering business. The resources exploring the principal-agent problem demonstrate the risks of such a problem arising and its impact on entire markets. Research has gone as far as to link the principal-agent problem to the misbehaviour of mortgage brokers within the regulated mortgage industry, an issue that became evident in financial crash of 2007/08. Minimal literature exists on business development practices involving the offering, and accepting, of gifts, gratuities, and hospitality. 

In this research perceptions have been sought from stakeholders within the alternative real estate lending market to determine the use and acceptance of gifts, gratuities, and hospitality. 

It is concluded that whilst there continues to be a place for such practices within the market, expectations of reciprocation from the recipient should be avoided, as it is at this point there becomes a significant risk of the principal-agent problem arising.

An important feature of China's housing market is the coexistence of high house price to income ratios and high homeownership rates, especially in several first-tier cities where house price to income ratios far exceed normal affordability. Based on questionnaire data from Hangzhou, China, and logistic regression models, our study finds that the most important factors driving the middle- and low-income groups to buy houses in China are: first, China's unique household registration and school district housing system, which leads parents who place special emphasis on education to buy houses in the city by all means; and second, the continuous rise in housing prices, which leads to a surge in investment demand and passive home purchase demand. The reasons why the middle and low income groups can afford the cost of home purchase are: first, China's unique kinship culture, where relatives and friends lend to each other to solve their down payment problem for home purchase; second, China's housing mortgage lending policy is more relaxed, and the middle and low income groups can easily obtain financial support for home purchase; third, China's economy continues to grow, and the real and expected income of the middle and low income groups keeps increasing, which guarantees the mortgage loan repayment ability. However, the high house price to income ratio leads to heavy financial pressure on the middle and low income groups and is not conducive to sustainable and healthy economic development. To this end, we suggest that the government implement a policy of equal rights for rent and purchase as soon as possible to promote the development of the rental market and expand investment channels for residents.

In this paper, we explore the health consequences of housing affordability on household members. We use the information about health in EU-Silc microdata from 2008 to 2020 for the European countries and identify the different impacts that lack of ‘ex-post’ housing affordability would have had at the country and regional levels. Based on previous studies, the paper tests whether different situations of lack of housing affordability (measured by the affordability ratio and housing stress) would have contributed to health conditions at a personal level, focusing on the different persons in the household and paying attention to children’s health. Thus, the personal files of EU-Silc are used for this purpose in a panel analysis for 2008-2020. The paper identifies and test the channels of transmission of lack of affordability to health, as direct and indirect. They are tested using panel-regression methods for 33 European countries. Results give empirical evidence that lack of housing affordability affects the self-reported health status in households with special incidence of mental health.

In this article, we use the framework of inflation beta to test the capacity of physical residential real estate to hedge against inflation and its components, and compare it to the inflation hedge ability of various financial assets. Specifically, the housing asset is represented by the residential market in the communes of the “Grand Paris” metropolis  with the different components of inflation. We start by analyzing the residential market in this area, its fundamentals, characteristics and dynamic. Then, applying the hierarchical clustering technique, we divide the Greater Paris area into five homogenous groups of communes and test its hedging ability using both correlation and regression analysis. Residential assets are confirmed to be a hedge against inflation, particularly against its unexpected component and thanks to its capital return rather than the rental return. On the other hand, the listed real estate does not provide the same hedging properties and thus cannot be considered as a substitute for this aim.

We study how the announced future land rent increases capitalize into leasehold prices. We investigate a case, where the City of Helsinki, Finland, announced over 15-fold rent increases for the ground lease contracts on residential land that were expiring in the near future. Our empirical strategy is based on a difference-in-differences design where we compare transactions of the leasehold units with those of near-identical freehold apartments. We find that before the first rent increase episode homebuyers were inattentive to their expected long-run housing expenses, which resulted in significant overpricing of leasehold apartments relative to corresponding freehold units. The results further suggest that housing market participants react on announced contract renewals and appear to learn the importance of the ground ownership feature when they are exposed to more and more information regarding rental contract updates. Our paper provides new causal evidence on the capitalization of information on indirect and nontransparent financial flows in the long run. Our novel finding is that market participants learn the new policy regime and the market prices (only) gradually reflect the information on future financial flows. The market reaction to new information is not immediate or absent but sluggish, which is in line with a simple model of information diffusion.

Coworking Spaces first appeared in large metropolitan cities, with a concentration of urban amenities and proximity to high-skilled workers, business hubs and public transportation. The coworking concept is still evolving, considering spatial changes, new governance structures and proliferation from urban to remote, peripheral and rural areas. This development goes along with the pressure of land and building prices in the core of EU metropolitan areas, CSs are pushed outside the central business districts towards peripheral neighbourhoods or to deprived inner-city areas with affordable rents.

Recently peripheral areas started to attract a growing number of coworking spaces in various European countries. There are different pull factors behind the emergence of CSs in these areas. While other researchers recognize the benefit of the low rent prices in rural real estate markets and associate the establishment of coworking with availability of affordable renting. It is becoming acknowledged that the factors behind the emergence of CSs in peripheral areas are miscellaneous. However, it is recognised that this relation is weak and ambivalent. By arguing that location factors of housing and CSs are similar but not the same, we open up the real estate perspective and follow a broader view on the success factors of coworking spaces. 

Based on the desk research, the authors constructed their own database of CSs in Germany and the UK. The authors gathered data on the residential prices and rents on a district level. To identfy real market differences between districts with and without CSs, the authors applied statistical analysis for independent samples.

The research shows that periperheral locations are attracting CSs to significant extent and that CSs are attracted by different determinants. The authors argue that the role of CSs in rather limitited in attracting real estate investors and boosting the real estate market in periphereal areas.

The focus of this study (CSs in peripheral areas) and the comparitative approach is original. Additionally, applying the housing prices to study the location of CSs is novel as well.

The Covid Crisis affected nearly all European countries. In contrast, house prices continued their upswing without any exception across European Countries. However, in line with the economic recovery coming to an end from summer 2022, signals for the end of the house price bubbles could be seen as well. How did the housing markets in European countries develop during the Covid crisis and how were they affected by various shocks (Ukraine war, supply shortages and increasing inflation) the following year? First results of the analysis underline that house prices went up all over Europe, but turnover figures (number of sales, volume) started to decline already in the first half of 2022. The development of house prices over the last decade since 2013 differed widely between European countries and much more than the development of economic activity within European countries. Comparing the developments since 2008, it is worth mentioning that GDP recovery following the GFC and the Covid Crisis allowed nearly all countries to reach their pre-crisis level until 2022 before the Ukraine war related effects hit again the European economies from summer 2022. In contrast to the economic developments, housing markets in various European countries did not yet reach the pre-crisis level until 2022 although the upswing of the housing markets started in Europe around 2014 even without being hampered by the Covid crisis. In a small number of European countries house prices doubled between 2008 and 2022. The available data on quarterly house sales (number of transactions and volume) seems to be a promising data source to develop projections of the housing market in many European countries.

The ultimate purpose of this study is to empirically analyze the difference in the level of the Sense of Community(SoC), according to the type of housing. To achieve the purpose of the study, this study analyzed the microdata of Seoul Survey. In the Seoul Survey data, the measurement questions on the level of the SoC used overlapping measures with the items of the SCI(Sense of Community Index) presented by McMillan & Chavis(1986). As a result, it shows that the difference in the SoC, according to the type of housing existed at a statistically significant level. First, the average level of SoC of Seoul residents was at a low level overall. Second, the level of SoC by housing type is high-rise condominium dwelling group, house dwelling group, and low-rise condominium dwelling group  and so on, in the highest order.  Accordingly, in order to enhance the sense of community among local residents, it is essential to clarify the ownership and right to use the site of a house or apartment complex, and to increase the level of control over entry into the site of a house or housing complex.

Due to the massive amount of real-estate related text documents, the necessity to automatically process the data is evident. Especially purchase contracts contain valuable transaction and property description information, like usable area. In this research project, a natural language processing (NLP) approach using open-source transformer-based models was investigated.   

The potential of pre-trained language models for zero-shot classification is highlighted, especially in cases where no training data is available. This approach is particularly relevant for analyzing purchase contracts in the legal domain, where it can be challenging to manually extract the information or to build comprehensive regular expression rules manually.  

A data set consisting of classified contract sentence parts, each containing one size and context information, was created manually for model comparison. The experiments conducted in this study demonstrate that pre-trained language models can accurately classify sentence parts containing a size, with varying levels of performance across different models. The results suggest that pre-trained language models can be effective tools for processing textual data in the real estate and legal domains and can provide valuable insights into the underlying structures and patterns in such data.  

Overall, this research contributes to the understanding of the capabilities of pre-trained language models in NLP and highlights their potential for practical applications in real-world settings, particularly in the legal domain where there is a large volume of textual data and annotated training data is not available. 

This study analyzes whether changes in residential housing prices affect family relationships and life satisfaction among the older household heads based on life satisfaction theory and wealth theory. To do so, we analyzed the residential housing prices of 596 respondents at two points in time between 7th and 8th wave of the Aging Research Panel Survey in Korea. We summarize our findings as follows First, we found that changes in housing prices have different effects on life satisfaction for different age groups. Second, we found that women are more sensitive to housing prices than men. Third, we found that family relationships are more sensitive to wealth at older ages. These results indicate that the impact of residential housing prices on life satisfaction differs among different age groups of the elderly and suggest the need for a Korean life-cycle hypothesis design to guide successful aging of the elderly.

The recovery pattern before and after the impact of the COVID-19 pandemic differs by urban commercial districts. Meanwhile, Cox et al.(2004)1 revealed intergenerational linkages between parents and children in consumption behavior. For example, millennials and Gen Zs attract attention as urban consumers, having their parent generation as open and wealthy baby boomers and Gen Xs. Since these generational characteristics are rising as an essential factor in retail, empirical research is needed.

The change in the characteristics of the commercial district consumption population demands a change in perception of the population and the regional factors considered in studies about the vitality of commercial districts.

Therefore, this study aims to determine how consuming population and regional characteristics change a commercial district's stagnation and recovery pattern. To this end, we identified the type of resilience in commercial districts through DTW(Dynamic Time Warping) clustering, a machine learning method based on quarterly sales and floating population changes in 1,306 commercial districts in Seoul for 5.5 years from 2017 to the first half of 2022. Furthermore, it analyzes the leading causes that affect each type of commercial district's resilience with multinomial logistic regression. In detail, the demographic traits consist of the characteristics of visitors, residents, and workers around commercial districts. This detailed approach to the population factor was possible due to the government-driven data accumulation over the past five years, including origin-destination data based on mobile phone signal data. The analysis shows that the size of newly developed housing and offices near the commercial district, access to public transportation, and households with three or more members, including baby boomers, had a significant impact.

Considering that the child generation of the baby boomers is the millennials, this study is meaningful in that it demonstrates the mutual consumption impact between the millennial-baby boomers and the Z-X generation at the urban commercial level. The results of this study can contribute to the revitalization of urban commercial districts and consumer trends of stakeholders such as government agencies, retail developers, and investors in situations where low birth rates, aging, and changes in generation characteristics affect urban vitality.

• 1. Waldkirch, A., Ng, S., & Cox, D. (2004). Intergenerational linkages in consumption behavior. Journal of Human Resources, 39(2), 355-381.

Environmental, social, and corporate governance (ESG) is extensively researched in the economic sector, but there is a gap in ESG literature in the real estate sector. This paper examines how ESG factors affect the London office market from the perspectives of occupiers and investors. Using a quantitative approach, the paper analyzes the preference of tenants to lease green across different industries, the correlation between a company's ESG rating and its occupancy cost in the London office market, the impact of ESG performance on its ability to attract and retain tenants in the London office market, and the extent to which ESG considerations affect rental pricing in the London office market. Preliminary results of the study indicate that ESG ratings are positively correlated with occupancy costs, that office buildings with higher BREEAM ratings generate more rental premiums and that tenants in specific sectors are more willing to pay a green premium. The study's adoption of stakeholder theory provides a broader perspective on the role of the London office market in society and emphasizes the importance of creating value for all stakeholders. The paper provides evidence to demonstrate the significance of ESG considerations in the London office market. The findings have important implications for real estate practitioners, investors, and policymakers interested in sustainable and socially responsible real estate practices.

Mandatory energy performance certification for buildings is increasingly used in many countries and is seen as a key policy instrument for reducing energy consumption. Despite the widespread use, empirical evidence on whether or not mandatory certification reduces residential energy consumption is nonexistent. I study the introduction of mandatory energy performance certificates since November 2008 in Flanders, Belgium. I find that houses that were sold after mandatory certification consume 6% less energy. The lower energy consumption is mainly due to lower expenditures on fossil fuels. The results are robust to a whole range of possible alternative explanations such as pre-trends and changes in energy prices or subsidies over time.

There are three things that matter in property: location, location, location", states Lord Harold Samuel in his iconic sentence. 

Even though the location is certainly not the only characteristic of a property that determines its market value, it is undoubtedly one of the most important, if not the most important. 

In this research, the authors wish to discuss how the fixed effects influence the best estimate of the market value of a premise through an innovative use of multi-parametric estimation techniques. 

In particular, the aim is to detect the different marginal appreciation of intrinsic and extrinsic characteristics of properties at three different timings: 

• before the Covid-19 pandemic, 
• two years after the first Covid-19 alerts but before the War in Ukraine, 
• one year after the breakout of the War. 

The marginal appreciations of the building’s features are diachronically analysed for a case-study in Northern Italy through a Random Forest feature importance analysis and an Optimized Multivariate Polynomial Regression. 

This study also integrates several techniques, such as computer programming in Python languages, multi-parametric value assessment methods, feature selection procedures and optimisation algorithms. 

The results may represent an interesting ongoing monitoring of how these abnormal events affect the buyer's willingness to pay to specific characteristics of the buildings, with particular attention to the location features of the neighbourhood and accessibility.

The "Climate and Resilience" law aims to accelerate the ecological transition of French society and economy. All sectors are concerned: agriculture and transport, among others, but also housing. More specifically, this law targets landlords of the most energy-consuming properties by banning them from the rental market. In France, according to the regulation, more than 5.2 million dwellings are considered inefficient and won’t be allowed to be rented in 2028. The first rental restriction of this law came into effect in January 2023: the worst housing in terms of energy performance cannot be rented anymore. This represents around 500,000 housing units.

In this paper we assess the impact of this new regulation on the french real estate market. Do landlords renovate their housing or do they prefer to sell? Do their behavior have an impact on sales and rental prices ? What is the perception of the owners about these regulatory changes in favor of energy transition in housing?

Based on the observation of 5 million listings published on the french leading professional real estate portal between 2018 and 2022 (SeLoger.com) and a survey that collected 5,000 responses related to the perception of the impact of the law on the decision process to sell or buy a property, our results suggest that energy consumption of the dwelling has started to become a valuation and selection criteria to buy and sell on the french real estate market. Our results show a significant increase in the number of sales of low-energy homes since 2021: 19.2% of the properties listed on the market for sale in 2022 are not energy efficient versus 11% in 2021. In addition, dwellings with high energy consumption are listed on the market with a selling price of -3.9% less expensive than an equivalent property with better energy efficiency. Therefore, there is a significant difference in the evolution regarding the energy efficiency score. In France, prices of properties with higher energy efficiency have increased on average by +3.7% since July 2021, which is two times less than the other properties (+7%)

Nowadays, Chinese real estate firms (CREFs) are facing challenges of tightened financing criteria, raised prices of land use rights, and increased industrial concentration. In response to market changes, more and more CREFs are involved in collaborative delivery through project-based joint ventures (JVs). However, when influenced by pluralistic delivering logics, the JVs’ internal operations can be hard to understand, and their behaviour may be difficult to predict. This paper uses institutional theory and hybrid organizing as a theoretical framework to explore how JVs coordinate and integrate their resources and competencies, as well as govern tensions between competing logics. In doing so, we first use a broad literature review and field interviews to capture institutional logics embodied in the Chinese real estate sector. As a result, two logics (i.e., mass production and unit production) and the underpinned practices are refined. Secondly, based on the case of CREF- Gemdale, we further investigate how the JV-Gemdale’s organizational structure, activities, and processes are assembled and mobilized during the collaborative delivery. In particular, we show that, instead of integration or differentiation approaches, as the literature typically suggests, JVs can selectively hybrid organize elements prescribed by competing logics. Subsequently, this paper further explores the manifestations of tensions and how the JV-Gemdale responds to them. The result shows that tensions and responses are influenced by how JVs selectively hybrid organize. Overall, our findings theoretically contribute to a better understanding of how project-based organizations navigate in pluralistic institutional environments. 

The research analyzes the business models adopted in several European countries to pursue the energy refurbishment of the building stock. The aim is to identify the best practices that allow the development and diffusion of the circular economy in the building industry.

After the enactment of Directive 2010/31/EU, the energy efficiency of the building stock has become a central theme to the policies of the governments, which have promoted subsidies and tax incentives to encourage efficiency-enhancing works. Some countries immediately adopted efficiency policies aimed at pursuing this objective, obtaining satisfactory results, such as Belgium, France, Germany, Holland, Spain and Portugal. 

In the current phase of the research, after the literature review, data is collected for specific case studies concerning efficiency improvement works that took place in the analyzed countries. By matching the evidence from the literature review and the case studies, the most used business models are identified: the One-stop shop model, the Energy Performance Contracting (EPC) model and the ESA/RENESCO model. 

The first one is characterized by the presence of a single contractor (ESCo), which deals entirely with financing the efficiency improvement works and their implementation. The customer interfaces exclusively with the latter and is repaid for the work carried out once the work is completed. The second business model, EPC, which still features the presence of a contractor, offers advantages in terms of flexible sources of efficiency, contract integrity, risk sharing and the ability to penetrate the energy efficiency market. The contractor finances the intervention, assumes both the financial and performance risks and is repaid by future cost savings if these are higher than originally agreed. Finally, the third model is again characterized by the presence of a single contractor (ESCo) which provides the customer with retrofit interventions and the energy performance guarantee for specific services exceeding 15 years in exchange for the purchase by the latter. 

For each of the three models, the elements that constitute their archetype are identified: Value Proposition, Supply Chain, Customer Interface and Financial Model. The forthcoming research period at a construction company is meant to identify which of the best practices has the greatest expectation of success in the Italian context.

One of the key factors inhibiting the growth of the listed sector is the fact that generalist investors, who are the price setters, and drive funds flows and valuations, do not find it easy to group real estate stocks with other equities such as Financials, Information Technology, and Healthcare. As a result, they can often regard the sector as a unified whole and take a sector weighting according to the real estate and economic cycle, rather than maintaining a holding in certain stocks throughout the cycle. Historically, listed real estate has had very real estate-specific labels, be they asset (Retail, Office, Industrial, etc) or structure (REIT, PropCo) based. Even adopting the labels of unlisted funds, (Core, Value Add, Opportunistic) does not provide much guidance as listed real estate companies do not have a finite life and listed equity returns are not based on IRRs. In this study, we attach labels to the listed real estate sector which are commonly used by multi-asset fund managers to characterise equities across GICS groups. We draw upon the principles established by Fama and French in their work on factor models. Size, valuation, and leverage factors are utilised in the study, but the labels are expanded to take account of many other key price drivers. Much work has been done in the sector on cluster analysis, showing how companies with similar underlying asset types perform in a similar fashion and therefore provide little in the way of diversification. In this work, we look at how clusters can be grouped not by asset type but by theme (exposure to online retail, cloud storage, interest rates, the UK domestic economy, etc) across equity sectors, and how including listed real estate in these themes affects performance. We conclude by providing a new set of style and factor guidelines that can be used by generalist equity fund managers which enable them to include real estate stocks in their theme-based strategies. 

This paper investigates the relationship between ESG ratings and the operational, financial and market performance of Public Real Estate Companies (PRECs). By investigating a large sample of listed real estate firms from 2015 to 2021 in 35 countries, we find a positive relationship between overhead ESG metrics (and its sub-components) and firms’ market performance. Furthermore, we observe a negative relationship between ESG-Scores and the net operating income, general and administrative costs and financial costs. Our results remain robust after correcting for selection bias. Our results suggest that firms engaged in more socially responsible practices suffer from more financial costs and thus, have lower operational and financial performance. On the other hand, the stock market appreciates any decent investment in ESG, by overvaluing the corresponding companies.

Developing the “right” new workplace concept is a design task not only on the architectural and organisational levels but on the mental level as well. Building upon expert/laypeople communication, change management and person-environment-fit research, my PhD-thesis seeks to answer what activities work best to help users construct a viable mental model of their future work environment early. Three studies will investigate: Which research exists regarding early user involvement and how can it be integrated? (Literature analysis) What process activities do users report as helpful for developing a mental model? (Case studies) Does Virtual Reality help users to get a bet-ter understanding of the options and implications of a new workplace environment? (VR focus group workshops) It is expected to find that early support in the mental model construction will make the workplace project more successful with less user frustration and higher productivity.

We investigate the relationship between homeownership and life as well as housing satisfaction. Using panel data from Germany, we find that compared to renting, owning a home positively affects housing satisfaction. Contrarily, we find no significant effects on life satisfaction in the long-term. Analyzing short-term effects in an event-study design, we show that both life and housing satisfaction anticipate the event and adapt shortly after. Debt-free buyers, however, do not experience anticipation or adaptation effects at all. Comparing outright homebuyers to debt-financing owners, we show that having a real estate loan affects homeowners’ life satisfaction negatively. Paying off a loan does not differently affect the housing satisfaction of both types of buyers. We conclude that the negative effect of the financial burden of a mortgage could offset the positive effect of homeownership.

