Urban problems in rural small towns in Korea are manifested in various forms, such as the aging of the population, the smart gap, the departure of young people, and the inefficiency of urban space. Accordingly, the state and local governments are presenting various solutions to solve the above urban problems. Among them, the Ministry of Land, Infrastructure and Transport conducted a public competition project to develop and demonstrate technologies such as smart common cultural space creation, smart education support, smart crime prevention and safety, smart healthcare, and smart information plaza as a way to create a smart city. Based on the project selected in the 2021 public contest, this study collects the opinions of actual residents through the operation of a living lab before the actual smart solution space construction, and based on this, secures the direction for space composition and curriculum development, and applies local customized applications We tried to derive a method for To this end, a living lab was operated prior to the establishment of a smart solution space, and various opinions were shared and collected through the participation of experts in each field, local residents, and universities. Based on the convergence results, the present day problems and local issues of small towns were discovered and served as a test bed to solve them. In addition, in order to further secure the justification and feasibility of building a smart space, the opinions of local residents were actively collected through a total of three surveys. As a result of living lab and governance results and survey analysis results, the necessary services and solutions were built in the order of smart crime prevention, smart healthcare, convenience for living, education support, smart information plaza, smart shelter, and multi-purpose studio. Through this, it was possible to build a space that maximizes the sensibility of actual residents.

This study presented a methodology for how to build a resident-led bottom-up development model rather than the central government-led top-down development, and carried out actual demonstration. It is judged that this study can be provided as basic data to some extent in the design of a smart city customized for each region in the future to spread a similar public offering project. Smart cities and proptech following the 4th Industrial Revolution are an irresistible trend, and accordingly, they will become more sophisticated and concrete. Therefore, it is hoped that various results for actual verification through demonstration projects can be drawn, rather than looking at smart cities, living labs, and smart solutions only from an academic point of view, and various policy implications can be derived.

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 25 000 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 indices, 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.

Housing affordability is one of the most pressing issues in urban areas. During the Covid 19 pandemic, this problem spread to surrounding and more rural areas due to changing demand dynamics. At the same time, the economic downturn has exacerbated challenges for certain tenant groups.

Based on an adapted Social Business Model Canvas, we are working with student groups on an interdisciplinary project to look at the entire affordable housing value chain from both the user perspective and the perspective of private and public housing companies, i.e., from design and planning to construction, operation, and redevelopment. The aim is to identify the main variables for achieving affordable housing prices, the interdependencies between them and their respective manifestations in Germany and five other European countries: Netherlands, Italy, Austria, Denmark and the United Kingdom. Based on this, we derive limits and drivers of value creation as well as potentials for the realization of affordable rents or housing costs.

The Affordable Housing issues examined in each country are:

1. Definition of 'affordable housing' and characteristics, needs and quantity of the most relevant user groups.
2. Building conditions, structural-functional designs, and construction costs for Affordable Housing.
3. Characteristics and business models of investors or providers of affordable housing.
4. Legal framework / regulation for affordable housing (outside of building law).
5. Tax framework and subsidy options for investors and users.

In this presentation, the findings on business models as well as legal and fiscal framework conditions of Affordable Housing are presented. In addition, the findings on business models as well as legal and fiscal framework conditions of Affordable Housing are outlined.

This paper, part of a more comprehensive research line, aims to discuss how the covid-19 pandemic has affected the demand in the real estate market in Padua. Padua is a medium-sized city that represents the typical Italian town.

The authors have been investigating the real estate market in Padua for a few years, collecting information on the buildings on sale from related selling websites. This data collection procedure has been accomplished with the help of an automated web crawler developed in Python language.

For this reason, the authors are now able to compare the real estate market in Padua at different times. In particular, two databases are here put into a detailed comparison. Database A dates back to 2019 (II semester), capturing a pre-Covid-19 scenario, while database B is dated 2021 (II semester), representing the actual situation.

First of all, two forecasting algorithms to predict the market value of the properties as a function of their characteristics are developed using an Artificial Neural Networks (ANNs) approach.

ANNs are a multi-parametric statistical technique employed to forecast a property's market value. The input neurons of the network, i.e. the independent variables, are the buildings' descriptive features and characteristics, while the output neuron is the market value, the dependent variable.

ANN(A) is developed on database A, and ANN(B) is created on B. The comparison of the two forecasting functions represents the differences in the demand after two years from the first Covid-19 alerts.

Since ANNs are a multi-parametric procedure, this methodology isolates each attribute's singular influence on the forecasted price. It is, therefore, possible to understand how the preferences of the demand have changed during the pandemic. 

Some characteristics are now more appreciated than before, such as external spaces, like a terrace or a private garden. Also, systems and technologies seem more appealing now than before the pandemic, for example, the presence of optical fibre or mechanical ventilation. Moreover, wider building typologies are more appreciated now, like villas, detached and semi-detached houses, or farmhouses. But, on the contrary, other characteristics are less appreciated. The location, for instance, is less influential than before in price formation. 

These changes in preferences can be attributed to the new lifestyle since new habits have been produced after the lockdown experience and new smart working schedules that the pandemic has led to.

Due to the COVID-19 pandemic, the indoor air quality of school buildings is a much-discussed topic. It is important to know whether indoor climate of buildings influences the physical and mental situations of users in these buildings, and with that, performance of users. 

The aim of this study is to establish a direct link between users’ health, well-being and performances, and indoor air quality in a case study that focuses on the ‘Marie Kamphuisborg,’ a building owned and used by the Hanze University of Applied Sciences in the Netherlands. The study was conducted by using a mixed methods approach, consisting of a literature review, surveys among students and teachers, and interviews with facility management staff. It has tried to measure the degree of well-being of users related to the indoor air quality in this building. 

Results of the literature review showed that poor indoor climate leads to a negative influence on concentration of users due to discomfort and weakened physical and mental health of students, in the end leading to lower performances of users.

The survey showed that students as well as lecturers experienced a lower performance in situations of a poor indoor climate in classrooms. Both indicated that they develop physical complaints during a lecture in a classroom with poor indoor air quality. Lecturers tended to give a lower and insufficient grade to the indoor climate of the Marie Kamphuisborg compared students, who rated the building sufficient.  

Expert interviews showed that complaints about indoor climate only have to do with classrooms without windows in the inner circle, the so called M-wing, of the building. Outcomes from the interviews show that complaints, both from teachers and students are related mainly to high temperatures, high Carbon dioxide and low oxygen levels. These complaints mainly occur in the warmer season. Complaints about noise levels and light intensity are very rare. In addition, the experts argued that other aspects can influence the well-being for users in buildings, such as green walls, wall decorations with recognizable sceneries, colors, friendly staff at front offices and a proper canteen.  

We can conclude that both teachers and students assess classrooms in the M-wing as negative for their well-being and, with that, for their performances. This is in line with the findings of facility staff members of the Marie Kamphuisborg and confirmed by prior research.

Purpose: The purpose of this research is to evaluate the impact of the newly build Doha Metro System in Qatar onto property values using a unique data set. We compare property values at two significant points in time during the delivery process of the Doha Metro Red Line: Announcement stage and construction phase.

Methodology: To our knowledge this is the first quantitative study using panel data collected from the Doha Ministry of Municipality on property values. The data set was compiled using Geodata and classified data provided by the Ministry. We use attributes from established Hedonic Pricing Models as well as spatial characteristics (distance to metro). We amend the econometric model by comparing the impact on and respective deviation on land values at two significant points in time, announcement of metro and end of construction, using statistical methods.

Findings: In contrast to the expected we find that there is a positive effect on land values in the 500m to 1.000m distance band in comparison to the 0m to 500m band to new Metro stations in Doha. We also find that the announcement phase has a significant positive impact on property values in Doha. This contrasts with the related work of Grass (Grass, 1992) or Damm et al. (Damm David, 1980). 

Originality and Value: The meta-analysis on “Impact of Railway Stations on Residential and Commercial Property Value” Debrezion et al (Debrezion, 2007) finds mixed results ranging from negative to positive impact on property values due to spatial characteristics, temporal effects, and methodology. For the first time the impact of Rail Infrastructure on Land Values in Qatar was analysed. We found that impact on Land Value is correlated to specific project live cycle phases and to complement Hedonic Pricing models with its explanatory power.

This study examined measures for applying proptech to provide property services to both smart cities and smart villages from the perspective of national land and space management. Proptech had been limitedly implemented in the field of urban property. In this regard, this study suggests that a range of regional proptech applications should be expanded to non-urban regions to ultimately provide proptech-based property services to all of South Korea. To this end, this study analyzed major characteristics of sub-projects of the smart challenge project executed by the Ministry of Land, Infrastructure and Transport. It also examined project execution strategies by classifying smart challenge projects selected for application to small local cities in rural areas as local models led by local governments and base models led by branch offices of the Korea Land and Housing Corporation. According to the models classified, the study analyzed cases of proptech application in the property industry regardless of regional hierarchy to enhance daily living services for residents, reduce the smart information gap, expand the smart market, create new industries, and ultimately change national land and space under the smart city system.

Efforts to equip office buildings with cutting-edge technology to measure and improve its energy performance have been going on for years. However, not only the building itself consumes energy, but the occupant influences this as well, i.e., their presence, interaction with and movement through the building. Sustainability studies have suggested that the solution to improving environmental sustainability of office, from the perspective of behavioural social science and environmental psychology, would be the transition to more user-centered smart real estate. In the Building and Environment field, similar approaches have been introduced, that occupant-centric building design and operation are also a solution for capturing occupancy and occupant behaviour.

A multidisciplinary literature review is conducted. Firstly identifying the theory, connotation, and application of occupant behaviour in both social science and engineering science respectively, e.g. Environmental real estate user behaviours versus Occupant adaptive behaviours. Secondly, the review identifies the most suitable theory from both scientific field which complement each other and enhances the interdisciplinary theory's synergy process.

This systematic literature review thus identifies the relevant knowledge of occupant behaviour in both fields and develops a theoretical framework for the term "Sustainability related occupant behaviour", as a catalyst to the synergy and knowledge exchange process between social science and engineering science.

Data-driven machine learning algorithms have initiated a paradigm shift in hedonic house price and rent modeling through their ability to capture highly complex and non-monotonic relationships. Their superior accuracy compared to parametric model alternatives has been demonstrated repeatedly in the literature. However, the statistical independence of the data implicitly assumed by resampling-based error estimates is unlikely to hold in a real estate context as price-formation processes in property markets are inherently spatial, which leads to spatial dependence structures in the data. When performing conventional cross-validation techniques for model selection and model assessment, spatial dependence between training and test data may lead to undetected overfitting and over-optimistic perception of predictive power. This study sheds light on the bias in cross-validation errors of tree-based algorithms induced by spatial autocorrelation and proposes a bias-reduced spatial cross-validation strategy. The findings confirm that error estimates from non-spatial resampling methods are overly optimistic, whereas spatially conscious techniques are more dependable and can increase generalizability. As accurate and unbiased error estimates are crucial to automated valuation methods, our results prove helpful for applications including, but not limited to, mass appraisal, credit risk management, portfolio allocation and investment decision making.

The retailing industry in the UK is undergoing an unprecedented level of structural change. The impact on retailers, seen through administrations, CVA’s and redundancies has often dominated headlines, along with directly linked impacts on local economies. Less attention has, however, reflected on the implications for property investors and how they are dealing with these challenges. Understanding how and where owners are responding, what strategies they are pursing - are they innovative or tweaks on previous practice, and do they reflect ‘sticking plaster’ approaches or something more robust and durable? - is critical to understanding where the retail market goes from here. 

This paper, based on a wider study covering various aspects of the transformation of the retail property market, used a qualitative research approach generating primary data through semi-structured interviews across a range of real estate professionals. The findings span the period prior to and during the first year of the Covid-19 in 2020. It examines the practical response made by retail property owners/managers in adapting to the fundamental transformation in the retail sector. These range from mitigating short-term risk through greater use of temporary tenants/licensees, preparing standard, generic ‘white box’ offers to better capture the tenant demand that remains, greater exploitation of tenant mix to provide ‘the retail experience’ right through to changes of use for parts of buildings and withdrawal from the sector altogether. Some of these approaches can be considered innovative and many were occurring before the pandemic took hold. This paper identifies and evaluates the approaches taken by practitioners in response to the fundamental changes referred to, the success, or otherwise, of which, will only be judged, fully, in time.

How can the adaptation to the Enviromental, Social, and Governance (hereafter ESG) criteria contribute to the sustainability of the real estate value chain? Specifically, what lessons can we learn from key best practices in Italy? 

Although the introduction of ESGs dates back to the beginning of the new century, to date the goals associated with the Agenda 2030 have definitely boosted their importance. In this commonly acknowledged landscape, the real estate industry seemingly constitutes no exception (e.g., Deloitte, 2021). However, field research covering the topic in this industry still appears scant. Thus, as its main value, this research project aims to address the questions above through a multiple case study analysis (e.g., Lee and Saunders, 2017) investigating on the antecedents, processes, and outcomes of some key players in the Italian real estate value chain. Specifically, the best practices object of the case analysis will be chosen among selected firms currently members of Confindustria Assoimmobiliare, the leading Association of real estate players in Italy.

At its core, the project draws on the key economic role always played by the real estate industry both at national and international level. This industry, as known, currently witnesses new behavioral dynamics (e.g., Cafferata and Mari, 2015). For example, the radical changes occurring in the real estate value chain have considered important processes regarding the concentration (or outsourcing) of the construction activities; in turn, from a service perspective, these activities have grown in parallel with the equally significant growth of finance as their necessary support (e.g., Filotto et al., 2018). In fact, borrowing logics typical of the stock markets, emphasis has been increasingly put both on the economic nature of buildings and on real estates as purely investment assets (e.g., Morri and Mazza, 2013; Mattarocci and Pekdemir, 2015). Relatedly, another significant change has regarded the growing tertiarization of the advanced economic systems; in the real estate value chain, in turn, this change has contributed to the birth and development of new working processes and new professional roles absent before (e.g., Mari and Poggesi, 2014). 

Over time, all what we have introduced above has originated not only the relevant rethinking of the buildings’ specific features, but also the rethinking of the ways to use them. In particular, the overall organization of the construction activities has been radically modified, together with the nature of all the different players involved, at various degrees, in the production and selling of the good and services offered (e.g., Dawson et al., 2015). An evolved real estate production guaranteeing, at the same time, functionality, efficiency and (always increasing) attention towards the environment; technological and organizational innovation; demand and offer of services targeting a specific audience and real estate ownership: these are only some among the elements highlighting the ascending, in the real estate value chain, of the growingly diversified structure of the activities performed. From all this, there emerges an industry whose boundaries cannot be easily traced (e.g., Abatecola and Cafferata, 2014). In this industry, in fact, together with the traditional players, a growing amount of more specialized players is emerging, which physiologically impact on the industry’s co-evolving relationships (e.g., Abatecola et al., 2020). 

To date, in substance, we find ourselves in front of an industry made of players whose value chains result always more interdependent (e.g., Mari, 2011; Dobson, 2015). Relatedly, it is a matter of fact that, affecting the real estate value chain as a whole, the dynamics illustrated stress the attention towards the adoption of management processes oriented towards sustainability (e.g., Morri and Soffietti, 2013), these including ESGs. Thus, the results from this research project can be of interest both for real estate scholars and practitioners, with the latter also including policy makers. In particular, by comparing the similarities and differences from key best practices in the Italian real estate value chain, the project aims to develop a conceptual framework potentially useful to contribute to the extant literature on the topic. In parallel, the framework can result useful not only for cross-industry comparisons, but also as a “how to” guide for all those real estate players currently and prospectively committed in the adoption of ESGs. 

As the rise in property prices and influx in urban areas continues, affordable housing is increasingly becoming a scarce commodity. The German housing allowance (so-called “Wohngeld”) represents one prominent measure of securing affordable housing as low-income households are eligible to receive rent subsidies subject to their place of residence and rent conditions. This paper aims to analyze the effects of the housing allowance on the affordability of renting units for transfer recipients. For this purpose, rent data is utilized to compute the rent burden before and after transfers of the housing allowance. The results indicate that the German housing allowance was effective in significantly reducing the rent burden for transfer recipients, particularly in dense regions in Germany.

The emerging co-working space phenomenon provides a unique case for the knowledge spillover under the hybrid working style. We investigate the micro-location choices of co-working offices at the postcode district level. With the co-working space locations from 12 co-working operators in central London during 2009-2020, results from the conditional logit model show that, the co-working offices tend to choose the districts with higher industry diversity, a higher proportion of Culture and Creative Industry (CCI) business, or where the local industries contain more “teleworkable” job types. Meanwhile, co-working spaces tend to locate at those where start-up firms concentrated, echoing that the influences of knowledge spillover differ among firms’ life cycles. The results are robust when controlling the business strategies of co-working office providers, as well as the infrastructure, connectivity, and urban density at the local level. The findings cast light on the discussion of spatial clustering and micro-location choices with the case of sharing economy. It also shares substantial policy implications on the strategy design of boosting agglomeration benefits and productivity returns with co-working space.

Growing evidence shows that short-term rental growth in large cities across the globe—through e-platforms like Airbnb or Homeaway—has had an impact on the rise of housing prices and rents before the pandemic. 

The hypothesis in this paper is that housing prices and rents would have increased also in absence of short-term rental contracts due to the increased valuation of amenities.  An increase of inequality drives high-income demand toward homes with better access to attractive amenities. In this view, the presence of Airbnb is not the main driver for housing prices in these areas and—while statistically significant—it may be playing a marginal role overall. 

In order to test that hypothesis, a combined micro dataset is built based on five different databases in Spain: i) the 2011 Census, providing data about the housing stock at the neighborhood level including housing features; ii) a housing rental database, including information of (non-short term) rents  at micro level; iii) a transaction database,  yielding information about housing transaction prices; iv) a database containing geolocated amenities identified in each city, which allows to calculate the distances between every single house rented or transacted; v) and an Airbnb dataset, which provides information about short-term rental prices and frequencies at the  household level. The hypothesis is tested on the matched database. The estimation is undertaken for 2015 to 2019, the critical years where the short-term rental market experienced dramatic growth. 

The analytical process takes the Census district as the reference region.  In every district, the distances to main amenities are calculated by using the georeferenced feature of each database. We calculate a quality-controlled price index based on a hedonic model in order to avoid quality biases across districts. We control for lagged housing characteristics as of 2011, in order to avoid endogeneity issues. 

We model the long-term rental and property price increase controlled as a function of  distances to amenities and other key neighbourhood characteristics using a regression model inspired by the AMM (Alonso-Muth-Mills) framework. We also control for the short-term rentals market activity and compare the importance of each relative factor.

The empirical evidence comes from five different Spanish cities: Madrid, Barcelona, Valencia, Sevilla and Bilbao, Spain,  well-recognized cities with strong attraction due to their amenities and culture, and with both large housing price increases and short-term rental activity between 2015 and 2019.

Mobilizing social value in property development is complex, specifically under entrepreneurial urban governance settings where public and private parties have variegated interests, targets, and values. Essentially, social value has been the responsibility of the public sector. More recently, however, the property industry has been keen on including social value objectives into their agendas making both municipal and property market actors social value creators. Despite their endeavors, efforts in steering social value remain fragmented and insignificant. I argue that effectively steering social value in property development processes requires an integrated approach. This approach relies on two dimensions. The first is a common understanding of social value from key actors involved in the realization of property development. The second is their capacity to mobilize resources and collectively devise strategies for social value creation.

Using empirical data, this study examines the relationships between municipal and property industry actors and the institutions that drive them, to establish the extent to which social value is steered in four large-scale property developments in Amsterdam. Data is sourced from fifteen interviews conducted with municipal and property actors to identify perceptions, motivations, the resources deployed in aiding social value creation, and collaborative efforts made by these actors, as key characteristics integral to social value creation in property development. Furthermore, secondary sources including municipal reports, policy documents, and property market publications are studied to understand the framework municipal and property actors rely on. The aim is to gain insight into the barriers actors face and their implications on steering social value in property development.

Focussing on the firm level, this paper investigates the importance of specialist land promoters in the strategic housing land market in the UK. Planning data for the period 2018-19 were collected and analysed to estimate the proportion of large housing sites where outline consent was granted to specialist land promoters. The paper makes three contributions. Firstly, it maps the diversity of organisations that promote land through the UK planning system and demonstrates the diversity and definitional fuzziness of the organisations operating in the contemporary UK land market. Secondly, in contrast to prior studies which have grouped specialist land promoters with other types of market actor, it was found that specialist land promoters made a relatively small contribution to the supply of housing land in the study period. Finally, the paper shows that housebuilders accounted for a minority of planning consents for residential development, thereby suggesting that the degree of vertical integration in the land and housing development sector in the UK may be lower than presumed.

The purpose of this paper is to support a better decision in choosing the most suitable vacant office(building) to house new tenants. In order to achieve that a decision support tool (DSS) based on three methods is proposed. First, a discrete choice model (DCM) can estimate the future tenants' rent willingness to pay (WTP) based on the data generated with an online experiment. Second, a multiple-criteria decision analysis (MCDA) used a pair-wise comparison of building experts to establish the weight of criteria for a building transformation potential. Afterwards, an MCDA “multiplied” with the officially published cost approximation for five different levels of transformation.  Lastly, rent WTP from DCM and transformation costs from MCDA are included in a discounted cash flow (DCF). With this DCF we can rank many buildings that are available on the market and make their preselection. The possibilities of this tool have been tested in a case study. Although applying decision tools for the building transformation projects has been studied, this paper suggests a specific tool that supports the transition from office space to housing for young people.