The adverse impact of climate change on the environment has seen the building industry adopt environmentally-friendly building codes. In Australia, new buildings are required to meet minimum standards in terms of their use of energy. Green Star certification recognises the energy, water and ventilation efficiency in buildings. More efficient energy use in buildings decreasing the impact on the environment. Society’s support for buildings being more environmentally-friendly can be influenced by their views on the environment. This study surveys university students on their attitude and behaviour in terms of the environment.  Undergraduate and postgraduate students studying finance and building subjects were surveyed. These subjects cover topics on environmental decision making. The findings of the survey provide insights into the behavioural attitudes towards the environment by individuals. They expose whether action needs to be undertaken to improve society’s understanding of the positive impact energy efficient buildings have on the environment.

Limited land resources and large demand calls for intensive use of industrial land in China. However, delay in land development and idle land greatly deteriorate land use efficiency. This research focuses on the land development performance of industrial land in Guangdong, China. Land transactions of 4 cities from 2010-2016 have been investigated, among which more than two thirds have different degrees of delay in project completion. Influencing factors of land development efficiency are tested and analyzed from perspectives such as bilateral dependency. 

Bilateral dependency has been exemplified in Williamson’s transaction cost economics. It is often caused by asset specificity, which affects ex post contractual behaviors because lower values are implied for the re-arrangement of the assets. With motives to achieve optimal uses of industrial land, local governments in China often intervene the land market, for instance, designate areas to specific industries, or require the buyers to fulfill certain qualifications during land sales. Industrial clusters based on one or several core enterprises are common patterns in industrial land planning. Considering the long contract period and the uncertainty during contract enforcement, even if the achievement date of land development is dealed in land contract, it’s possible for both enterprises or governments to hold up the other party and cause delay.    

According to the empirical results, high-tech enterprises show worse performance than low-tech enterprises in land development efficiency. Nature of firm also has significant influence. State-owned firm delay the most while foreign developers perform the best. Besides, location of land, floor area ratio, investment scale etc. have influence on the land development efficiency. Different cities show different patterns under different industrial structures and land policies. The research findings are used for policy recommendations on land contract governance.

Global crises, economic changes, development in technology, and growing dynamics in organizations change the way of working and the place of work execution. The initially forced change of work location from office to home at the beginning of the COVID-19 pandemic has long since transitioned into an increasing demand for location-flexible work. It is of great relevance for companies to ensure that, despite distributed work outside the office, they do not suffer any loss of productivity, team dynamics or corporate loyalty among their employees. However, in response to vacant offices, because of a higher share of employees working from home or at third places, some companies reduce office space.

While companies have found ways to execute promising office space provision by extending the physical office workplace by a digital component, success is largely driven by the employee’s ability and intention to adopt such solutions. Innovative technology-supported working system, or so-called ‘digital workplace’, is characterized by a virtual work environment that enables employees to access company resources and work temporally and spatially flexible. Digital technologies are used to improve collaboration, communication, cooperation and foster knowledge work when employees work from anywhere and at any time.

The success factors of distributed work and the design of digital workplace environments have been discussed in different strands of literature. Research examines factors that are relevant to the design and transformation process of digital workplaces. To the best of the authors' knowledge, however, the question of the factors influencing positively the intention to adopt digital workplaces has so far remained without empirical evidence.

This research project contributes to uncovering the key factors influencing intention to adopt the digital workplace through novel empirical evidence. Innovation and acceptance research is connected with workplace research in order to identify how a digital workplace can serve as an alternative to physical office space. A model of aspects based on a corporate and an individual level is applied. For an empirical analysis, 610 knowledge workers in Germany are surveyed. Explorative factor analysis and regression analyses are used to analyze the data. 

The findings enable companies’ corporate real estate management to better incorporate digital technologies to compensate for the reduction of the physical workplace and maintain a successful workforce. Not only do the results show which individual and company factors, such as employee technology readiness or company communication, have a significant impact on intention to adopt, but also that the significant aspects differ between workers with experience and newcomers. In addition to the contribution the findings make to management practice, they expand the literature on the digital workplace by testing the identified aspects and measures for the design and transformation of digital workplaces for their effectiveness for the first time in a cross-company study.

The offer of programs related to education and training in the field of real estate is widespread in Europe. This applies to the duration, mode of delivery, prerequisites for admission, etc.

This contribution will consider the relation between (part-time) real estate education in conjunction with an internship. Some study programmes define this as a prerequisite in the curriculum. However, if this is not the case, the advantage of professional work can be regarded as an add-on. On top of this others incentives serve as a driving force for further qualification in a dual mode.

In the current geo-political context, attention to sustainable finance issues has grown with an increase in institutional and private investors who prefer Environmental Social and Governance (ESG) compliant investments: these investments are considered "resilient" with respect to possible future shocks markets, especially in the real estate sector. In order to support investment decisions, numerous metrics have been created to evaluate the level of ESG, often not very transparent and robust, which prevent comparison and discourage investors. The proposed research is aimed at defining a methodological approach that, consistently with the EU taxonomy and Sustainable Finance principles, is able to determine the ESG level of real estate investment funds for supporting the institutional and private investors during the decisional phases of choosing the best fund to invest in. The aim is achieved through the development of a transparent methodological approach structured into the following phases: i) analysis of the criteria and construction’s structure adopted by the main ESG metrics (es. GRESB, Sustainalytics etc.), ii) examination of the criteria considered by the metrics among the three environmental, social and governance issues, iii) identification of an adequate and balanced set of quali-quantitative indicators related to the ESG issues of the real estate investment funds, iv) development of an innovative assessment metric (ESG index) through the use of multi-criteria aggregation based techniques. In this way the proposed methodological approach allows to: i) provide a systematization of the existent literature on the ESG metrics’ features in order to highlight the main weaknesses, ii) ranking the ESG performances of the real estate investment funds, iii) support the institutional and private investors with a transparent and retraceable methodology that can be used for comparing the different real estate investment funds’ ESG performances and identify the most suitable one. The main contribution of the proposed research relates to the possibility of fostering the standardization of the ESG metrics construction in order to facilitate the comparison, avoid the “black boxes” of the construction process and applying the ESG principles in the real estate sector.

Improving the energy efficiency of the built environment is a critical element of the UK’s strategy to achieve net-zero emissions by 2050. Enhanced standards in new homes and subsidies for renovation are among the measures put in place to encourage energy efficiency. On the one hand, a literature stream has focused on the heterogeneity of energy savings across different household types and building typologies to assess renovations. On the other hand, the hedonic pricing literature has delved on the existence of energy premiums across different housing markets. While the distributional impact of different fabric interventions has recently become a focus of research, this has not been the case for increases in house prices across housing quality and age groups. It is in this context that this paper poses the question: “How do increases in house prices affect consumption across age groups, tenure and dwelling energy performance?” To assess the relationship between house prices and consumption, this paper draws from a body of economic research dealing with the Marginal Propensity to Consume (MPC) out of house price increases. This paper builds on a combination of two micro cross-sectional datasets: the English Housing Survey (EHS), including data on the housing stock and its inhabitants, and the Living Costs and Food Survey (LCFS), which holds detailed financial and consumption information. We find that older households, more likely to own outright and live in less energy-efficient houses, have increased their consumption in line with rises in house prices. On the contrary, middle-aged groups, more likely to rent and own with a mortgage, have not increased their consumption in line with house prices. The youngest group does seem to increase their consumption with raises in housing prices but less than the oldest one. Noticeably, improvements in the built environment related to energy efficiency drive consumption down since improved fabric standards result in increased housing costs that are compensated by reduced consumption. Based on the heterogeneity of consumption responses to house price increases, this paper contends that an energy transition model that subsidises older households to retrofit their homes is regressive by strengthening the wealth of older households while penalising younger ones with less housing equity and larger housing needs. The distributions of housing wealth and marginal propensity to consume are particularly relevant as grants and subsidised loans dependent on fabric conditions are likely to have heterogeneous effects over generations reinforcing the concentration of assets among older households.

Assessing the condition of a property is an important part of determining its value. To assess the condition of, for example, a house, certain exterior and interior characteristics are evaluated according to a scheme in which each characteristic is weighted for the final condition classification. Since property valuation depends on the experience of the appraiser, professionals and court appraisers predominantly do the determination of a condition classification. A condition assessment can also be made from pictures and does not require an on-site visit. Therefore, this article examines the extent to which students, as a sample of the general (unexpierenced) population, evaluate the condition of single-family homes based on pictures of the exterior. We compare the evaluation by students with an evaluation by professional evaluators following a standardised scheme. In addition, we investigate how colours and distance of the photographer, among other factors, affect the condition classification assigned by students. The results of this work provide information about the extent to which lay people are able to evaluate single-family houses. We find the wisdom of the crowd comes to approx. 60% correct condition class predictions. Furthermore, the depiction of pools upwardly biases the predictions of the students sample. Colour or grey scale seems not to have an impact.

This study examines international real estate investors’ strategy choices and the implications for the commercial real estate (CRE) market. The empirical work adopts a network analysis framework to quantify the market connections of the institutional investors and their influences, with a two-stage endogenous binary model employed to address foreign investors’ incentives to choose strategic partnerships and strengthen the bargaining power in the host market. We first show network patterns and dynamics. We also highlight the impact of network formation on transaction pricing. The findings from selected CRE markets in England indicate that investors with broker representation, foreign investors, and those working with external management partners achieve pricing premia in property purchases. The local experience accumulated from past transactions strengthens bargaining power. Compared to London and non-London markets, it also looks at how the institutional environment might affect the prices of goods and services in both places.

Leaseholds are finite assets sold at a discount to its freehold value. The government intends to make it easier and cheaper for lessees to renew their lease or purchase the freehold interest. We analyse the potential financial implications of leasehold reform from changing the extended lease length and eliminating the marriage value payment beyond the distribution of a premium reduction.  Lessees who extend a short lease will benefit from a premium reduction and from the increase in the extended leasehold value from a long to a very long lease. We argue that lessees’ who do not extend also benefit from the capitalisation of the premium reduction into short leasehold prices. We find that there will be regional variations in the increase in the short leasehold stock value, decreases in housing affordability and in how financial gains are distributed among different lessee types. Some of these outcomes contradict current government policy. We also find that owning a freehold share does not protect against selling at a price discount. Key words: leasehold reform, marriage value payment, capitalised leasehold prices.

This paper investigates the inflation hedging capability of listed real estate (LRE) companies from 1990 to 2021 in four economies: the US, the UK, Australia, and Japan. By using a Markov switching vector error correction model (MS-VECM), we identify that the short-term hedging ability moves towards being negative or zero during crisis periods. In non-crisis periods, LRE provides good protection against inflation. In the long term, LRE provides a good hedge against expected inflation, and shows a superior inflation hedging ability than stocks. Additionally, we propose inflation-hedging portfolios by minimizing the expected shortfall. This inflation-hedging portfolio allocation methodology suggests that listed real estate stocks should play a significant role in investor portfolios.

Modern location analysis evaluates location attractiveness almost in real time, combining the knowledge of local real estate experts and artificial intelligence. In this paper we develop an algorithm – The Amenities Magnet algorithm – that measures and benchmarks the attractiveness of locations based on the urban amenities’ footprint of the surrounding area, grouped according to relevance for residential purposes and taking distance information from Google and OpenStreetMap into account. As cities are continuously evolving, benchmarking locations’ amenity-wise change of attractiveness over time helps to detect upswing areas and thus supports investment decisions. According to the 15-minute city concept, the welfare of residents is proportional to the amenities accessible within a short walk or bike ride. Measuring individual scorings for the seven basic living needs results in a more detailed, disaggregated location assessment.

Based on these insights, an advanced machine learning (ML) algorithm under the Gradient Boosting framework (XGBoost) is adapted to model residential rental prices for the region Greater Manchester, United Kingdom, and achieves an improved predictive power. To extract interpretable results and quantify the contribution of certain amenities to rental prices eXplainable Artificial Intelligence (XAI) methods are used. Tenants' willingness to pay (WTP) for accessibility to amenities varies by type. In Manchester tram stops, bars, schools and the proximity to the city center in particular emerged as relevant value drivers. Even if the results of the case study are not generally applicable, the methodology can be transferred to any market in order to reveal regional patterns.

Recent research has shown that macroeconomic uncertainty is a signifcant factor that is contemporaneously incorporated into asset returns. Therefore, it should not have a role in predicting future returns. At the same time, separate research has demonstrated that illiquidity is related to future returns. We examine the interplay between these two dynamics in a commercial real estate setting, where (il)liquidity is a defining characteristic of the asset class. Empirical tests confirm the absence of return predictability for liquid assets (publicly traded property portfolios). However, we find significant return predictability predicated on ex ante macroeconomic uncertainty when we examine assets that are not as liquid (directly held property portfolios). Our findings are robust to several refinements, including adjustments for delays in the transaction closing process to establish transaction prices in the directly held market, controls for leverage inherent in publicly traded real estate asset returns, and pro-cyclical liquidity variation in private real estate markets.

A key challenge for the UK is the current housing crisis. Part of this challenge is the funding of Social Housing Providers (SHPs) and the tensions this causes within such organisations. This paper examines this situation through the perspective of board directors within these organisations. Increasingly, SHPs are now encouraged to operate entrepreneurially with less central government funding available. Within this context, the role of the board director has become increasingly challenging due to political, social, and financial pressures. The consequence is a new turbulence between tenant and society and the mediating role of the housing board. This paper analyses the funding and social tensions of SHPs using an innovative multi-layered research methodology including, a detailed documentary analysis of practices relating to decision making capabilities, and in-depth interviews with board directors as they seek to mediate the tension between state, market and civil society via SHP board decision making. The paper concludes that SHPs need to consider adapting their provision to meet the needs of the community (civil society). These findings shed new light on the working practices of the SHP under the context of austerity and new modes of housing governance.  

Mandatory energy efficiency disclosure policies are increasingly being used by governments around the world to reduce information-driven market failures. We exploit two policy changes in Flanders to study the causal effect of mandatory energy efficiency disclosure policies on house prices. We find that the introduction of mandatory energy performance certificates in 2008 that include an energy efficiency score did not affect the association between energy efficiency and sales prices, indicating that the policy change did not reduce information frictions. However, the introduction of EPC labels in 2019 affected the willingness to pay for energy efficiency.

We use a large sample of residential dwellings transactions to test for a variety of changes in the Austrian real estate market triggered by the COVID-19 pandemic. To account for the country's heterogeneous topography as well as degree and type of economic activity, we build hierarchically structured hedonic pricing models. We strategically expand these models by various direct and indirect COVID-19 measures and check their importance over several phases of the pandemic. We find strong co-movement of residential real estate prices with the intensity of the pandemic measured via the timing of strict lock-downs, incidence rates and mobility rates.

After a severe downturn of prices and quantities during the first lock-down, both measures recovered rapidly and followed largely accelerating trends thereafter. In addition to that, the pandemic led to relative changes across different segments of the Austrian residential real estate property market: Apartments not offering some kind of open space lost in value as compared to those having access to such amenities. The degree of relative value loss is significant from the second lock-down onward. Between the start of the pandemic and 28 February 2022 the total relative gap in prices amounts to 11.61 percentage points.

In times of accelerating inflation, financial instruments to protect capital against loss of value are becoming increasingly important.  It is therefore an open question as to what to invest in in order to, if not outpace, then at least match the level of inflation in investment returns. This has raised the question of whether there are such opportunities in the market. However, according to some authors, this type of analysis is not easy and simple econometric methods are not able to demonstrate the relevant relationships. One example is real estate investments, which - especially in the short term - may not be an adequate hedge against the impact of inflation on capital values. (Fogler 1984) The idea therefore arose to test a modified beta coefficient, a measure of sensitivity, in addition to the commonly used methods of analysis, as a tool to assess the response of the profitability of investments in selected assets to changes in the level of inflation (Bampinas and Panagiotidis, 2015; Arnold and Auer, 2015).

For the purpose of the research paper, the objective of the study was formulated: to demonstrate whether investments in the capital market are able to protect capital from depreciation caused by inflation. In order to realise the objective, a research hypothesis was formulated: investments in the bond, stock, gold and real estate markets are able to effectively protect the capital held against the negative impact of inflation. 

Research on the relationship between investments in different asset classes and inflation is abundant, although it mainly concerns periods in the economy when elevated levels of inflation were observed. During periods when inflationary processes lose their relevance, interest in protecting capital from loss of value fades. Meanwhile, the global economy is constantly changing and the knowledge from the 80s or 90s of the previous century is no longer satisfactory. New investment opportunities are emerging worldwide and access to assets of different classes is much easier for even small investors.  Thus, the proposed research will fill a gap in the analysis of capital protection options against inflation. The research will be carried out in the markets of Central European countries.

The author's study will use quarterly data including bond market indices, equity market indices, gold price indices and property indices, as well as quarterly inflation data. The study will use Spearman's correlation analysis (Spearman 1987), and cointegration analysis using the Engle - Granger test (Engle, Granger 1987) and sensitivity analysis using a modified beta coefficient (Sharpe 1964, Jensen 1968).

The issue of urban decay is a common challenge experienced globally, characterised by the deterioration of buildings, declining economic activity, and increasing crime and unemployment rates. Urban regeneration policies have been introduced to revitalise infrastructure, housing, and economic activities while reducing unemployment and crime. However, such policies often raise concerns about gentrification, which may lead to the displacement of low-income residents from regenerated areas. This paper aims to develop a conceptual framework that can mitigate the negative effects of gentrification resulting from urban regeneration. A systematic literature review is employed to propose the conceptual framework, which draws from sociological institutionalism and investment theories to reduce gentrification effects by engaging all stakeholders. The context of Johannesburg, South Africa is particularly important in guiding future urban regeneration policies and practices to ensure equitable distribution of regeneration benefits among all community members.

The purpose of this study is to investigate the effect of conventional and unconventional monetary policy shocks on housing price dynamics and the economy. We also examine the effect of a housing price shock on monetary policy and its implications for the economy. To do so, we implement an SVAR model for the six major European countries (France, Germany, Italy, Netherlands, Spain and the United Kingdom) and thirteen European markets (Paris, Lyon, Marseille, Berlin, Munich, Frankfurt, Amsterdam, Madrid, Barcelona, Seville, London, Birmingham and Manchester) for the last 20 years (2000-2020). We use impulse response functions to understand the effect of a policy rate and a balance sheet shock on housing prices. We also conduct a forecast error variance decomposition analysis to explore each shock’s effect on housing prices across markets. We find that a contractionary policy rate has a negative influence on house prices. Moreover, an expansionary balance sheet shock has a positive impact on housing prices in all countries, but the effect is heterogeneous according to markets. An unconventional monetary policy shock has greater explanatory power regarding housing prices than a conventional one except in the United Kingdom. The market-level analysis indicates that a conventional monetary policy shock explains a larger share of total housing price variance than an unconventional monetary policy shock in markets such as Paris, Lyon, Madrid, London, Birmingham, Manchester and Amsterdam whereas the opposite is true in the German markets, Barcelona and Seville. In Marseille, both policy types have the same explanatory power. Finally, we find that conventional and unconventional monetary policy shocks have a greater impact in more liberalized credit markets.

Today's data analysis techniques allow for the combination of multiple different data modalities, which should also allow for more accurate feature extraction. In our research, we leverage the capacity of machine learning tools to build a model with shared neural network layers and multiple inputs that is more flexible and allows for more robust extraction of real estate attributes. The most common form of data for a real estate assessment is data structured in tables, such as size or year of construction, but also descriptions of the real estate. Other data that can also be easily found in real estate listings are visual data such as exterior and interior photographs. In the presented approach, we fuse textual information and variable quantity of interior photographs per condominium for condition assessment and investigate how multiple modalities can be efficiently combined using deep learning. We train and test the performance of a pre-trained convolutional neural network fine-tuned with variable quantity of interior views of selected condominiums. In parallel, we train and test the pre-trained bidirectional encoder-transformer language model using text data from the same observations. Finally, we build an experimental neural network model using both modalities for the same task and compare the performance with the models trained with a single modality. Our initial assumption that coupling both networks would lead to worse performance compared to fine-tuned single-modal models was not confirmed, as we achieved the better performance with the proposed multi-modal model despite the impairment of a very unbalanced dataset. The novelty here is the multimodal modeling of variable quantity of real estate-related attributes in a unified model that integrates all available modalities and can thus use their complementary information. With the presented approach, we intend to extend the existing information extraction methods for automated valuation models, which in turn would contribute to a higher transparency of valuation procedures and thus to more reliable statements about the value of real estate.

With the advent of the COVID-19 pandemic, many have raised the vitality of proper green space planning as the association between green spaces and public wellbeing became more obvious due to various mobility restrictions. In this paper, we examine how multidimensional factors of green spaces (i.e. quantity, quality and accessibility) are associated with public visits to green spaces and whether these factors influence the extent of benefits of green spaces to mental wellbeing. We perform comparative analyses between Singapore and Hong Kong, which present a significant difference in green space planning. A total of 298 surveys were conducted in Singapore and Hong Kong, with responses comprising green space usage, mental wellbeing, and socioeconomic information of respondents. Our analysis findings demonstrate that for their decision to visit green spaces, people are more sensitive to the green space dimension lacking in their local environment. For example, respondents in Singapore that features lower green space accessibly than Hong Kong are much more to this while Hongkong respondents were more sensitive to green space quality. We also find that respondents in Hong Kong have increased their visits to green spaces more significantly than Singaporean counterparts after the COVID-19 outbreak, and the association between this increase and enhanced mental wellbeing is more significant in Hong Kong. This provides an important implication that green space accessibility can play a more important role to mental wellbeing compared to the role of green space quality, especially when people restrict their mobility due to health concerns.