Over time, the need for shelter, called housing, has been a challenge for mankind. Hence housing techniques have been developed and advanced from ancient ways of using mud materials and other earth with good building properties that could be applied by the builder, civil engineer or architect. However, the question remains unanswered if mud housing, wooden housing and open glass buildings are architectural masterpieces for green buildings or simply views of sustainable real estate? This study looks at different newer related designs that have been considered, applied and successfully utilised in the built industry. Some key qualities of the building materials used are also identified and presented. Recommendations were made towards the frontiers in achieving green buildings globally for sustainable real estate.

Investor sentiment has been empirically proven to have a significant contribution to price trend and stock make dynamics. With a focus on the Nigerian capital market, the study assesses the investor sentiment towards real estate stock (RES), aimed at ascertaining the presence, source and statistical significant of investor sentiment in the capital market. The descriptive statistics such as weighted mean score and the inferential statistical tools namely stepwise regression model and analysis of variance (ANOVA) is used to analyse the data. The study found the empirical evidence of investor sentiment towards RES, and the prominent sentiment induced measured is market news (4.1765). Meanwhile, investors' response to the good news was very high (4.2353) against the relatively low response to bad news (2.8824). Findings reveal that investors react to all the sources of news (3.1 ≤ WMS ≤ 4.0) but at vary levels, with news from pronouncement/announcement ranking highest, followed by market survey and media/press report with respective mean scores 3.6974, 3.6386 and 3.5588. Also, during the bullish period, 64.7% of the investors said they often took the decision to buy RES, similarly, 64.7% of them stick to the selling decision in the bearish market condition, whereas, under normal (balanced) market condition, 82.4% decide to hold the RES. The causal-effect analysis (stepwise regression) showed that pronouncement/announcement news with a positive beta (β) coefficient (.504) and a statistically significant p-value (P<0.05) has a statistically significant effect to explain variance in investor sentiment towards RES in the bullish market condition. While during the bearish period, the predictive power of all the sources of news were less significant (p>0.05) therefore lacking significant explanatory power. The study concluded that the evidence of investor sentiment towards RES in the Nigerian capital market signal its relevance in the assessment of the RES growth and market dynamics, with a need to take into consideration the market news especially the news emanating from pronouncement/announces on the exchange floor. The study, therefore, suggests the need to continually appraise the market news that could induce investor sentiment towards RES to complement the market underlying and technical analysis, ensure holistic review of RES performance and for informed investment decision when thinking of investing RES.

The aim of this paper is to address the problem of unavailability or inaccuracy of information on the quality of housing in the existing data sources. This may lead to obtaining biased results in the hedonic analyses of the market conducted for macroprudential and statistical purposes. We target this problem by proposing a supervised machine learning framework that base on the Wordscores algorithm. We try to answer the question, whether it is possible to reliably, automatically assess the quality of apartment, based solely on the textual description of its listing posted in the internet advertisement site. The accuracy of the method has been tested on the example of the Polish-language apartment sales and rental listings from 2019-2021. The obtained point estimates of the quality level show a high correlation with the human assessments. The results indicate that the application of the Wordscores algorithm gives 71% effectiveness in categorizing the apartments for rent into three quality groups: low, medium and high. For the apartments for sale, the effectiveness equals 64%. The study indicates that textual descriptions of apartments’ listings convey usable, yet most often unused information on the housing quality. The usage of the fruits of the method may lead to the increased accuracy of the performed analyses of the market, thus to its better understanding. The relative easiness of application of the algorithm and its high interpretability make the proposed method advantageous over the already developed, more econometrically sophisticated approaches.

There are numerous historic and monumental properties scattered all over the nooks and crannies of Nigerian Cities which are in ruins due to poor management and neglect. Despite the facts that historic buildings play vital roles as places of tourism and recreation thus enhancing economic development and growth of many countries yet many of such sites in Nigeria are poorly managed. The study which is exploratory in nature seeks to discover why such properties are not properly managed and what can be done to sustain such properties so that they do not go into extinction. The study adopts a survey approach and makes use of online surveys to reach out to Property Managers on the role they play in the management of such properties, barriers to effective management and likely solutions for sustainable management of such properties.

Institutional investors’ irrational familiarity bias can dominate their information advantage under adverse performance shocks to the home assets in their portfolios. Using data of U.S. REITs from 1993 to 2015 and the events of public non-REIT firm acquisitions, this paper investigates how institutional investors react to the geography-specific shocks to home assets. Equity REITs perform worse if they hold more properties in counties where the acquired non-REIT firms are located. If<br>the value of properties that a REIT owns in the target county increases by 10 percentage points, its abnormal return (alpha) decreases by 14.7% in one month after the acquisition announcement. This negative impact is more prominent if the REIT owns more offices than other types of properties in the county, or if the acquired firms are larger than other remaining public firms in the county. Also, the REIT’s return on asset and dividend yield decrease by 6.4% and 5.4% in the next quarter. However, using a difference-in-differences model, I find that institutional home investors are less likely than institutional non-home investors to lower the holdings of affected REITs after the acquisitions. This familiarity bias is stronger if the investors are closer to the affected properties or implement more active investment strategies.

A clear university management vision for sustainability in the campus built-environment by 2030, coupled with continual encouragement to bring about an impact for a better society, and unparalleled access to un- or partly demonstrated innovative technologies at universities, provide the ideal environment to use campus as a living laboratory. However, changing the university campus into a testing and demonstration platform of new technology poses a particular challenge to Campus Real Estate (CRE) management units. New technology and innovation are by nature undemonstrated over the longer term, new and risky when compared to business-as-usual, and stakeholders in the process of implementation do not have clear performance indicators for innovation implementation. Innovation implementation decisions on campus is therefore an inter-disciplinary balancing act. 

In this study, two approaches to identify the decision making criteria and decision points for innovation assessment and implementation were used. A multi-criterion decision making process, using an expert model and verification approach (Chorus, Ten Broeke, et al.,  2021) was used to develop a transparent model highlighting decision-making preferences for innovation implementation on campus. This process focusses on capturing and reiterating expert decisions for numerous innovations. However, due to the unique nature of innovations, the benefits of an expert model might be limited. We therefore also used the Preference-based Accommodation Strategy (PAS) method (Arkesteijn, 2019) to identify decision making criteria. The value of the PAS method is twofold, first, in its essential consideration of the broader requirements from four stakeholder perspectives in real estate management (den Heijer, 2011) which is especially important in inter-disciplinary decision making; second, in its systematic compilation of preference scores along the identified decision criteria. 

Initial indications are that innovations with clear added value in sustainability, education and research, which are simple, aligned to current systems and relatively easily embedded in current regulation, as well as representing low financial, construction and operational risks are preferred. However, both research approaches go beyond identification of the decision-making criteria by plotting the acceptable levels of alignment, benefit and risk as informed by a broad panel of stakeholders. The result is a first, clear view on the elements and preference points used in the balancing act which is necessary to facilitate a safe, thriving technologically advanced and innovative campus. 

Finally the two decision making models are assessed on their ease of use, attractiveness and effectiveness, elements identified by Visser (2016) for assessment of decision support tools.

Although many theories aim to explain IPO underpricing, initial-day returns of US REIT IPOs remain a “puzzle”. Considering equity offerings, literature provides several theories for the occurrence of underpricing. Theories on asymmetric information and value uncertainty based on Rock’s “winner’s curse” (1986) and Beatty and Ritter (1986) were among the first. Since then, the literature on REIT IPOs has focused on indirect respectively quantitative proxies for information asymmetries between REITs and investors to determine IPO underpricing. This study, however, proposes textual analysis to exploit the qualitative information, revealed through one of the most important documents during the IPO process – Form S-11, as a direct measure of information asymmetries. To our knowledge, this is the first study which applies textual analysis to corporate disclosures of US REITs in order to explain IPO underpricing. 

Specifically, we determine the level of uncertain language in the prospectus, as well as its similarity to recently filed registration statements, to assess whether textual features can solve the underpricing puzzle. To do so, we have gathered all prospects and data regarding firm characteristics, offering characteristics, third-party certification and market conditions for US equity REIT IPOs from January 1996 to December 2019. Our overall sample includes 114 IPOs for which we first clean the prospects to reduce linguistic complexity and facilitate the textual analysis procedure. Afterwards the level of uncertainty is derived using the Loughran and McDonald (2011) sentiment wordlist for uncertainty and the similarity is calculated by mapping the documents onto a vector space model which enables us to measure the similarity between two vectors using cosine similarity (Hanley and Hoberg, 2010; Brown and Tucker, 2013). 

In accordance with Ferris et al. (2013), we assume that uncertain language makes it more difficult for potential investors to price the issue and thus increases underpricing. Furthermore, it is hypothesized that a higher similarity to previous filings indicates that the prospectus provides little useful information and thus does not resolve existing information asymmetries, leading to increased underpricing. Incorporating these measures into an OLS, contrary to expectations, we do not find a statistically significant association between uncertain language in Form S-11 and initial-day returns. This result is interpreted as suggesting that uncertain language in the prospectus does not reflect the issuer's expectations about the company's future prospects, but rather is necessary because of forecasting difficulties and litigation risk. Analyzing disclosure similarity instead, this study finds a statistically and economically significant impact of qualitative information on initial-day returns. Thus, REIT managers may reduce underpricing by voluntarily providing more information to potential investors in Form S-11. 

This demonstrates that textual analysis can in fact help to explain underpricing of US REIT IPOs, as qualitative information in Forms S-11 decreases information asymmetries between US REIT managers and investors, thus reducing underpricing. Consequently, REIT managers are incentivized to provide as much information as possible to reduce underpricing building (Sherman and Titman, 2002), while investors could use textual analysis to identify offerings that promise the highest returns. 

It is well established that value firms with high book-to-market (BM) ratios earn a significant premium over growth firms with low BM ratios around the world, yet considerable debate exists about whether the return differential reflects compensation for risk or mispricing. Under mispricing explanations, prices of growth (value) stocks signal systematically optimistic (pessimistic) expectations; thus, the value-growth returns should be concentrated among firms with existent market expectation errors. Classifying real estate firms based upon whether expectations implied by current pricing multiples are congruent with their operating flexibility, we document that value-growth returns are concentrated among firms with ex ante market expectations, but absent among firms without such errors.

We investigate the relation between commercial real estate (CRE) returns and regional innovativeness and find that regions with more innovation exhibit higher total returns on commercial property. And, when we investigate the extent to which income return and capital return on commercial properties are related to local innovativeness, we report a positive relation between innovativeness and income return but little to no association between innovativeness and capital return. Our paper also provides some initial evidence, suggesting that local innovativeness is related to better future CRE performance. Overall, this paper suggests that innovativeness of a region is economically and statistically positively related to CRE returns, adding to a budding literature investigating CRE returns, as well as a large literature researching innovation.

Financial literacy is seen as root cause for false household portfolio choices and thus wealth and retirement discrepancies. However, the increasing literature on financial literacy fails to recognize the fundamental caveat of financial consumer protection: commissions based financial advice. Many countries such as the UK or the Netherlands have recognized the innate conflict of interest between financial advisors and their customers that comes with a commissions-based system. In response, commission bans were introduced. To analyze the effect of commission bans on portfolio choices we conduct a difference-in-difference panel regression utilizing data from countries that have and haven’t introduced commission bans. The results indicate that commission bans - unlike many forecasts - have not negatively impacted consumers and the financial industry.

Introduction – Comparable evidence is at the heart of virtually every real estate valuation and is fundamental in producing a sound estimate. Although valuers are experienced in handling and analyzing comparable data, approaches vary with many degrees of freedom potentially leading to incorrect decisions. And even with the increasing amount of computer-driven estimates, the evidence of comparable transactions remains paramount.

Purpose – This paper formalizes certain aspects of selecting comparables. We apply economic theory to select criteria that make properties comparable, determine how comparables can be weighted and ultimately, make decisions about what comparables should be reported such that the estimate is both unbiased and of minimum variance. In addition to this quantitative optimum, we hold a survey among real estate experts to test qualitative how well the model outcomes translate back to practice to gain additional insights where and why misalignment might occur.

Design/methodology/approach – We start with an extensive literature review about the work that has previously been done in this space. We then apply hedonic price theory to estimate the weights of the comparables and construct a novice comparability rater model. Finally, we briefly evaluate how these results compare to other promising methodologies found in the literature review and survey these among expert valuers.

Originality/value – To our knowledge, this paper is the first to cover a critical overview of work that has been done in this field. Furthermore, the application of established hedonic price theory for the purpose of weighting comparables deserves a new light within the abundance of 'newer' complex approaches. Lastly, since the relevance of this research is more practical, the translation of the results back to the experts is not found in previous work.

Findings – None yet (finish end of April)

Purpose – Driven by laws, and regulations, the transformation of the built environment is a herculean task. Green buildings seem to be a megatrend in corporate real estate management, especially for firms headquartered in the region Europe. This contribution aims to explore what the requirements of a respective corporate management fulfilling actual and future applicable laws, regulations, and responsibilities of green buildings are. Furthermore, it is examined to what extent the higher education programs take these requirements into account and what the gaps are.

Methods – The study is based on literature review, interviews with professionals, corporate reports, and collected data of academic programs in Europe.

Results – Green buildings requires different aspects of corporate management which is not represented by a singular discipline. In Europe, higher education programs focus some of the required content to prepare students for a corporate green building management but integrate rarely all knowledge required throughout a building life cycle. As a result, a framework of an education model is introduced integrating disciplines, and knowledge required of green building management.

Conclusion – Only few higher education programs appear to be considering the transdisciplinary context of green buildings requiring knowledge in, amongst others, real estate, workplaces, architecture and engineering, facility management and its services. This contribution provides fundamental considerations and presents a structural framework enabling higher education in green building management.

The Covid-19 pandemic is having wide-ranging economic effects on a global scale, significantly influencing economic capacities and household incomes, also affecting Real Estate sector in terms of investment decisions. In this sense it has led to changes in market demand, especially concerning residential properties, resulting from the different appreciation of intrinsic positional and technological factors, as location, presence of open spaces and number of rooms. In fact, the most significant effect is that the Covid-19 pandemic and the consequent restrictive measures have deeply changed the concept of 'inhabited space' in order to meet different needs of users. The present research aims to analyze market behaviors characterizing the Italian context with a view to investigating the variation of house prices starting from the identification of the new type of domestic space required by potential buyers. The main practical implication of this research is to address the investment choices in the development of adequate planning strategies in the residential sector, in order to adapt the urban planning and the residential design to a different market demand.

Indoor environment with crowded and poorly ventilated rooms has become an issue during COVID-19 pandemic, especially in workplace. From this, COVID-19 regulation has been enforced in Malaysia namely Standard Operating Procedures (SOP) to reduce COVID-19 spread in workplace. Past research believes that built environment could produce valuable contribution in addressing solutions for COVID-19 and green measurement such as Indoor Environmental Quality (IEQ) would ensure long-term social and environmental protection. However, there are lack of concentration on Indoor Environmental  Quality (IEQ) attributes towards the existing COVID-19 SOP enforced in Malaysia. Therefore, this study aims to integrate the IEQ attributes into the existing guideline for workplace. Focus group discussion (FDG) and questionnaire survey were conducted and analysed using content analysis and descriptive analysis method, respectively. There are seven IEQ categorized as the most important attributes for COVID-19 SOP.  A resilient COVID-19 framework is developed based on the validation of many perspectives expert to reduce COVID-19 spread in workplace. This study significant for building manager or COVID-19 management team in workplace to set up a sustainable COVID-19 resilient framework as an improvement for current COVID-19 SOP by integrating with IEQ attributes into their current guideline.

Although there are a number of established Corporate Real Estate (CRE) alignment models that strive for maximum or optimum added value of the real estate portfolio, the procedure find the optimal solution is often a black box decision (lacking transparency about structural, procedural and substantive aspects of decision making). This study elaborates on previous successful pilots using the Preference-based Accommodation Strategy (PAS) design and decision approach. In this pilot we identify stakeholder preferences for large lecture halls at a one University in The Netherlands. The goals of the study was two-fold, first, to use the PAS method to develop an evaluation framework to assess their current lecture halls and guide future real estate and organizational interventions. Second, to explore the impact of the COVID-19 pandemic on stakeholders’ preferences for large college halls at universities. We therefore compare this study, undertaken between October 2021 and February 2022, to our pre-COVID research on lecture halls in 2015 at TU Delft, using the same method.

The PAS method enabled a procedurally and structurally clear process to list preferences develop an evaluation framework and calculate a current overall preference score for the large college halls portfolio at the university in our study. Participants evaluated the development of an evaluation tool using the PAS method positively. Compared to pre-COVID research, an increased preference for hybrid education (especially as a policy requirement) became clear; in addition flexible classrooms facilitating a broader range of simultaneous educational activities in one hall was highlighted.

The PAS method pushes beyond the direct evaluation of alternatives (Barzilai, 2016), or the theoretical evaluation of preference based design approach (Binnenkamp, 2010) to systematically facilitating the compilation of an evaluation framework as a decision approach (Arkesteijn, 2015). It is recommended that future work focus on identification of the optimum design alternative based on these preferences. The positive evaluation of the PAS method confirm that the PAS can be used to develop an evaluation framework to enhance portfolio alignment.

The introduction in International Valuation Standards of Cyclical Assets raises several questions to the community of real estate professionals and academician (IVS 105 Valuation Approaches and Methods para 50.09 lett d). Cyclical Assets can be defined as property whose value is “influenced by upturn and downturn of the market in a significant way” (d’Amato et al.,2019). Ordinary direct capitalization is normally considered pro cyclical in its present form (De Lisle Grissom,2011), for this reason alternative approach to direct capitalization may be useful in the determination of robust opinion of value. The valuation standards propose an alternative determination of terminal value in the Discounted Cash Flow Analysis, recommending that for cyclical assets, the terminal value should consider...” the cyclical nature of the asset and should not be performed in a way that assumes “peak” or “trough” levels of cash flows in perpetuity” (IVS 105 Valuation Approaches and Methods para 50.21 lett e). The paper propose different solutions to the problem.

The fourth industrial revolution has transformed how data and information are shared and managed in the built environment. The adoption of various technologies (such as BIM, drone technologies, VR, Big Data, Machine learning etc.) for an effective data management in the built environment has therefore created many challenges for professionals to upgrade their practice. This study therefore explore the prospect and challenges of data management in the Nigerian built environment in the fourth industrial revolution. A qualitative technique (such as oral interview) with the review of relevant existing literature on the subject was adopted for this study. Several challenges outlined by professionals include the effect of cloud computing, big data, mobile devices, and financial and ethical concerns. Some possible solutions were discussed for an effective adoption of data management in the fourth industrial revolution. The study recommends that professionals need to upgrade their knowledge and competencies with the changes in the built environment through training, education opportunities and continuing development programmes.

In 2021, the Public Company for Social Services Istituti Milanesi Martinitt e Stelline e Pio Albergo Trivulzio (ASP IMMeS and PAT), the Politecnico di Milano - Department of Architecture, Construction Engineering and Built Environment (DABC) and the University of Trento - Department of Civil, Environmental and Mechanical Engineering (UNITN-DICAM) promote a scientific and technical research project aimed at “developing tools and methods of analysis and audit for the knowledge of the current state of assets and defining guidelines to manage non-instrumental assets”. The research project is a result of the cooperation between public entities, and it enhances the know-how and experiences of each actor. The integrated, synergistic and multidisciplinary approach is functional to pursuit the principles of efficiency and good performance of public administration.  

In the logic of applied research project, the real estate assets of the Institution represent a case study of national relevance and maximum scientific interest in the field of public real estate management (PREM). The real estate assets have a significant consistency and a value of about € 500 million (including agricultural properties). 

The research has a twofold objective. The first consists in defining an integrated system of analysis and verification of tools and methods for the knowledge of the real estate assets. The second is represented by the definition of guidelines for managing non-instrumental assets with criteria for their classification, monitoring, maintenance, and management. 

To pursue the aims, the research project divides the activities into two stages:  the reconnaissance of the state of assets and then, a methodological proposal aimed at evaluating the feasible evaluation strategies. The activities refer to: (1) the reconnaissance of non-instrumental real estate assets by techno-typological characteristics, by intended use, age, etc .; (2) the analysis of tools adopted by the Entity; (3) the analysis of procedures and parameters used for the definition and classification of critical issues; (4) the analysis of the “state” classification of buildings and their parametric indications of recovery costs; (5) the analysis of the evaluation criteria used for defining disposal plan (where applicable); (6) the proposal of a procedure to compare real estate values; (7) the definition of guidelines and procedures for analyzing the current state of buildings to support the definition of priorities and/or opportunities; (8) a proposal of methodologies, tools and control parameters (technical, documentary, economic) to support the evaluation phase, technical and economic management of the real estate portfolio; and finally, (9) the test of proposals on a significant sample of case studies. 

This paper presents the applied methodologies and the results achieved in the early stages of the research.  In particular, the paper presents the importance of the correct setting of information, the methodologies and the first procedural proposals based on the profitability criteria. The overall results will be achieved one year after the start of the research.

DeAngelo, Gonçalves, and Stulz (2018) offer a “credit-card” perspective of debt and document that firms periodically deleverage to restore financial flexibility. However, the valuation consequences of deleveraging have been left unexplored. Lines of credit, closely monitored by the associated lending institutions, represent the closest analog to corporate credit-cards. Employing a sample of equity issuances, we find that deleveraging via repayments of credit lines is viewed favorably by markets. We posit that repayments replenish credit lines and restore financial flexibility, while preserving bank monitoring (Acharya, Almeida, Ippolito, Perez, 2014). We refer to the integrated beneficial effect as Monitored Financial Flexibility.

In the German purchase price database, millions of transactions are recorded in just few years. The information is necessary to assess the local real estate markets. To evaluate the purchase prices correctly it is necessary, that all information that has an impact on the price is included in the evaluation process. Information about the inside of the real estate can only be obtained by questionnaires or construction files until now. However, the response rate of questionnaires and access to construction files are limited. Unfortunately, for that reason, many data-gaps exist in the samples. 

The goal of this approach is to derive the information about the inside geometry and fill these data-gaps in the database. With the German CityGML level of detail 2 (LOD2) building models it is easier to derive the characteristics about the size. Every building in the model has information about height, surroundings, shape of the roof and geographical location.

In this approach, we use a parametric and a non-parametric method to derive the size of the living space, the number of floors besides the existence of a basement and the usable attic from LOD2 models. As training and validation data, we use several thousand building models and the existing information about the inside geometry from the purchase price database which was derived by questionnaires and construction files. In the literature we can find information that shows, that the size of the walls and utility shafts depend on the building age. We therefore expect that the usage of the information about the building age as an influencing parameter can improved the accuracy of the estimation.

We use a cross-validation approach with parametric and non-parametric regression to derive the information about the inside geometry from the outside geometry and compare the methods.

We expect that non-parametric methods over-perform parametric methods. 

To use the approach in the future for the missing data, the premise that the missing data in the database is missing at random has to be true.

In near future, further data (digital twin – LOD3+) can be used to derive the information even more accurate.

This paper deals with the funding of institutional investors that invest in commercial real estate assets. The aim of this paper is to investigate what are the main factors that lead bankers to grant credits to institutional real estate investors.  To explain the credit acceptance, the impact of many variables has to be explored. This bunch of variables can be synthetized in four dimensions: The quality of the borrower, the quality of the asset funded, the quality of the tenants (of the asset funded) and the quality of the funding contract. After having identified the different drivers, we explore what is the marginal contribution of each dimension on credit granting. To proceed, the methodology we selected is conjoint analysis. To sum up, it consists to construct different credit scenarios based on the four dimensions (for example: scenario 1: high quality building, low quality borrower, high quality tenants, low quality contract). Next, these scenarios are presented to bankers through interviews or online surveys. The aim is to ask them to express a preference/judgement to each scenario (ranking each scenario by order of preference, rating each scenario, propose an interest rate, indicate which scenarios are accepted). Finally, we implement a model to infer the contribution of each dimension on the preference of the bankers. 

In the end, this article could allow to develop a scoring indicator that aggregate all the idiosyncratic risk factors for commercial real estate in structured finance. It could represent a new tool for bank risk management departments to help them to manage their risks

This research examines whether most variation in house price changes is mainly driven by local or national factors. Employing a novel data containing both capital appreciation and income component in the U.S. Metropolitan Statistical Areas, results show that macroeconomic factors, absorbed by time fixed effects, account for 43% of the variation in capital gains and 2% of the variation in rental yields. Overall, the findings empirically support the prior literature assuming that the nature of housing markets is mainly local. The findings suggest a greater role of local factors for understanding cross-sectional income returns in housing markets.

The introduction of minimum energy efficiency standards (MEES) for buildings has been hailed as a milestone for improving the carbon footprints and energy consumption of the lowest performers in a number of countries. However, there is a concern that landlords will either pass on the additional costs to tenants via increased rents or withdraw non-compliant cheaper properties from the market altogether, thereby reducing supply in this market segment and driving up rents.  As tenants in properties with lower energy efficiency performance tend to have lower incomes, the any direct or indirect rent increases stand to affect them disproportionately. This paper estimates the impact of the MEES policy on rents in the UK private rental market using a proprietary dataset of 3.6 million rental observations and property characteristics. It comprises a large set of control variables such as location, size, age and condition. The latter is particularly important as rental properties with lower energy efficiency levels are on average older and located in less attractive areas than their more energy efficient counterparts. To estimate the dynamic effects of the change in policy, we also apply a difference-in-difference (DID) estimation and a regression discontinuity design. This allows us to compare the rental price trajectory of a treatment group (EPC F/G rental properties) to one or several control groups (higher EPC bands and/or non-rental properties).

Purpose: This study analysed the response of indirect real estate asset and other listed investment assets to macroeconomic fluctuations in the Nigerian property market. This is with a view to determining the long-run convergence of indirect real estate assets and other listed investment assets when combined in a portfolio in the Nigerian emerging market.

Design/Methodology/Approach: The secondary data collected comprised quarterly returns on the indirect real estate asset and the other listed investment assets; Nigerian Stock Exchange (NSE) Banking, NSE Oil and Gas, NSE Industrial, NSE Insurance and NSE Consumer, for the period of January 2009 to December 2020. Others include quarterly data on five macroeconomic variables which are inflation rate, unemployment rate, exchange rate, GDP and interest rate over the study period. The data were obtained through the daily price list of the Nigeria Stock Exchange (NSE) via NSE website, the Central Bank of Nigeria Statistical Bulletin and the National Bureau of Statistics. The data were analysed using the holding period return, percentages and the impulse response function obtained from the Variance Error Correction Model (VEC).

Findings: The result showed that the response of indirect real estate to each macroeconomic fluctuations vary from that of other listed investment assets along the short run. However, the indirect real estate and other listed investment assets readjusted and exhibited similar responses along the long run which connotes that indirect real estate asset and other listed investment assets have long run equilibrium, in order words, they comove at the long run.

Practical Implications: The paper implied that indirect real estate asset and other listed investment assets have similar responses to macroeconomic fluctuations along the long run which implies that the asset classes have long run convergence.

Originality/value: The paper represents one of the few attempts to examine the long-run response to macroeconomic variations of real estate investment asset and other listed investment asset from emerging market perspective.

With buildings accounting for 40% of the UK carbon footprint, environmental issues are becoming a significant focus for the commercial property industry. Since 2007 almost all units marketed for sale or lease have been required to exhibit an Energy Performance Certificate providing a rating of the energy efficiency of the unit from A (very efficient) to G (least efficient) as assessed by a specialist surveyor. However, there has been no consensus in the academic literature that energy efficiency is associated with higher transaction values and rents. But whether the behaviour of investors and tenants have changed due to the pressure of climate change. In this study, using a unique data set of existing office property rents and energy efficiency rating across the UK in 2021, we did not find that a better rating automatically gives rise to a higher rent. Other factors obviously come in to play too - for example, how recently the building may have been refurbished, other services the building provides such as a food service, bicycle shed, etc. The data also revealed that buildings with lower ratings commanded a higher rent than those with a superior EPC rating.

Real Estate prices are influenced by the presence of multidimensional factors and many studies have been carried on to prove the correlation between property prices and extrinsic (location, neighborhood’s quality, etc.) as well as intrinsic (structural features, systems, etc.) characteristics. As it emerges by many consumers’ preferences investigations, the COVID-19 pandemic has prompted a shift to healthier cities. In major cities, green and open spaces are typically  the only chance citizens have of coming into contact with nature and they fulfils environmental and social functions which improve quality of life and wellbeing. The aim of the current contribution is to assess the value of the urban quality by considering both spatial multicriteria variables and its marginal price, in order to explore its impact on real estate market. In fact, the quality of the built environment is a multidimensional notion, as it deals with the land use patterns and mixes, the spatial and temporal distribution of activities, the accessibility to services, the open spaces and green areas, the air quality, the arrangement and appearance of the physical elements of urban design. 

Given the spatial nature of urban quality and the multiple aspects to be considered, a hybrid evaluation approach has been defined by combining Spatial Multicriteria Analysis with the Hedonic Price Method. In line with urban design domain of research, the features contributing to the overall urban quality and analyzed within this study are the presence of public open spaces, influenced by i) the physical setting, ii) connectivity, iii) vitality, iv) meaning, v) protection, the accessibility and the provision of services.  Since the linear regression models cannot take into account the interaction effects between different variables, non linear exponential multiplicative model computed via Maximum Likelihood Estimator (MLE) has been applied.

The proposed evaluation approach has been tested on three urban districts in the city of Milan (Italy), with different location features and located on the north-eastern side of the Municipality, from the center to the administrative border. By putting a light on urban quality marginal prices, the results of the this study could be considered as a contribution to address the real estate market actors choices about the trade-offs between economics and environmental quality.

In a time of technological upheaval and energy decentralisation, Australian property sector is becoming more concerned about building energy needs and strategic about how to source energy services. Consequently, this has enabled energy service providers to offer innovative energy services and develop new business models. Energy-as-a-service (EaaS) as an emerging business model has shown potential under this complex energy transition. However, with limited studies into this business model, there is a research gap in determining what really drives such a business model.  In addressing such a research gap, this paper investigates about drivers for EaaS from an industry perspective. More specifically considering property sector the paper focus to identify perspectives of customers of property sector and energy service providers representing EaaS. A generic qualitative research design within a constructivist paradigm was adopted in this exploratory study with twenty-nine semi-structured interviews. Thematic analysis resulted findings to be classified under four driver categories of: Financial, Organisational, Functional and Market. Empirical analysis revealed that financial drivers can both be connected to reduced energy expenses in buildings as well as increased revenues while similarities to performance risk transfer was highlighted beyond traditional energy contracting models. Sustainability concerns was emphasised as an organisational driver however with consequential challenges to service providers from much active and involved prosumer clients. This deviation was seen in market drivers as well where interviewees agreeing on the influence of digitalisation, decentralisation and decarbonisation for EaaS, however has resulted property sector customer to become a service provider of EaaS to building inhabitants. Although findings were in the context of property sector similar drivers was also seen for energy system transition, meaning EaaS applicability to energy system levels well.

Causal studies on the effect of air quality on house prices, specifically focusing on a large metropolitan area, are rare and difficult to obtain because of potential endogeneity from residential sorting.  In this study, we use the Aliso Canyon gas leak as a natural experiment to examine the effect of air quality on housing prices of Los Angeles City. Using a spatial difference-in-differences model, we estimate that houses within the 5-mile radius of the gas well experienced a 3% discount in price during the leak, and an additional 4.4% discount after the well was sealed and the air quality was restored. The decrease in price lasted beyond 18 months, with houses closer to the leak suffering higher discounts. We conclude that air quality degradation has a direct and longer term negative impact on house prices.

Property tax assessment revenue is the main income of local authority and is used to provide services and maintenance to the community. Past research has found the link between property value and property tax whereby any differences affecting property value reflect the property tax assessment value. Over decades, numerous studies have been conducted to investigate the relationship between green elements and property value. Past research has identified tangible elements of green building as green envelope components that affect property value. However, to date, no research has been conducted to determine the effect of both tangible and intangible green elements on property value. Henceforth, this research intends to identify and measure the effect of intangible green elements on local authority property tax revenue. A comprehensive review of literature and guidelines by green rating tools was conducted and analysed through systematic analysis. The findings are used to construct questionnaires and distributed among property valuers to identify the effects of tangible and intangible green elements on property value. Furthermore, hedonic models through multiple regression analysis were developed to measure the percentage of value increment and decrement for each green element. The results are used to validate the effect of tangible and intangible green elements on local authorities’ property tax assessments revenue. The findings shows that local authorities’ property tax assessment revenue is estimated to increase by 36.4% if the property under their administrative area implements green elements that have a positive effect on the value and decrease by 7.0% if the property under their administrative area implements green elements that have a negative effect on value. This research is significant for the local authority to support sustainable agenda by promoting green building development at the local level.

Greenspace exposure to humans have benefited them in terms of mental health and wellbeing. Although various studies have shown the benefits of greenspace there is very limited studies that the overall efficiency of greenspace in improving mental health and wellbeing in various countries. This paper explores the efficiency of green space in improving mental health and wellbeing. The objective is achieved by reviewing past research papers and articles from database such as Google Scholar, Emerald Insight, ResearchGate, ScienceDirect and Elsevier that relates to the greenspace, mental health, and wellbeing. The findings found 40 articles that meets the requirement of the review. The efficiency of greenspace information from the reviewed articles are grouped into five groups, name of author, type pf greenspace, type of analysis, the city the research was done and the percentage of efficiency. The results were tabulated using content analysis method. In overall, the results show a positive relationship between green space and mental heal and wellbeing. This paper contributes to the residents in terms of location selection to buy a property and to the developer in terms of planning and consideration to include greenspace in the upcoming developments.

This paper investigates how auction bidding formats affect U.S. mortgage foreclosure sales. Exploiting a staggered adoption of electronic bidding across<br>adjoined counties in a “stacked” difference-in-differences design, I show that foreclosure auction success increases by 27%, and price discounts contract by<br>42%. The effects are stronger in areas with more remote courthouses, and for properties in better conditions. Buyer composition of electronic foreclosure<br>auctions shifts towards local non-professionals, who are less likely to buy-to-let and flip acquired properties ex-post. This evidence suggests that technological<br>modernizations in real estate markets can lead to better matching, deepen liquidity and foster financial inclusion.

Whilst there is a broad consensus that energy efficiency as measured by the environmental performance certificates leads to higher asking rents, there is little evidence about investment strategies that consider energy efficiency as an optimisation factor. This paper focusses on identifying the conditions that lead to the highest increase in the willingness to pay for energy-conscious refurbishment. By making use of more than 1.5 m observations in Germany and the UK we disaggregate the expected willingness to pay to spatial, socioeconomic, and hedonic characteristics via Generalized Additive Models (GAMs). In a simulation study, we show that an investment strategy in residential real estate can be optimised via intelligent asset selection considering energy efficiency as an optimisation factor.

The Covid-19 pandemic has forced most workers to work from home (WFH). At a first glance, this seems not a big change for academics, who, even in normal time, are used to performing their research activities autonomously and to balancing on-campus and off-campus locations. Instead, exactly for their flexible habits it is interesting to study where academics have worked during the Covid-19 pandemic and which factors relate to their location choices. This paper addresses these issues by relying on survey data from a sample of 7,865 Italian tenured academics. First, cluster analysis unveils four main location choices of Italian academics during the Covid-19 pandemic depending on the frequency of access to home, university or other spaces, namely Home-centric, University-centric, Between home and university and Multi-located. Second, multinomial probit models reveal a nuanced picture of the factors associated to the belonging to each cluster. Decisions over location choice depend, mostly, on work-related factors (i.e., discipline); then on space-related factors (i.e., satisfaction towards campus workspace characteristics and the need of a laboratory); finally, on, life-related factors (i.e., living with school children or a partner) and other factors (i.e., commuting times and gender). However, each of the four location patterns depend on different determinants. The results offer university and practice-wide implications anticipating future changes in how work in academia is spatially organized.

In the absence of any empirical estimation, standard theoretical models of the housing market follow the framework developed for the job market that assume a Cobb-Douglas form with constant returns to scale for the matching function. The present study aims to fill the gap and provides a first estimate of a matching function for the housing market. To that end, we assemble a unique dataset, through Internet traffic analysis, with measurements of the numbers of home buyers and home sellers active in the forty-four largest urban areas in France, from October 2013 to June 2017. We confirm that a Cobb-Douglas form fits the data well. However, our results indicate decreasing rather than constant returns to scale. Two extensions of the baseline model random matching are explored. The first accounts for the intensity of the buyers’ search, the second, for some characteristics of the market participants. Both bring evidence that these elements matter in the way buyers and sellers meet and transact and that the matching on the housing market is not purely random.

Housing affordability is one of the most pressing issues in urban areas. During the Covid 19 pandemic, this problem spread to surrounding and more rural areas due to changing demand dynamics. At the same time, the economic downturn has exacerbated challenges for certain tenant groups. 

Based on an adapted Social Business Model Canvas, we are working with student groups on an interdisciplinary project to look at the entire affordable housing value chain from both the user perspective and the perspective of private and public housing companies, i.e., from design and planning to construction, operation, and redevelopment. The aim is to identify the main variables for achieving affordable housing prices, the interdependencies between them and their respective manifestations in Germany and five other European countries: NL, IT, AUT, DK and UK. Based on this, we derive limits and drivers of value creation as well as potentials for the realization of affordable rents or housing costs. 

The Affordable Housing issues examined in each country are.

1. Definition of "affordable housing" and characteristics, needs and quantity of the most relevant user groups.
2. Building conditions, structural-functional designs, and construction costs for Affordable Housing.
3. Characteristics and business models of investors or providers of affordable housing.
4. Legal framework / regulation for affordable housing (outside of building law).
5. Tax framework and subsidy options for investors and users.

This presentation will introduce the project setup and findings on user and construction issues of Affordable Housing.

(An second presentation presents the findings on business models as well as legal and fiscal framework conditions of Affordable Housing.)

The work environment of knowledge workers has been subject to constant change not only due to the ongoing Covid-19 pandemic. Shifts in technology, the economy, and society are changing the way we work. In addition to the office, work from home and third places are now available for the completion of tasks. The Covid-19 pandemic globally forced knowledge workers to work from home and thus, enabled employees to gather experiences in working from home, accelerating the development. It can be assumed that many knowledge workers are weighing up their preferred place of work.

Previous studies have shown that working from home can have positive effects for companies in the form of productivity improvements. So far, this potential has mainly been shown for the average of the total workforce. Yet, it is not clarified which employees exactly benefit from working from home and which employees should work from the office or from third places. The aim of the study is to identify clusters that have their own work location distribution and to describe these based on personal, work-related, and real estate characteristics. In addition, it is to be examined whether the desire for the specific work location distribution (modal split) promises success.

The identification of clusters is carried out using hierarchical cluster analysis including previously identified personal, work-related, and real estate characteristics. The assessment of the results is based on the comparison of the cluster characteristics, the stated preference for work from home, third places, and company office as well as previously identified variables on work success at different work locations. Data from a survey of 1159 knowledge workers in Germany and the U.S. is used.

The results of the study provide important information for corporate real estate management and other actors in the real estate industry. They suggest that knowledge workers have developed a good sense of which work location they can successfully work at. Nevertheless, companies must carefully decide which employees could work from home or at third places with regard to the company's success. In addition, the results underline the necessity of upgrading the quality of corporate spaces: On the one hand, to be able to offer suitable workplaces for cooperation and, on the other hand, foster corporate culture through an appropriate real estate portfolio.

Real estate is a heterogeneous commodity where no two are alike. Therefore, making assumptions about determinants and the way they influence the value of a property is difficult. Traditionally, parametric and, thus, assumption-based regression techniques are used to identify those dependencies. However, recent studies show that these relationships can only be mapped to a limited extent by those approaches. On the contrary, modern Machine Learning (ML) approaches are less restrictive and able to identify complex patterns hidden in the data. Nevertheless, these algorithms are less transparent to human beings. An ML approach may be the best solution to predict the value of a property, but it fails at determining the factors driving that value. To overcome this limitation, explainable artificial intelligence (XAI) has come forward as a new important direction of research. So far, there has been almost no research applying XAI in the field of real estate. Therefore, we introduce two different state-of-the-art XAI approaches, namely Permutation Feature Importance (PFI) and Accumulated Local Effects Plots (ALE) in the context of real estate valuation. Focusing on the residential market, we use a dataset consisting of around 1.2 million observations in Germany. Our findings show that using XAI methods enables us to open the “black box” of ML models. In addition, we find several unexpected non-linear dependencies between real estate values and their hedonic characteristics and therefore deliver important insights to better understand the fundamental functioning of residential real estate markets.

Over the past ten years (2009 – 2019) Botswana has experienced vast urbanization and industrialization by margins, within such a time frame a percentage increase of about 9.23% as to urban population (from 60.94% to 70.17%) and growth is still anticipated as years pass. The constant degeneration of natural spaces has eroded plantation life paving way for property development, therefore this study aims at establishing awareness of biophilia concepts and design amongst real estate development professionals whilst pinpointing the benefits to such. Greening science "Biophilia" is the newly explored way to ensure that environmental, social and economic sustainability is attained by countries. In light of plausible information to complete the project, the use of surveys (interviews and questionnaires) in accordance with the target population (design team) of the study were explored. Furthermore, although Biophilia is adduced as a solution towards the probing human health complications and dire environmental degeneration, awareness of such design principles and patterns is somewhat minimal and propelled by human skepticism. Biophilia being the next route towards sustainable development it proves to be the solution towards health for humans (air pollution related health conditions; resulting from increased car dependency and industry mushrooming causing underlying diseases like asthma) and the global environment (environmental degradation and climate change) amongst others creating a harmonious space of habitation giving Botswana a platform for economic, social and environmental sustainability.

The uncertainty generated by the COVID-19 pandemic lockdowns and restrictions has challenged the strategic vision on campus development and management, intensifying the existing financial, functional, and spatial complexities of the university campuses. The purpose of this paper is to reveal the impact of COVID-19 on campus management and assess the current supply of campus buildings in the light of existing changes that stem from remote education and work experience. This study draws on the vision and strategies that Delft University of Technology’s campus research team has developed since the early 2000’s. To this end, the team incrementally conducted interviews with the campus managers and compiled a campus database that encompasses organizational, functional, physical, and financial data on 13 Dutch Universities and 64 campus buildings. Qualitative findings demonstrate that while the campus managers developed considerable experience in facilitating online work and study processes during the COVID-19 pandemic, they acknowledge the value of the campus as the home base for interaction and focus. Ultimately, campus managers opt for a hybrid model that can simultaneously accommodate the online and physical work/study environments. By utilizing the campus database the capacity of the current campus supply to accommodate this hybrid condition is assessed. Despite the experience gained during the campus lockdowns, we argue that only a limited part of the campus supply can accommodate this hybridity. Finally, we discuss the potential strategies in campus development to decrease this gap between the demand and supply.