The ESG topic has arrived in the European finance & real estate industry (RE) at the latest with the European Commission's Sustainable Finance Action Plan. ESG stands for "Environment - Social - Governance" and is intended to examine all relevant areas of economic activity for their environmental ("E") and social ("S") compatibility, as well as sustainable corporate governance ("G"). The real estate sector is of particular interest. In our latitudes, buildings are responsible for 40 percent of total energy, 30 percent of CO² emissions and consume a large amount of resources, in particular land, during construction and operation.  

On the one hand, regulations such as the EU Taxonomy (2020/852), SFDR (2019/2088), directives such as NFRD/CSRD, as well as guidelines from European and national financial supervisors including central banks are forcing companies and financial market participants to non-financial/sustainable disclosure. On the other hand, the market demand exerts pressure on real estate actors to improve in terms of sustainability. The revival of sustainable building certifications (DGNB, LEED, BREAM, etc.) can be seen as proof. Both developments (i.e. the sustainability performance of buildings), have or will have a financial impact on real estate assets and the market. This corresponds to the underlying logic of ESG, according to which sustainability stands in a reciprocity with the financial performance of an economic activity and/or asset. In the mid- & long term, sustainability enhances financial returns through risk reduction and growth opportunities.  

However, the technical implementation of ESG, in particular the financial aspect, still remains difficult. Existing ESG ratings have multiple deficiencies, they are (either)… 

• assessing RE Companies based on disclosure reports without any information on assets level (ex. MSCI). 
• are mainly expert-based weightings of ESG indicators with limited conclusion on financial implications (ex. GRESB). 
• are assessing single objects with a dependency on lots of input data provided by RE asset managers or owners (ex. GRESB). 

Furthermore, data and methodology divergences are causing incomparableness. 

The research done by DataScience Service GmbH (DSS), a proptech/fintech company based in Vienna with focus on automatic real estate valuation (AVM), consists of two mayor efforts tackling some of the existing deficiencies.  

1. The development of an ESG tool which is capable of a nationwide ESG performance monitoring of assets and parcels with regulatory conformity. The underlying ESG indicators assess new and existing buildings, and are sensitive to different building types. 
2. The translation of ESG performance data into financial risks. A core component will be the integration of the ESG performance data into our AVM (regression model) to determine (statistically) the financial impact on real estate value (long term goal – no findings yet). 

The current status of our research will be presented at the conference focusing on the first mayor effort. The ESG tool required the development of a new conceptual framework structuring ESG indicators and a multi-scale hierarchy (market – location – property). The derived ESG indicators considering physical & transitional risks are the result of an intensive screening process of regulatory, certification and disclosure frameworks. The methods are based on scientific findings and therefore, they are referred to as "hard facts" (quantitative metrics), i.e. they are objective, independent and verifiable. The foundation of the tool relies on the combination of high-resolution images from air, space and property (including interior images), as well as other geodata, floor plan and other third-party documents such as energy performance certificates, building certificates and consumption data. This variety of data is analyzed using the latest methods of image recognition, time spatial analysis (GIS), text mining, etc. A particular advantage of high-resolution earth observation / geospatial data is, in addition to the spatial resolution and the global coverage, the possibility of constant monitoring. This means that the smallest changes can be detected at an early stage and immediately communicated to affected stakeholders. The new approach enables a high quality & consistent ESG rating at granular level (property level).

In recent years, climate change has caused severe impacts on various countries and exacerbated the impact of natural disasters on human settlements. Due to Taiwan's high risk of multiple natural disasters and complex terrain changes, the impact and damage of disasters it faces are more severe than most countries. This makes Taiwan a suitable research site to observe and discuss the impact of natural disasters on human settlements. Research on natural disaster risk has long focused on the impact of a single disaster. However, the impact of disasters is often multiple and related to the vulnerability of the regional environment. In this case, the assessment of terrain is critical. On the premise of natural disaster prevention, the livable environment and areas not suitable for development should be defined first. Through the integration of topography and natural disasters, this study uses a geographic information system to explore the relationship between Taiwan's livable environment, unsuitable development areas, and the current population distribution and agglomeration; By contrasting the spatial distribution of disasters such as landslides, flooding, and land subsidence, we explore how the diversity of natural disasters directly affects the living environment and indirectly causes fluctuations in housing prices.

The economic consequences of weather and climate disasters in the United States are of significant concern to institutional investors. In this paper we study commercial real estate market outcomes in response to natural disasters. In particular, we draw on recent research examining resilient regions and show how measures of resiliency may predict which markets and property types recover more quickly from natural disasters. We first investigate the price and cash flow impacts of a natural disaster to understand how market signals are responding to the occurrence of extreme climate events. Second, we consider how investors are responding to, and potentially mitigating, evolving climate risks by examining capital expenditure strategies in areas before and after extreme events occur. In each case we investigate these questions in the context of the economic resiliency of the region in which the property is located. 

This paper investigates if exposure to natural hazards in its underlying assets affects the equity risk of a real estate fund. In a panel dataset of 139 distinct Real Estate Investment Trusts (REITs) over the period of 2004 to 2021, we find that REITs with a higher natural hazard exposure show a higher market beta. This finding persists even when possible endogenous market selection is taken into account, using historical hurricanes as a natural experiment and an instrumental variables approach. The increased systematic risk is explained by the increased cost of debt and reduced rental income. Assets in more resilient communities, more green buildings in the portfolio, and higher ESG performance are all shown to attenuate the impact of natural hazard risk on the market beta of a REIT. Investors seeking to lower their exposure to climate risk can use the proposed metrics at various levels of spatial aggregation to gauge the resilience of their investments.

The lockdowns imposed by COVID-19 put inner cities and high streets to a test. In the meantime, visitor frequencies have returned to pre-pandemic levels. Nevertheless, retailers' sales have not recovered to the same extent. The aim of the paper is to clarify whether a so-called “social transformation” of the inner city is taking place and whether or not it is part of the reason. For this purpose, based on mass-mobile-data in a comparative GIS-multi-layer-approach (mix of methods), different analyses were conducted in the downtown area of major German cities (i.e. Berlin, Hamburg, Köln, Frankfurt, and Leipzig) in the years 2019 (Pre-COVID) and 2022 ("Past"-pandemic). The results show: visitor frequencies have positively regenerated, the temporal use of high streets has changed slightly, the catchment area has changed massively, and accordingly the user groups changed seriously. The social transformation of the inner city is thus in full motion, affecting retail business models and thus the business models of asset managers with real estate in inner cities. Consequently, the results call for a stronger focus on the new user groups and their demands on the inner city. The results are also relevant for policymakers and urban planners, as they make hitherto unmeasurable changes transparent.

Distance and commuting costs are well-established as key determinants of location choice for place of work and place of residence. However, technological changes in recent decades have greatly affected these factors. Moreover, triggered by the COVID-19 pandemic, the widespread adoption of various forms of flexible working, work-from-home (WFH), and hybrid working, enabled by digital infrastructure and services, has been increasingly evident in our daily lives and appears to be prevailing even after the pandemic. As workers are increasingly able to choose residence locations farther away from the place they work, it raises a significant question: how are urban markets affected by the introduction of new ways of working and infrastructure improvements? In this study, a simple two-city model is employed for analysing the patterns of induced changes in aggregate population and employment levels and their impacts on property prices and rents. We also analyse the implications for productivity and the provision of local amenities and look at the possibility of the inequality gap widening due to varying levels of access to new work patterns. This research has substantial implications for policy-making and investment decisions.

The context to this research is office and industrial property market cycles in three Canadian cities - Calgary, Edmonton, and Vancouver. Each of the three cities has a distinct economic base and, as a result, has significantly different commercial property construction cycles. The variations in the primary office and industrial user groups shape these markets and affect investment cycles. The three cities are shown to be rarely in the same phase of a development/investment cycle. The paper examines the implications for the structure of their property stock and the operation of individual city markets.  The key focus is on the role of property market cycles in the emergence and changes in office sub-markets. The analysis encompasses annual office building construction cycles in each market on a building-by-building basis over the past 100 years. The analysis is based on traditional multiple regression models and compared to the output of a machine learning model. The results are considered in the context of local and regional policy implications.

Homeownership is considered a measure of financial stability and security in many countries, such as in Taiwan. Constrained by the current social and economic environment of high housing prices and low wages, young adults have a higher threshold for entering the housing market than their parents, resulting in generational inequality in housing opportunities. 

Past studies have found that young adults whose parents have higher levels of education and income are more likely to own their own homes. In Taiwan, owning a house is the best tool for accumulating wealth. Therefore, if parents have a house and resources, they are more likely to support their children to buy a house. That is, if parents have a house, the proportion of their children who own a house should be higher than those whose parents do not have a house. This article focuses on children born between 1980-1990 (a total of 3,932,350 people). According to administrative data statistics, parents had a house in that year (2004), and now (in 2020, that is, the 30-40-year-old group) they or their spouses have/have no house compared with those whose parents had no home.

This study also found that in Taiwan, like in other countries, the younger generation has difficulty buying a house. The increase in the rate of parental home ownership has squeezed the housing opportunities of young and middle-aged adults, which may also lead to a slowdown in class mobility. The results show that parents who own a house have a higher chance of their children owning their own house. At the same time, children of high-income parents have a higher proportion of home ownership than children of low-income parents, regardless of whether the parents own a house. It can be seen that the children of the previous generation with higher incomes, especially those whose parents own houses, are more likely to hold houses. Therefore, the government should think about how to weaken the function of housing as a wealth accumulation tool to weaken the relationship between high housing prices and class mobility.

We evaluate the impact of the rent control regulation implemented by the city of Paris since July 2019 on the rental market. We take advantage of the mass of data available in real time on SeLoger platform with the ads published by professional realtors, with a database of 422,874 observations from January 1, 2018, to July 31, 2022. We apply a difference- in-differences model, where control units are located in eight major French cities in which the rental market is particularly tense but not regulated during the period of analysis. We show that the rent control policy decreased rents by 3.2% in Paris on average but that the policy is heterogeneous depending on dwelling characteristics. In particular, we find that small apartments are more affected by the policy than others.

The rise of blockchain technology has led to the creation of a new generation of virtual world projects, which have attracted a range of commercial activities. The economic potential of these virtual environments has caused an increase in the virtual land market. While there are many virtual worlds, the land in each is limited in size and ideally cannot be changed, which reduces investment hold-up issues and constraints. Thanks to publicly available open-source technology, it is now possible to easily explore these new blockchain-based virtual land markets and its price dynamics. This study provides guidance on how to adequately model virtual land price indices. The study analyzes one of the first and most relevant large-scale blockchain- based virtual worlds, Decentraland. The data set used in the study is compiled from secondary market sales from the most relevant NFT (non-fungible token) marketplace. Using information on identical virtual land parcels, the study develops a weekly repeat sales index of prices for the period between January 2019 and August 2022. The study also performs several performance tests, which show that the repeat sales method provides superior index estimates compared to using an arithmetic price average or median price, which are often used in the market for virtual land. In addition to serving as a price benchmark, a virtual land market index can be appealing for asset pricing studies, as it can be used as a proxy for an unobservable market portfolio. Therefore, research on the physical real estate market can guide any research of virtual land markets.

Property investment decisions are made within complex and dynamic market environments that are increasingly challenging and susceptible to disruptions. Whereas scholars have consistently researched property investment decision-making from different perspectives, the explicit consideration of investor personality and its impact on the decision-making process in a disrupted market is limited in the property investment literature. This study therefore attempts to understand how disruption-driven property investment decisions are made, by focusing on the unique personalities, perceptions, and experiences of decision makers. The study will leverage the tenets of the five-factor theory of personality and a qualitative strategy involving case studies of Listed Property Trusts (LPTs) in executing the research. Decision makers across participating Trusts will be engaged in semi-structured interviews where they will provide descriptive, in-depth accounts of how disruption-driven investment decisions are made in their respective organizations. 

This study examines how recurrent changes in policy approaches and measures have affected housing construction activity and housing transactions in Germany. The increasing uncertainty of market participants due to these changes and the subsequent adjustments of the market form the basis of many studies in this field. In order to examine the political unpredictability and thus establish a link to the real estate construction sector, a real estate-specific, regionally differentiated index is developed from several reports. In doing so, we observe regional as well as national newspaper articles from 2010 onwards. In addition to the private transaction volume, we also analyze the main determinants of property development decision making. We have found that political changes and housing activity are related. Thus, due to an external shock, private real estate transactions are expceted to decline, which therefore affects the attitude of developers. The results of the study prove the influence of political changes on housing construction as well as transactions and contribute to the traceability of German housing activity.

Energy consumption prediction on buildings can help building owners and operators to reduce energy costs, reduce environmental impact, improve occupant comfort, and optimize building performance. Study aims to develop a prediction model for energy consumption prediction in university campus buildings using machine learning techniques with time series and physics/engineering-based datasets. Time series energy consumption data sets from existing buildings, as well as building physics/engineering data, will be analyzed to estimate campus scale energy consumption. Time series data will be used for heating/cooling and lighting, and physics/engineering data will be used for outdoor data such as outdoor air temperature, relative humidity, and building specific characteristics such as building floor area, floor height, and material type. To improve prediction accuracy, a simulation study will be conducted using a physics-based approach, and a model will be developed. The results of this approach will be used as input for the data-based approach, and a hybrid model will be presented for prediction using deep learning techniques such as LSTM and RNN. Within the scope of the study, studies on energy consumption prediction of existing buildings generally use models containing time series datasets on energy consumption or models containing building physical information. Considering that each of these data impacts energy consumption, evaluating data together helps make more accurate consumption forecasts. However, evaluating these data together is a big problem in itself. Within the scope of the study, predictions will be made for using these two data types together and the advantages and shortcomings of the model results compared to data-based models will be discussed. While previous research has primarily focused on either time series datasets or building physical information, this study will think to be one of the first to evaluate these two data types together in order to provide more accurate energy consumption predictions and generalizable results.

This study examines the widely documented positive price-volume correlation in the housing market. Unlike some earlier studies that hinge upon the presumption of sellers’ liquidity constraints, we develop a search model in which rational sellers with search costs seek to optimize their selling objectives. We show that the positive price volume correlation at the macro market level is merely the result of individual sellers (rationally) seeking optimal selling outcomes at the micro market level. Our further analysis reveals rich insights into the intricate relationships among housing prices, time-on-market, and trading volume in the housing market. It lends broad theoretical support to a number of prior empirical studies and reconciles some of the conflicting findings.

The aim of this paper is to study the evolution of office prices on the Paris market through the construction of a hedonic price index. The underlying heterogeneity of assets included in the index is a serious source of bias if not correctly considered. To solve this problem, we propose a methodology enabling to develop an indicator of perceived location quality in our model. This indicator is based, first, on the identification of a set of characteristics that contribute to the location quality of an office. Second, each attribute is weighted with a collection of preferences through surveys realized with professionals of commercial real estate. The tests we have realized so far seems to suggest two main results.

First, when controlling of location quality with our perceived quality indicator, the growth of office prices in Paris seems to have been more important during the 2010 decade than the one expressed by the indices used by CRE professionals. This increase of price seems to accelerate around 2015, which is the period where the European central bank launched a program of Quantitative easing to support the economic growth in the European Union.

Second, the investigation of the coefficients of the location quality indicator seems to indicate that the sensitivity of prices to it has risen during the period. This observation could reveal an increase of the price of centrality during the period.

The recent volatility in real estate has again brought into sharp focus the importance of security of income streams on the value of commercial real estate. The aim of this study is to empirically investigate the impact of cashflow related certainty factors on the pricing of commercial property. In particular, we look at the value of initial occupancy and remaining lease term. We hypothesize that these asset-level risk factors significantly affect the prices and that the marginal effects differ over space and time. Using a unique dataset of private office, industrial and retail transactions from 2010 through 2021 we find that for every additional year of lease term remaining the value of a property is on average 2.6% higher. Similarly, for every 10 percent of additional space let the price is 0.8% higher. We furthermore find that the coefficients remain significant over both space and time, but its effect is lower in prime markets and up-cycles suggesting more optimism. The results imply that the risk premium, which is often seen as a ’black box’, can be decomposed into components allowing for more transparency in both the transaction and valuation process.

Private investment in and management of public urban space has been a subject of practice and debate in real estate studies and industry in recent years (De Magelhães & Freire Trigo, 2017; Le Clercq et al., 2020). Such mainly Anglo-Saxon endeavours can be explained by an continuous austerity era of government retrenchments in urban planning and expanding private sector-led urban development practices (Heurkens, 2012). Moreover, real estate developers and investors are increasingly aware of the economic added value of attractive public space for their assets and the potential benefits of public space investment and management (Urban Land Institute, 2018). Whilst previous studies focused on the implications of private investment for public space governance arrangements, publicness safeguarding mechanisms, or private sector business benefits, little research has been conducted on the actual reasons for real estate developers and investors to pay for the public realm. Therefore, this research (Van de Gaar, 2023) aims to explore the possibilities of extra voluntarily private investment in the public space of urban regeneration projects, by studying the main conditions and motivations. In order to do so, we conducted a literature review resulting in an adapted conceptual framework from De Magelhães & Freire Trigo (2017) which we specifically applied to the Dutch real estate practice. Based on two qualitative research methods, semi-structured interviews with eighteen real estate professionals and an expert panel validation session, the following results are distilled.

In terms of motivations, our study reveals that the location and immediate surrounding is decisive for real estate companies’ willingness to extra invest in public space, as these investments do not pay off as much everywhere and are conditioned by the financial viability of urban regeneration project itself. Additionally, real estate companies indicate that ESG business objectives are increasingly important in investment decisions, with public space functioning as potential tangible means and proof. In terms of conditions, real estate developers and investors indicate that control over assigning rights, distributing responsibilities and shaping characteristics of the investment in public space is decisive. They want to be able control how extra investments are spent to ensure that their own company vision and the development concept for the project is realised to a sufficient degree. The biggest challenge in making public-private agreements about the extra investments are local authority public space standardisation regulations that hinder customization. Additionally, the lack of proven private management instruments for the use phase currently directs Dutch developers and investors to full legal ownership of public space as the only (limited) solution.

Based on the above empirical findings, this research illustrates that it is not possible to determine an ‘ideal framework’ for the distribution of roles and responsibilities for private public space investment and subsequently the management thereof, as public space is non-generic in nature. Nevertheless this research indicates possible conditions under which real estate companies are willing and able to extra invest in public space, thereby seeking collaborations with the public sector and establishing attractive public spaces to the potential benefit of both organisations and users alike. Scientifically, our study adds new insights about the importance of private sector investment considerations into public-private agreements besides those that safeguard the publicness of urban spaces. Research limitations include the external validity (generalisability) of the findings beyond the Dutch institutional real estate practice, and the internal validity due to the limited triangulation and qualitative nature of methods used.

Real estate development contains a broad field of activity. It includes the entire life cycle in the context of individual properties, at neighbourhood or regional level. The process is characterised by the interdisciplinary cooperation of a large number of actors from different professions. The economic viability of projects is of central importance within real estate development. This is measured on the basis of profitability indicators. They can be used to identify and control problems and to recognise opportunities and risks. The introduction of new regulations, but also current tax and market devel-opments indicate that using profitability indicators for early risk detection is becoming increasingly important. 

An examination of the currently available literature indicates a large number of profitability indicators in real estate development. The literature does not determine whether the application of the various indicators is related to the entrepreneurial structures and the professional background of the users. So far, the identification of the criteria for the respective choice of performance indicators or their respective contexts of application is missing.

In the context of this study, we test the hypothesis that the choice of profitability indicators depends significantly on the professional background of the user as well as the corporate structure. Based on a literature study, key profitability indicators are collected. In order to identify profitability indicators, we develop an online questionnaire to collect data from international real estate development companies. As part of the evaluation, we investigate the choice of indicators applied in relation to the above-mentioned contexts. 

The aim is to gain insight into real estate developers' choice of profitability indicators and to reveal their decision-making processes.

Active learning has gained widespread acceptance over the past few decades as a way to enhance student learning in higher education institutions (HEIs). Unlike the traditional teacher-focused approach, active learning prioritises the constructivist learning theory and places students at the centre of learning design and delivery. Research shows that active learning can enhance knowledge retention, foster independent learning, and improve student satisfaction. Despite its numerous benefits, however, the adoption of active learning practices by HEI teachers is not always natural or intuitive. To address this challenge, HEIs often provide or mandate teacher professional development (TPD) programmes to enlighten and influence teachers to adopt active learning strategies. However, this practice is not universal. In Nigeria for instance, academics are usually employed based on their relevant (subject-specific) qualifications and are mostly not required to undergo any special teacher training to be promoted. This lack of teacher training opportunities is a significant obstacle to the widespread adoption of active learning practices in the sector. To address this challenge, this study - currently at the data collection stage - assesses the role TPD programmes could play in driving active learning in Nigeria, focusing specifically on the property and related subjects. The study adopts a qualitative research approach and semi-structured interviews for data collection. Data will be collected from Nigerian lecturers who have migrated to take up teaching roles in the UK and those currently lecturing in Nigeria. Ultimately, this research seeks to identify effective TPD strategies that can be employed to promote the adoption of active learning practices in Nigerian HEIs. 

The system of property right, the way it is organised, protected and executed affects the land development process and the timing of land development. Real options literature that explains impact of additional uncertainties connected with organisation of property right system on timing of land development concerns mostly western countries. Poland and other CEEC (Central and Eastern European Countries) have some unique issues concerning ownership right system that come from post-war, communists, and transition times (previous owners, specific property titles derived from a communist era, reprivatisation, communalisation, etc.). Ownership right is perceived as a very strong right by society, what results from long time of collective ownership, and have some implications on executing property rights. Thus, this paper explains on an example of Poland, CEEC specific property right issues and analyses how it can affect the timing of land development basing on western solutions from real option theory.  

The importance of topic: The topic is important because land markets are strongly influenced by institutions which may vary even in countries with the same economic and political systems like unified EU countries. Therefore, it is essential to understand past historical influence and societal background that have an effect on those institutions.   

Design/methodology/approach: secondary literature review, desk based study, qualitative institutional analysis

In India, there are several challenges facing the real estate education sector. One of the biggest challenges is the lack of standardization in the industry. There is no formal accreditation process for real estate education programs, which means that the quality of education can vary greatly from one institution to another. Another, challenge is the lack of practical training opportunities for students. Many real estate education programs(Bhatia & Reema, 2019) in India focus heavily on theoretical concepts, rather than providing hands-on training that would help students develop the skills they need to succeed in the industry.

Despite these challenges, there are also many opportunities for growth and development in the Indian real estate education sector. One opportunity is the increasing demand for real estate professionals in India, as the country's economy continues to grow and develop.(Real Estate Demand in India Will Boom in 2023, n.d.) Additionally, the Indian government has recently announced plans to invest in the development of affordable housing(PMAY (U), n.d.), which could create new opportunities for real estate professionals(Indian Real Estate Industry: Overview, Market Size, Growth, Investments...IBEF, n.d.). Also, with the advent of technology and internet penetration, the online education system is getting more popular, and it is expected to play a vital role in providing education to people from remote areas, who otherwise have limited access to physical education centres.(10 Reasons to Study Real Estate! - Naveen Jindal School of Management | The University of Texas at Dallas, n.d.)

This paper shall look at the various universities offering a master level degree in real estate. Further, looking at the various accreditations offered and their credibility and suitability for the Indian market. Being a professional course, requiring direct approach with this dynamic industry; how outreach(McGrath & Geurts, 2022) would play an important role in curriculum development(Real Estate Continuing Education Research Paper - 501 Words | Cram, n.d.). A comparative(Oloyede et al., 2017) with other jurisdictions(Kim & Pior, 2018) that offer real estate programs shall also be undertaken to highlight the best practices(Full Article: The Future of Real Estate Education: A Multi-Faceted Perspective, n.d.) that may be inculcated in India.

This study investigates the risk-adjusted performance contribution of ESG REITs and real estate companies from a portfolio management perspective by comparing the diversification benefit of investing in conventional real estate indexes compared to ESG real estate indexes. Using a sample of European REITs and real estate companies from January 2006 to September 2022, we construct a set of novel ESG real estate indexes and shed light on the effect of ESG real estate investments in the portfolio risk-adjusted performance, testing three different models. The results suggest that the performance of portfolios using different strategies and levels of ESG screening in the real estate asset class varied, with the portfolio with the most stringent ESG requirements for real estate having the highest levels of volatility and return and the real estate portfolios with environmental screening having the best risk-adjusted performance. However, a socially responsible real estate portfolio would produce valuable positive externalities as real estate drives almost 40% of global emissions.

Private and institutional investors alike use real estate investments in their multi-asset portfolios to reduce their total risks by the positive characteristics such as low volatility or correlation with other asset classes. However, investments in direct or private real estate also bear drawbacks such as high transaction costs, long transaction time, large volumes, low liquidity, or the need for real estate market expertise. Thus, the financial industry has developed various investment vehicles (open-end or closed-end funds, REITs, stocks, etc.) to lower the market entrance barriers for investors with lower investment volume and knowledge. One recent engineered product is a real estate token, a digital form of assets that is equipped with value, rights, and obligations. It enables the fractionalization of properties into small investment volumes using the Distributed Ledger Technology (DLT), and the trading, as well as the rent distribution, are organized in an automated process with Smart Contracts. 

Currently, the possibility to tokenize properties directly is limited so most projects use the indirect way through legal entities. This paper explains the most used concepts, recent developments, regulations, and a first market analysis for the tokenized properties in the USA and Europe (Switzerland and Germany). The development on the primary and secondary markets is demonstrated after the tokens have been issued through Security Token Offerings (STOs), using empirical data points such as returns, standard deviation, skewness, kurtosis, and correlation. The goal is to compare the tokens with other asset classes such as stocks, bonds, and direct real estate.

In this article, we use the framework of inflation beta to test the capacity of physical residential real estate to hedge against inflation and its components, and compare it to the inflation hedge ability of various financial assets. Specifically, the housing asset is represented by the residential market in the communes of the “Grand Paris” metropolis  with the different components of inflation. We start by analyzing the residential market in this area, its fundamentals, characteristics and dynamic. Then, applying the hierarchical clustering technique, we divide the Greater Paris area into five homogenous groups of communes and test its hedging ability using both correlation and regression analysis. Residential assets are confirmed to be a hedge against inflation, particularly against its unexpected component and thanks to its capital return rather than the rental return. On the other hand, the listed real estate does not provide the same hedging properties and thus cannot be considered as a substitute for this aim.

Climate-related events cause catastrophic damage to individuals, communities, and property. Current trajectories and tipping points for minimising global warming suggest these events will exacerbate substantially in coming years in both severity and regularity. While impacts of actual events on property are broadly considered by the built environment professions, other professions, governments, industry, and individuals. There is an absence in the literature and industry resources of a direct consideration of the impacts of climate change risks (current and future) in valuation and property practices. 

This research investigated 30 Australian valuers in 2021 and 2022 through semi-structured interviews to explore valuers’ consideration of climate-related risks and climate change implications in valuations. 

The research found valuers engage with obvious and immediate physical risks; and seek to engage with searches and make other enquiries to identify the impact of past events. However, there appears to be a lack of consideration of the potential impacts from climate change, and its effects on extant risks. Constraints such as costs and client instructions, adversely impacted what is considered; how much past data is engaged with; and how such risks are reported. The risks specifically engaged with also depended upon property type. Where climate risks were reported, this was accompanied by disclaimers, and or statements, referring the client to seek specialist advice. 

It is suggested there may be a lack of appropriate consideration and acknowledgment of such risks by property stakeholders, and valuers; and a lack of appropriate education and support documents. There could be potential for substantial ramifications on property and finance markets if these risks are not acknowledged or properly considered.  While not (yet) evidenced in court decisions, in the future these knowledge gaps could expose valuers to claims (and or findings) of negligence.

Energy efficiency is nowadays one of the main targets for reaching sustainable economic growth in the medium long term. Real Estate is one of the main drivers of pollution, and more responsible investments may represent a reasonable strategy for reducing the negative impact on environment.

Empirical analysis on the characteristics of real estate assets by REITs may allow identifying if market recognizes a premium or a penalization due to more responsible investment in the real estate industry. Results on a worldwide diversified sample show that currently there is no premium for investing in green oriented REITs and there is not a financial incentive related to REITs’ portfolios characterized by lower energy consumption and more usage of renewable energy.

Modeling real estate prices in the context of hedonic models typically involves fitting a Generalized Additive Model, where only the mean of a (lognormal) distribution is regressed on a set of variables, without taking into account other parameters of the distribution. Thus far, the application of regression models that model the full conditional distribution of the prices, has been infeasible for large data sets, even on powerful machines. Moreover, accounting for heterogeneity of effects regarding time and location, is often achieved by naive stratification of the data rather than on a model basis.

We apply a novel batchwise backfitting algorithm in the context of a structured additive regression model that enables us to efficiently model all distributional parameters of an appropriate distribution. Using a large German dataset of rental prices comprising over a million observations, we choose variables relevant for modeling the location and scale parameters using a boosting variant of the algorithm. Moreover, we identify heterogeneity of covariates’ effects on the parameters with respect to both time and location on a model basis. In this way, we allow varying influence of variables on the prices’ distribution depending on the dwelling’s location and the date of sale. Modeling the full distribution of prices further enables us to investigate the influence of the variables not only on the median, but also on other quantiles of rental prices.

The problem of principal impossibility to satisfy the housing needs of all citizens according to Constitution of Ukraine, subsequent housing property laws and other documents on housing management - was never articulated properly in scientific literature and remains still unsolved. The technical and economic problems of continues improper upkeep of existing buildings, reducing their service life, are also understudied. Ideas of new approach to housing policy firstly appeared in our recent publications. Unlike other researchers, we criticized condominium model, pointing out also on the wrong social policy, imperfect ownership regulations and the need of their scientific rethinking, poor condition of buildings and uncertain cost of its repair, tenant’s insolvency and budget limitations. All authors pointed out on the necessity to transfer poor residential real estate to efficient public or private owners.

The history demonstrates that private ownership could play only limited role in housing provision, especially while economic depression or after the war. On the other hand, the value of existing housing property should be taken into account as the household means of payment. In our opinion, in the framework of liberal policy, any external expenses on housing and utility services as well as on capital repair of buildings should be exchanged for the share in property. The challenge appears: how to convert the future state subsidies into renovated public housing? Does the existing Ukrainian form of condominium let us to realize this task?

Under conditions of insolvency of apartment owners in the worn-out of destroyed buildings, neither contributions nor loans could be possible, and mass budget subsidies, as we have showed, are socially unfair. Thus, the classic dualistic models could not help. The transition to the unitary model has the same obstacles.     Only the corporative model allows to transform the shares of insolvent owner into funds to pay for the building maintenance and operation of dwelling, or, on the contrary, to transmit the ownership to investor who can bear appropriate responsibility. The last case need improvement of Finnish model.

Of course, staying in a sort of shared property apartment means partly renting it using the same financial mechanism.  Thus, residential property ownership in the legal form of a housing company will also make possible to obtain company’s ownership of a land plot, to register through the corporation the ownership on real estate with a land plot, to clearly define the shares and their value (instead of joint undivided ownership); to simplify these operations by treating shares as movable intangible assets (tokens). There are some additional advantages of corporative house ownership, like direct investments in the development project or company, life-cycle cost control as well as market value depending on the building condition. It could be easier to realize the reconstruction projects.

In actual situation with thousands of demolished houses in Ukrainian cities, the housing policy must take into account the combination of existed property and new public or private investments in restoration. In the future, it would be possible also to carry out digital transactions with part of shares divided by tokens treating shares as intangible assets.

The proposed model and tools will supplement the existing housing system and could be introduced both in houses under construction and under operation.

We measure the impact of retail externalities on the productivity of stores in shopping malls. We focus on (1) retail externalities generated by anchor stores, and (2) retail externalities generated by competing stores. We identify these retail externalities using variations in the composition of stores within shopping malls over time. We use monthly sales data from 1,170 stores that were located in 9 Turkish shopping malls over 2013-2016. We find evidence for anchor and competition externalities within shopping malls. Both externalities show distance decay effects within the shopping malls. We also find considerable heterogeneity in the impact of the two retail externalities and their distance decay effects across stores from different product categories.

After the crisis due to the pandemic, 2022 has generally been characterized by recovery of construction sector; however there has been recorded a constant upward trend in prices of building materials. The Italian government, with the Ministerial Decree of the Ministry of Infrastructure of 12th May 2022, confirms the substantial increase in building prices in the last year in Italy. The main causes of this trend have been identified in particular geopolitical events as the war in Ukraine and the rising cost of energy. In the light of the above, various measures aimed at countering the substantial increase in the materials of construction products have been implemented through various regulatory changes. The present research aims to analyze real estate market behavior characterizing the Italian context relating it to price trend of building materials. The main practical implication of this research is to investigate the variation of house prices, distinguishing new buildings from existing ones, compared to the cost of raw materials, in order to forecast the consequence of geopolitical events on residential market.

Using a hedonic regression, we examine the relationship between natural hazard exposure and residential rents using a sample of 18.339 dwellings in Switzerland. Hillslope debris flow and storm hazard are found to be associated with a significant discount across the study area. Flooding and surface runoff hazard are associated with significant discounts outside of urban areas, but results are inconsistent within urban areas. We explore some possible explanations for this finding. Results on the effect of avalanches, debris flow, landslides, hail and rockfall on rents are inconclusive. Exposure to heat is not associated with lower rents in Switzerland. Similarly, we find no evidence that increased exposure to flooding and surface runoff (in the form of living on the ground floor) is associated with lower rents relative to dwellings on higher floor levels. Furthermore, we find that the “MINERGIE” energy-efficiency rating is associated with a small premium depending on the general standard of the building.

According to the U.S. Energy Information Administration (EIA), the real estate sector is associated with about 39% of national total energy consumption, with an attendant share of energy-related greenhouse gas emissions. To support sustainability in the built environment, those certified under platforms such as LEED, BREEAM, Energy Star, Green Star, and CAL-Green, purport to promote responsible environmental design in reducing scarce resource consumption. In the past, lack of access to actual energy consumption data, especially in the multi-family housing sector, has hindered efforts to determine the true effectiveness of sustainability designs and certifications. This research investigates the effectiveness of LEED and CAL-Green certifications in California by analyzing actual energy consumption data from large scale sustainably designed housing developments that have been built under LEED and/or CAL-Green design criteria and comparing them to a benchmark set of non-sustainably designed housing projects in the same general geographic location. 

Under California Assembly Bill AB 802, California is the first state in the US with a benchmarking program that requires the reporting of energy consumption for certain large size multi-family housing projects starting in 2019.  The benchmark energy data provides the total annual carbon dioxide associated with building operations on a square foot basis when the consumption of all fuel sources is accounted for. The benchmark data provides approximately 7,092 multifamily buildings’ energy emission information from 2019 to 2021 and the sum of gas and energy usage level per square footage of building size (total greenhouse gas (GHG) emission intensity) is our key variable of interest. We additionally use the United States Green Building Council (USGBC) data to identify whether or not a building is LEED-certified. USGBC provides the LEED certified building information such as LEED application date, LEED certified status (approved or not), LEED class (Platinum, Gold, Silver, Certified), building address, building type, building size, and built year. There are 670 LEED-certified multifamily and multifamily affordable housing projects in the state of California. However, 113 buildings are classified as confidential, which does not provide any property information other than LEED-certified status. While benchmark data provides data at a project level, USGBC provides data at the building level: one project can have multiple buildings (e.g., Building A, Building B). Thus, we sort the USGBC LEED data using building address and key property characteristics to bundle buildings to project level. Specifically, we assume that buildings are identified as the same project if building’s project name, zip code, and LEED-certified level (Platinum, Gold, Silver, Certified) are the same. After cleaning the data, we find 298 unique projects that are LEED certified, of which 101 projects are matched with the benchmark data using project name, address, and building characteristics. 

The results from our empirical examinations show that LEED buildings do not produce significantly lower levels of GHG emissions compared to non-LEED buildings. More interestingly, we find that LEED buildings generate 17.30 to 20.81% higher levels GHG emissions than non-LEED buildings during post-Cal-Green period (from year 2015). These results are robust even after considering the occupancy rates (stabilization period). We also propensity-score match the data between LEED and non-LEED and the results are still consistent. On the other hand, Cal-Green is effective in reducing the GHG emissions by 7.16% to 7.88% compared to pre Cal-Green period.  In addition, we find that smaller buildings consume considerably more energy and emit more greenhouse gas per square foot than larger buildings.  The final consideration from this research is that to achieve the Net–Zero greenhouse gas emissions that California and the world has targeted, the building industry and the regulators must reexamine and improve the design standards for built environments.

I study the impact of sea level rise (SLR) on commercial real estate (CRE) pricing and commercial lending. Using novel property level sale transactions from 2011-2018, I find that commercial properties exposed to a 6-feet sea level rise are sold at a 6% discount. This discount appears to be driven by local buyers and buyers’ brokers that are more sensitive to climate risks. In addition, discount significantly rises after an extreme hurricane, suggesting that salient risk impact pricing. Likewise, lenders require higher down payments for properties exposed to SLR, and this requirement is amplified following an extreme hurricane. These findings suggest that commercial real estate investors and banks are becoming more cognizant of the risks posed by sea level rise.

Based on search cost and information asymmetry and using a two-level setting with REITs, we want to figure out whether there is a significant total return performance difference between local and overseas properties among A-REITs. The results are consistent with search cost theory and then we want to explore the reason why the REITs managers still like to conduct overseas acquisition under property-level return performance disadvantage. We compare A-REITs which hold overseas properties (International A-REITs) and A-REITs which just hold local properties (Pure A-REITs) and further explain this by our analysis of marginal investors’ behavior.

Cross-sectional dispersion is an attractive metric in examining the volatility of the market at any one point in time.  It is even more useful if total dispersion is decomposed into its beta and non-market components, helping fund managers understand whether there are still investment opportunities, even during financial, economic, and political crises.

Using monthly data for 11 sectors and 15 regions from the MSCI database in the UK, over the period from 2002:4 to 2022:12, we draw a number of conclusions.  First, in times of market crisis, there is a sharp increase in cross-sectional dispersion.  Second, beta risk dominates non-market risk, especially in times of market stress, which suggests that fund managers have very few investment opportunities that can outperform the market.  Third, the amount of beta and non-market risk has grown considerably, relative to that in regional portfolios, following the results of the BREXIT referendum, the COVID era, and especially in the political uncertainty following the resignation of Boris Johnson.  However, even in periods of market stress sectors display greater levels of non-market risk than regional portfolios, which indicates that fund managers could still have found potentially attractive investment opportunities, even during those periods.  As such, sector allocation should be the first level of analysis in constructing real estate portfolios.  Fund managers, however, need to carefully examine the size and sources of non-market return dispersion to determine their optimal investment approach at any one point in time.

Economists have been advocating for a land tax rather than a reg- ular property tax. There are, however, several challenges to value land for tax purposes. Indeed, data on vacant land transactions are scarce, land and structure are conventionally traded in a bundle and it is hard to capture all factors that determine the value of land. We propose to use a new Bayesian spatial model and apply the model to the uni- verse of vacant and improved land sales from Belgium in 2018. Our results indicate that vacant land prices are substantially more difficult to predict than house prices. However, the predictive performance of the spatial model improves considerably in comparison to a regular linear hedonic approach. Models that combine data from vacant and improved land are unable to improve the predictive accuracy.

Among the three appraisal methods, the sales comparison approach is based on the principle of marketability. It determines the value of the subject property by comparing and adjusting its value-forming factors, circumstances, and the timing of the subject property with reference to comparable properties that are identical or similar to the subject property. The sales comparison approach is commonly used in Korea, as well as in other countries, for the valuation of residential properties. Since the sales comparison approach relies upon examples of previous sales transactions, it is compelling as an empirical appraisal method, but there is the disadvantage of the possibility of evaluator subjectivity in the selection of examples and factor comparison. Furthermore, this can lead to the possibility of price distortion resulting from agreements between the relevant parties, but currently there are no objective standards to control this.

The purpose of this study is to measure the effects of the selection methods on the property valuations. Since the valuation amount may differ depending on the selected comparison examples, there is a need to research on selecting examples based on analysis of previous sales transactions. In this study, previous apartment evaluations will be used as a precedent to analyze differences in the property valuations of comparable examples according to the respective selection methods, and their intent by the parties involved. Previous apartment appraisals from Seoul, Korea in 2022 will be used to examine this. This report will demonstrate various methods to consider similarity when selecting comparison examples, such as floor area, distance from the subject property, transaction date and unit size, and propose the possible implications for the appraisal system in Korea.

This study explores the importance of sensory experiences of visitors to commercial streets and their role in vitalizing commercial districts, based on big data analysis using review data of social media. With the growth of online commerce, the vitality and function of commercial streets has been declining. According to sensory marketing theory, it is essential to develop commercial spaces that allow consumers to have positive experiences directly with their five senses, which is difficult to replace with online commerce, in order to attract more visitors. Urban designers and scholars have also emphasized the importance of sensory experiences in urban open spaces to revitalize commercial areas. Visitors evaluate their experiences with their five senses - sight, hearing, touch, smell, and taste - in offline commercial streets or stores, and unique and enjoyable sensory experiences can lead them to stay longer or revisit the places. Special visit experiences are often shared on social media, and these reviews contribute to attracting new visitors. Therefore, this study examines whether stores with positive sensory experiences on the commercial street attract more visitors.

To explore the relationship between sensory experiences and commercial revitalization, this study analyzes Google review data for a place of interest (POI) in Seoul between 2017 and 2021 using text-mining techniques. Based on a dictionary-based classification of five sense-related experiences from the review data, the sensory experiences of each POI are quantified. Then, the sensory experiences of each POI are aggregated into those of a commercial block. Finally, the connection between floating population and sensory experiences at a commercial block level is analyzed using a spatial econometric model. The findings of this study could provide a new perspective in understanding the characteristics of urban commercial districts and be the basis for developing revitalization strategies of commercial areas.