The paper explores the relationship between ESG factors and the rental income and property value with a zoom in the study of cloud based smart locker operators. The key sustainability attributes researched in the paper cover tenant’s expectations and property value in relationship to ESG factors. Given the increasing popularity of cloud based smart locker operator in partnership with building owner and manager to provide alternatives to last mile logistic delivery to minimize cost and carbon emissions.  E-commerce is significantly growing with no sign of slowing down hence cloud-based technology smart locker offered 24/7 contactless pick up and real time parcel status update with the benefit to reduce carbon emissions materially per parcel unit. Sensitivity of rental income and property value to the captioned sustainability factors associated to the Sustainability Development Goals (SDGs) highlighted by high transparent real estate markets in Hong Kong is being studied. The author aims to provide insights in how smart locker operators managed to develop last mile delivery solution for e commerce logistics supported by technology and create win-win with property owner as real estate investors and lenders putting more emphasis of ESG factors in financing decisions.

The aim of this study is to analyze and compare the abnormal earnings announcement returns of«concentrated» and «diversified» U.S. REITs from 2000 to 2017. Using a unique property-level dataset, we analyze the impact of geographic concentration on the relative performances of real estate investments trusts (REITs). More precisely, we focus on financial analysts’ forecast accuracy, market-level uncertainty, REIT-level uncertainty and synchronicity. Therefore, as robustness check, we develop different geographic concentration measures. First, we document the coverage, the accuracy and the bias of financial analysts’ earnings forecasts on «concentrated» and «diversified» REITs. Our results report that the level of accuracy and the level of optimism are statistically different for these two categories, especially after the Global Financial Crisis. Second, we observe that abnormal stock returns, abnormal trading volume and abnormal volatility may be related to the level of geographic concentration and synchronicity. Our results shed a new light on the geography of real property information and investment. More generally, they highlight the potential link between the level of geographic concentration, or home bias at home, and the level of information on stock markets.

Brownfield redevelopment projects are frequently perceived as riskier with respect to greenfield investment and the financing opportunities may be more limited and more expensive. Different financial aid projects have been developed for supporting regeneration projects and empirical evidence had shown that all the buildings near the intervention area will benefit from a price increase once the brownfield project is complete.

The paper considers the Connecticut market and the evaluates the characteristics of the brownfield projects that had access to a financial aid program (loan or grant) and the impact of the regeneration process on the liquidity of the housing market and the gap between the price and the appraisal value of the residential unit. Results show that the financial aid determines a lower concentration because of a wider urban area that will be available to satisfy housing demand and the average price increases in the surrounding area and it will be more consistent with appraisal valuation.

We study foreclosure discounts for all forced Norwegian house sales between December 2001 and February 2018. Micro-data from two Norwegian banks are further analyzed to shed light upon biased valuation methods. We estimate foreclosure discounts using an advanced statistical valuation model (AVM), repeated sales, and a real estate agent’s value estimate. We expand on earlier research by exploring how homeowner participation, centrality and the valuation method (human vs. automated valuation) adopted at origination are interlinked and contribute to the explanation of foreclosure discounts. Homeowners in rural areas are less likely to participate in foreclosure sales, and banks granting mortgages are less likely to employ AVM valuation. Our findings enrich research on biased valuations and link the bias in valuation methods with bias in banks’ valuation methods. Banks granting mortgages with a high loan-to-value ratio should exercise caution in rural areas while deviating from AVM valuation and calibrating their lending models considering risk differences.

The ongoing digitalization is picking up speed in slowly changing industries such as real estate. Especially in the field of real estate valuation, which is strongly dependent on data quality and quantity, automation is able to change the appraisal process substantially. However, in most countries, only the use of Automated Valuation Models (AVMs) based on simple non-statistical methods is allowed, as the regulatory system does not yet give the green light to higher-order methods. This study provides a relevant contribution to the debate on why AVMs based on statistical and machine learning methods should be widely used in practice. Therefore, various methods for AVMs are implemented and applied to a dataset of 1.2 million observations across Germany. An automation of the traditional sales comparison method, two hedonic price functions, as well as a machine learning approach are compared with each other. The aim of this paper is to show how the methods perform in direct comparison with each other as well as in different structural regions of Germany and whether the use of modern learning-based algorithms in real estate valuation is beneficial. The results of this research have various implications regarding the different accuracy and transparency levels of the methods from a regulatory and practical perspective. Moreover, the comparison at the spatial level shows that the models perform differently in urban and rural areas. This allows conclusions to be drawn about the design of AVMs for cross-regional models.

This study tried to examine how Covid-19 affected house prices in online listing platforms for the Istanbul Metropolitan area. In all online listing platforms in Turkey, net living area, building age, being in a gated community, the number of floors, and floor of the apartment are the primary filtering and evaluation criteria. We analyzed how and in what direction these parameters affect house prices, depending on people's preferences, from the beginning of 2020, which is considered the beginning of Covid-19, to June of 2021, the period when life began to continue relatively independent from covid-19. While doing this, we had 635,234 observations of house sales from online listings. We divided the data into three groups for houses with lower, middle and upper-income level prices, running them in a split model would be a better option when considering Istanbul's metropolitan structure. For each dataset, we have created regression models on a monthly basis and tracked the change of parameter coefficients. While all parameters in the model gave meaningful results for the lowest price segment, the significance level decreased as the prices increased. During pandemic, the tendency of the low-income group has evolved towards a modern form of housing in gated communities. As a result, the tendency to live in old buildings has decreased and the "large space requirement" related to size has left its place to "more room" houses in these preferences. When we run two co-models constructed at the beginning and end of the period, the coefficients for living in the gated communities increased by 58%, the coefficients for the number of rooms increased by 41% and the coefficients for the net living area increased by 21%. The building age coefficient changed its sign to negative as expected. Furthermore, none of the parameters except the net living area in the highest price group yielded to a significant result.

The Great Financial Crisis (GFC) affected all European countries. House prices were affected later and with some exceptions in European Countries. It could be illuminating to compare this downturn with the latest Corona crisis.

How developed the housing markets in the European countries during the Corona crisis and the follwing recovery compared to the periods after the GFC? First results of the analysis underline that on one hand market activity (turnover) declined during the pandamic. However, prices went up all over Europe.

Comparing the developments since 2008 it is worth mentioning that GDP recovery after the GFC allowed nearly in all countries passing the pre-crisis level before the Corona crisis hit again the European economies in 2020.

In contrast to the economic developments, housing markets in various European countries did not reach the pre-crisis level until 2019 and sometimes not until 2021 either although the upswing of the housing markets started in Europe around 2014. In a small number of European countries prices doubled between 2008 and 2021.

DeAngelo, Gonçalves, and Stulz (2018) offer a “credit-card” perspective of debt and document that firms periodically deleverage to restore financial flexibility. However, the valuation consequences of deleveraging have been left unexplored. Lines of credit, closely monitored by the associated lending institutions, represent the closest analog to corporate credit-cards. Employing a sample of equity issuances, we find that deleveraging via repayments of credit lines is viewed favorably by markets. We posit that repayments replenish credit lines and restore financial flexibility, while preserving bank monitoring (Acharya, Almeida, Ippolito, Perez, 2014). We refer to the integrated beneficial effect as Monitored Financial Flexibility.

The 15-minute city is an emerging concept, developed and theorized by Carlos Moreno. This city model proposes to question the development of the city through the analysis of the proximity of the inhabitants to the six essential social functions identified by the author: living, working, commerce, healthcare, education and entertainment. The COVID-19 crisis has highlighted profound urban issues and among the new urban models, the 15-minute city responds to the challenges of developing a more resilient, sustainable, inclusive and smart city.

The objective of our study is to understand how to characterize and how to understand the capacity of a city to be and become a 15-minute city. Our study is focused on the territory of the city of Saint-Fons and its neighboring municipalities. This territory of the metropolitan area of Lyon (France) is going through an important urban transformation with the construction of a tramway line which will allow it to open up and vitalize this very industrial territory, with a difficult socio-economic context and environmental issues (air pollution and noise), and to integrate vegetalization on this new infrastructure and its right of way. This new dynamic will also allow for a response to the important land pressure in the metropolitan area, particularly for the residential sector.

A total of 159 variables were collected to characterize the 6 functions of the 15-minute city.  We performed a principal component analysis for each function to characterize the territory. The data was collected at the IRIS scale (aggregated units for statistical information created by the National Institute for Statistics and Economic Studies of France). A total of 95 IRIS were included in our study. Our analysis was completed with a study of the residential real estate market in the municipality in order to highlight several urban and real estate potentialities and opportunities of the territory.

Thus, the purpose of the present study is to perform a diagnostic method of the potential of a territory to become a 15-minute city, to develop a decision-making tool in land use planning and to better understand the global dynamic of a territory.

One of the largest problems in the real estate market analysis, which includes valuation, is determining the significance of individual property attributes that may affect value or attractiveness perception. The study attempts to assess the significance of selected attributes of real estate based on the detection and analysis of the emotions of potential investors. Human facial expression is a carrier of information that can be recorded and interpreted effectively via the use of artificial intelligence methods, machine learning and computer vision. The development of a reliable algorithm requires, in this case, the identification and investigation of factors that may affect the final solution of the problem, from behavioural aspects through technological possibilities. In the presented experiment, an approach that correlates the emotional states of buyers with the visualization of selected attributes of properties is utilized. The objective of this study is to develop an original method for assessing the significance of property attributes based on emotion recognition technology as an alternative to the commonly used methods in the real estate analysis and valuation, which are usually based on surveys. The empirical analysis enabled determination of the mainstream property attributes significance from evoked emotions intensity within the group of property clients. The significance ranking determined on the basis of the unconscious expressed facial emotions was verified and compared to the answers given in a form of questionnaire. The results have shown that the conscious declaration of the attribute ranking differs from the emotion detection conclusions in several cases.

Data storage service demand is increasing year by year and the smart working approach adopted by several companies during the pandemic has increased significantly the interest of developing efficient solutions worldwide. The usage of third party data centres is growing and only few large corporations are using their own facilities for managing their data (Greenstein, 2020). The demand of data centres is expected to grow in the market for the next years but there are still only few data centres traded in the real estate market (Colliers, 2022) and some European countries are considered among the more interesting locations for the investment pipeline of the main players in the market (Arcadis, 2021).

Literature on the location choices for data centres has shown that there are some technical constraints that matters for selecting the location related to the size of the area, the seismic and flood risk, the temperature, the electricity cost, and the quality of ethernet connection. Among the areas that satisfy these minimum requirements it is possible to distinguish the market for urban, suburban and footloose data centre that may target different types of customers with an higher or a lower interest to visit the facilities over time (Greenstein and Fang, 2021). The development of a new building necessary for offering third party data storage service requires huge investments both in term of time necessary for completing the projects (around one year) and economic resources spent (more than € 100 millions for the smaller projects). Empirical evidence on the drivers of the location choices are still limited and mainly focused on the US market;. results provided cannot be generalized for the other international markets.

The paper will consider all the third party data centres existing in the EU 28 countries in year 2021 (1,427 buildings) in order to provide an updated map of the location choices in different European areas by distinguishing the urban, the suburban, and the footloose facilities. Data at city level will be supplemented with both census and companies data in order to study the main drivers that increase the interest for developing the data centres. Results show differences among countries and some interesting results related to the comparison of location choice drivers for urban, suburban, and footloose buildings

Empiricism on institutional land administration in developing countries have historically and currently conveyed an anthology of process delays, database mismanagement, titling irregularities and data falsification encumbrances to real estate investment. In spite of these lingering information management deficiencies, a common argument does appear in extant research that the plethora of scholarly and cross-industry demonstrations of blockchain data management and security capacities and propensities are seemingly overlooked by land information managers in this region, especially in the focus area of Sub-Saharan Africa. The paper offers an instantiation for the validation of the Dynamic Capabilities Theory as predictor for blockchain-driven re-engineering of land information management processes in the area. The objectives of the study were to identify encumbrances of blockchain adoption in land information management in the study area, and to examine idiosyncratic dynamic capabilities which can be deployed in their attenuation. The methodology was a systematic review of related indexed studies which premised the theorizing of nexuses between idiosyncratic dynamic capabilities and organizational performance hindrances. From the findings of the study, pathways to a research agenda were established using 5 testable propositions for land information management. The paper promotes a theoretical framework for better understanding of the prospects of dynamic capabilities theory in engendering an improved and sustainable land information management system in the developing countries.

The goal of this paper is to investigate the link between historical trends in working from home and the evolution of key indicators of office occupier markets across Europe over the past three decades. Based on the data from Eurostat and CBRE, the paper uses panel regression to investigate the temporal as well as cross-sectional relationships between the share of the workforce working from home and office rents and vacancy rates in major cities. The results are interesting in several ways. Firstly, changes in the share of employees working from home did not appear to have any significant impact on the evolution of rents or vacancy rates over time. However, occasional homeworking was significant in explaining cross-sectional differences in office market indicators. Moreover, contrary to the initial expectations, higher share of employees occasionally working from home appeared to be associated with stronger performance of the respective office market. As explanation, the paper proposes a hypothesis that this was due to working from home being only one aspect of broader changes in the office work environment and related socio-economic trends that had a net beneficial effect on office occupier markets. Although the results refer to historical developments and may not be fully applicable to the current context of the Covid-19 pandemic, they highlight the need to consider working from home in a broader perspective of office occupier trends and ways of working.

World health Organization (WHO) acknowledge that coronavirus airborne transmission could be potentially indoors with crowded and poorly ventilated rooms. From this, COVID-19 Standard Operating Procedure (SOP) guideline for office building that has been issued by Ministry of Health Malaysia is expected to be part of the ‘new norms’ in workplace. However, there is lack of concentration on Indoor Environmental Quality (IEQ) attributes even it has been proven in many research that the transmission of COVID-19 actively occurs indoor environment and IEQ could mitigate the virus transmission. Therefore, this study aims to discover the important IEQ attributes for office building to reduce COVID-19 spread based on building management perspectives. There are two objectives outlined in this study which are 1) to identify IEQ attributes for office building, and 2) to analyse important IEQ attributes for office building. Questionnaire survey is conducted among building manager in Malaysia and analysed using frequency and  descriptive analysis to achieve research objectives. Overall, it is resulted that there are nine important IEQ attributes that could reduce COVID-19 spread in workplace based on building management perspectives. This study is significant for building manager or COVID-19 management in workplace to enhance their current SOP by integrating IEQ elements to reduce COVID-19 spread in workplace.

Purpose: The study is aimed at creating a testable model to serve as guide in the study of the influence of client sophistication in tangible asset valuation practice, especially for developing economies, which can be used to establish and document positive and/or negative impacts of such client involvement. Subjecting the model to practical application may eventually contribute significantly to the emerging discourse about sustainable asset valuation practice.

Design/Methodology/Approach: With particular reference to asset valuers in developing economies (case study of Nigeria), the study assessed and evaluated previous related studies and literature on the subject in diverse fields, both in developed and developing economies. Relevant theories, borrowed from the discipline of market research on customer satisfaction, have also been evaluated in the paper. These theories suggest how clients/customers/consumers react to product/service offerings, which reflects the level of their sophistication. Thereafter, the paper identified testable indicators and concepts from extant studies to model the influence of client sophistication in asset valuation practice. 

Findings: Clients' service delivery preferences are dynamic and becoming sophisticated. Advances in ICT (via the internet), increasing globalisation and internationalisation facilitate the capability of valuation clients in obtaining sophisticated knowledge and stay up to date with trending standards observed in other, more developed countries and older professions. Clients bring to fore their level of sophistication in the asset valuation requirements. Working knowledge of the dimensions, levels, and implications of client sophistication in asset valuation practice could be a significant step toward developing sustainable asset valuation practice.

Research Limitation/Implication: This is a general review paper. Eventually, empirical results of the ongoing doctoral research on the matter may afford areas for more discourses.

Originality/Value: The study tends to be a deeper insight and a dynamic dimension of the behavioural study of client influence in asset valuation practice in developing economies.

This research explores the scale and nature of international and domestic investment flows in London, Paris, and Amsterdam, the three cities under investigation in the ESRC-funded ORA research project “What is Governed in Cities” (2019-2022). Using data provided by Real Capital Analytics/MSCI and other sources, we compare market churn and trends related to capital flows, existing residential investment, and new housing developments. The research charts the shifting landscape of institutional investment into residential property, and concentrates on the UK market, with Paris and Amsterdam included for comparison. 

The paper draws on literature from a variety of theoretical approaches to frame the investment flows across the three cities, considering real estate investment literature and institutionalist perspectives (Adams and Tiesdell, 2010; Theurillat et al., 2015), as well as the internationalisation of the real estate market (Fuerst et al., 2015; Falkenbach, 2009). 

Incorporating interviews with developers and investors, we analyse the key actors and locations for institutional investment across a 15-year time horizon (2005-2020) and highlight ways in which institutional investors have contributed to the creation and recreation of the urban form across the geographies of our three case study cities. The paper broadly examines investment trends and flows, as well as more detailed reflections on the strategies of particular investors, with a specific analysis of REITs. The presentation will reflection on market trends, in addition to a selection of the strategic narratives around the types of investor that are present across our European case studies of the residential market. The variations in regulation and governance, market knowledge, institutional actors and local real estate context across London, Amsterdam and Paris offer interesting insights into these investment actors and processes. 

The literature has shown that financial institutions and banks in countries give fewer loans due to the increases of financing costs with the increases in CDS premiums. As a result of this, a noticeable decrease in housing prices occurs. (Benbouzid, Mallick, & Pilbeam, 2018). In this context, this paper will examine which factors affect Turkey's CDS premium and how Turkey's CDS Premium affects housing prices. This article also covers the statistical relationship between global and local variables. In the studies carried out to determine the variables affecting Turkey's CDS premium, the volatility in CDS premium is more affected by global variables than local variables. However, it is thought that the higher volatility in premiums stems from political and economic problems.  A VAR model will be established using a data sample from November 2010 to January 2022. Local variables are the housing price index, CDS premiums, growth rate, real effective exchange rate, stock and bond returns, interest rates, risk appetite, external debt balance, banking sector performance will be examined. Global variables, which are VIX, S&P 500, US bond market, global risk appetite, NASDAQ variables, will be examined.

Out built environment is an important cultural asset. As Baukultur, it shapes our identities and defines our legacies (Swiss Confederation 2018, p. 12). But architecture or architectural design, as key elements in the creation of what is understood as Baukultur, is also an important process step in economic organization of real the estate firm.

Without answering questions of architectural design, buildings do not come into existence. Many of these questions do not have a direct economic relevance, or their economic consequences remain opaque. Quality may involve higher production costs, however increased expenditure on quality does not automatically yield into profitable investments or better architecture. From the point of view in real estate economics architectural design can be understood as step in the production process of real estate, a technical necessity for a functioning real estate market. From an cultural or sociological point of view however, architecture primarily serves the functioning of societies and establishment of cultural identity. It can be defined as a “social art” (Cuff 1992), involving many disciplines and stakeholders, including the real estate sector.

In recent years the commercial real estate sector has been scrutinized on the architectural quality of the buildings it produces. This has led to various kinds of initiatives and regulations that establish the importance of architectural quality and aim to provide incentives or regulations to those who assign for buildings to be built. But how is architectural quality managed in the real estate organization? What defines architectural quality, and how can this be implemented in company from an organizational point of view?

The thesis aims to provide an answer to these questions by means of a systemic exploration of high quality architecture as an objective for of economic organization of the real estate firm. It explores the concept of high quality architecture and which elements are essential for the process of real estate production. Thereafter it turns to a reflection on organisational principles such as principal agent theory and other organisational approaches derived from the field of institutional economics. Finally the thesis aims to concluded on a set of measures that can be implemented in real estate organizations, real estate and architecture education. As such the research contributes to the discussion on the implementation of ESG standards in the real state industry.

The paper is a (modified) continuation of the PhD project presented at the ERES Conference in Delft 2017: “The Imperatives of the Real Estate Industry and its Effects on Architecture and the Built Environment; Case Studies Presentation” (Kuil and Wellner 2017).

People’s risk perceptions are generally regarded as an important determinant of their decisions to adjust to natural hazards. Several studies have explored the effect of flood risk on property investments. However, mixed results were reported. This study conceptualises three non-monetary value characteristics of property investment (utility, desirability, and marketability) to examine the influence of flood risk on residential property value and the subsequent decision to invest. The study evaluates private investors’ perceptions of these characteristics and compares them with estate agents’ to understand how they influence investment decisions in areas liable to flooding in Lagos, Nigeria. The survey data was gathered through questionnaires administrated to private investors and estate agents within the study location in Lagos, Nigeria. Findings broadly show a consensus among the respondents on the contribution of each variable that makes up the usability, desirability, and marketability of property investment at risk of flooding. Out of these factors, the desirability to own/rent properties within flood risk neighbourhoods is significant in driving private investors’ decisions. Surprisingly, there was also a low level of trust and confidence in insurance activities among private investors.