Investment decisions made under uncertain conditions are among the most critical considerations for corporations. The significance of financial constraints in a firm's investment choices has been emphasized by the recent financial crisis. In this study, we focus on modeling a typical shopping center that includes both anchor tenants and in-line or mall tenants. To ensure alignment of interests with the tenants, the center owner usually employs a percentage lease contract. However, in-line tenants necessitate a co-tenancy clause that stipulates the payment of no rent if the anchor departs from the center. Our model is calibrated using a sample of shopping center leases.

This study examines the daily time series data of the short-term rental market, including Airbnb room bookings, rental supply, and asking rents, from 2015 to 2022 in 16 Asia-Pacific cities. The analysis employs a Vector Error Correction Model (VECM) approach to investigate the causal relationships among the variables and to estimate the short-run and long-run dynamics of the market. The study reveals that the short-term rental market exhibits a high degree of volatility, with considerable fluctuations in rental supply and asking rents across the cities and over time. Furthermore, the study shows that Airbnb bookings have a significant impact on rental supply and asking rents, indicating the importance of the platform in the market. The findings also suggest that the COVID-19 pandemic has had a substantial effect on the short-term rental market, with reduced bookings, supply, and rents during periods of strict pandemic control measures. The study provides insights into the dynamics of the short-term rental market in the Asia-Pacific region over an extended period, highlighting the importance of considering both short-term and long-term factors, including pandemic-related effects.

Herding and contrarian (reverse herding) behaviours have received considerable attention in finance studies. The former generally refers to market participants’ behaviour of mimicking the action of others while suppressing their own private information; while agents are seen as contrarians if they ignore their private information about value uncertainty and trade against the trend in the market. Both behaviours can cause price distortion and hence potentially exacerbate the volatility of the financial market.

One approach to detect herding (contrarianism) is to see if return dispersions, usually measured by the cross-sectional absolute deviation of returns (CSDA), decrease (increase) non-linearly if the overall market return increase as investors converge towards (against) market consensus. Using this approach, this study focuses on investors’ behaviours in the US equity Real Estate Investment Trust (REIT) market. While both herding and contrarianism are evident in the existing empirical studies in REITs, the explanations for such behaviours are anecdotal. This paper aims to further examine the factors that amplify or reduce such behaviours. We put forward two novel empirical strategies: first, we decompose dispersions in returns due to fundamental stock market factors (i.e., Fama-French factors) and fixed income assets factors. This strategy reflects on the argument that equity REITs have the characteristics of small stock as well those of fixed income assets including direct real estate and bond. Second, we define volatility signals derived from US stock market, treasuries yield (3-month and 10-year), and sentiment measure (CBOE VIX) and investigate such signals induce investors to converge towards or depart from market consensus.

Our results are threefold. Firstly, using survivorship-bias free CRSP Ziman REITS daily data for equity REITs from January 1980 to December 2021, our static CSAD models show strong evidence of contrarianism for the whole equity REITs market as well as in all sub-sectors (including Diversified, Healthcare, Industrial/Office, Residential, Retail, and Self-storage) except lodging. Using rolling window specifications, our results show short periods of herding in the 80s and 90s when the industry was relatively new and in 2020 at the beginning of the Covid pandemic, but contrarianism is evident throughout the time period. Once CSAD is dissected into stock and fixed-income elements, neither herding nor contrarianism is evident in stock elements, however volatility signals from VIX and short-term T-bill induce investors to converge towards market consensus, whereas signals from the stock market induce departure from market consensus. In the fixed-income proportion of CSAD, contrarianism is strongly evident, but signals from the stock market reduces such behaviours. Our results imply that investors in the REITs market predominately trade against the market, this could be that they place more emphasis on the market fundamentals related to direct real estate and bonds. Such contrarianism behaviour however, is dampened by informative volatility signals from the macro-economic factors as well as market sentiment.

Limited economic feasibility due to high investment costs and relatively small energy cost savings is seen as a major reason for low refurbishment rates of the building stock in many countries. Improving economic feasibility can therefore be essential to grow refurbishment rates. Carbon tax or funding grants are possible ways to achieve this. Furthermore, the cost-effectiveness of energy-efficient modernization depends on the necessity for refurbishment. If refurbishment measures are necessary, additional energy-efficient modernization can be carried out at comparatively low cost. Accordingly, modernizations are strongly dependent on the refurbishment cycle of the building.

Based on a self-developed housing stock model for Germany, this paper presents a modeling approach to link the influence of the economic efficiency of modernizations on the modernization rate in the housing stock. This makes it possible to investigate the effects of adjustments to the economic framework (e.g., carbon tax or funding grants). This further allows the identification of target-oriented economic framework conditions for the transformation to a climate-neutral housing stock.

The modeling results suggest that modernizing all existing buildings by 2045 would require unrealistically high economic incentives. In particular, the efficiency of pulling instruments such as funding grants decreases with the amount of funds used, since the share of funds allocated to those already willing to modernize increases steadily. Additionally, the economic obstacles would be particularly high for younger buildings, which have significantly lower energy savings potential, and for buildings that do not require refurbishment. Instead, the model is used to show how a successful transformation to a climate-neutral housing stock in Germany can be achieved with a mix of measures consisting of legal regulations and subsidies that address the current weak points. The results are also relevant to housing markets in Europe and beyond.

Nowadays, in “past"-pandemic-times, visitor frequencies in inner cities and high streets have returned to pre-pandemic levels. Nevertheless, retailers' sales have not recovered to the same extent. The aim of the paper is to clarify whether a so-called “social transformation” of the inner city is taking place and whether this is part of the reason. For this purpose, based on Mass-Mobile-Data in a comparative GIS-Multi-Layer-Approach (Mix of Methods), different analyses were conducted in the downtown areas of major German cities (i.e. Berlin, Hamburg, Köln, Frankfurt, and Leipzig) in the years 2019 (Pre-COVID) and 2022 ("Past"-pandemic). The results show: visitor frequencies have regenerated, the temporal use of high streets has changed slightly, but the catchment area has changed massively. Accordingly, both the user groups and especially the retail-relevant purchasing power have changed seriously. In the city of Frankfurt, the shift in the social milieu has led to an average reduction in retail-relevant purchasing power of more than 500 euros per person in three years. The social transformation of the inner city is thus in full motion, affecting retail business models and hence the business models of asset managers with real estate in inner cities. Consequently, the results call for a stronger focus on user groups, their demands on the inner city, and a new definition of the inner city or its purpose respectively. The results are also relevant for policymakers and urban planners, as they make hitherto unmeasurable changes transparent.

Problems and objective

Social media platforms have become vibrant online platforms where people share their opinions and views on any topic (Yadav and Vishwakarma, 2020). With the increasing volume and speed of social media, the exchange of stock market-related information has become more important, which is why the effects of social media information on stock markets are becoming increasingly salient (Li et al., 2018).  Business organizations need to understand these dynamics, as it reflects the interest of all kind of market participants – retail investors, institutional investors, but also clients, journalists and many others. Therefore, it is not surprising that there is evidence for public sentiment, obtained from social media, correlating with or even predicting economic indicators (e.g. Bollen et al., 2011; Sprenger et al., 2014; Xu and Cohen, 2018).

Regarding real estate, Zamani and Schwartz (2017) successfully used Twitter language to forecast house price changes for a small sample at the county level. Except this limited research on real estate markets and the research for the general stock market, there is no more general study that examines the relationship between social media and real estate markets. Nevertheless, real estate markets are of particular interest, not only because of its popularity as an asset class among retail investors, but also because real estate is ubiquitous in daily life and the intransparency of the market. Sentiment indicators extracted from social media therefore promises to cover perspectives from all kinds of people and could therefore be more informative than traditional sentiment measures. However, as described by Li et al. (2018), social media-based sentiment indicators are not intended to replace traditional sentiment indicators, but rather complement them, as these are usually based on the knowledge of only a few industry insiders instead of that of the general public. Besides, the study focuses on indirect real estate (i.e. REITs) as it allows retail investors who represent the majority of social media users sharing equity-related information, to participate in real estate markets.

Methodology & Data

Using a dictionary-based approach, a classical machine learning approach as well as a deep learning based approach to extract the sentiment of approximately 4 million tweets, this paper compared methods of different complexity in terms of their ability to classify social media sentiment and predict indirect real estate returns on a monthly basis. The baseline for this comparison is a conventional dictionary-based approach including valence shifting properties. The dictionary used is the real estate specific dictionary developed Ruscheinsky et al. (2018). For the classical machine learning method, a support vector machine (SVM), which already has stated to be potent in a real estate context (Hausler et al., 2018), is utilized. The more complex deep learning approach is based on a Long Short-Term Memory (LSTM) model. The usefulness of deep learning-based approaches for sentiment analysis in a real estate context has been proven before by Braun et al. (2019).

As high-tradevolume-stocks tend to be discussed most on Twitter, posts are collected from this platform (Xu and Cohen, 2018), including a ten-year timespan from 2013 to 2022. Hereby selection is made on the basis of cashtags representing all US REITs. The monthly total return of the FTSE Nareit allEquity Total Return states the dependent variable, whereby the created sentiment variable is the variable of interest.

Contribution to science and practice

The aim of this study is to create a standardized framework that enables investors of all kinds to better classify current market events and thus better navigate the opaque real estate market. This framework could be applied not only by investors, but vice versa by REITs to understand and optimize their position in society and in the investor landscape. To the authors knowledge, this is the first study to analyze the impact of social media sentiment on (indirect) real estate returns, based on a comprehensive national dataset.

We use generalized additive models to predict residential real estate prices in Germany. Creating a single model for the whole country would fail to account for spatial heterogeneity in model outputs while too finely grained spatial units would lead to bias due to data sparsity. To overcome this problem, we subdivided Germany into clusters that pool as much data as possible, while also being sufficiently small to retain internal homogeneity. To this end, we employed the SKATER algorithm developed by Assunção et al. (2006) to group spatial units based on postal codes into clusters. The algorithm uses minimum spanning trees to identify regions that share similar characteristics regarding urbanization level, average real estate prices and the number of observed real estate listings. We use real estate listings data to build separate models specific to each of the resulting 25 clusters. In doing so, improve the overall accuracy of our model outputs, i.e. real estate prices on Germany, by capturing regional differences in urbanization and socioeconomic factors.

In France, since many years, urban disparity based on income is increasing in most metropolitan areas (INSEE 2023). This urban disparity refers to the unequal distribution of social groups in the urban space (Rhein 1994). This phenomenon is explained by 2 main factors: first, since the financialization of the French real estate market in the 90’s (Nappi-Choulet 2013), many households and investment funds are turning to real estate for investment, as it is presented as a safe haven, particularly luxury real estate. This has led to a significant concentration of property wealth by a small number of households, particularly in bourgeois districts (INSEE, 2021). Second, we observe an “entre-soi” phenomenon, particularly within the upper social classes (Préteceille 2006). The location of the housing became central for the upper social classes, to the point of becoming the most important characteristic in the housing choice process (Bouzols 2019). These social characteristics of luxury housing are not well documented in the real estate literature, and not quantified.

The marketing literature brings elements to determine whether a product is considered as luxury or not. Based on the conceptual framework of luxury of Bachmann, Walsh, and Hammes (2019), which details different constructs of the luxury product , we will pose the following research question: is the social dimension of luxury the most important dimension in luxury real estate perception? Is location a luxury?

To answer this question, we will develop a method in 3 steps. First, based on advertisement data, we will evaluate the proportion of properties that are posted on luxury ad sites in each municipality. This will determine if the municipality is perceived as luxury location by the real estate agent or not. Second, we will implement a mass appraisal model following XGBoost algorithm from an exhaustive transaction database (DV3F) to estimate the value of the whole stock of dwellings in Île-de-France (from land declaration database). Finally, we will develop spatial econometrics models (GWR, SDM) based on the estimated database from land declaration, to determine which factors determines what is a luxury housing. We run these models including each municipality defined as luxury by real estate agents.

The implications of this work are two-fold: first, it will bring the conceptual model of Bachmann, Walsh, and Hammes (2019) in the poor luxury real estate literature: is luxury real estate only a question of social construct? This conceptual model will be modified according to the results. Second, it raises questions about growing spatial segmentation and “entre-soi” dynamics.

Recent research has shown that macroeconomic uncertainty is a signifcant factor that is contemporaneously incorporated into asset returns. Therefore, it should not have a role in predicting future returns. At the same time, separate research has demonstrated that illiquidity is related to future returns. We examine the interplay between these two dynamics in a commercial real estate setting, where (il)liquidity is a defining characteristic of the asset class. Empirical tests confirm the absence of return predictability for liquid assets (publicly traded property portfolios). However, we find significant return predictability predicated on ex ante macroeconomic uncertainty when we examine assets that are not as liquid (directly held property portfolios). Our findings are robust to several refinements, including adjustments for delays in the transaction closing process to establish transaction prices in the directly held market, controls for leverage inherent in publicly traded real estate asset returns, and pro-cyclical liquidity variation in private real estate markets.

Security tokens, based on blockchain technology, are rapidly becoming widespread as new-era investment products. Real estate tokens have long stood out as one of the most popular of these tokens. The underlying reason is that the real estate industry is associated with low liquidity and lengthy and expensive transaction processes. Tokenization platforms and real estate market experts believe tokenization will solve many problems in the traditional market. The products that will emerge through tokenizing real estate assets can increase liquidity by removing high entry barriers in the market and creating a secondary market where intermediaries are minimized. Theoretically, this technology, which can provide secure access to a broad market in a short time, can also mean a new platform for both debt and capital increase. This thesis study examines the tokenization of real estate assets with both quantitative and qualitative approaches. Within the scope of the study, the structure of real estate tokens as financial products were examined, and their similarities and differences with traditional products were discussed. Moreover, an empirical analysis has been made by comparing the financial performance of real estate tokens actively traded in the secondary market with specific reference indices. The results of this study showed that real estate tokens have higher returns than selected market portfolios but have higher risks than traditional market products.

Academic achievement of students is a major determinant for their subsequent professional careers. Thus, university classrooms should offer optimal learning environments fostering students’ cognitive performance and development. However, university buildings are often poorly ventilated and in need of renovation. Past studies have shown that poor indoor environmental quality in terms of the thermal environment and air quality impairs cognitive performance.

This study uses a quasi-experimental setup to investigate the effects of a sustainable university building on students’ academic performance and wellbeing. We randomly assigned a sample of about 1200 first-year Maastricht University bachelor students in economics and business into a control and treatment group. The treatment group had their four weekly 2-hour tutorials in a newly renovated building certified with the WELL Building Silver Standard. The control group stayed in the old building, which has been in service for the university since 1976, with the most recent renovation in 2002. In each of the tutorial rooms, we measured indoor temperature, relative humidity, the concentration of carbon dioxide (CO2), fine particulate matter (PM) and volatile organic compounds (VOC) during two course periods from November to December 2022 and from February to March 2023, each lasting seven weeks. We recorded the grades, the course evaluations, and student survey responses on their perception of the indoor environment during each course. Each tutor taught classes in both buildings, allowing a natural tutor-fixed effect.

Preliminary results from the first period showed that CO2 and VOC concentrations were significantly lower in the certified building. No substantial differences in students’ grades were found. However, students reported a better mood, a higher satisfaction, and believed that the certified building had a positive impact on their performance. Contrarily, they reported that the lighting conditions and noise levels of the certified building hindered their performance. The next step will be to incorporate the data from the second test period examining possible longitudinal effects. All data collection will be finished by the end of March 2023, and we will do the remaining analysis and the paper write-up in April and May.

Property development are highly capital intensive, most real projects opt for bank or institutional finances, to finance the construction. In a construction-linked payment (CLP) plan, buyers, developers and financial institutions come together, to ensure participation of each stakeholder. BIM can be used to support construction-linked payments, which are payments made to contractors based on the progress of construction work. By using BIM, stakeholders can monitor the progress of the project in real time and track the completion of specific tasks. This allows for more accurate and timely payments to be made to developer, based on the items of the work that has actually been completed. This would serves dual purpose, firstly that money released by financial institutions will be used on the project for which it is allocated and also with BIM model, the nearly exact dates of payments required can be predicted with more accuracy and certainty. These digital advances in construction projects would help on time and on budget. This helps to ensure that payments are made based on actual progress, rather than estimates or assumptions.

Customer satisfaction is a leading indicator of their demand and the companies' performance, however, limited evidence research on how the satisfaction of tenant-customers of commercial offices, could contribute economic value to the building. The tenant survey provides us with the opportunity to research this question. Using the Kingsley tenant survey dataset collected from 2,965 U.S. office buildings and 55,951 corporate tenants, matched to the building characteristics data and financial performance data from the Costar database, and green certificate data from USGBC, we estimate the impact of tenant satisfaction on tenant's following leasing decision and the performance of the building. We document that 1 point higher overall satisfaction (on a scale of 1 to 5) is positively related to 8.36% higher willingness to renew the lease, 11.03% higher building recommendation, and 19.40% lower probability of actually moving out. In addition, analysis of the financial performance found that after controlling for the current period performance, 10% higher building level average overall satisfaction is related to 0.17% higher growth of gross rents, 0.66% higher growth effective gross rent, and 2.32% lower growth of vacancy rate. Besides, this beneficial effect is more significant for those tenants who have already stayed in the building for a long time, for the properties that are located in the submarkets with high occupancy rates, and for properties that have lower initial satisfaction levels. Further analysis using the mediation model documents that putting in sustainability and better property management company could improvement to tenants’ satisfaction and the performance of the building. Our research provides a shred of evidence for the financial implication of good customer relationship management in the real estate sector.

We infer the term structure of discount rates through the implication of relative price discounts between short leaseholds and very long-term leaseholds in UK repeat-sales housing markets. The price discount reflects the cash flows starting at the short leasehold expiration and is informative about the implied discount rates that households use in their payment valuation. For our empirical analysis, we use repeat-sales regression on properties transacted more than once to deal with the omitted variable and selection bias issues that the hedonic model might have. We find that the term structure of discount rates has a downward-sloping shape over a long horizon with a low implied gross discount rate of 1.3% at 100 years. In addition, we find households living in poor and rich areas or London and Non-London areas apply low but different discount rates from 1.2% to 1.8%, suggesting the consideration of the regional difference in policy design and investment.

Transit-Oriented Development (TOD) is gaining wide acceptance by many state’s governments in Malaysia due to its potential to create a liveable neighbourhood with enhanced mobility. Therefore,  the present study  to examine criteria that are considered critical for the success of TOD adoptions based on integrated perceptions from residents and retail operators who live nearby or work at the selected northern KTM commuter stations in Malaysia. The data for this study were gathered from a survey on 360 residents who used the Northern KTM commuter train service. Descriptive and inferential technique was performed to analyse the data and produce the findings. The findings of this study shown that there were significant differences in travel behaviour patterns (companions, frequencies, and walking durations) with respect to respondents’ travel purposes. Moreover, it was revealed that land-use diversity and walkable design as important TOD principles that contribute to their quality of life. Besides residents’ perspectives, the present study also considered the retail operators’ viewpoints in estimating the impact of TOD adoption on quality of life. Unlike residents’ perspectives, retail operators’ quality of life was assessed in terms of business performance and business well-being. “Density” principle showed positive impacts on both retailers’ business performance and business well-being. The findings of this research would serve as a base but critical information to direct future National Estate Development Plan.

Pension funds worldwide have experienced increasing allocations to alternative assets, the most important being real estate. The question is, however, what the drivers of that real estate allocation are. We exploit the global pension fund database of CEM to shed light on this issue. We find that pension funds’ strategic allocation (net of performance effects) to real estate is the result of the historical performance of the asset class compared to other asset classes and that pension funds adjust their actual allocation percentage quickly to the strategic allocation: we find allocation reductions in years after high returns, and increases in years after low returns. Market risk attitudes – measured by the credit risk spread and the term spread – do not play a role in the overall real estate allocations. Last, we observe that while pension funds’ allocation to real estate has grown over time, this is not the case after we adjust for capital appreciation: In terms of physical real estate assets, pension funds’ portfolios are generally shrinking, with the US leading the way.

Cities concentrate almost 60% of the world's population. Worldwide, urban populations are highly vulnerable to climate change. Urban green spaces and related ecosystem services help increase inhabitants’ quality of life and well-being and mitigate the impacts of climate change. However, in terms of urban planning, green spaces can raise a dilemma by reducing the space available for vehicle traffic and parking. In this paper, we focus on green spaces around the tram network in the Lyon metropolitan area, France, to assess the social demand for the greening of the urban transport infrastructure, using a Discrete Choice Experiment (DCE). The survey was conducted in 2022 with 500 inhabitants. Our results show that respondents are in favor of urban greening due to its capacity to reduce air temperature and increase biodiversity. However,they are, on average, against a high reduction of the available space for traffic and parking, because of urban greening development. Outcomes also demonstrate a high heterogeneity in inhabitants’ preferences partly driven by their sensitivity and commitment to the environment.

Recent studies have shown an increase of Embodied Carbon of buildings while operational emissions were reduced in many countries. Since renovations are crucial to tackle climate crisis, this paper aims to investigate to what extent embodied carbon of energetic retrofits is beneficial from an ecological perspective. In particular, this paper researches the question of how long the carbon payback period is for the asset classes and on which ones the focus should initially be in the upcoming modernisations. Starting off with a literature review on embodied carbon in building materials and construction, a set of case studies is then analyzed in terms of avoided emissions and embodied carbon emissions that come along with the retrofit. Typical renovation packages and scopes are compared with each other by calculating the environmental impact as well as their economical payback period. Subsequently, the energy consumption before and after retrofit is considered and the extension of the life cycle by the measure is evaluated. As a result, benchmarks will be established for different energetic retrofit measures in different regions. This paper helps to prioritize retrofit measures from an ecological point of view and at the same time is to the best of the authors' knowledge a first-time framework for the comparison between emission savings and initial carbon emitted during the retrofit.

After the great turmoil of the latest financial crisis, the criticism of the regulatory frameworks became increasingly stronger. The rules that banks needed to comply with are presumed to be procyclical and unable to prevent and mitigate the extent of strong financial and economic cycles. As a result, Basel III introduced a set of macroprudential tools to overcome these regulatory shortfalls. One tool that strives to counteract the issue of procyclicality is the countercyclical capital buffer (CCyB). This paper introduces a heterogeneous agent-based model that investigates the implication of the new regulatory measure. We develop a housing and a financial market where economic agents trade residential property that is financed by financial institutions. To examine the macroeconomic performance of the CCyB, we evaluate the dynamics of key stability indicators of the housing and the financial market under four different market conditions: in an undisturbed market and in times of three different structural shocks. Computational experiments reveal that the CCyB is effective in stabilizing the housing and the financial market in all market settings. But the extent of the stabilizing effect varies according to market conditions. In the shock scenarios, the CCyB performs better in dampening market fluctuations and increasing banking soundness. Although the new macroprudential tool helps to mitigate economic fluctuations and to stabilize market conditions in the aftermath of a crisis, it is not able to prevent any of the crises tested.

The research builds on the knowledge that under high-rocketing housing prices in many attractive cities with favorable em-ployment prospects, some talented workers are forced to leave due to poor housing affordability. To retain them, some municipalities adopt housing subsidies for targeted talents as a policy instrument. In China, such policies are named as Talent Housing (TH) policies. However, due to complex effects (i.e., positive, negative, composite) of housing prices on talent flow, along with impacts of cities’ socio-economic conditions on talent flow, policymakers are uncertain about whether TH policies will have expected outcomes. Therefore, the research aims to explore the impact of TH policies on talent agglomeration, along with its relevant determinants in terms of cities’ economic conditions (e.g., work opportunities and housing affordability). Generalized Method of Moment (GMM) and Finite Distributed Lag Model (FDLM) were applied to analyze the causality between talented human capital and TH subsidies of 70 Chinese cities. The findings show that TH subsidies are conducive for talent agglomeration, in particular to home-buying subsidies which have a 1-year lag positive effect. Nevertheless, TH subsidies might be less effective in cities with poor work opportunities and high housing affordability. The research provides insights into the economic impacts of TH policies on talent flow and helps policymakers from different cities design more suitable TH policies for sustainable development.

The demand for housing in Turkey has been increasing in recent years to meet the need for shelter as well as an investment good. Especially during Covid-19, housing prices continued to increase in many regions of Turkey, similar to the development in many other countries around the globe. The Turkish government conducted various measures to counter the severe economic consequences of Covid-19, and several of these measures have had direct and indirect impacts on the housing markets, too. This study analyzes the effect of selected economic measures applied during the pandemic on Turkey's housing prices. Due to data availability, this study focuses on the main housing markets in Turkey: Istanbul, Ankara, and Izmir, which account for more than one quarter of the Turkish population. The conducted economic measures and other macroeconomic factors are assessed over the Central Bank Money Supply, Consumer Price Index, Unemployment Rate, and Housing Loan Interest Rate variables to analyze potential effects. Hereby, residential real estate prices are evaluated on a regional level to show the potential diverging impacts of the respective measures on local housing markets. Descriptive statistics and stationarity levels of the variables used in the study are examined with the Dickey-Fuller (ADF) test. In the study, a Vector Auto-Regressive (VAR) model is used to analyze the various variables’ impact on housing markets in Tukey. While already several studies analyzed the impact of economic measures on house prices in different countries, this study uniquely assesses the impact of such measures in Turkey during Covid-19. The study also evaluates the impact of multiple macroeconomic factors on house prices, providing a more comprehensive understanding of the factors that cause fluctuations in house prices in Turkey. The study can guide policy decisions and investment strategies by providing insights into the impact of economic measures and other macroeconomic factors on house prices.

Energy efficiency in the housing market is considered an important tool to reduce energy consumption and carbon emissions, as well as to enhance national energy independence and protect consumer balance sheets. Home insulation plays an important role in improving the energy efficiency of a home. However, the impact of insulation measures on actual gas consumption is typically based on engineering predictions, and the efficacy of insulation measures is subject to debate. This study exploits a unique home insulation sample, combined with detailed household data on actual gas consumption before and after these interventions, and information on the socio-economic characteristics of occupants. Using a difference-in-difference approach, we document that home insulation reduces gas consumption by about 20%, on average, both for owner-occupied and rental homes. For the latter, the treatment is plausibly exogenous. We find no evidence of a temporal rebound effect: the reduction in gas consumption is consistent up to ten years after the intervention. At 2022 gas prices, the average treatment effect translates into an €866 reduction in the annual gas bill, and an average rate of return of 41.6% on the initial investment.

In last decades, there is a trend to renew buildings and make them more sustainable. The idea is that as buildings will function more cost-efficient and will last longer, sustainability should also add value to the property. Yet, there seems to be a lack of evidence that positively relates sustainability measures to financial benefits. Moreover, as sustainability is a very broad term, the effects of different sustainability measures on real estate values are even more unknown. This study examines the relationship between multiple sustainability aspects and the value of real estate. Official data on commercial real estate transactions from the Land Registry Office in the Netherlands were used in this study as well as official valuations and sustainability assessment scores from a Dutch real estate consultancy. The assessment scores cover, on aggregate level, 5 categories of sustainability: energy, environment, health, usability and future prospects. In total, 5,875 real estate properties between 2012 and 2021 were analysed. By use of a hedonic price model, the relationship between these 5 dimensions of sustainability and the real estate value is examined. The results will provide clearance on the financial benefits of different sustainability measures that are common in building and renovating real estate.

This paper is dedicated to the study of student housing using the example of Aachen, Germany's seventh-largest student city with 61,500 students (Statista, 2022). The focus lies on the current satisfaction of students with affordable dormitories. New needs and requests for future development are analyzed.

The market for student housing is tense. Between 2002 and 2022, the number of students in Germany increased from 1.9 million to 2.9 million (Destatis, 2022). At the same time, the social infrastructure, especially housing, has not grown with it to the same extent. More and more private investors are entering the market and exploiting the shortage of dwellings with high rents. In addition, current crises such as inflation and rising energy costs mean that students are competing with more and more people in search of affordable housing (Tagesspiegel, 2022). Especially in inner cities, where universities are often located in close proximity, this leads to a massive increase in rents. But it is not only in Germany that the number of students is rising and the housing shortage is increasing. Across the EU, the number of first-year students increased by 8.8 percent from 2013 to 2020. (Eurostat, 2020). The high rents mean that the free choice of where to study is no longer guaranteed and thus academic freedom is at risk (Tagesspiegel, 2023). Funding for student housing is required to take the pressure off the housing market and to enable different groups of students from different social backgrounds to continue studying.

To promote and open the housing market for a wide range of students, more publicly funded housing for students must be provided in the coming years. As part of the study, a quantitative survey was therefore conducted in the 22 publicly funded dormitories in Aachen on the requirements for living in a dormitory and future needs. A total of over 1,200 students took part in the 10-minute online survey.

It will be found that especially after the COVID pandemic, dormitories are still a popular form of housing for students due to the large community. The survey also shows that the location requests of students are highly comparable to other housing seekers on the open market. However, few students are currently able to afford housing on the open housing market with the financial resources available to them. Although community plays an important role in students' lives, living arrangements for one to two people with their own bathroom and partial furniture are preferred. Shared rooms such as kitchens and study rooms should be available as well as sufficient storage space. Furthermore, it is apparent that, especially for students, sustainability also plays an essential role in the construction and operation of the dormitory.

For further real estate developments in the future, it needs to be clarified how these specifications and requirements can be implemented in publicly funded dormitories in the future and what steps need to be taken to promote student housing. It also is necessary to determine how sustainability and the resulting higher investment costs can be realized and what the role of the public sector and private investors is in the development. The paper gives first insights into the conducted investigation and context of the results and opens further discussion with other scientists on public housing.

Legal title is a crucial instrument to secure the possession of assets and to enable the transfer of property in the formal market system. Without legal titles, property holders will be posed to a great threat of expropriation and eviction, and they will also feel hard to derive economic benefits from property exchanges because of restrictions from formal institutions. As pointed out by De Soto, a property without legal title is the dead capital rather than the asset that can accumulate wealth.

Previous studies have assessed the market value attached to spatial distributions of dwellings in the absence of full legal titles by investigating the transaction of informal housings, because 'location' always matters in the real estate analysis. However, the concept of location not only refers to the geographical position at the horizontal dimension, but also involves other settings on the vertical dimension. Different vertical locations may bring different utilities for dwellers, leading to the variation of housing prices. Despite that, few attentions have been paid to the valuation of vertical location of properties when legal titles are absent.

To fill this research gap, this study seeks to decipher how consumers value the vertical attributes of dwellings under the premise that de jure property rights are absent. The housing market in the urban fringe of China provides an ideal laboratory to conduct this investigation. Besides formal housings, a unique informal property named small property rights housing (SPRH) is also an important residential source for local people at the fringe of megacities. This type of informal housing is built on rural land collectively owned by villagers and then sold for urban residents without collective memberships. Like most formal residences in China, SPRHs are built in high-rise forms, and they can provide dwellers with spacious buildings, high-quality facilities and pleasant surroundings. In fact, it is hard to distinguish SPRH projects from other formal residential communities in terms of physical features. Despite the impressive built environments, SPRH still cannot be titled by governmental agencies. This is because that the development of SPRH fails to adhere to restrictions on collective-owned land use regulated by formal land systems. Due to the lack of legal titles, the transaction of SPRH is excluded from formal housing market of China, and it can only occur under the shadow.

An empirical estimation is carried out with a dataset from an urban-fringe township named Chang’an where SPRH transactions are quite active. By comparing the difference in prices paid for formal housing units and SPRH units in the local housing market, this study finds that the selling price of SPRH unit at the local is significantly lower than that of formal housing unit with similar characteristics, all else being equal. More importantly, this study captured that the absence of legal titles can impact the value contribution of vertical attributes to the overall prices of housing units. Specifically, this study finds that: (i) the lack of full legal title can enhance the detrimental effect of building height on the selling price of housing unit; (ii) although high-rise residence has been the norm in urban China, dwellers still prefer to living in multi-storey buildings by paying price premiums, and this preference is stronger if the title of dwellings cannot be registered by formal authorities; and (iii) the deficiency in legal title status does not impact the valuation of consumers on the vertical position of housing units in the high-rise block. These findings reveal interesting interactions of property rights, housing attributes and housing prices from the vertical dimension. This research can shed new light on the understanding of market value of legal titles in a broader context.

Foreign capital and buyers are often blamed for pushing up housing prices and reducing the supply of affordable housing in Australia. We examine this issue by assessing the impact of Chinese macroprudential policies, such as the limitation on currency transactions (LCT), on Sydney housing prices. Using propensity score matching and difference-in-differences techniques, we find that the LCT policy issued by the People’s Bank of China in 2017 had a strongly negative impact (about -3%) on housing prices in suburbs with larger concentrations of Chinese residents, which are measured by multiple cutoff points—hereafter, Chinese suburbs—in Sydney, Australia. The results are consistent with home bias abroad, which implies that Chinese capital for residential real estate overseas most likely flows to predominately Chinese neighbourhoods in the destination city. We also find evidence that the relationship between this Chinese macroprudential policy and overseas housing prices is more direct to Chinese suburbs, with little impact on housing prices outside Chinese neighbourhoods within the studied period.

Flexible workspace providers are substantial occupiers of commercial real estate in the UK that usually lease large proportions of a building over a significant period. The covenant strength of these tenants is not as straightforward as blue-chip companies. While providers offer diversity to a building and an additional amenity to other existing tenants, their covenant strength might not be as compelling as their peers given that they depend on volatile revenue streams obtained from subletting the space through a membership scheme. The covenant strength impacts default probabilities during the lease and is a dynamic that is factored into the risk premium component of the capitalisation rate. In the grey literature, there is some evidence that the share flexible workspace providers occupy in a building can drive capitalisation rates up or down, reflecting the risk of this tenancy. Therefore, the valuation of a freehold that houses flexible workspace providers as tenants is not uncomplicated and the yields applied to capitalise the rental income need to be properly considered. This research analyses transaction information from CoStar to investigate the impact of flexible workspace tenancy on capitalisation rates in the London market. Preliminary findings suggest that office buildings with less than 40% of their total net internal area occupied by flexible workspace providers produce little to no loss in value.

There is an intense debate regarding the relationship between the firm performance and the degree of geographic diversification. Yet, the results are inconsistent. Learning from the literature of international business, we divide the overall geographic diversification into intra-provincial and inter-provincial diversification to obtain a clearer insight of this relationship. In this research, we manually collected data from listed Chinese real estate firms’ annual reports over 10 years. Using both the property-based and the sold-area-based measurement of geographic diversification level, we find that a more diversified strategy would lead to better firm performance when diversifying within a specific province. Meanwhile, firms would confront a firm value reduction at the first stage and then higher firm performance when diversifying across provinces. These findings add to the extant literature on the impact of geographic diversification on firm performance and shed light on the expanding strategy for real estate firms. The future work of this study is to examine the moderating effect of the geographic distance between firms’ headquarters and properties in each city on this relationship.

This study details the findings of a study that seeks to establish how minimum energy efficiency standards have affected the domestic private rental sector using data from England and Wales. The research questions studied mainly concern rent affordability both in the general market as well as above and below the energy efficiency thresholds for legally renting out space under the new regulations. The present study also estimates the effect the policy has had on the attractiveness of investing into rental properties relative to other asset classes and the owner-occupied property market segment. The main findings are:

• Rents of F/G rated properties were lower before and after MEES implementation compared to higher EPC grades which is in line with previous research
• During the implementation period, an additional rental discount to properties in the F/G band can be detected with increasing magnitude over time.
• Above-threshold properties in the EPC E band and/or D show a moderate rent increase in response to MEES
• No signs of a significant sell-off of properties from the private rental sector into the policy-neutral owner-occupied market segment are detected.

The main finding is hence that substandard energy efficiency as indicated by an F or G EPC rating has become significantly lower over time and the evidence suggests that the introduction of MEES has contributed to this trend. Although causal inference is complicated by the staggered introduction of standards which does not permit a clear separation between a pre and post MEES period, it appears that government intervention aimed at upgrading lowest EE has at least supported and augmented a trend towards higher energy efficiency, even if this upgrading process may not have been entirely due to this policy instrument. Concerns about MEES impacting negatively on rental affordability are not supported by the present analysis although some moderate uplifts are found for D/E-rated properties and further research will seek to corroborate these first findings.

The existence of non-tradable shares was a unique phenomenon in the Chinese mainland stock market. Before the non-tradable share reform, only newly issued A-shares were tradable shares. Other shares issued before IPO were non-tradable. Non-tradable shareholders are usually major shareholders who also appoint the managers (CEO) of the company.  Due to the absence of the rights to transfer in the stock market, non-tradable shares are, in theory, less valuable than tradable shares. The purpose of the non-tradable share reform was to equalize the rights of all shareholders.

Non-tradable share reform has increased the shareholders’ rights, which also increased their incentive to monitor the performance of the management and thus corporate governance of the company.   This study aims to investigate whether the non-tradable share reform has impacted on the corporate governance of listed real estate companies (“Indirect Real Estate”). Previous studies are inconclusive, and the empirical results were also mixed. This study measures the quality of corporate governance by the linkage between share price movements of the listed property companies and the price movements of the tangible asset (“Direct Real Estate”) held by these companies (“Linkage”).  This measure is viable for real estate companies due to the availability of real estate price indices (indicator of Direct Real Estate Prices).  Since the major form of tangible asset held by listed property companies are real estate assets, good governance should minimize the agency problems so that the company’s valuation reflects closely the price movements of the real estate assets it holds and therefore a stronger Linkage. A difference-in-differences approach is used to test the impact of the non-tradable share reform on the strength of the Linkage.   The empirical results show that the increase in the strength of the Linkage after the reform for central state-owned companies is the largest and most significant, while that for private companies is the smallest and least significant. Among the state-owned companies, the strength of the Linkage after the reform has increase less for the local state-owned companies compared to that of the central state-owned companies.  The results are consistent with the conjecture that the impact of non-tradable share reform on corporate governance, measured by the strength of the Linkage, decreases with the management’s incentive to maximize the value of the company.

Cell phone tower deployment is globally met with public concerns relating to the aesthetically unappealing nature, health risks associated the electromagnetic field (EMF) emissions from these devices, and as a result, the negative effect of these devices on property values for properties in close proximity to these devices. As such, this study analyses the impact of cell phone towers on the house prices. Using a GIS tool to determine distance of cell phone towers to the houses, the study employed a hedonic price model using sales prices of residential transactions between 2012 and 2022 for Randpark Ridge, Johannesburg, to determine the actual impact of proximity to cell phone towers on house prices. In the Johannesburg context, the results of the study found that were no statistically significant findings that suggest there is a correlation between the presence of cell phone towers in close proximity and house prices. The findings of the study were contrary to the findings of the majority of similar studies, where cell phone towers were found to have a negative impact on the price of houses. Due to the limitations of line-of-sight confirmation, budget constraints and time limitations, there is difficulty in using the findings for generalizability.

In recent years, social media platforms have become vibrant online platforms where all kinds of market participants share their opinions on equity markets. This provision of opinions and thus of information has attracted the interest of the financial industry. Parallel to this trend, the finance and real estate industry have also recognized the importance of environmental, social, governance (ESG), due in particular to increasing pressure from the public. Bringing these developments together, this paper uses a textual analysis approach to analyze the public’s opinion on social media regarding the ESG performance of real estate related companies. The aim of the analysis is to examine how the public opinion on ESG is reflected in Twitter data and how it can be used to predict the performance of US REITs (Real Estate Investment Trusts). Therefore, using a three-step procedure, this paper first identifies ESG-related tweets, then measures the sentiment of those tweets using different natural language processing techniques and, using the results of the sentiment analysis, calculates the impact of those tweets on the performance of the corresponding company. The first step is achieved, by employing a Global Vectors (GloVe) model, which allows to select tweets based on ESG-related keywords of the corpus. In the second steps a lexicon-based method is applied to create a sentiment index, which is the baseline for the following analysis. Besides, a CNN-LSTM based sentiment index will be created, which might be more powerful in capturing the linguistic complexity of language in social media. Last, the sentiment indices are compared to the performance of the corresponding company in order to determine any correlation and predictive power. Our results not only show a significant correlation between the sentiment indices and the performance of the companies, but also a significant predictive power with positive tweets being associated with better performance and vice versa. These findings suggest that Twitter data can be a valuable source for predicting ESG performance and that using word embedding models, such as GloVe, and lexicon-based methods for sentiment analysis can improve the accuracy of the results.

Automation of the property valuation has no doubt improve the accuracy of value estimation. The capabilities of GIS technology to spatially display objects, event or phenomenon in their real time have also uplift the property market. The GIS with its statistical module have enhances the house price determination taken into account the spatial relationship between the house price and the determinant factors eliminating the problem of autocorrelation and accounting for spatial interdependency of predicting factors against the hedonic (OLS) model. The study focuses on spatial statistics utilising exploratory and geographic weighted regressions in comparison to OLS regression in housing price estimation. Data for the median house price and predicting variables for the 33 Burroughs of Greater London was accessed from the database of the UK Data Service through the webpage of the London Data Store both of the geographical boundary data and statistics dataset. The study found that autocorrelation remains a problem in OLS regression with Moran’s I value of 0.1771and P=0.0139. Exploratory regression provided three (3) variables of significant contribution to house price having highest R2 (90%) and other statistics satisfied for the model fit resulting in more accurate price estimation.

Data on commercial real estate (CRE) transactions differs in many ways from owner occupied housing transactions. CRE has low transaction numbers, is more heterogeneous and can also be traded as a company share deal. There is one more aspect in which CRE differs: it is often sold in portfolios. In this setup, multiple real estate properties are sold in one transaction. This is also called a portfolio sale. In the construction of real estate price indices, a portfolio sale is problematic, because it includes properties of various types in various locations. In the construction of price indices, portfolio sales, therefore, must be broken down into separate properties.  This study examines the price index construction problems, caused by portfolio sales, provides possible solutions for handling them and assesses the usability of these options by discussing the advantages and disadvantages. This study uses official data on commercial real estate transactions from the Land Registry Office, official valuations and official information on buildings in the Netherlands. The assessment involves simulations in which one on one sales are constructed as if they were sold in portfolio sales. This allows us to assess which breakdown estimation methods deliver solid approximations for the original transaction prices. The provided solutions will provide compilers of CRE price indices handles on how to cope with portfolio sales and the simulation technique will provide them a way to assess the results.