House price dynamics, housing bubbles and housing crisis have drawn public attention. Aside from various policy implications the links between fundamentals and house prices has been tackled with some success both theoretically and empirically. Still new evidence is needed since Covid-19 pandemics has shifted many mechanisms governing housing market behaviour. 

We investigate the dynamics of house prices in Poland both on metropolitan level from 2000 to 2021. We test whether the price adjustments were caused by fundamental factors such as income, population growth, construction costs. 

The analysis covers two sub-periods of relatively high house price increases: 2004-2007 and more recent 2017-2021 sub-period. We check whether house prices are similarly related to fundamentals in both subperiods or whether there are distinct differences. Additionally, based on the economic literature we test and compare several housing bubbles indicators. 

The paper narrows the gap on housing bubbles on regional housing markets, especially in less mature economies.

Job satisfaction can be viewed as a general feeling about work or as a set of attitudes relating to different aspects of work. The nature of the job provides one of the traditional explanations for differences in job satisfaction. It is expressed by job characteristics according to Hackman and Oldham, that is, the degree of variety, autonomy, task identity, task importance, and feedback. It is expected that higher levels of each of these characteristics will positively translate into intrinsic job motivation, job satisfaction, and job engagement.  In addition to the importance of job characteristics, past research clearly indicates that attitudes toward work depend on cultural context, and levels of job satisfaction vary across countries and nationalities. Our research focuses on the job satisfaction experienced by valuers in Poland and Austria. Based on surveys and in-depth interviews with valuers from the two countries we identify differences in job satisfaction and the reasons behind them. Factors explored include general attitude to the profession, client relationships and pressure exerted on the valuer, the reputation of the valuation profession in society and the ability to balance professional and private duties. Our survey is the first to address the issue of job satisfaction among real estate valuation professionals.

The purpose of this paper is to enhance the granularity in the modelling of exogenous risk factors on financial performance of illiquid assets such as real property. In this context, financial literature has not connected those on alternative present value (APV) methods and on linear risk factor modelling (LFM) yet. The present piece fills this gap by setting up a formal method for applying this novel LFM-APV approach to modelling and pricing the risk for real estate investments. For this purpose, we design a theoretical framework consisting of a modern stochastic discounted cash flow model, which in turn is based on risk factors that are priced in using a linear factor model. Additionally, we illustrate the described pricing mechanism for standing investments based on real property data in an empirical study. Thus, we provide a clear algebraic solution to the problem of risk modelling for heterogeneous and illiquid investment positions such as direct real estate in a present value calculus. The practical implications to APV-LFM are the enhanced understanding of the functional relationship between underlying risk factors and the pricing of assets. The elaboration of the APV-LFM helps to have a better understanding of the functional relationship between underlying risk factors and the pricing of assets in practice.

It has become quite an accepted interpretation that higher buildings and more density allows more affordable housing. In economic terms, Glaeser’s thesis argues for more high rise buildings to overcome the affordability of housing by increasing the elasticity of supply and removing constraints on the building heights. In this context, the paper uncovers the impact of density led regulations and policies on the net housing market supply and availability of affordable housing through empirical evidence. 

The city of Mumbai offers a unique window into the correlations between housing supply and densities. The city allows, in certain circumstances, the development potential of a plot of land to be separated from the land itself and be made available to the owner in the form of Transferable Development Rights. These Rights (TDR) are utilized as  commodities that can be traded in the market to be added as extra built up in upcoming projects, the costs of which are linked to the value of land. The city of Mumbai has long been criticized for its dependence on using density regulations and its trade as the primary planning mechanism of housing delivery. Amidst a skewed supply of housing units in the city, where unaffordability is widespread, such mechanisms are accused of creating supplementary markets of density trading leading to a scarcity of housing units. 

Through the use of GIS and data driven analysis of the newly created (2016) Real Estate Regulation Authority’s (India) large dataset of housing projects, the study exposes the spatial flows and patterns of density and housing units across the city. As more construction density is being consumed by ever fewer people, the research demonstrates the geographic signature of the competing aims of policy viz., Decongestion of the city versus Adequate housing.

This paper explores the question in which market phases arbitrage between listed real estate companies and non-listed real estate funds is possible for institutional investors.

The term arbitrage implies the skimming of profits by exploiting price differences of assets in different markets. Applied to listed and unlisted real estate portfolios, this describes the fact that profits can be made by converting listed real estate portfolios into unlisted ones and vice versa. Arbitrage between listed and unlisted real estate portfolios is basically possible in two ways:

• Firstly, through a de-listing or conversion of a listed real estate company to a real estate special fund;
• Secondly, through a listing or IPO or spin-off of a special real estate fund to a listed real estate company.

For this purpose, the total return time series of listed and non-listed stocks in the same period are compared in each case. The FTSE EPRA NAREIT Developed Europe Office Index was used as the total return time series for listed European real estate companies and INREV data of special real estate funds with a comparable regional and sectoral investment focus as the total return time series for non-listed holdings. The period under review covers the periods from Q1 2007 to Q3 2018.

In doing so, the authors examine the data series for both non-risk-adjusted and risk-adjusted arbitrage. The risk-adjusted analysis is carried out using a modified Sharpe ratio, based on the one hand on a forecasted arbitrage time series and on the other hand on an arbitrage time series supplemented by a (supposedly) risk-free investment alternative. Both predicted arbitrage time series are set in relation to the "more" risk as the difference from the respective dispersions. In this context, only the forecasted arbitrage time series or the forecasted arbitrage time series supplemented by a (supposedly) risk-free investment alternative are responsible for the positive or negative characteristics of the modified Sharpe ratios, since the risk of EPRA is always above the risk of INREV.

For analytical reasons, this study deliberately abstracts from legal and operational restrictions and transaction costs of the respective conversion.

It can be seen that negative modified Sharpe ratios exist in three time periods - in these time periods, arbitrage against listed real estate companies can therefore be expected through investments in real estate special funds or through de-listing or conversion of listed real estate companies to real estate special funds.

Conversely, positive modified Sharpe ratios can also be identified in three periods - in these periods, arbitrage against listed real estate special funds can therefore be expected through investments in listed real estate companies or through listing or IPO or spin-off of real estate special funds to listed real estate companies.

The Covid-19 pandemic has had disruptive effects on the ways we live and work in cities. These outcomes have been widely discussed, both in the media and the scientific literature, using various underpinning assumptions and prospective thinking. Both academic and non-academic discourses further tend to support pre-pandemic housing forms and planning principles that are believed to be ideally suited for the so-called ‘post-pandemic’ city. This paper aims to confront these discourses with feedback received from residents living in such idealized live-work environments in Brussels (Belgium) to reflect on their possible relevance for the future. In practice, we identified acclaimed housing forms and planning principles after examining media sources and scientific literature. From there, we conducted a survey in a selection of real estate operations based on a typology of projects and environments to pinpoint first trends in terms of changing housing needs and residential preferences. The combination of the results of the review and the survey allowed us to critically discuss to what extent current housing solutions and planning strategies may foster adequate live-work urban environments and make suggestions for further research on the post-pandemic city.

This paper investigates the term structure of discount rates over the very long run, using the repeat-sales housing transactions and the unique housing contract of leaseholds in England and Wales. We estimate the price discounts and price appreciation discounts for 0-300 years leaseholds maturities relative to very long-run leaseholds and deprive the implied discount rates. We apply hedonic and augmented repeat sales regression for our empirical analysis under various types of restrictions. We find the results support the declining discount rate schedule, implying the benefit of the far future should be discounted at very low rates. In addition, although the declining trend remains consistent, poor and rich region have a different reaction in terms of QE. Before QE, the difference in the average discount rate in the two regions is only 0.2%. It increases to 2.1% during QE, with households in the rich region applying a significantly low average discount rate of 1%, suggesting that monetary policy could affect households’ preference of riskiness, especially households in the rich region.

The construction and real estate industry features long product life cycles, a wide range of stakeholders and a high information density. Information is not only available in large quantities, but also in a very heterogeneous and user-specific manner. Digital building documentation is partially available in some companies and even non-existent in others. The result is often analogue, unstructured building documentation, which makes the processing of data and information considerably more difficult and, in the worst case, leads to media disruptions between those involved.

However, the benefits of a lean, complete and targeted digital building documentation can be manifold. In particular, automated information extraction and further information retrieval are seen as having great potential. Information extraction as  an ultimate aim, requires a defined handling of analogue documents, transparent criteria regarding data quality and machine readability as well as a clear classification system.

The research project ML-BAU-DOK (funded by The Federal Office for Building and Regional Planning BBSR, SWD-10.08.18.7-20.26) presents the necessary preparatory processes for advanced digital use of building documentation. First, a set of rules is created to digitize paper-based documentation in a targeted manner. The automated separation of mass documentation into individual documents, as well as the classification of documents into selected document classes, is mapped using machine-learning. The document classes are consolidated from the current worldwide class standards and prioritized according to their information content. The project includes the evaluation of 600,000 document pages, which are analysed class-specifically with regard to two use cases, energy efficiency and life cycle analysis. The methodology ensures transferability of the results to other use cases.

The key result of the ML-BAU-DOK is an algorithm that automatically separates individual documents from a mass scan, assigns the individual documents to defined document classes, and thus reduces the amount of scanning and filing required. This leads to a classification system that enables information extraction as a subsequent goal and brings the construction and real estate industry closer to a Common Data Environment.

The aim of this study is to analyze the role of Chinese foreign direct investments (FDIs) in the dynamics of real estate in the Asia-Pacific region after the global financial crisis. We use a linear asset pricing model including macroeconomic risk factors and develop a metric to measure FDIs in the real estate sector. Based on panel econometrics, our robust results report that Chinese FDIs significantly influence Asia-Pacific region’s public real estate markets, shedding new light on China’s economic internationalization in the Asia and the Pacific region. We also provide strong evidence that our findings are not driven by a reverse causality phenomenon, whereby a country with superior performance of public real estate sector is in better position to attract Chinese FDIs.

The goal of this paper is to show whether the Greater Paris housing market is integrated and can be defined globally or whether housing submarkets are present. Therefore, our aim is to understand whether macroeconomic shocks are homogeneous across the metropolis and to check for the presence of ripple effects. For this purpose, we implement a panelvector autoregressive model at the metropolis and submarket levels to capture, through impulse response functions, the consequences of macroeconomic shocks on housing prices. In a second step, we perform a spatial panel-vector autoregressive model to test for the presence of ripple effects and to check for robustness. We find the presence of housing submarkets and hence heterogeneous reactions of house prices to macroeconomic shocks across submarkets. Finally, we notice the presence of ripple effects in some submarkets.

Maximising the added value of real estate (RE) for the organisation, has been subject of study of many scholars in the field of Public Real Estate Management (PREM). Through PREM, public organisations such as the Dutch National police, aim to maximise the added value of the RE portfolio consisting of over 1.000 objects. For the Dutch National police, sustainable development of the portfolio has, in the past 15 years, become increasingly important. The growing importance of this RE value can be recognized through its prioritisation relative to other values, such as supporting user activities and attractiveness. And through an increased number of criteria RE managers need to take into account when striving for sustainable development. Both the increase in comprehensiveness and prioritisation of sustainable development, have an effect on the alignment process and specifically which values are traded off for others. Although these trade-offs are decisive for how RE ultimately should enable organisational performance, little is known on how sustainable development has affected the trade-offs being made. Thus, this research provides an insight in the trade-offs between values and whether patterns in trade-offs can be found in the past 15 years, using Dutch police stations as case study. To uncover these effects and patterns, first PREM values are operationalised into a framework of criteria and key performance indicators. This framework is used to measure the performance of Dutch police stations realised in the past 15 years, which allows for a comparison. This comparison reveals the ‘proof of the pudding’: which values were traded off for others? By doing so, this research provides a comprehensive insight into the trade-offs RE managers made while striving to maximise the added value of RE.

The family law courts in Australia are currently ill equipped to assess property valuations in regard to divorce. Judges face conflicts in the system, and there appears to be a lack of clarity regarding current market valuations. Judges look at valuations from both sides, resulting in outcomes that can be harmful to litigants and wasteful to society. While judges face the same valuation uncertainty as the parties themselves, expert witnesses will consequently continue to be called by the courts. This situation has prompted the interest in this study to evaluate the necessity for a review of court decisions.

Geographic Information Systems (GIS) and Machine Learning methods are widely used in mass real estate valuation practices. Focusing on the physical attributes of properties, locational criteria are insufficiently used during the price prediction process. Whereas, locational criteria like proximity to important places, sea or forest views, flat topography are some of the spatial factors that extremely affect the real estate value. In this study, a hybrid approach is developed by integrating GIS and Machine Learning for automated mass valuation of residential properties in Turkey and the United Kingdom. GIS-based Nominal Valuation Method was applied to produce a land value map by carrying out proximity, terrain, and visibility analyses. Besides, ensemble regression methods like XGBoost, CatBoost, LightGBM, and Random Forest are built for price prediction. Spatial criteria scores obtained from GIS analyses were included in the price prediction data for feature enrichment purpose. Results showed that adding locational factors to the real estate price data increased the prediction accuracy dramatically. It also demonstrated that Random Forest was the most successful regression model compared to other ensemble methods.

Choosing a location on retail streets means being next to many other brands. This proximity allows companies to reach more users and foot traffic. Furthermore, this costs firms as in paying higher rents. It is difficult to predict the rents on the retail streets. Therefore, rent estimation studies are much more critical when necessary to make estimates throughout the country.

In the paper, the brand mix variable, which is a significant factor in determining rent in shopping centres, was also tested for retail streets. For the brand mix definition, the brands in the catchment areas of the retail stores were used. In the hedonic rent model, physical variables of the retail stores are included as well as spatial variables.

As a result of the model, the effects of physical variables of stores on rent are explained. In the model results, it was seen that being a single storey increased the unit rent of the store, while the more gross leasable area and building age negatively affected the unit rent. The relationship between the brand mix and the rent is positive. However, the model's explanatory power, which is built by considering only physical variables, is higher. It is already known that internal variables have significant effects on rental values. However, even if the brand mix cannot be used alone in determining rent, it is understood from the model outputs that it is an important determinant. By diversifying the location data, it will be possible to produce more inclusive models.

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. In order to achieve the intended climate targets for the building sector, it is therefore necessary to use refurbishment options for energy-efficient modernization as well. In addition, it must be taken into account that the younger the building is, the lower the potential for energy savings and thus the economic sense due to lower energy cost savings. The most challenging modernizations are all yet to come. As the refurbishment cycle is essential, the question arises as to how high the theoretical refurbishment rate is, how high it is effectively, and how high it must be to achieve the climate targets for the residential building stock. This paper aims to model the basis for the target-oriented transformation of the residential building stock, so that scenarios in line with climate goals for the residential building stock can be simulated depending on the necessary economic incentives. Using current statistics and the past development of the German residential building stock, central parameters like living space, new construction, deconstruction and the modernization rate are modeled endogenously. The modernization rate represents a full modernization and thus allows an easy connection of the model with energetic parameters for building classes defined in the European web database TABULA. The results are of relevance for modelling the building stock and deriving suitable modernization measures also in other countries.

The fixity of location makes the types of surroundings and neighbourhood in which a property situates affect its price. There is a usual saying by real estate agents that the three key factors that determine the price of a house are location, location and location. Considering the importance of location in determining the prices of properties, this paper aims to evaluate the effect of locational characteristics on the prices of undeveloped land in Ile-Ife city, Nigeria. This is with a view to developing a model to predict the prices of properties. Using a survey approach, information on locational characteristics and sales prices of undeveloped plots of land (N = 31) transacted between 2021 and 2022 within five nuclei/ residential neighbourhoods (Parakin, Modomo, Moremi, Eleweran, Fashina) in Ile-Ife were obtained.  The data obtained were analysed using mean and multiple regression with the aid of GIS tools including ArcGIS, google street map, QGis, and Google Earth. The regression analysis, using prices of plots of land as the dependent variable showed that in all the neighbourhoods, distance to locational attributes (nodes of interest such as secondary school, supermarket, university, church and motor park) and location accessibility were significant in the determination of the price of properties in the selected neighbourhood. However, the effect of the locational attributes on each of the locations was different. The study concluded that locational attributes had a positive impact on the determination of the price of properties.

After II World War a subsidy system called 1. Förderweg was implemented in West-Germany to cope with the challenges of housing shortage after and due to the war. In the late 80ties of the last century this policy was left behind. During the first decade of this century public housing policy was based on the conception `Germany is built´and therefore there is no need to build new dwellings. After the GFC and the forthcoming European development, heavy capital inflows, low interest rates, and advantages within the common currency Germany experienced a relatively strong growth and with rather inflexible rents in the housing stock a felt shortage of affordable housing. Although migration is the dominant political topic, housing policy is becoming important, again. This paper based on a report for the Bundesverband der Deuschen Wohnungs- und Immobilienunternehmen (GdW) identifies possibilities of effective housing policy by separating the three main instruments of housing policy, the subsidy of the demand, the purchase of rights for housing, and the subsidy of the supply.

Green leases in commercial real estate have gained widespread attention from real estate investors in recent years. As an appendix to the lease contract, a green lease is designed to reduce energy consumption in buildings and ensure compliance with climate targets in their markets. Using a unique database, we study 7,246 leases in 376 commercial assets to determine whether green leases lead to higher investment returns.  Using a propensity score matching method, we find significant green lease premiums on investment returns in commercial assets. A 1% increase in green leases raises the rent by 0.23% and the net asset value by 0.38%, and decreases the operational expenditure ratio by 0.02% on average. The highest premiums were observed in Germany, with increases in rent of 0.40%, and in France, where the net asset value increased by 0.56%. The highest premium on leakage was 0.02%, in Germany, and the highest premium on yield was -0.01% in France.

The purchase of a house or apartment and the related choice of a mortgage provider and product constitute a pivotal financial decision for many households. Accordingly, mortgage loans represent the largest proportion of household debts in most OECD countries and an important proportion of the retail banking business. Even though homeownership in Switzerland is with a homeownership rate of 40% remarkably low, the Swiss mortgage market is one of the largest in the world. This is related to the fact that homeowners can borrow up to 80% of the value of their property. Also, Swiss property prices are on average relatively high in comparison to other countries, and they have been dramatically increasing over the last years, rendering the acquisition of residential properties even more difficult. According to the Swiss National Bank, the outstanding volume of the domestic mortgage loans in Switzerland amounted to 1.07 billion Swiss francs by the end of 20201—accounting for almost 150% of the country’s nominal GDP—with 75% of bank credits concerning mortgage loans. 

In view of these circumstances, the mortgage market in Switzerland is very attractive and represents a major source of profit for mortgage loan providers. the otherwise traditionally conservative mortgage market in Switzerland is gradually manifesting certain dynamics. We observe the emergence of new players and products. Even though banks rank first as lenders for real estate purchases—accounting for 95% of the market—they are no longer the only option for Swiss households. Alternative providers, such as insurance companies, pension funds and crowdfunding platforms, have been steadily gaining ground in the market. New or revised market rules, along with further disruptions are anticipated in the housing and mortgage markets, given the technological advances, as well as the currently notably low interest rate environment—conditions that are expected to encourage further market penetration. The hitherto reserved role of mortgage brokers also seems to be changing, and an increasing number of households rely on corresponding service providers, whose offer clearly increases market transparency. Interestingly, we also observe differences in particular with respect to the role of mortgage brokers between the German- and French-speaking part of Switzerland. The language regions are related to existing cultural differences, which are also reflected in these financial choices. These facts lead to the conclusion that Switzerland is a very interesting market to study the mortgage choice behavior of private households.

Main research questions, data and methodology

How do households choose their mortgage supplier? How is this decision related to their creditworthiness and the value of their property? What sociodemographic characteristics of the households and geographic factors come into play? How does financial literacy and attitudes such as risk aversion affect mortgage decision-making? Which households get credit from their first-best mortgage provider, and which ones shop around? Given the nature of the credit allocation problem, that is characterized by asymmetric information, do we observe a selection process with potentially harmful consequences for the economy as a whole? Taking into consideration (i) the importance of mortgage decisions for the households, (ii) the high relevance of the mortgage business for retail banks in Switzerland, and (iii) the dynamic market environment with the new supply possibilities and the expected intensification of the competition among the mortgage providers, it is important to have a good understanding of the mortgage choice behavior of the borrowers. The purpose of our study is to understand the mortgage choice behavior of private households as function of the sociodemographic profile, their level of financial literacy and their degree of risk aversion. 

Our results will be based on a large-scale and unique online survey with 1’000 respondents from the German- and French-speaking part of Switzerland. We will use a regression framework to analyze the mortgage provider choice of private households in Switzerland. The expected results will provide new insights about the preferences of households with respect to the different mortgage providers as a function of household-specific, institutional and market-specific characteristics. The insights will not only be interesting from an academic point of view, but they are also addressed to practitioners who are able to better understand the changing market environment in order to optimize their mortgage offer. Finally, the regulatory authorities, which are keeping a close eye on the mortgage market, especially nowadays with the existing fears of inflation, will be able to draw interesting conclusions from the results.

We analyze the impact of newly developed malls on the shopping trip behavior of nearby residents. Using the difference-in-differences approach and big data from a major taxi company in Singapore, we find that households residing within 800 meters from the new mall are significantly less likely to take taxis to other shopping destinations after the mall opening. This travel behavior change encompasses both intensive (share of the number of shopping trips out of total taxi trips originated from each residential building) and extensive (share of shopping trip distance out of total taxi trip distance) margin responses. We further demonstrate that the magnitude of this shopping trip reduction is more significant during PM peak hours and for residential buildings that are located farther from the Central Business District and in less self-sufficient communities. Our research provides suggestive evidence on the significant role of neighborhood retail amenities to the change in mode and destination choices for shopping. An important policy implication is that improving self-sufficiency for suburban neighborhoods could not only enhance the wellbeing of their residents but also increase aggregate welfare by reducing the level of congestion.

The research NOMAD, Nomad MAnagement of Urban Development - The value of temporary communities, is exploring the impacts of temporary use on urban areas and the role of urban nomads in the development process. Currently, there is a lack of affordable space for housing and workplaces, while cities have many vacant spaces, representing a significant potential for new activities. In Europe, more than 38 million dwellings were unoccupied (permanent or seasonal, or secondary residences). From the 1970s to now, the squat, anti-squat and co-management forms of housing occupation movements represented a strong space demand. Young people, activists or creatives, claimed space and experimented with co-managed forms of living. These temporary communities are urban nomads, voluntarily or not. They temporary inhabit spaces for a short time span, usually for low rents with different forms of public or private agreement, and generate value through active use and management of space, but eventually have to move if higher rents can be achieved or the space will be redeveloped. The reuse of abandoned spaces improves urban sustainability and contributes to activating the principles of the circular city, by recovering discarded real estate. In fact, buildings and areas, waiting for new permanent functions, are temporarily wasted. What happens in the meantime (months or years) in these spaces has a strong impact on urban dynamics and values. In virtuous cases, nomadic communities generate vibrant neighbourhoods, attracting new activity, improving street safety, generating intangible urban values, and boosting real estate markets, eventually leading to gentrification. As a consequence of increased real estate values and gentrification, the temporary users who co-produced the increased values, have to move again and start again in often precarious conditions. This is the paradox that this research will focus on.

The paper focuses on the case of Art33 - Cultural Hub. In 2015, the “Gioco Immagine e Parole” association won the call for proposals "Giovani per la valorizzazione dei beni", with the project "GiovaniArtistixGiovaniUtenti", co-financed by the Municipality of Naples and the Presidency of the Italian Council of Ministers, Department of Youth and National Civil Service. ART33 is the first cultural hub in Campania Region, created to support art and culture in the eastern area of Naples - San Giovanni a Teduccio neighbourhood, through the regeneration and redevelopment of some spaces of a former school building part of the 47° Circolo didattico Enrico Sarria de Robbio. The centre activates processes of social inclusion, urban regeneration and cultural innovation on a local scale, hosting various temporary communities and cultural projects. This paper aims to reveal which values have been generated by ART33 in the San Giovanni neighbourhood through the practice of the school adaptive reuse. The paper is part of a research that aims to understand how complex values are created in urban redevelopment, and to what extent temporary reuse contributes to accelerate value development.

Current trends in house prices are an important input into decisions on monetary and fiscal policy and macro-prudential supervision. However, long lags in the availability of transaction data imply that current transaction prices are generally unavailable for this purpose. These information lags can be quite long; e.g., in Poland, the current registration lag lies at over 200 days. We show how micro-level list price data can be used to now-cast the current direction of transaction prices in the residential property market and thus fill a vital information vacuum. In particular, we show that to estimate the current direction of the transaction price index, a simple model based on current list price changes outperforms a range of other model specifications based on lagged transaction data. We illustrate our method and results with the help of a detailed list and transaction dataset that covers two large Polish cities (Warsaw and Poznan) for over two decades. The multiple up-and-down movements of the Polish property market during our sample period provide an ideal setting to test the performance of our approach. Our findings imply that list price indices can provide valuable “real-time” market estimations. Employing them in conjunction with official transaction price indices can significantly reduce the information vacuum of policymakers.

The office market is one of the most inefficient real estate markets, and it takes time to adjust. Factors of it include high transaction costs, constraints due to long-term contracts, and time delays in supply. Research on the adjustment mechanism in real estate markets has been accumulated over many years, mainly in Europe and the United States. In recent years, research has been conducted in developing countries. However, the main focus of these studies has been on the market's response to demand and supply shocks and the speed of rent adjustment, and there have been few studies on the factors that cause market inefficiencies and their effects. In addition, although the Tokyo office market forms one of the largest markets in the world and attracts a great deal of attention worldwide as a target for investment, there have been very few academic studies on the dynamics.

This study aims to quantitatively clarify the dynamics of the Tokyo office market from 2000 to 2015 and the factors that cause market inefficiencies.

We applied the rent adjustment process model devised by Englund et al. (2008), which considers the interaction between rents, stock, and vacancy rates, to data divided into four submarkets according to building size, and discussed the results in combination with the differences in market characteristics by submarkets.

Our result shows long-term contracts and supply constraints contribute to market inefficiencies more than information asymmetry. By comparing the results with those of other countries, it became clear that Japan's unique contract system with fewer restrictions on the tenant side - the standard tenancy contract - speeds up the market adjustment. In addition, the results imply that the Tokyo office market may still have issues in terms of information asymmetry and low liquidity in the labor market.

In today's knowledge work, employees in companies pursue a variety of work modes. During the COVID-19 pandemic, the home office was explored as the most commonly used work location and questions about the role of the office were addressed (e.g., Nappi and Ribeiro 2022).  Employees make their choice of work location much more consciously and increasingly consider where they would like to pursue what type of work. Nevertheless, the relevance of the office as a place where work and people are locally embedded continues to be frequently attributed, rather than its disappearance predicted.

New user demands such as the changing environment of companies in need of interacting faster, more agile and leaner are driving changes within the office sector. If the needs and requirements for future-oriented and user-oriented office space are met, positive effects on employees and, conversely, on the success of the company can be realized. 

The purpose of corporate real estate (CRE) is expanding from standard office space, as a place of pure space provision, to a place where productivity and employee well-being are equally maintained. It's becoming more and more apparent that employees visit the corporate office for social interaction, meetings and networking, while staying in the home office for concentrated individual work. As a result, the layout and space configuration of offices will have to change significantly in the future. To provide this opportunity, a variety of different spaces must be available in appropriate proportions, for example individual workstations, group workspaces, and spaces for social encounters. 

In this research project, based on a classification of employee work types, needs and requirements for future-oriented and user-oriented office space are derived. For an empirical analysis, 754 knowledge workers from one of the largest German pharma companies were surveyed. A cluster analysis, is used to show how office space layout can be derived based on different work modes. 

The results show that based on the derived work modes from the cluster analysis six different work types with specific characteristics and preferences occur. Based on the results, CRE managers can estimate which layout configuration is needed for each work type. Exemplary layouts for each work modes are shown which differ in number and size of workstations, meetings rooms and collaboration space. Depending on the configuration of work modes in a firm, the optimal space layout and capacity of workstations can be estimated by using these exemplary layouts. The paper has practical relevance for deciding what types of space should be made available and in what proportions as part of the real estate strategy based on work modes performed.

With companies locating on university campuses more and more, many universities are designing interactive places where different campus users can meet, such as faculty, company employees, and students. By increasing interaction between these campus users, it is pre-supposed that this will lead to more cooperation and knowledge sharing, resulting in more innovations and knowledge valorisation. 

A campus’ spaces and services have a significant impact on interaction. These may block or facilitate interaction between different campus users. Adding to the body of knowledge of critical success factors (CSFs) for campus interaction, a survey was distributed under campus users of three Dutch university campuses. Due to Covid-19 restrictions, the survey was distributed online, through the university email addresses of 4.312 campus users. This resulted in 492 responses, identifying 224 location points where meetings between companies and knowledge institutions took place. Respondents were specifically asked to indicate only unplanned meetings, where a connection was made that was beneficial for knowledge sharing. Respondents also indicated what space and service factors were most important in facilitating this meeting (critical success factors).

After analysing the results, the indicated locations show that most meetings take place within the respondents’ own buildings, regardless of the indicated quality of the spaces or services. This may be due to time and travel constraints. There are however some buildings that do successfully attract these type of meetings: buildings with a strong theme (e.g. Energy) and company buildings. A regression analysis, conducted in SPSS, also showed that there a no or only very limited differences between different types of campus users, and that general conclusions can be drawn from combining the data of the three different campuses.

These critical success factors were compared with those found in the literature and show that there is a match between the CSFs identified by practitioners (Campus facility directors) and campus users. 

Comparing CSFs from literature, practice and campus users, this study allows for more effective application of CSFs in campus design policies. A framework for future studies on CSFs for interaction on campuses is provided. The study is limited as only campus users from knowledge institutions respondent to the survey, a follow up study with respondents from companies is recommended.

The implementation of smart technologies in the built environment poses many new issues to the real estate sector. Among these issues is behavioural control of building occupants thanks to increasingly sophisticated smart real estate’s technological apparatus. Behavioural control in digital space (e.g., the internet) has generated passionate arguments about human dignity. Stances founded on technology or ethics foster a Manichean perspective, either by focusing on technological innovation and ignoring the negative consequences of embedding smart technology in human lives for the former, or by condemning the very use of digital technology altogether in the name of human freedom for the latter. By doing so, they tend to obscure our ability to rationally assess the impact of technology on space users in smart buildings. This paper applies an economic approach to determine the nature of control in smart real estate and proposes the blueprint for a code of digital governance in the real estate sector. Based on Lecomte (2019, 2020, 2021), it concludes by ascertaining the need for regulators to step in, for instance through tougher ad hoc privacy laws designed for the built environment.

Using a natural experimental setting where a solar PV subsidy is assigned randomly to applying households, we estimate the impact of subsidy provision on the adoption of solar PV, installed capacity, timing of the adoption and energy consumption. The results imply that the provision of subsidy leads to an 11.9 percent increase in the probability of adopting solar PV among the households who applied for the subsidy. The findings also indicate that the households who are accepted to the subsidy program invest in an 8.9 percent larger installation as compared to rejected households, and adopt solar panels 55.9 percent faster. Finally, examining the subsequent electricity consumption of the applicants, we report that subsidy provision leads to a 3.74 percent decrease in households' electricity consumption as compared to the rejected applicant group after 1 year, and a 3.93 percent decrease after 5 years.

Purpose – The development of adaptable and circular buildings has been argued as a means that could enable built properties to withstand numerous societal challenges that could occur in the future. This study intends to reveal the extent in which circularity and adaptability related strategies are being operationalised in a selected sample of case studies in the Netherlands.

Design/methodology/approach – A theory-practice oriented approach is followed. Literature review is conducted to define a set of potential strategies for developing circular and adaptable buildings. A selected sample of case studies in the Netherlands will be analysed, using in-depth interviews and archival research as main data sources. Cross-case analysis of the findings will be conducted and examined against the literature. 

Findings – The initial screening of the cases points out that spatial multifunctionality, use of demountable products and secondary material, and material reuse are common strategies that are carried out to operationalise circular and adaptable strategies.   

Quality/value – The study has the potential to expand the boundaries of the relevant bodies of knowledge by providing empirical evidence and understanding of the current status of operationalisation of adaptability and circularity related strategies in a sample of Dutch properties. This outcome will contribute to refine and expand theoretically conceptualised frameworks.

In this paper, we analyse the influence of housing policies on the relationship between homeownership and life satisfaction. Using cross-sectional multi-level regression analyses, we estimate the effect of homeownership on life satisfaction conditional on the financial burden of a mortgage of a self-occupied home. Further, we show that in societies where the owner-occupied home plays an important role as a tradable good and investment, the satisfaction gap between owners and renters is larger than in societies with a well-developed rental sector with high security of tenure. We conclude that the commodification of housing is an influential moderator on the association of ownership and life satisfaction.

Infrastructure has become an important part of institutional investors´ alternative asset portfolios all over the world. This paper documents that larger pension funds, public pension funds, and pension funds with a larger allocation to alternative assets are more likely to invest in infrastructure, and to manage it internally. Smaller pension funds make more use of intermediated external investment approaches, face higher investment costs and realize lower returns. We observe significant economies of scale for the investment performance of pension fund investments in infrastructure, while financial intermediation does not seem to lead to worse performance. Overall, as an institutional investment, infrastructure has proven to be the best-performing asset class over the 2007-2018 time period. The increase in infrastructure allocations by pension funds seem to be justified from a risk/return point of view.

Examining German residential construction activity using quarterly flows of building permits, this study investigates the linkage between politics and housing supply. Applying separate dynamic time series regression models for commercial property developers and owner-occupiers proves the heterogeneity of decision-making concerning considered external factors. The approach finds quarterly flows of building permits for residential property developments to be negative correlated with significant changes in election polls triggered by exogenous shocks. Owner-occupier building activity is found to be positive associated with household’s savings rate appearing to increase during times of crises. Slumps in construction activity are further identified during COVID-19 lockdown periods. The study results prove the impact of political surrounding factors on decision making processes related to residential construction contributing to the comprehensibility of German construction activity.

In communities with a growing population the structure of housing can easily be adjusted to changes in demand, through building new dwellings of the type for which demand is increasing. In communities with a shrinking population, by contrast, both the total supply and the structure of housing is given, inherited from previous decisions on the number and type of dwellings to build. As the population declines an increasing mismatch between the types of housing supplied and demanded may therefore arise in some communities. We use a panel data set of 430 Norwegian municipalities for examining these issues. Almost 50 percent of the municipalities have a shrinking population. We use data from municipalities with increasing population to build an econometric model that explains the structure of housing in such communities. This model provides information about the optimal structure of housing and is used to predict the optimal structure of housing in municipalities with a shrinking population. Next, we use the discrepancy between the actual and predicted housing structure to estimate the mismatch in housing structure in the shrinking municipalities. Finally, we discuss the implications of a mismatch in the housing market. Presumably, with declining populations in many countries, even at the national level, mismatch in many local housing markets may become an even more serious problem in the future. A continuing urbanization will make this problem even more serious.

Automatic valuation systems have found several applications in real estate market. It is common to build such systems on historical data aiming at predicting new properties in a comprehensive manner. In recent days it is common that the data are collected not based on valuations but from other sources and, hence, they can be incomplete. The paper aims at examining the effect of such incomplete data in the prediction accuracy. We apply a nearest neighbor imputation technique to see how the proportion of missing information can affect the results but also to reveal for separate variables their impact and importance in the derivations. We make use of a real valuation data set from a Greek financial institution, and we see how much the proportion of missingness impacts the results but also that there are variables that when missing it is very difficult to impute them.

A safe haven is an asset that is unrelated or negatively related to other assets in highly uncertain or turmoil markets.  Therefore, a safe haven asset has the ability to mitigate risk and increase returns in extreme market conditions.  A hedge is an asset that is negative related to other assets, on average, but does not have safe haven features during periods of market stress.  While, a diversifier is an asset that has an imperfect positive correlation with other assets, on average, and like a hedge does not offer safe haven features.

While, private real estate provides diversification benefits to stocks it may also be a hedge or safe haven asset as it is a hedge against inflation and the majority of real estate returns comes from rent payable in all market cycles.  Yet as far as the author is aware, no study has examined whether private real estate is a safe haven or hedger in the US.  Using monthly transaction based real estate data and both OLS and quantile regression we find that private real estate is both a “weak hedge” and a “weak a safe haven” asset.  In other words, private real estate is more than a diversifier.  

This paper provides a new forecasting methodology for commercial real estates in Istanbul using social big data. Big data has gained popularity as a tool for the growth of real estate research in recent years. Location-based social networks (LBSNs), in particular, provide an excellent potential to demonstrate the characteristics of metropolitan cities and human activities within. Whilst there is relatively limited research on the relationship between social big data and real estate values, most of the existing research focuses on residential properties. This paper aims to discover the potential of social media data to forecast the future rent/price levels of retail properties in İstanbul. Two different LBSN platforms, Instagram and Twitter, are chosen as the social media data sources. For the timeframe, June 2019 - May 2021, 16 million geo-tagged Instagram posts and 230 thousand geo-referenced tweets from a total of 174 thousand venues are collected by the authors. The data set is clustered by relevant districts of Istanbul and the spatial distribution of social media content is observed. Finally, the data sets are combined with the commercial real estate data temporally for the districts. Multivariate time-series analyses are conducted to obtain the optimum prediction model and interval. This method increases the accuracy in rent and/or price predictions by selecting the best exogenous variables and forecasting models for each district, where applicable. This paper demonstrates the significance and the leveraging potential of adapting human activities to the decision-making processes of the commercial real estate sector.

The most widely used approaches in hedonic price modelling of real estate data and price index construction are Time Dummy and Imputation methods. Both methods, however, reveal extreme approaches regarding regression modeling of real estate data. In the time dummy approach, the data are pooled and the dependence on time is solely modelled via a (nonlinear) time effect through dummies. Possible heterogeneity of effects across time, i.e. interactions with time, are completely ignored. Hence, the approach is prone to biased estimates due to underfitting. The other extreme poses the imputation method where separate regression models are estimated for each time period. Whereas the approach naturally includes interactions with time, the method tends to overfit and therefore increased variability of estimates. In this paper, we therefore propose a generalized approach such that time dummy and imputation methods are special cases. This is achieved by reexpressing the separate regression models in the imputation method as an equivalent global regression model with interactions of all available regressors with time. Our approach is applied to a large dataseton offer prices for private single as well as semi-detached houses in Germany. More specifically, we a) compute a Time Dummy Method index based on a Generalized Additive Model allowing for smooth effects of the metric covariates on the price utilizing the pooled data set, b) construct an Imputation Approach model, where we fit a regression model separately for each time period, c) finally develop a global model that captures only relevant interactions of the covariates with time. An important methodolical aspect in developing the global model is the usage of model-based recursive partitioning trees to define data driven and parsimonious time intervals. 

In the past few years Africa countries have developed infrastructure to a larger scale than they have ever done in the last 40 years or so since independence.  Though the improvement is welcome, two sectors have been completely ignored. Firstly, the physical structures that are the terminus, the bus stops and parking spaces within the terminal. In many instances facilities such as waiting areas, restrooms, organized shopping areas, luggage deposits and freight areas are lacking or poorly planned. Safety and security concerns have arisen, especially for long distance night travel, passengers stay in the buses until day-break or hire a hotel room. Those who venture out, have reported cases of being mugged and others almost killed. Secondly is the issue of policy and institutional goodwill from government entities to provide and maintain such facilities. The current situation shows that interest is only in the levying of parking fees payable by the travel companies, and to meet these demand, allocations of parking spaces are made along main roads creating bottle necks and traffic snarl-ups. These locations are also not ideal for provision of terminals and supporting facilities.  

The paper looks at the current situation in an effort to find out the existence, adequacy and management of these facilities.  It recommends that the public transport sector must provide bus terminus in urban areas that is properly designed, having proper places to eat, waiting rooms/lounges and clean restrooms.  All these places should ensure the security of the passengers and their families. There should be adequate parking for passengers’ cars and drop off zones.  In the rural areas, the same facilities should be replicated at a smaller scale. When these facilities are provided they must be maintained and managed properly by a facilities or property manager. Hence the need to include the management of these facilities in the management courses taught at institutions of higher learning.  The future of mobility in Kenya is not just about building of roads and railway infrastructure, it is about a proper interchange and provision of the last mile.

The housing industry in Germany is experiencing a profound and multidimensional transformation process, caused by changes in technology, economy, and society. These changes are based on megatrends that have their origin in the global environment. The housing situation is also subject to this transformation process, with the result that housing and location preferences as well as qualitative and quantitative housing needs are changing. In addition to digitalization and socio-demographic changes, growing environmental awareness is a widely discussed megatrend in the relevant literature. Homebuyers are subject to a number of environmental requirements, such as increasing energy efficiency or using renewable energies. However, little is known about the psychological antecedents and the impact of general environmental awareness regarding the purchase intention of sustainable housing.

By using the theory of planned behavior (TPB), the aim of this study is to identify the effects of attitudes towards the behavior, subjective norm, and perceived behavioral control on the purchase intention of sustainable housing in Germany. Furthermore, the TPB is extended by incorporating environmental awareness as a moderator variable.

Based on literature research, a survey is conducted among 1,000 homebuyers in Germany. With the help of a confirmatory factor analysis (CFA), constructs derived from the relevant literature are first tested for reliability and validity. This is followed by a hierarchical regression analysis which proceeds in three steps. Initially, only the baseline model including control variables is integrated into the regression analysis. Thereafter, the baseline model is extended by constructs of the theory of planned behavior. Lastly, the moderator effect of environmental awareness is integrated to predict the purchase intention of sustainable housing.

The results emphasize the importance of environmental awareness in the decision process of purchasing houses. Furthermore, the study provides important implications on which psychological factors affect the intention to purchase sustainable housing in Germany. These results can be used to better predict actual sustainable housing purchase behavior and to better evaluate different environmental factors that determine housing prices.

The increase in CO2 emissions leads to rising temperatures and a change in the climate. The change in the climate is connected to various risks. These risks can be either labeled physical climate risks or transitional climate risks. 

Under physical climate risks for the real estate industry one can summarize direct challenges like heat, droughts, flooding, storms etc. but also indirect effects, like that the insurance against these damages become more expensive or impossible and that finance opportunities will be costlier. Furthermore, potential of conflicts through water shortage, famine, migration could be seen as an indirect physical climate risk.