Under the strict land use regulation, the illegal residential use properties face the risk of being fined and the intensity of law enforcement and the possibility of being legalized will affect their prices. This study examines the influences of property right restrictions and rent seeking behavior on housing price by using the transaction data of illegal residential properties in commercial and entertainment district, Dawan north section, Taipei City. The empirical results show that the price of illegal residential use properties is about 21% discount of legal residential use properties. When Taipei City Government strength its law enforcement, the price discount of illegal residential properties increases to 26%. The empirical results confirm that property right restrictions do have profound influences on property prices, and the price gap between illegal and legal use properties depends on intensity of law enforcement. Since land use regulation and its law enforcement will affect not only the quality of environment, but also the value of property rights, equality among land owners, and government authority. We suggest the governments have a more long-term and comprehensive land use planning and regulation, and a stricter enforcement to avoid speculation activities.

Data storage and IT equipment housing is demanded rapidly over the last decade parallel to improving the significance of big data. Data Centers (DCs) have supplied service to this demand for decades by being real estate assets built up in strategic locations with housed IT equipment. In parallel with this demand, data center investments have boomed around the globe in the last decade. To develop the supplied service quality of the data center investments, a reputable private organization Uptime Institute provide certification to measure how well a data center as a real estate can be designed and developed by classifying it in 4 classes of tiers. Data center tiers are a classification system, ascending 1, 2, 3, and 4 show the commercial reputation and operational efficiency of data center investments. Data center tiers are awarded after the measurement of operational redundancy in general. The measurement includes performance criteria such as design, infrastructure efficiency, energy efficiency, operational cost structure and location. The research paper focuses on location criteria and their correlative significance on the other performance criteria in general and narrows down into the problem statement; “Many data centers in Turkey are developed by mainly wrong location selection and, it results in operational performance and TIER III and less certified investments”. The research paper aims to test whether a model can be invented for location selection and the best operational use correlation of data center investments. It analyzes Central & Eastern Europe data center real estate market data and selected data centers in a particular methodology for a benchmark to understand how location affects the operational use of a Data Center in Turkey. In the methodology, the research paper explores past data center location decision models like DEMATEL Method, Fuzzy DEMATEL Method and EDAS Method and their results on both energy efficiency and cost of the facility. Furthermore, the research paper utilizes this method to benchmark TIER IV certified data centers using the same fiber optic cable network and data infrastructure.

This continuing research provides a map for Turkey data center investor's correlation between selecting the right location and the operational best use of a data center as a real estate.

Using a micro-level dataset of over 1 million listings, the housing rental index for Poland from 2000 to 2023 was constructed. The offer data for the biggest cities comes from two different sources. The earlier data were obtained from archival advertisements in photocopies, photographs or periodicals, then digitally reproduced and arranged in a database. The data from 2009 were collected from advertising portals (gratka.pl / otodom.pl)  several times a quarter. The hedonic indices were determined for the city level and then aggregated. This allowed us to investigate the rental market during the financial crisis, COVID-19 or the refugee crisis caused by Russia's invasion of Ukraine.

The disconnections experienced as a result of being removed from the workplace and extended working from home (WFH), have illuminated distinctions in the needs and nature of connection to the office, professional identity and enablers of work for men and women. Globally, research has shown female employees disproportionately impacted by domestic and caring pressures throughout the course of COVID-19 imposed lockdowns, risking a setback of decades worth of gender equality progress in the workplace (Babatunde et al., 2022; Caligiuri and de Cieri, 2021; Garrido et al., 2021; Ipsen et al., 2021; King and Frederickson, 2021; Krivkovich et al., 2022; Oakman et al., 2022; OECD, 2021; Rozman et al., 2021). The focus has been socio-economic impacts, safety, workload, mental and physical health, attrition, and promotion opportunity. This paper documents and investigates key gender differences in Australian employees’ affective relationships to the office, needs for connection, efficacy, and flexibility in ways of working shown through extended working from home- or-elsewhere and return-to-office experiences (in lockdown-imposed and voluntary circumstances).

Statistical testing and comparative content analysis of data using SPSS and NVivo 12 from three rounds of online surveys (November 2020 through February 2021, April through May 2021, August through November 2021) with Australian employees and organisations is presented. The survey sample is comprised of Organisations (n=30) and Employees (n = 169) from 11 industry sectors (Property, Design and Construction, Education, Media and Arts, Professional Services, Retail, Government, Engineering, Mining, Health, and Technology) expanding the breath of current Australian research in gender which focusses on private or specific sectors (i.e., education, training, and healthcare). Findings show the trajectory of experiences of men, women, and organisations across the 2020-2022 timeline in Australia with particular focus on the 2021 return-to-office experience between two major state-wide lockdowns in Victoria (July through October 2020) and New South Wales (June through October 2021).

Flexible workplace policies in place prior to the pandemic remain a leading contributor to successful transition and continued adoption of hybrid working practices. Significant differences were found between genders in both their satisfaction with WFH and choices in ongoing number of days WFH, supporting similar global studies from the same period. More importantly, despite the freedom to choose where, when, and how to work, t-tests uncovered significant differences in male and female employee’s ongoing sense of connection and value to teams, autonomy and ownership over work and knowledge sharing overall with females reporting notably lower average scores across all domains. Gender biased nuance was also discovered in the nature of connections to employees’ physical work environments supporting existing research on principle empathic differences between genders (Mestre et al., 2009). This paper provides key insights for organisations towards development of more effective and equitable management of team workstyles and hybrid working. It also raises important inclusivity and gender-based considerations for the design of future workplace environments as optimised tools for productive work.

The retail sector is experiencing unprecedented change, caused by shifts in shopping behaviour, multiples downsizing their portfolios and withdrawing from urban centres and business failure, compounded by the covid-19 pandemic. Consequently, the number of vacant units in many city centres has risen significantly, creating redundant space, which has both a negative impact on the user experience and leads to a further decline in footfall for remaining city centre businesses. This has raised questions about how to fill the subsequent empty space and how city centres should be positioned, what their role should be. With a focus on adaptability at the individual property level, the aim of the paper is to examine the impact of the physicality of the built environment in the practice of transforming vacant floorspace. This raises questions about both the surrounding area and the challenges of adaptation to mixed-uses. The importance of the physicality of real estate in processes of change and adaptation is not often explored, yet can often be fundamental to the viability of change.

It is evident that the COVID-19 pandemic has accelerated the adoption and popularity of proptech. Remote work, social distancing, and the need for contactless transactions have driven the need for enhanced solutions that enable virtual property tours, online lease signing, and other digital services. Such global growth of the proptech sector has been mirrored by accelerated funding campaigns, increased number of proptech startups, and unprecedent interest from real estate developers as well as policy makers. A specific shift has been observed in the networks of the proptech around the world. Industry associations, accelerators, incubators, co-working spaces, and other forms of collaboration and networking have played a decisive role in taking the proptech into the next level. However, this networking intensifying efforts were not only attributed to the crisis as a trigger, but also to well-developed international-local high-tech innovation linkages, active innovation personal networks, and, in most cases, regional public and private readiness to adopt the new changes. In this study, we adopt a complexity-evolutionary perspective to illustrate the evolution of the proptech networks before and after the Covid-19 pandemic. Such approach is allowing us to assess the emergence of a cluster of proptech through studying the linkages between real estate actors, high-tech actors and startups and the funding organisations. Notions such as small events, windows of opportunities, local-international pipelines, regional readiness and path dependency are employed to draw a quasi-full picture of the proptech ecosystem in the last five years and its perspective for the near future. The study is taking the French proptech market as a case study. Our paper introduces the theoretical approach and the preliminary results of this study.

Determining the relationship between the economy, the banking sector and the real estate market is a problem that is of interest to researchers around the world. Since the beginning of the 20th century, scholars have been formulating theories about the cyclicality of the real estate market. Burns [1935] was one of the first researchers to analyze the causes of their formation. Other scientists analyzed the lengths of the individual phases. It has been proven that the cycles are influenced by, among others, the availability of financing for housing investments, population changes, problems in the construction industry. An important role is also played by government housing programmes, which stabilize the level of investment in the economy. In indirectly the programmes stabilize the labor market also.

One of the methods of studying the changes taking place in the real estate market is to analyze the parameters on the clock face of the real estate market. The main purpose of the presentation is to determine the current place on the clock face of the real estate market in which Poland is located.

The study analyzes economic indicators of the country and parameters of the construction market as well as information from the banking sector. As a result of a long-term analysis of parameters that may affect disruptions in the business cycle and the real estate market cycle, in the presentation will indicate the moment of transition to the next phase on the clock face. It is a kind of continuation of an important thread of research started many years ago by other researchers around the world.

To identify the course of the cycle, an analysis of real estate price dynamics and an analysis of the volatility of macroeconomic and market factors were used in Poland.

Green building advocates have stated that improved productivity is linked to green buildings, specifically due to enhanced indoor environmental quality (IEQ). Previous research indicated mixed results in this regard, and therefore conjecture still exists. The purpose of the research was to examine both individual productivity and organisational performance of occupants and businesses, respectively, located in green certified office buildings in South Africa. The research focused on financial services companies (FSCs), where each FSC offered a low, moderate and high risk investment product. Quantitative research was conducted on ten FSCs located in nineteen green certified and ten FSCs located thirteen conventional (non-green) office buildings, to assess organisational performance. Qualitative research was conducted in the form of semi-structured interviews across two FSCs comprising fifteen knowledge workers, to assess individual productivity. The research was conducted within the context of a theoretical framework that focused on the implementation of green building features and initiatives (GBFIs) that focus on IEQ. There was a statistically significant positive relationship (high risk products) when comparing annualised returns to IEQ (Pearson’s Correlation). Interview respondents indicated that location and amenities contributed to organisational culture, collaboration spaces, employee attraction and retention, and safety. These attributes were contributed in some degree to individual productivity. The results continue to indicate that the relationship between enhanced IEQ and individual productivity and organisational performance are not absolute, as there may be external contributing factors.

Building Extensions without prior permission such as a penthouse on top of a building or conversion of a balcony into part of a living room are not unusual in Taipei City, actually all over Taiwan. Some of those unauthorised extensions are reported to the city and waiting to be demolished. However, due to the resource constraint, unauthorised extensions are often not torn down for another few months, even years. In addition, some building owners seek assistance from city councilors to make a plea to the officials in charge to demolish the extensions at a later date. Assistance of this kind is often regarded as the return of a favour from the councilor to his potential supporters. The exchange of vote and assistance between residents and politicians has long been recognized in Taiwanese culture. However, empirical evidence is at best anecdotal. Based on the details of 180,925 listed unauthorized extensions recorded between years 1995 and 2020 in Taipei, a survival regression model is undertaken to explore the factors that determine the expected remaining life of those extensions after they are placed on the demolition list. Among other factors, political lobby is proven to be effective in prolonging the remaining life. Besides, involvement of more councilors reinforces the effectiveness of lobby.

Housing assets and mortgage loans play an essential role in household financial well-being and macroeconomic stability. The central role of credit conditions in the mortgage debt-service channel makes it an appealing macroprudential instrument for government interventions in the housing market. Despite the potentially salient policy implications, micro-level empirical evidence on the relationship between credit conditions and house prices in practice is scarce and mixed. In addition, “targeted” housing policies that intervene in a specific market segment have begun to attract increasing academic attention. This study fills the gap in related literature by investigating the causal effects of relaxing credit constraints targeted at a particular market segment on housing dynamics. Exploiting plausibly exogenous variation in down payment constraints caused by mortgage insurance program (MIP) amendments in 2019 as a quasi-experiment, we evaluate the unintended market responses and strategic behaviors using difference-in-difference (DID) and bunching regression.

We present the main findings based on property-level transaction data in Hong Kong residential market. First, relaxing credit constraints in the targeted market segment significantly increases home sales and prices for properties within the affected price ranges. Besides, such direct stimulus effects in targeted segments are pronounced and persistent during our sample period. We further scrutinize the market clearing process with search frictions and endogenous entry of broad searchers to rationale such positive policy effects. Second, we provide empirical evidence that targeted policies have unexpected and far-reaching spillover effects on neighboring segments triggered by derived demand for moving up housing ladders. Specifically, we explain why the initial segment-specific demand shocks trigger the housing ladder effects and moving chains. The derived demand from the housing ladder transition can be attributed to (i) a relaxation in ex-post financing constraints due to credit-driven housing appreciation and (ii) an increase in the ability to sell current homes of mismatched homeowners attempting to move. Our findings suggest that housing stimulus programs may be justified due to their welfare-enhancing role of general equilibrium effects, particularly in a cold market where the equilibrium is far from efficient due to illiquidity and frictions.

Third, we exploit the exogenous policy-induced sharp discontinuity in required down payments around the MIP eligibility threshold to identify the local behavioral responses of households by using the bunching regression. We find a substantial “diffuse bunch-ing” excess mass just above the notch and a visible missing mass just above the notch. Besides, we find empirical evidence that households behave strategically to qualify the MIP through tacit collusive agreements on underreporting sales prices. Our analysis has implications that policymakers should account for the strategic behaviors of market participants when designing macroprudential policies.

This study contributes to related literature by showing how relaxing down payment constraints targeting a specific segment operate in practice. It provides a better understanding of the direct impact of targeted housing policies and general equilibrium effects. Specifically, our research contributes to a broader literature on spillover effects across housing market segments triggered by housing ladder transitions, which inspires further research to consider segmented markets and multiple equilibria. Moreover, by studying the degree of bunching behaviors at the eligibility threshold of amended MIP, our research sheds new light on the strategic behaviors in designing the macroprudential policies or other government interventions, as the strategic behaviors might distort the policy effects and induce unintended consequences.

Since the onset of COVID, restrictions have forced many workers to change where and when they work (Marzban et al, 2021; Mendrika et al., 2021). In Australia, three distinct stages were experienced (ABS, 2021; Stobart & Duckett, 2022). In 2020, strict lockdown restrictions and the absence of vaccines meant that workers were mostly working from home (Duckett & Stobart, 2020; Durakovic et al., 2023). In 2021, a combination of snappy lockdowns and the increased vaccine uptake, meant that there was a slow push towards returning to in-office work (Massar et al., 2022). In 2022, lockdowns were lifted and the “living with COVID” stage meant a stronger emphasis on in-office work which has been received with little enthusiasm by most workers (Property Council of Australia, 2022). This reports findings from these three stages, focusing on the working experience reported by office workers in Australia. A total of 233 questionnaires from three rounds of the SHE (Sustainable and Healthy Environments) COVID survey were deployed in Australia, enabling descriptive and correlational analyses to be conducted. During the first of lockdowns in 2020, workers found the ability to perform more focused work and work-life balance were the most positive aspect of working from home. However, they were struggling with increased workload and setting up their home-offices with appropriate ergonomics. During all three stages of the survey, the most consistent positive aspect of not having to work from the office HQ was not having to commute to work and the most negative aspect was internet connectivity. Other reported positives and negatives changed through time though which serves as an indicator of how workers adapted their work and lifestyles. For instance, in 2021, survey results show that while workers were still reporting satisfaction with the improved balance between life and work, they also started to report their struggles with stress of increased workloads and isolation from colleagues. In 2022, during the “living with COVID” stage, isolation from their colleagues was the most notable pitfall of working from elsewhere. However, they found that having more control over their workplace and the ability to customize their workspace based on their needs as the most positive aspect of working from elsewhere. In all rounds of the survey, workers reported being more satisfied with flexible working arrangements post COVID-19 than with what they had access to before the pandemic and as such a clear desire for the gained increased flexibility to be kept in the longer term. Further, workers also indicated that interactions with their colleagues were the most important reason to work from office HQs. Since unshackled from office HQs in 2020, Australian workers may have gained greater appreciation of the value of in-office experiences and the need to interact with colleagues in person has increased over time but they are still unwilling to revert to pre-pandemic ways of working. In moving forward, findings highlight the need for companies to foster a supportive and adaptable work culture and style that suits the post-pandemic, unshackled Australian workforce.

The NSW Land Acquisition (Just Terms Compensation) Act 1991 makes provision for compensation for the acquisition of land, including any native title rights and interests in relation to land, which may include compensation for cultural loss by indigenous groups. 

Cultural loss may arise in many forms such as travelling over and camping, hunting, gathering and fishing and conducting ceremonies and rituals on the acquired land and the loss of the ability to look after and speak for culturally significant sites and areas.

The paper outlines the findings of a research project to identify and classify forms of cultural loss and to develop a process and valuation method for quantifying compensation.

Major unexpected events have substantial effects on the volatility of listed real estate (LRE) investments, the most recent ones being the Covid-19 pandemic and the Ukraine conflict. Societal changes, such as the rise of e-commerce and remote working, are also affecting how we use buildings and hence how LRE prices react to shocks, these impacts often differing across property sectors and countries. Although listed and direct real estate have common economic drivers, it is well known that LRE reacts more sharply to shocks than direct real estate; this frequently being considered a drawback of LRE by investors. However, little research has investigated whether the higher volatility and liquidity of LRE can lead to higher risk-adjusted returns stemming from tactical portfolio rebalancing. This paper seeks to understand better how the volatility of European LRE across sectors and countries has changed over the period 2007-2022 and how this information can be incorporated in a dynamic portfolio framework. We investigate the impacts of rule-based tactical rebalancing on the performance and composition of a listed real estate portfolio. Finally, we examine the effects of such reallocation on the composition of a mixed-asset porfolio containing LRE. Specifically, this paper attempts to investigate the following research questions:

• How has the volatility of European LRE across sectors and countries changed over time?
• Can rule-based tactical rebalancing exploit changes in volatility to generate excess risk-adjusted returns?
• What are the implications of LRE tactical rebalancing on the composition of a mixed-asset portfolio?

UK housing policy has focused on restricting investment behaviour and boosting the homeownership rate in recent years. This article estimates the effect of a 3% additional transaction tax (stamp duty land tax) on the Buy-to-Rent, known as Buy-to-Let (BTL) market in the UK. We find evidence of average price decreases but with the trend of immediate increase after policy announcement and decrease rapidly after the implementation date. The additional stamp duty land tax (SDLT) not only affects the transaction price but also leads to a significant drop in BTL transaction volume and an increase in the rental price, showing that landlords compensate their loss in investment by increasing the burden of tenant and indirectly affecting the ability of tenants for owning a home.

The housing sector consumes a large amount of energy and natural resources. The impact on the environment during a building’s lifetime is substantial. In order to handle these challenges, the United Nations adopted the 2030 Agenda for Sustainable Development with the Sustainable Development Goals (SDGs). Particularly digital technologies play a key role in achieving the SDGs as they offer benefits for individuals, organizations, and society in the future. However, to successfully implement digital technologies, the society and its attitudes towards digitalization have to be considered. To date, in housing, little is known about the psychological antecedents and the impact of affinity for technology regarding the purchase intention of digital housing.

By using the theory of planned behaviour (TPB), this study aims to better understand why consumers tend to purchase digital housing. Therefore, the effects of attitudes towards the behaviour, subjective norm, and perceived behavioural control on the purchase intention of digital housing are examined. Furthermore, the TPB is extended by incorporating affinity for technology as a moderator variable.

Based on literature research, a survey was developed and n = 748 private households in Germany participated. Partial Least Squares Structural Equation Modelling (PLS-SEM) is used for the analysis since it is particularly suitable for applied science because it makes it possible to test hypothesized relationships. To empirically evaluate the derived hypotheses a two-step approach is applied. In the first step, a base model including attitudes towards the behaviour, subjective norm, perceived behavioural control, and purchase intention of digital housing is run. In the second step, the moderation analysis for affinity for technology is conducted.

The results emphasize the importance of subjective norms and perceived behavioural control on the intention to purchase digital housing. Moreover, affinity for technology positively moderates the effect of attitudes towards the behaviour on the intention to purchase digital housing. The study provides important implications for theory and management practice in order to realize a more digital and greener future in housing. As society’s affinity for technology grows the intention to purchase digital housing increases. Consequently, digitalization and sustainability must be integrated in order to meet the requirements of the SDGs in the future.

During the pandemic time, the UK government introduced Stamp Duty Land Tax (SDLT) rate reduction to stimulate the housing market. Reduced Stamp Duty Land Tax (SDLT) rates would apply for residential properties purchased from 8 July 2020 to 30 September 2021 inclusive. According to the policy, the temporary nil rate band of £500,000 would be in place until 30 June 2021, then extended to 30 September 2021. Thereafter, the nil rate band would return to the standard amount of £125,000 on 1 October 2021. The purpose of SDLT reduction was to support the housing market and the jobs and businesses which relied on it. At the same time, it would lower the transaction costs of moving home to maintain the liquidity of the housing market. Evidence suggests the stamp duty holiday made a positive impact on the property market. In this research, we investigate how the tax temporary reduction affects housing prices in the UK, using all housing transactions in the UK from March 2020 to December 2021inclusive, three months pre and post-SDLT cut with quasi-experimental variation from reduction. We also examine whether the effect was consistent across all price bands.