Transitional climate risks are connected to legislative changes and further rises in regulations as reaction to climate change and to increases in CO2 emission costs. This leads to changes in relative prices and some business models, products and services become obsolete but also to new opportunities arise. Reputational risks or judiciary risks could be linked to these transitional risks.

Ways to quantify these risks are discussed in this study. Thereby it is possible to approximate the damage of physical climate risks to buildings through calculations based on the values covered by insurances. However, it is more difficult to quantify indirect effects like production losses or limitations in usability. Various parameters are used within climate models to estimate the risks for property. These can be combined to deduct a monetary magnitude of climate risks.

Our research is based on econometric models, nonetheless, it serves to verify the rationality of participants (investors) in the office market in Warsaw. Investor, when deciding to start a construction of a new office building, should take into account not only the potential yield, but also the potential risk associated with market conditions reflected by vacancies. In the office market equilibrium vacancy rate is equal to the natural vacancy rate. The natural vacancy rate was determined by various authors based on various models. Nowadays, it is agreed that the natural vacancy rate is local in nature and can fluctuate over time.

In the study we use quarterly time series of the Warsaw office market (stock, supply, vacancy rate, rents, yields) along with demand data and financial data (interest rates) starting at Q1 2001 and Q1 2007, ending Q2 2021. To make the analysis and inference more robust to missing data, in this paper, we determine the natural vacancy rate based on five approaches often cited in the literature (Voith and Crone, 1988; Wheaton and Torto, 1988; Hendershott, 1996; Hendershott et al., 2002; Englund et al., 2008; McCartney, 2010; Ke and White, 2013). After determining the natural vacancy rate, we formulate a model in which the supply of office space is explained by the difference between office yield rate and risk free interest rate, as well as, the difference between market vacancy rate and natural vacancy rate. Using autoregressive approach (VAR, VECM, Treshold autoregression) we verify the relationships including shocks, leads, lags and asymmetry. The conclusions of the analysis should allow us to answer the question whether investors in the Warsaw office market do make rational investments or are systematically wrong, causing overbuilding.

A methodological shift in both research and practise is now required to plan and manage low-carbon investments in large real estate assets, in order to satisfy the European energy efficiency criteria recently (see EU Directive 2018/844). Even though a rapid increase in large-scale building retrofit rates is expected, new strategic methods should analyse entire building portfolios rather than single-building perspectives in order to determine the amount of energy retrofit that will result in the greatest overall value.  In this paper, discussions on housing decisions is built for the assessment of investment in both monetary and non-monetary benefits of a retrofit expenditure, as well as determining the best efficiency programme across a large building portfolio. In terms of monetary benefit, the savings generated by the investment over its entire life cycle can be achieved. With recent calls for sustainability he environmental benefit in terms of averted CO2 emissions is the first non-monetary item can be achieved. When energy efficiency is also intended as a strategy to maintain the history. Hence, realtors should also examine the value of enhanced indoor comfort and the value of building preservation.  This study also intends to raise knowledge in the sustainable real estates, private residential housing market and green buildings to add to the value of biodiversity and urban ecosystem services, as well as the real estate market.

The Covid-19 pandemic has had a profound impact on all economic sectors, including the real estate market. The World Health Organization officially declared the Covid-19 pandemic on 11 March 2020, and a few days later, on 16 March 2020, a state of emergency was decreed in Romania. The authorities had to reconsider their policies and procedures to limit the spread of the coronavirus while allowing economic activities to continue. The aim of this paper is to provide insights into the changes that have occurred in the Romanian real estate market due to the economic slowdown induced by Covid-19 and to suggest a mitigation framework to minimize the effects. For this purpose, residential and commercial real estate markets are analysed from the perspective of properties supply and demand and their impact on prices during the Covid-19 period. During the pandemic, the real estate market was marked by divergent developments in its two sub-components: while the residential market saw an acceleration in activity, the commercial market experienced a decline. Demand for residential property was accelerated by improved saving and working behaviour of the population during the pandemic period, low-interest rates on loans, but also by expectations of increases in house prices in the coming period, as the authorities announced an increase in the threshold for the application of the reduced VAT rate for property purchases (BNR, 2021). Against the general trend of increased demand, supply has also been on the rise but remains insufficient to cover the high demand, which has been reflected in a sustained increase in house prices in most Romanian cities. Due to the persistence of the pandemic crisis and economic uncertainty, activity in the commercial real estate market has slowed down significantly, with some developers extending project delivery deadlines or postponing investments.

The Covid-19 pandemic has seriously disrupted our way of teaching and of doing research in institutions of higher education. For over two years, many of us had to teach remotely or in a hybrid fashion, had to organize and manage exams over the Internet, and supervise student research through video conferences. Similar problems arose with the usual research activities. Since travel was restricted, many conferences and workshops were either cancelled or moved to electronic media. While distance friction became less important for cooperation in established contacts, informal exchange and meeting new colleagues at events largely vanished.

The pandemic led to a flood of Covid-19 related research with many articles published on – often newly established – preprint servers. University administrators, policy makers, and the public press are speculating about the long-term implications the pandemic will have on universities and the higher education industry.

These two years have led to an accumulation of anecdotal evidence, speculation, and a few hypotheses about the future development in higher education. Some argue that the sector will quickly return to the pre-pandemic mode once the pandemic is over. Others predict higher education will be torn apart by the fundamental disruptions caused by the pandemic. Relatively little, however, is known about the experiences and the expectations of the main actors in higher education, the faculty members. In our paper, we will present the results of a systematic questionnaire survey of faculty members in Europe about their academic experience during the pandemic and about their expectations for the near future. The purpose of the paper is to identify patterns of reactive and proactive behaviour of lecturers and researchers and to investigate differences in their perceptions.

Since it became obvious over the past years that disciplines were affected and also reacted very differently, it is important to investigate academic disciplines separately and to compare across disciplines. Our investigation will focus on regional science and on real estate economics. These disciplines are thematically quite close, but differ in the types of students they attract and in the segment of society that is interested in their research results and alumni. In our paper, we will show differences between these disciplines as well as differences by country or region, by gender, by academic status, by age, etc. Our survey deals in a systematic way with the experiences during the pandemic as well as with the expectations about the near future in terms of teaching and research management.

Private and intuitional 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. The 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 is limited so most projects use the indirect way through special purpose vehicles (SPV). This paper explains the most used concepts, recent developments, regulations, and a first market overview for the USA and Europe (Switzerland and Germany). We show the development of the primary and secondary markets after the tokens are issued by Security Token Offerings (STO).

After solving the double-spending problem of digital assets (tokens), the application possibilities of digital rights and goods have increased enormously over the past years. Even if the market for digital tokens is in its infancy, it is an innovation that has the potential to disrupt how we transfer ownership of financial instruments. The real estate market has been identified as a major market for digital fractional ownership using the Distributed Ledger Technology (Blockchain). In addition to funds and REITs, real estate tokens are an additional form of indirect investment vehicles, which lower the high entry barriers into the asset class of real estate and allow diversification in multi-asset portfolios.

We collected the data of real estate tokens in the USA between 2019 and 2021 and trace back the transactions published on the Blockchain. In doing so, we analyze the success determinants of Security Token Offerings and secondary market trading. We disentangle the success on the property and wallet/investor level. We find that in addition to the fundamental factors (cash-flow, size, and property type), also the market sentiment for the local real estate market and general crypto market are relevant for explaining the success of the offering. The attractiveness of the location is of minor importance.

Real options can account for a significant portion of the value of real estate assets. Methods exist to value real options in real estate but there is little evidence they are in widespread use. This systematic literature review examines the evolution of research on real options in real estate, identifying its main themes and drawing out its key insights. The tools developed to value real options in real estate and guide their optimal exercise are thought superior to net present value analysis for capital budgeting when outcomes are uncertain. Also among key insights of the literature is the identification of characteristics of real estate markets and assets that affect the flexibility of real estate owners to act in relation to their real options, and in doing so affect real option value and exercise decision making. These characteristics are among possible reasons explored in this review why uptake of real option valuation tools by real estate practitioners appears to be limited. This review submits there are factors at play increasing the likelihood of these tools being adopted in the future, including increased uncertainty driven by societies’ changing real estate requirements following the onset of the COVID-19 pandemic. The search for well-designed modifications of real options valuation tools, with the aim of stimulating their uptake, forms the basis of suggestions for future research.

The financialization literature describes how the increasing mobile capital in the coming years will put a pressure on real estate to be transformed into high quality investible financial product (Haila, 2021). Even though the proportion of real estate in an investment portfolio has increased every year reaching 25% and real estate comprises up to 50% of the total value of words assets, however only 10% is high quality investible property with a profitable return on equity (Hartzell and Baum, 2020). The investors are challenged to implement main structural changes driven by digitalization, sustainability and the rapidly changing market trends some accelerated by COVID. But, the yieldable property became scarce and more active measures need to be taken by investors to increase the net operating income. There is a need for re-engineered business models to make sustainability and digital transformation the new drivers of performance.

Based on a systematic literature review to identify the main drivers of structural change: sustainability, digitalization and investment market trends, the reconceptualization of the Real Estate Development (RED) is proposed to become a business incubator for sustainable and smart urban products. In a second stage, a re-engineered business model for real estate investors is proposed. Within the context of direct investment in real estate development (either by building new, partially demolish or major conversion of existing building stock) the research explores new value creation systems based on the drivers of three major structural changes: digitalization, sustainability, market trends. Entrepreneurial management, an important quality of the RED process is a key element for initiating the sustainable and digital transformation of the built environment by bringing ideas to reality. Miles (2015) points out the distinctive entrepreneurial spirit present in a development process and needed to realize a vison by stirring the processes of design, finance, building and leasing processes. By taking the role of an entrepreneurial innovator and making use of the existing digital technologies, real estate investors have the potential to generate innovative sustainable and smart city concepts.

The current market conditions require a re-conceptualisation of real estate development as a more agile process to challenge the real estate asset class established characteristics, make the transition from project to product and become a tool for real estate investors in reaching value-add strategies by integrating ESG goals, smart building technologies and rapidly changing market trends.

The combination of policy concerns over climate change, resource efficiency and the natural environment, has caused that municipalities, as owners of real property assets, need a new approach to their management. They are no longer only required to have accurate data on the condition they are in, the ongoing cost of their operating, maintaining, rehabilitating and eventually decommissioning, as well as knowledge about the value of the assets in their portfolio. More and more often municipalities are expected to embed sustainability targets in their real property asset management. Some of them are beginning to introduce the highest and best use analysis in the decision-making process that considers long-term environmental, economic and social objectives.

So far, the reflection of sustainability in the analysis of the highest and best use of municipalities' real property assets has captured limited attention among researchers of the subject. The existing publications focus mainly on the mentioned analysis in enterprises. There are also a few papers which present the concept of the highest and best use in municipalities of the most developed countries, however not in the context of sustainability. Thus, this paper aims to fill this gap in the literature and to investigate the scope of sustainability incorporation in the process of determining the highest and best use of municipal real property assets including four tests (legally permitted, physically possible, financially feasible, maximally productive), based on the example of Polish biggest municipalities.

The Permanent Observatory on Local Public Administrations (OPPAL) survey aims at:

• offering an opportunity to promote the territory by promoting transparency about and disseminating the practices adopted for investment licensing procedures;
• providing valuable support in defining the strategic investment choices of Real Estate operators.
• providing a unique tool at national level, for attracting investment for the enhancement of Real Estate Assets.

The research presents the survey's results of Permanent Observatory on Local Public Administrations (OPPAL), which deals with the efficiency of the licence-issuing procedures applied by the Local Public Administration (LPA) in Italy with a focus on alternative financial strategies.

The redevelopment and enhancement interventions promoted by the Local Public Administration (LPA) allow to secure the environment and to recover abandoned and former production areas for collective use and natural heritage.

This study investigates the effect of corporate regional diversification on the cost of debt securities. It observes the yield spreads on debt securities issued by U.S. REITs and employs asset-level data to measure portfolio diversification levels across NCREIF regions. By utilizing a Herfindahl-Hirschman index-based measure of diversification, the results show that, on average, a one standard deviation increase in regional diversification increases the spread by nearly 8 basis points. Also, expanding to one additional NCREIF region increases the spread by nearly 4 basis points. Put differently, in our sample, being amongst the most diversified tercile could increase the spread premium by about 26 basis points, while maintaining a low level of diversification (falling in the least diversified tercile) could reduce the spread by about 12 basis points. These results are robust to controlling for credit rating and other potential confounders. The findings highlight a latent channel for the so-called corporate diversification discount.

An accurate volatility forecast is essential in financial investments and risk management. Existing literature finds that the implied volatility (IV) from options trading best predicts the realized volatility in various financial products. In 2016, real estate was added to the S&P 500 as the eleventh sector; however, a reliable IV measure for the real estate sector has not been developed yet. The existing literature in real estate investment trusts (REITs) relies primarily on insufficient volatility forecasts, such as IV for a broader market or time series analysis. In this research, we develop a REIT sector IV index derived from options on the US Real Estate exchange-traded fund, IYR. As Whaley (2009), the creator of the VIX (IV in S&P500), points out, enough liquidity in option trading is critical in developing an IV index. This study shows that IYR option trading is liquid enough and informative that our REIT sector IV index outperforms other volatility forecast measures. Our findings suggest that the REIT sector IV index from option trading data can be utilized in future research and industry risk management.

Operators (owners/facility managers) of high-rise buildings are continuously faced with the challenge of finding innovative means of controlling and managing facilities of high-rise buildings. This is due to the consistent change in the nature and functions of building systems. Meanwhile, the use of computerized systems affords building operators the tools and method that will enhance facility management activities. This study examined the importance of automation to the facility management of high-rise buildings. The study adopted a survey research approach, administered structured questionnaire to 53 facility managers of the identified commercial high-rise buildings in Ikoyi, Lagos Island and Victoria Island. It also, applied regression analysis in determining the significance of automation on facility management activities. Findings of the study revealed that security service is the most automated facility management activity. Results also showed that automation had positive effect on facility management practice with R square of 0.66. The study concluded that although automation is seldom used in carrying out facility management activities; it has a positive impact on facility management services with 66% significance level on facility management activities. It then recommended that steps should be taken by all stakeholders to develop the practice of facility management, research and facility management education.

In France, a lot of rent markets are said to be “saturated”, which means that there exists a structural dwelling disequilibrium between demand and supply. In some cities, finding a place to stay is becoming a challenging task. This is the case, inter alia, for Paris. Thus, a rent control has been coerced in 2019. It is today effective in few other cities in France: Lille, Lyon, Villeurbanne, Plaine Commune, Est Ensemble. This rent control limits rent amount with respect to room counts, typology (furnished or not), construction period and administrative suburb of the dwelling.

However, despite the rent control, we observe that some leases exceed the ceiling fixed. By doing so, the introduction of a ceiling places all leases that exceed the latter in the category of administrative luxury goods. In this research, we observe what causes these exceedances: is it about the intrinsic characteristics of dwelling (high floor, Haussmannian, large surface); about the extrinsic characteristics (green spaces proximity, iconic monuments); both? Or is it about an a priori conception of the regulatory authority, as quality and luxury are mostly a matter of perception (Zeithalm (1988), Walls (2011))?

The "superstar" approach, developed by Rosen (1981), is an interesting benchmark to understand from where comes administrative luxury. This approach states that there is a "superstars’ phenomenon" in the economy, when a "small number of people earn enormous amount of money and dominates the activity in which they engage". Applied to the housing market, Gyourko et al. (2013) find that there exists "Superstar cities", in which there is an inelastic supply of land which increases house prices and crowd out lower income households.

Is there "superstar suburbs" in Paris, where exceedance frequency is higher? Or is it generalizable to Paris as a whole? Has living in Paris become a luxury?

The retail sector is undergoing a period of unprecedented structural change, compounded by changing behaviours and contraction of economies due to the covid-19 pandemic. The amount of vacant space in city centres has risen dramatically and debate is taking place over optimal future uses. The process of repurposing vacant space is fraught with risk and uncertainties but remains critical to realising a resilient and adaptive city centre. The process of repurposing space involves multiple stakeholder groups, often with shared aspirations but sometimes seemingly competing commitments and responsibilities. Stakeholder relationships are explored here, to better understand the practice of repurposing retail real estate in UK city centres and provide guidance for real estate and planning practice on how best to enable change. 

Assemblage theory is adopted to best reflect the complexities of the real estate market and the wider city centre environment. This theory, or way of thinking, offers a way of recognising the processual and relational nature of change in the repurposing of space, and the heterogeneous nature of both real estate itself and the stakeholder groups involved. It provides the conceptual framework for the study and guides the data collection and analysis, through five case studies.

Purpose – “The revitalisation of the Deliplein has enabled Katendrecht to shed its longstanding reputation as one of the worst districts in Rotterdam. It is now one of the most sought-after neighbourhoods in the city”. The Fenix food factory is located near Deliplein in the Katendrecht neighbourhood, and plays an essential role for the success of this regeneration project. The purpose of this paper is to evaluate the success of the adaptive reuse project of the Fenix food factory, as part of a case study research of several adaptive reuse projects in the Netherlands. Accordingly, this paper seeks to answer the following questions: What are the factors that lead to the success of adaptive reuse projects? How can the success factors of adaptive reuse be implemented in the Dutch redevelopment practice?

Design Methodology/approach – The case study approach has been adopted to evaluate the success factors for adaptive reuse of heritage real estate as found through previous literature review. As part of the case study, interviews are held with the stakeholders of Fenix Food Factory, for better understanding the overall framework of the project, such as stakeholder partnerships, reuse regulations and limitations determined by the municipality, financial and social viability. The case study material furthermore includes project documentation and written sources about the project. 

Findings – The findings show how success factors are applied in the decision making process of adaptive reuse projects. Furthermore, new factors that are not found in existing literature but are considered effective for the success of the Fenix food factory will be added to the body of knowledge on this topic. Originality/value- This research contributes to providing more comprehensive data as input for decision making models for successful adaptive reuse projects. This study reviews the classification of success factors that was revealed in previous studies. The final result of this study will contribute to develop knowledge for the management of heritage real estate. 

The short-term rental market has grown rapidly over the last decade. Airbnb (and other online accommodation sharing platforms, which provide an online market that links people with each other as host and guest system) is attracting much interest, as it has implications for the real estate market worldwide. The impacts vary across the globe depending on the context. As Airbnb comes at the forefront of short rentals platforms in this market in Istanbul, Turkey Airbnb has the biggest share, which attracted many researchers trying to answer the generated and raised questions. Using scrapped data from Airbnb websites, this paper offers insights into Airbnb usage patterns and how they vary across different districts of Istanbul with different types of provided properties and how they correlate with asked prices. Seasonality has a significant effect in the real estate market as it directly affects supply and demand, so We used the number of reviews variable in the dataset as an indicator of the demand to study the seasonality pattern and how prices fluctuate over time to different reasons. The paper also explored the asked rent prices in the long-term leases using data from Emlak 360 and Endeksa websites and compared it to short-term rentals. This is continuing research that provides a map for the Istanbul dataset that will inspire and establish new aspects to academics and professionals in the Turkish market to further analyze how the market acts at certain times.

The introduction of blockchain-based solutions to the real estate transaction process has received significant attention in the recent years. However, there is still little clarity as to what the impact of such step might be on the dynamics of the real estate market. We build an agent-based model calibrated on the Swedish market and use it in a simulation analysis to study how redesigning of the house sale process with blockchain can affect housing price dynamics. First, the model looks at the traditional transaction setup using the sequence of interactions between parties as is typical in Sweden today. In the second step, we simulate a streamlined transactional workflow orchestrated by a hypothetical blockchain smart contract and compare its outcome with that of the traditional process. Our main goal is to investigate whether streamlining housing transactions via permissioned blockchain application exacerbates market volatility and generates flash crashes. At this point, the analysis is still ongoing and the results are outstanding.

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 population, evaluate the condition of single-family homes based on pictures of the exterior. The student’s population consists of students with no real estate experience, students which are studying in a bachelors’ program in real estate management and students which are studying in the same masters’ program, in both groups there are students which study extra occupationally. The sample composition facilitates the examination of different experience levels. In the next step, we compare the evaluation by students with an evaluation by professional evaluators following the scheme. In addition, we investigate how colours and distance of the photographer, among other factors, affect the condition classification assigned by students. The result of this work will provide information about the extent to which lay people are able to evaluate single-family houses and compare them with professional evaluators and if the wisdom of the crowd comes to a comparable conclusion as the professionals.

Rethinking the claim on the negative association between social interaction and the decision to move into homeownership from renting. A hypothetical shortcoming of related literature is that social interaction is taken as exogenous while neglecting the problem of moral hazards, arising from information asymmetry. In this paper, these shortcomings are confronted conceptually with reference to Gronevetter(1973) tie strenghth hypothesis and empirically using the self-reported panel information from a representative British household panel. The conclusions suggest that the value of social interaction for homeownership may be uncovered, where it is observed indirectly in the individual’s utility function, as an other-regarding preference rather than directly in the individuals’ deep preferences for homeowenrship. Consequences for social and housing policy are further discussed.

Several authors have stressed rising housing prices associated with intensifying tourism activity as a significant negative externality of tourism development (e.g., Mikulić, Vizek, Stojčić, Payne, Čeh Časni, & Barbić, 2021). The relationship between levels of tourism activity, typically measured in terms of arrivals and/or overnights, and housing prices has also been confirmed empirically in a number of studies (e.g., Biagi, Lambiri & Faggian, 2012; Biagi, Brandano & Caudill, 2016; Balli, Balli, Flint-Harle & Yang, 2019; Paramati & Roca, 2019, Churchill, Inekewe, & Ivanovski, 2021). 