The city centres in Europe and Germany are in the process of structural change, which is questioning the current real estate value-creation concepts, especially the mono-functional focus on retail. Structural change is caused by megatrends such as social, technological and ecological change. The corona pandemic has further pushed and consolidated the change in citizens' habits. The change manifests itself, among others, in lower footfall and declining turnover. Vacancies are already on the rise in small and medium-sized towns as well as on the outskirts of large city centres. For owners of inner-city properties, it is existential to adapt the inner-city properties to the new environmental situation. Failure means further increases in vacancy rates, falling rents, trading-down effects and the permanent decline of the capital tied up in city centres. The current discourse sees numerous fields of action in the inner cities. At the core is the need to enrich and balance the diversity of functions. More housing, urban production, strengthening of communication and integration Climate adaptation/climate protection, to name a few. The aim is to increase resilience through numerous functions and uses, to make the inner city more exciting and attractive for citizens and generally to reverse the threat of trading-down effects. Currently, the perspective and interests of property owners are rather secondary in the debate. Accordingly, there is hardly any evidence of concrete mixes of uses in the properties that guarantee an equal balance of interests between the benefits of the citizens and the capital preservation of the owners.

A representative survey of 1,000 citizens will be used to fill this research void. The resulting database is intended to help owners of large-scale retail properties, in particular, those with a strategic and long-term approach, to find sustainable concepts for follow-up use that ensure the long-term preservation of the value of the capital tied up in the properties by providing needs-oriented real estate solutions that make a visit to the city centre an experience for citizens, while at the same time ensuring that the transformation is economically feasible and the long-term preservation of the value of the capital bound up in the properties. Since structural change is an international phenomenon, the insights gained in the survey of German citizens can also open up development perspectives for properties in other European countries.

The results of the survey define the room for action for real estate owners and thus lay the foundation for the evidence-based and sustainable transformation of inner cities that brings added value for all stakeholders involved.

Energy transition from fossil fuels has been a key focus of  governments post Paris Agreement. In 2019, the UK government legislated a net zero emissions target by 2050. Existing buildings account for roughly 40% of the energy related global CO2 emissions, of which nearly 30% comes from operational carbon. Given their contribution to total greenhouse gas emissions, residential buildings operations’ impact has received increased attention with targeted legislative frameworks at the national and supranational levels. A key aspect of the net zero transition are heat pumps as the alternative to fossil fuel, particularly in climates with limited solar energy potential. This paper investigates the heat pump take up rate by new dwellings across local authorities in England and Wales. In addition to documenting the perceived low take up rate, we analyse the factors determining the nuanced dispersion of these rates. We conclude that further action is needed in heat pump take up if they are to constitute a key factor in reducing CO2 emissions to help the UK government achieve its net zero ambition by 2050.

Triple-net lease (NNN) agreements require tenants to pay all property operating expenses in addition to rent and utilities. These expenses include real estate taxes, insurance, and maintenance, significantly relieving the landlord of a property’s operating burden. Given that much of the property’s operating responsibility rests with the tenant, NNN leased properties collect comparatively lower rents than those with conventional leases or other net leases that corresponds to the lower amount of risk assumed by the property owner.  Extant literature provides little evidence on the impact of holding triple-net leased property portfolios on Real Estate Investment Trusts (REIT) performance. In this paper, we examine the relative performance of Equity REITs holding NNN leased property portfolios and the relationship between REIT NNN property portfolios and firm operational efficiency, profitability, and value. We believe this examination is relevant given the nature of REITs as pass-through identities designed to pay out 90% or more of earnings as dividends where the goal of the REIT manager is to efficiently and profitably operate real estate assets. We explore whether the strategy of holding NNN portfolios improves or sacrifices REIT performance and shareholder value.

In this paper we examine the impact of various housing policies from the perspectives of planners, investors, developers, public officials, and other stakeholders. Policies include those encouraging home ownership, help for first-time buyers, disincentivising housing as an investment asset, encouraging Build-to-Rent, and local authorities’ increased propensity to develop and invest in property. The focus is primarily on London, with more than 100 stakeholders having been interviewed for this research. We investigate developers’ and investors’ contributions to policymaking and discuss how to maximise the likelihood of successful policy implementation.

Alcohol outlets are ubiquitous in UK urban centres and play a significant role both in the development of the built environment and in how people interact with urban spaces. There is a well established literature focusing on the health and social outcomes of the density and distribution of alcohol outlet. However, there is a clear research gap in examining how socioeconomic and urban characteristics impact the density and distribution of alcohol outlets. Factors relevant to the study of the density and distribution of the alcohol outlet industry are diverse but can be fitted into two main categories: variations in the rate of change in alcohol outlets densities; and variations in the change in market share between alcohol outlet typologies. This research takes a longitudinal approach applying panel count regression analysis techniques to model adaptations in the alcohol market across two UK cities, Manchester and Nottingham. Manchester and Nottingham make representative study areas for the UK context, with wide variation in urban density and socioeconomic characteristics. A novel dataset is employed that contains spatio-temporal counts of alcohol outlets across the study areas for the years 2002 to 2020. A high specificity of alcohol outlet characteristics allows for the creation of niche outlet typologies, allowing for the granular analysis of the wide range of sub-markets reflecting the market heterogeneity.

This paper examines the relationship between the Sustainable Finance Disclosure Regulation (SFDR) and private equity real estate (PERE) fund returns as measured by the IRR. The SFDR, which has been effective since 2021, applies to financial entities operating within the European market and is intended to provide market participants with a comprehensive understanding of the sustainability strategies and risks of financial products. While existing literature primarily focusing on the impact of voluntary sustainability disclosure (e.g., through certifications or reporting standards), this paper addresses a significant research gap by conducting a panel regression analysis on approximately 36 funds and examining the effects of different SFDR classifications on fund returns. The results are validated through a J-Curve analysis, which is constructed using cubic spline interpolation. A priori, the SFDR classification of Article 8 and 9 funds is supposed to be accompanied by higher costs compared to Article 6 funds. The findings indicate that a higher classification under the SFDR is not associated with detrimental effects on funds’ performance. Additionally, the results suggest that either upfront costs, such as due diligence on the acquired properties, do not differ significantly or higher costs are amortised after stabilisation of funds’ cash flow. This study, to the best of our knowledge, is the first quantitative examination of unlisted real estate fund performance under the SFDR and provides unique insights into J-Curves of PERE funds.

The paper seeks to consider the use of the stories behind cases and a Socratic teaching method to engage non-law students.  Although often perceived as intimidating, and not a standard method of law teaching in the UK (which has never adopted the US tradition), the Socratic method can be seen to appeal to non-law students’ overarching desire for ‘relevance’.  

The author has taught law in an English university for over 20 years to real estate students on full time Bachelor’s and Master’s programmes, to degree apprenticeship students whose main interests lie in business and working life rather than theory and textbooks, and also CPD programmes for a range of professions, but largely in legal subjects for those in the real estate sector (valuers, land agents, estate agents and the like).

The paper will explore the development and theory behind the Socratic method including the considerable criticisms and its fall from fashion in US law schools. It will explore (through reference to experience and to empirical research conducted with a range of students) perceptions of law, and will share practical ideas of how complex legal matters have been introduced through a contextual coverage of case law and the perceived value Socratic style classroom activity.

The paper will have relevance to lecturers and trainers, and also to practitioners in evaluating their own approach to legal knowledge and understanding.  The paper seeks to impart an appreciation of the transferable skills which legal education can help develop in property professionals including analysis, clarity of thought and higher level reading.

This paper examines the storytelling imperative for professional practice of valuation reporting.  Drawing on semi-structured, in-depth interviews with practicing valuers in New Zealand, the paper advances scholarly efforts to position storytelling as central to the enactment of effective valuation reporting behaviour.  The paper begins by explicating the two core aspects – art and craft – of organisational storytelling advanced in literature, as a basis for understanding how valuers articulate the case for (or use of) storytelling in valuation professional practice.  Participants discourse suggests an important and multi-dimensional role for storytelling as a tool for improving the quality of valuation reporting, emphasizes the need for accurate, balance, clear and flawless stories in valuation reporting, and points to the role of deep market knowledge, multimodal tools, and good cooperative relationships as potential (dis)enablers for understanding the stories.  The paper also reflects on the intersections and departures between organisational storytelling and the practice of storytelling in valuation reporting and offers some suggestions on how storytelling can be integrated into valuers’ training and professional development.

The immersive nature of Virtual Reality (VR) might help users gain a better understanding of possible workplace concepts because laypeople are not used to imagine spaces based on floorplans and example pictures only. For the study a VR-tool with different photorealistic workspaces will be developed that allows to change aspects (furniture, colours, plants, etc.) instantly. Data collection will be embedded in real workplace strategy projects of an industry partner. During focus group-workshops 100+ participants will complete a pre & post activity survey to assess their personality and preferences as well as their VR-experiences. It is expected to find that VR helps office users to broaden their understanding of space options and their impacts on work and emotions. Further-more, the research will help to understand space preferences related to personality traits.

Sustainable and energy efficient homes in Australia are much needed in the objective to meet carbon targets and create sustainable homes that can ensure a resilient future. Despite an extensive amount of research, market implementation has been slow due to a limited regulatory regime and limited engagement by home builders. Many builders claim consumers have little interest and are not willing to pay, despite a number of consumer studies finding the opposite. A possible barrier is the communication between consumers and builders about sustainability and energy efficiency. Consumers typically have limited understanding of the home building process per se, let alone understand the nuances of sustainability and energy efficiency considerations for a new home. Thus their trust is in the builder to provide them with the information needed and offer appropriate products. The question of the research is, what kind of information is available and what is the quality of the information provided, particularly through key communication channels like websites, blogs and social media? 

This research used content analysis techniques to investigate the online communication channels of 23 New South Wales (Australia) volume home builders initially in 2020 and again in 2022. 

The study found the level of content and its quality to be non-existent or quite low, leaving consumers to trust that simple assignations that the home is sustainable, without explanation as to how it is more sustainable or energy efficient.  In the repeat analysis of 2022 the industry appeared to have retracted much of the limited sustainability and energy efficiency messaging across their online platforms. The research identified opportunities for the volume housing industry, to enhance their communication capabilities and provide meaningful information that may assist in generating the change required.

In this paper, the most influential variables that affect the liquidity (inverse of time on market) of rental apartments are analysed empirically for the city of Munich. Therefore, the random forest machine learning technique based on decision trees is applied. Micro data for more than 100,000 observations on the residential rental market from 2013 to 2021 is used. As a first step, the main housing, social and spatial predictors of liquidity on the residential rental market are revealed. Results show that the price as well as the size have the greatest impact on the liquidity of residential apartments. From the geographic variables the distances to the next hairdresser, bakery and school are most important. Second, this paper analyses how the survival probability of residential rental apartments responds to these major characteristics. And third, the partial dependency of cost and size on the survival probability is revealed. Hence, the segmentation of dwellings generated by the decision tree methodology results in a deep and profound understanding of the driving factors of liquidity. Although the decision tree methodology has been applied frequently on the real estate market for the analysis of prices, its use for examining liquidity is completely novel. To the best of the authors’ knowledge this is the first paper, to apply a decision tree approach to liquidity analysis on the real estate market.

Traditional economic theory applied to the field of real estate asumes a real estate cycle with regular patterns, especially up and down cycles. A certain minimum of economic stability is enabling factor for the business model of most real estate enterprises. Disruptive events hovever may challenge the paradigm of cycles that can be anticipated. This may imply a halt to economic activity. The current depression in transaction activity in Europe underlines reaction to uncertainty when investors are unsure about the „new normal“, hesitant to pursue transactions.

Recent example of disruptive events is the war in Europe. Uncertainties and disruptive events in real estate markets trigger the desire of investors to allocate funds to other markets that offer the stability that is missed in domestic markets.

For many decades US real estate markets have been considered a hedge against risks in domestic markets for various investor groups. Examples include outflows from countries in Middle and South America, for instance channelled into Florida real estate. Recent years also saw capital inflows from Asia into major US metropolitan markets. The current situation has reinforced the attention of German fund managers to look for geopolitical risks and other uncertainties when finetuning global asset allocations.

The paper looks at the motives and decision-making process for German real estate funds in deciding on US investment allocations. Key questions are: Which factors drive decision-making when allocating capital to US real estate markets? Which factors are expected to impact the future volume of cross-border transactions of German real estate funds into US markets?

Over the last few decades, there has been a consistent upward trend in global real estate investment, driven by global economic reforms and the emergence of an integrated global financial market. Previous studies have identified diversification benefits and the possibility of obtaining higher returns on investments as rationales for international real estate investment. However, there is still a paucity of literature examining the macroeconomic and institutional determinants of foreign real estate investment. In this paper, we use panel data models to determine the impacts of a range of those factors, such as infrastructure development, financial development, exchange rate risks, and interest rate on foreign real estate investment. The linkages between international volatility, institutional governance development, property regulations, and foreign real estate investment are also considered. Drawing on information on real estate sector transaction activities over 2003-2021 from the S&P Capital IQ Pro database and employing a range of econometric methods, the analysis finds robust economic growth, a strong domestic financial system, higher transparency of global real estate and a strong governance regime boost higher foreign capital flows into real estate sectors. However, different dimensions of governance appear to have varying levels of influence. These results are robust to a number of alternative specifications and common estimation biases.

The financialization of the Parisian office real estate market has led office users to become tenants, leaving the propriety to some big foreign investors. The latter need to reduce as much as possible the vacancy rate of the building in order to maximize their rent and to obtain an added value on the sale. However, the pandemic with the spread of telecommuting has reminded tenants that offices must meet the needs of their employees who are the end users (Gupta.2022) in order to bring them back to the office for the sake of integration and employee retention. The location is a significant criterion to attract new talents (Florida and Adler.2019). The study of Business Location Decisions has highlighted the role of quality of life as a Business Location Factor (Glaser and Bardo.1991; Love and Crompton.1999), especially for firms of the so-called “New Economy”, whose main input is the knowledge instead of natural resources. Studying office location strategies inevitably requires an interest in the people who occupy them.

This study aims to assess which location factors are crucial for workers through a survey analysis. Whereas most of academic papers are based on business decision-makers at a regional scale to measure the quality of life, we want to study workers ‘preferences within the Parisian area at the neighbourhood scale in order to work on more specific local factors. To do so, we collect data from a representative sample of workers from Ile-de-France. In a first part, we want to assess the impact of the daily living concerns (public transports, safety, cost of living) and the quality of life (green spaces, visual image, atmosphere, entertainments, and environmental quality) on the satisfaction of employees about the neighbourhood where they work. Do amenities matter as much as firms think?  In a second part, we ask them about their remote work habits because they could induce a mediating effect on their location preferences. Can we suppose than remote workers and non-remote workers have different expectations about public transport accessibility or entertainments? In a last part, we ask them about their sociodemographic profile. We know that workers ‘preferences vary between the age, the family situation, or the level of qualification. Finally, do amenities matter as much as firms think? Maybe the best place for workers is in fact the one closest to their house…

We use self-reported estimations collected on an Internet platform to study the formation of housing price beliefs of sellers and buyers of the Paris region. Comparing the users’ estimates with real prices of transactions, we are able to evaluate how accurate they are in predicting the selling price and to identify factors that influence their opinion. We confirm the already studied upward bias of homeowners but bring a first evidence that buyers are unbiased. Our results confirm that market participants follow an anchoring and adjustment scheme to set their opinion on housing price. Users' beliefs are influenced by the results of the platform Automated Valuation Model, which acts as an anchor. Buyers are less influence by this reference point, and the more the sellers progress in their sale project, the less their opinions rely on the model estimations. Finally, the estimates of owners whose property has lost value since they purchase it are anchored to its purchase price and less correlated to the AVM results. We interpret these results as proof of an updating mechanism of the buyers’ and sellers’ beliefs along their search for a counterpart.

Before the Global Pandemic, the UK office sector was already changing as businesses required flexible and agile workspace due to the changing nature of work. Compulsory lockdowns during 2020-2022 quickly accelerated these changes in the way of working - employees were able to work from home, if feasible to do so and for a time ordered to do so. Reflecting this trend, there is now an emerging emphasis on creating spaces that support value-added activities that require people to once again meet and work together. There is a considerable amount of research being published on how the office building can cater for hybrid working. However, using a case study of leading real estate employers, this research project follows the employees as they work in new work formats. The initial findings reported in this paper help to understand how people are acting and responding to this situation. The intention is that in time this will allow a framework to be created for businesses planning their workspace, organisational change, and wider academic debate.

The environmental, social, economic, institutional, and regulatory contexts in which organizations operate are increasingly critical and demanding when it comes to taking ESG issues into account. Corporate governance had to adapt and become increasingly sophisticated. The innovative organization must attest of the performance of its governance mode, its business model, and its sound management of ESG issues by measuring the impacts, both positive and negative, of its activities and decisions. We are entering a new era, the one of social, climate and ecological governance. The challenge is to identify the limits of the perimeter and the scope of these impacts, including their relationships with the different organizational levels.

The overview of the academic and documentary literature on the concept of impact reveals its omnipresence in several frameworks and regulations, but also its importance in the development of major disclosure standards.  The study of the nature of the impacts that must now be taken into consideration shows the preponderance of the environmental dimension, but also the complexity linked to the socio-economic dimension. In the real estate sector, the evaluation of the two-way impacts between the building and its natural and human ecosystem requires the integration of a multitude of research fields such as environmental psychology, social entrepreneurship, urban design, social life cycle analysis, etc. Indeed, the assessment of the impacts on the various stakeholders of the organization is multi-faceted, especially when it comes to assessing well-being. Their involvement seems essential for this exercise.

Facility management automation presents facility managers with innovative ways of ensuring functionality of the built environment through the integration of people, place, process and technology. Improved facility management practice through the use of automating systems will not only prevent economic and functional obsolescence of high-rise buildings. It will also ensure that investment in high-rise buildings is well preserved. Users of high-rise buildings will have little or no worries about break down of facilities, building management, space management, cleaning, security and other facility management activities if automating tools and systems are selected and operated with care and dedication. This study examined the willingness of facility manager to adopt automating systems in the facility management of high-rise buildings in Lagos Nigeria. The study adopted a survey research approach, administered structured questionnaire on facility managers of identified commercial high-rise buildings in Lagos metropolis. Conjoint measurement was used to analyze the result. The study revealed that majority of facility managers are willing to adopt automating systems. It then recommends the need to train and retrain staff of facility management staff   on recent and useful automating systems. 

This research project seeks to understand the relationship between gender, progression and promotion within transactional roles in the Real Estate Industry and also seeks to explore the current experience of women working within transactional teams, aiming to provide guidance for real estate firms on how they can support more females to progress to senior positions within Real Estate Transactional Teams.

The number of women entering surveying firms has steadily increased in recent times (RICS, 2022) and this increase is reflected within transaction teams. However  the number of senior females within transactional teams is not reflective of the wider real estate industry, showing an upward mobility limitation. There seems to be an indication that this may be mainly because of a masculine culture found within Real Estate and the effect and impact of this is significantly entrenched, even if not completely visible.

This paper will primarily seek to understand why this is, and then seeks to understand why women, specifically within transactional teams and departments, are even less likely to progress or be retained.

This research project will initially provide a review that analyses themes of existing research within real estate and associated industries such as construction and finance. Topics such as policies that promote increase female representation within Real Estate firms, Female representation on Leadership boards, as well as themes relating to lack of female role models, flexible working, bias and fee-earning culture, will be addressed. To conclude, an analysis of the factors preventing women from progression to senior roles will be presented.

Primary research has already been conducted dating from 7th June 2022 and spanning two weeks. It was conducted via a survey to 65 respondents working within the Real Estate Industry. Semi-Interviews were also conducted with senior members of transactional teams, both female and male, and this allowed for a more in-depth appreciation of findings.

These initial findings have pointed to several fundamental reasons for the drop-off of women between graduates and senior management mainly relating to life commitments; unequal parenting expectations, masculine workplace culture including networking and male banter, lack of senior female role models. It also shows that women within transactional teams do not experience significant negative bias during the recruitment/hiring process, and there actually being a significant positive discrimination towards females in the hiring process. With regard to progression and promotion specifically it shows that women mainly require more experience or qualifications in comparison to men to be promoted.

I provide a first empirical analysis of the intracity effect of Working From Home (WFH) on business districts in the Paris metropolitan area. Taking advantage of the Covid-19 crisis as a natural experiment and implementing a difference-in-differences strategy, I find that WFH has already had a small but perceptible negative impact on office occupancy, which tends to grow over time. Interestingly, my results show that this effect is stronger the further away from the centre, indicating the firms' strong preference for high quality amenities and accessibility in this new WFH environment. Furthermore, using a similar methodology, I explore the possible indirect effect of WFH on local consumption services as another implication for business districts.

Office buildings are undergoing massive structural change: In view of a changing working world and of increasing competition from work-from-home and third workplaces, they must meet rising user interests, also as a resource in the war for talent. Under the impact of climate change, the ecological transformation of the building stock is essential due to its particular significance for greenhouse gas emissions. At the same time, office buildings should continue to fulfil their investment function on the capital markets. 

The discussion about the transformation of office buildings has so far taken place academically among experts. The opinion of those most directly affected, the office workers, has so far remained unheard. Yet their opinion could be of particular importance due to the necessary acceptance of possible solutions for resolving any conflicting goals between user, investment and sustainability perspectives. 

This study fills the gap and examines stakeholders' trade-offs between the three perspectives. The aim of the study is to investigate office workers' preference for the requirements from the three perspectives as well as the influence of different personality traits, such as environmental awareness or financial literacy, on the trade-off process. For this purpose, a choice-based conjoint analysis was conducted among 1,000 German office workers.

The results represent the first measurement of the importance of office workers' requirements for office building from the three perspectives and underline the importance of personality traits for respondents' ratings. The findings highlight directions for further research and provide important implications for business practice around office building transformation.