This negative side-effect of tourism development gained new momentum with the proliferation of Airbnb and other peer-to-peer platforms that initiated a structural change in accommodation capacities at many destinations, essentially by turning flats into short-term rentals (STR) aimed at tourists (Dolicar, 2019). The negative consequences of these developments are well-documented in studies set within the context of “bucket-list” destinations struck by over-tourism, like, for example, Barcelona, Dubrovnik, New York, or Venice. Even the COVID-19 pandemic, which has hit the tourism sector very hard and led to a short period of under-tourism, did not stop this trend, with some European towns like, e.g., Split and Venice again being overrun by tourists during the peak of the 2021 summer season.

Generally, besides rising housing prices, negative consequences associated with STR-induced overtourism are gentrified city centers (e.g., Wachsmut & Weisler, 2018; Ardura Urquiaga, Lorente-Riverola, & Ruiz Sanchez, 2020), crowdedness (e.g., Park & Agrusa, 2020), and increasing retail prices (e.g., Stynes, 1997, Gholipour, Tajaddini, & Andargoli, 2021), to name only some of the most significant ones. Together, these effects significantly contribute to a lowering of quality-of-life of residents in tourist destinations (Biagi, Ladu, Meleddu, & Royuela, 2020), especially for residents who do not own a property and/or have no significant benefits from the local tourism industry, either direct (e.g., via employment) or indirect ones (e.g., boosting economy). 

However, what if these effects were not constrained to neighborhoods in the area or destination under investigation (e.g., Zou, 2020) but rather extended to other regions via spatial spillovers? 

On the one hand, this would imply that the pressure of tourism activity on housing prices is an externality that also affects those who do not have any direct or indirect benefits from tourism activity, as described above. On the other hand, this would also imply that actions taken at the local level, like housing policies, aimed at providing relief to residents who have difficulties affording housing at popular tourist destinations, should, in fact, be developed more holistically by taking into account tourism impacts on real estate markets at a regional or supra-regional, rather than focusing only on the local level.

As described above, potential regional spillovers have not been addressed in the tourism, housing, nor regional economics literature so far, which is a research gap this study intends to fill. The empirical analysis is set within Croatia, an increasingly popular Mediterranean destination, ranked 27th according to the World Economic Forum’s Travel & Tourism Competitiveness Report, putting it at a similar level like, e.g., Greece (#25) (WEF, 2019). Tourism activity in this country is densely concentrated in proximity to the sea and along the whole coast, whereas there are only a few tourist spots in the continental parts of this country. This is also reflected in a share of 97.3% of all accommodation establishments located in one of two of Croatia’s NUTS-2 regions, i.e., Adriatic Croatia (as opposed to Continental Croatia), which is also ranked first among all European NUTS-2 regions according to accommodation capacity (Eurostat, 2021a). At the same time, Croatia also has the largest share of private accommodation in overall tourist capacities compared to its Mediterranean peers. For example, the percentage of holiday and other STRs in total bedplaces in pre-pandemic 2019 was 61.3% in Croatia, whereas the same share was 34.5% in Italy, 32,2% in Greece, or 24.6% in Spain (Eurostat, 2021b). Accordingly, although geographically small, Croatia is ideal for examining regional spillovers as described above because its tourism sector heavily relies on apartment houses and is highly concentrated in its coastal area.

The research question we are addressing in this paper should also be placed in the context of the ever-increasing global tourism demand. International tourism receipts increased 4.9 percent in real terms to reach US$ 1.34 trillion in 2017, whereas tourist arrivals amounted to 1.336 billion in the same year (UNWTO, 2018). In addition, international tourist arrivals worldwide are expected to increase by 3.3% annually to reach 1.8 billion by 2030 (UNWTO, 2017), which suggests popular destinations already overwhelmed with tourists will start to experience more negative externalities of tourism activity, including the degradation of sociocultural and environmental conditions and the rise of house prices and rents coupled with declining housing affordability. In geographically smaller or island countries which depend more on tourism receipts, the emergence of over-tourism could potentially be more damaging to the local housing markets due to limited availability of building plots, higher population density, and often rigid urban zoning rules. In such countries, house price hikes taking place in a very popular tourist destination (local government units - LGUs) could easily spillover to neighbouring LGUs, then regions and eventually the entire country.  For this reason we study local/regional house price spillovers which are due to tourism activity in Croatian LGUs.

In order to understand the spillover process better, we will use spatial panel data estimators to model house prices and its determinants, which in turn will enable us to detect the main spillover characteristics and modalities. To the best of our knowledge, this would be the first study of its kind in the literature. The only other study addressing this issue is Kavarnou and Nanda (2018) who use dummies for neighboring regions as controls for spatial spillover effects, which is a static and rather limited way of addressing this issue.

The empirical part of our analysis relies on techniques from the family of spatial panel estimators. We use the Durbin spatial panel autoregression technique (DSM) (LeSage and Pace, 2009; Elhorst, 2013). This technique enables us to establish a direct relationship between the dependent variable and its effects in other spatial units (cities or regions), spatial effects of independent variables such as measures of tourism activity and unobserved spatially correlated heterogeneity. Moreover, we employ different types of spatially weighted matrices, symmetric matrices that define relationships between units in space. To this end, we explore whether spatial effects are limited to neighboring municipalities and cities or do they exert wider scale. Another advantage of spatial econometric analysis is the ability to estimate direct and indirect effects of the observed process. The change in individual city or region generates two types of impacts. A direct impact on itself and an indirect impact that goes first to other spatial units and partially returns through feedback loops (LeSage and Pace, 2009). These feedback loops arise because each spatial unit is considered a neighbor to its neighbors so the impact passing through neighboring units will create a feedback impact on the initial unit itself. There is reason to expect such feedback loops will arise with changes in tourism activity and dynamics of the housing market. To the best of our knowledge, such analysis has not been performed in context of tourism sector or its relationship with the housing market in general. 

Our dataset combines variables constructed from several reliable data sources. Most of the variables, including the tourism related measures, come from the National Statistical Office of Croatia, the official focal point for statistical data collection. We use five different proxies for tourism activity and intensity: number of nights spend per inhabitant, number of arrivals per inhabitant, the share of private accommodation in total tourism accommodation, the share of rental housing in total housing stock and the length of stay of tourists.

This database is supplemented with datasets obtained from the Ministry of Finance, i.e. its Tax Office from which Property income and Average wage data come from. Finally, the Institute of Economics Zagreb (EIZ) provides the data on housing transactions and housing and construction land prices from their annual reports on real estate trends prepared for the Croatian Ministry of Construction. The analysis covers the 2012-2019 period and contains 556 Croatian cities and municipalities in which real estate transactions took place over the years analyzed. 

In the context of house-price indices, location-specific neighborhood effects are increasingly modeled by including a geospatial spline surface into the hedonic regression framework. This paper examines how to overcome an essential drawback of polynomial spline behavior: overshooting of estimated spline functions in areas with poor data support. Such data-gap areas are common in real-estate economics as housing transactions are not distributed evenly across space. We introduce a new method for constructing price spline surfaces that avoids the spline overshooting problem by placing helper points in data-gap areas before estimating the spline surface. We use the Random Forest method, a simple yet powerful non-parametric method based on decision trees, to estimate the values for these helper points, but other methods (e.g., kernel regression) would also be possible. The important point is that the helper points stabilize spline behavior where data are missing but do not distort the spline surface in areas where data are plentiful. Our method also has a positive knock-on effect in that it can lead to lower overall spline penalization terms and thus improve the spline's response to changes in the actual price data. Price spline surfaces have multiple application possibilities. They can be used to inform on price gradients and local sub-centers, as an alternative to regional fixed effects in hedonic house price regression models, or as input for quantitative spatial models. To the best of our knowledge, our method is new - not only to the field of Real Estate Economics - but also to the spline literature. It should, therefore, not only improve the estimation of regional house price gradients but also has the potential to improve a wide variety of spline applications in other fields.

Comprehensive knowledge of the building stock is considered essential for the implementation of climate and resource protection policy objectives. In contrast to residential buildings, data on the stock dynamics in the non-residential building sector are scarce in Germany. With publication of the construction statistics via Scientific Use File (SUF) by the research data centres of the statistical offices of Germany, for the first time, in-depth analyses of the stock dynamics in the non-residential buildig sector are possible. The dataset contains Information on on the spatial distribution down to municipality level, the date of completion of the construction measure, the predominantly used building material, information on the building owner as well as information on the number of full storeys, the volume, the floor space before and after construction completion. This dataset enables spatially detailed analyses of stock dynamics and allows an analysis of the underlying causes - or cause-effect relationships - that are responsible for these construction dynamics.

The aim of this work is to identify factors that influence changes in the non-residential building stock and to quantify their influence. Based on a suitable typology of non-residential buildings, a pre-selection of influencing factors will be obtained through an expert survey. The analysis will focus on the use classes of warehouse buildings, office buildings, factory buildings and agricultural buildings. For each of these use classes within the non-residential building stock, individual influencing factors were identified. These factors are then correlated on the change in the non-residential building stock within pre-selected submarkets at the district level. For the selection of suitable districts, a cluster analysis is carried out. A factor analysis is used to reveal the interdependence between influencing factors and the respective use classes. As a result, this work can contribute to a more informed discussion on the future development of the non-residential building stock. It can be seen that comprehensive building activity statistics are essential for validating and updating future building cadastres.

In the face of ongoing climate change, increasing importance is being attached to the implementation of sustainable development principles. The construction sector has been identified as one of the key sectors in terms of its potential contribution to achieving environmental goals.

In Poland, the number of residential buildings with environmental certificates (BREEAM, LEED) is small, and particular technological solutions are more often the part of activities referred to as "greenwashing". The market situation in Poland makes it unnecessary for developers to strive for customers who care about the characteristics of green properties, because there is no external pressure on market development in such terms. Therefore, developers do not mobilize to scope out the needs of potential customers for sustainable housing. 

The aim of the research is to check the level of awareness among potential apartment buyers. The research is a part of a larger project that aims to identify the importance of sustainability in housing among stakeholders such as residents, developers, managers and local authorities.

The EU and its member states have recognized that reducing CO2 emissions in buildings is a decisive task for achieving climate protection targets. With regard to Germany, only moderate progress is discernible, which is primarily reflected in low modernization rates and modernization concepts that ultimately miss their goals.

A reason for this is that heat pumps, identified in many studies as the preferred and state-of-the-art heating technology, requires extensive modernization measures in existing buildings. This results in existing building owners usually opting for modernization variants that involve lower investment costs, which do not bring the necessary CO2 savings. But since these modernization concepts do not lead to the achievement of climate protection goals, repeated construction measures on the building become necessary, which exceed the previously saved investment costs. Therefore, more ambitious modernization concepts tend to be more cost-effective in the long term. The project ModEMS4Q, funded by the German Federal Ministry for Economic Affairs and Climate Protection, aims to improve economic feasibility of target-oriented modernization by generating synergies of a cross-technology and cross-building approach.

ModEMS4Q looks at three distinct residential districts with single-family houses and multi-family houses which, due to their different building types and years of construction, each offer different conditions for concept development. An energy management system is central part of the modernization concepts and allows coupling with other consumers such as e-mobility. In addition to variations in the modernization of the building's thermal envelope, various supply concepts for the building's technical equipment are being considered, and the economic feasibility is being assessed. Key points of the concepts are the utilization of the local potential for renewables, the possibility for modular expansion of the concept to adjacent buildings and neighborhoods, and long-term climate neutrality.

Depending on the local conditions, combinations of two concepts for the modernization of the thermal envelope, four variants for the heat supply and two financing models including potential expansion possibilities are examined and measured against reference concepts for each residential district.

Primary and secondary education are of critical importance to the future life of children, determining their future in the labour market. Thus, pupils should be provided with an optimal learning environment to work at their highest cognitive capacity, including the indoor quality of classrooms. However, school buildings are often old, poorly ventilated, and in urgent need of renovation. Past studies have shown that being in a poorly ventilated classroom can have negative effects on the learning outcomes of pupils. The question remains, however, if children with an unhealthy lifestyle are more susceptible to a poor indoor environment. This study aims to investigate the role of the pupil’s health status when being exposed to high levels of indoor carbon dioxide (CO2) in classrooms. It is hypothesised that among the students with healthy dietary behaviour and high physical activity level, despite being exposed to a high concentration of CO2 during the time they study for a test and during the time of conducting the test, they are more resilient towards the negative effects of indoor CO2 on learning outcomes, compared to students with a less healthy lifestyle. For this purpose, data from a quasi-experimental study was used, including indoor air sensor data for each classroom, data of the health behaviour of students, and the exam grades of an annual nationwide test. The sensors measure the concentration of CO2, fine particular matter, temperature and humidity levels, and noise levels in classrooms. Preliminary results from linear mixed model analysis have shown that an unhealthy diet and a higher BMI negatively affects test scores. Additionally, the effect of dietary behaviour on test scores interacts with the level of CO2 in the classroom. The next steps will be to examine this effect further by including confounders such as socioeconomic status, sick leave, and minutes spend in the classroom.

The retailing industry in the UK is experiencing unprecedented structural change, evidenced through increasing occupier business failures, vacancies, uncertainty and instability on the High Street. The global pandemic of the early 2020s has served to accelerate the already established changes in consumer behaviour. The impacts on retailers and local services have often dominated headlines, but little attention has been given to the implications for the property market. Exploring and understanding the responsiveness of the property market, in terms of, for instance, property use, retail market practices, and social structures, is essential to understanding the adaptive capacity of urban retailing centres.

This paper presents the findings of a large-scale mixed method study investigating the changes experienced across five UK case study cities (Edinburgh, Glasgow, Hull, Liverpool and Nottingham). Drawing on complex systems theory as a conceptual framework, and developing detailed databases for each city, the research begins by examining the relationship between diversity and adaptive capacity within the adaptive cycle of urban retailing centres, spanning a period of almost two decades (2000-2017). This provides understanding of how land use diversity has been evolving and responding to endogenous and exogenous shocks. 

Using thematic analysis, the study then draws on the key themes that emerge from three separate work streams examining different aspect of property market. Included in this discussion are the adaptations being experienced in retail asset use, design, management and ownership, connections to the experiential economy, and the social relations of key stakeholders, before reflecting on how these factors interact to create unique retailing destinations and facilitate, or hinder, adaptive capacity.

We investigate how horizontal (neighborhood) and vertical (tenants) agglomeration impacts the value of office buildings. We find that industry specialization of a building’s 5-digit zip code neighborhood and the extent to which a building is specialized by tenants within the same industry leads to a significantly higher rental rate and transaction price. By linking the within-building industry composition to its neighborhood industries, we find that spillovers are likely to be the most important attribute to the agglomeration gains in office building performance. We find that the agglomeration gains are also recognized by the stock market: REITs’ experience positive (negative) abnormal returns when acquiring (disposing) a building with higher tenant industry concentration or neighborhood industry specialization. Our findings suggest that agglomeration economies are operative at the neighborhood level as well as within individual buildings. Commercial rents reflect horizontal and vertical agglomeration gains which can in turn be used as proxies for agglomeration economies.

Most Inner Cities suffer from highly condensed built fabric which stores the heat of summer days. To relief this effect several architects have started to integrate not only earth bound greenery but to integrate plants in their vertical facades. Through the plants there is a mitigation of the Heat Island effect since the leaves of the plants prevent the sun rays to heat up stone and glass facades. At the same time plants are generating oxygene to improove air quality of the inner cities. One further aspect of green facades ist hat the leaves can clean air from inner city dust. The whole year greenery gives as well a a positive psycholgical well beening in the nature and are improving the  quality of life in inner cities One further positive effect is that plant have no hard surfaces and are therefor not reflecting noise but are reducing noise through their leaves. WLS are consultants for facades of a highrise bilding with a timber facade, a necessary sprinkler system and a planting system at vertical facades. This case study will highlight the state of art of facade greenery in the forefront of green technology with natural materials, combined with highly sophisticated building technology.

The physical work environment plays a role in a broad spectrum of indicators of employee mental health at work, such as concentration, stress, mood, fatigue, engagement, and others. As a (mentally) healthy workforce is a vital aspect for an organization’s success, it is important to optimize physical working conditions within the corporate real estate (CRE). Investments in employee mental health through improving the physical workspace are however not very common, since little is known on the organizational benefits that result from these investments. 

This study used a systematic literature review to identify all proven relations between the physical work environment, 10 indicators of employee mental health and typical KPI’s of organizational performance. Next, this information was used to develop a business case tool indicating the potential added organizational value of changes in the physical work environment that could improve mental health. The business case tool allows CRE managers to assess both the current workspace and design alternatives on their impact on employee mental health. 

Results of the 133 selected empirical studies indicated that respectively light & daylight, office layout & office design, and temperature & thermal comfort affect most mental health indicators concepts, particularly with respect to the concepts stress and productivity. In turn, enhanced mental health+ mainly affects the internal business processes of an organization (absenteeism, communication, job satisfaction, performance, presenteeism and staff turnover) together with employee growth (innovation and flexibility). In the long term, these improvements might lead to higher customer satisfaction, revenue growth and reductions in healthcare and recruitment costs. 

By providing first insights in the potential added organizational value of a healthier workforce, the business case tool presented in the current research enhances the transition where workspace interventions are no longer perceived as expenses but as an investment in the organization’s success.

A recent study by the European Central Bank (2021) shows that unlike previous financial and economic downturns, the covid-19 crisis did not impact the increasing tendency in house prices in Europe. Unexpectedly, both prices and loans rose respectively by 4.3% and 2.6% during the pandemic (ECB, 2021). While financial markets have plunged several times during the sanitary crisis, the real estate market continue to grow steadily. In this context, experts point out the existence of an increasing housing bubble and wonder if it will burst soon.

Like most of the European countries, France has experienced a fearful increase of the value of real estate assets since the late 1980’s. The peak does not seem to be reached even during the hectic period of the pandemic. The question about the existence of a bubble becomes even more relevant especially with the very recent rise that is expected to deflate the value of real estate assets and accelerate the burst of the bubble.

To the best of our knowledge, this paper is the first to study the French property market and examine the existence of a plausible bubble. Unlike previous studies, we use quarterly data of the residential property price index from Q1 1970 to Q3 2021. We contribute to the existing literature by using a longer span of time-series. We expect more relevant findings as our sample includes 206 observations per country. The first part of the paper is dedicated to a global analysis of the residential prices in a set of European countries (Belgium, France, Germany, Italy, Spain and the United Kingdom). We, then, focus on the French context in order to study the existence of a gap between the fundamental and market values of houses. We also suggest some explanatory variables to figure out the determinants of house prices in France and implement a cointegration test.

A large strand of literature suggests different econometric techniques to detect the existence of financial and real estate bubbles. Most of them are based on unit root tests, variance tests, Johansen-Ledoit-Sornette model and durations and regime tests (Mahalik and Mallick, 2011; Ren et al., 2012; Escobari et Jafarinejad, 2016; Vogiazas and Alexiou, 2017; Hu and Oxley, 2018a; Harsha and Ismail 2019. Dufitinema, 2020; Rafiq et al., 2021).

We implement an Augmented Dickey-Fuller (ADF) test, the Generalized Sup Augmented (GSADF) test and Phillips-Perron unit root test.   Our results prove the existence of a bubble in the residential French market and confirm a long-term cointegration between price indices and our set of macroeconomic variables.

The COVID-19 pandemic has influenced household housing demand especially with the dramatic increase in working-from-home (WFH) along with reduced mobility because of the restrictions and infection concerns. We provide a comprehensive understanding of changes in housing demand in Singapore where WFH became widespread and many restrictions including the lockdown were implemented after COVID-19. First, a word cloud analysis of the web-scraped data from PropertyGuru, the largest online property listing company in Singapore, suggests a significant change in keywords for housing advertisement. While words related with accessibility or location appeared significantly less in listings, the space and view of housing units were highlighted with words such as the study, unblock view, and renovation. Next, we investigate how the keywords that became popular after the COVID-19 have affected asking housing prices and transaction probabilities of online listings. Finally, we match the keyword information with actual transaction database and analyze whether features reflected in these keywords are indeed associated with changes in the price premium and transaction volume. Our findings capture detailed short-term shifts in housing demand reflected in real time at the online platform and provide important implications to the housing industry and policymakers.

There are numerous historic and monumental properties scattered all over the nooks and crannies of Nigerian Cities which are in ruins due to poor management and neglect. Despite the facts that historic buildings play vital roles as places of tourism and recreation thus enhancing economic development and growth of many countries yet many of such sites in Nigeria are poorly managed. The study which is exploratory in nature seeks to discover why such properties are not properly managed and what can be done to sustain such properties so that they do not go into extinction. The study adopts a survey approach and makes use of online surveys to reach out to Property Managers on the role they play in the management of such properties, barriers to effective management and likely solutions for sustainable management of such properties.

Around the world authors have distinct visions about the education on real estate emphasized due to the stage of development different from their regions. The study of real state in a local tend to be shaped through demand of knowledge of professionals working in the region. Among the study challenge of this topic has a lacking knowledge about the study of this discipline, and the references are uniquely than what are noted in economies more advanced, the nomenclature used is not standardized, and there is not a unique body knowledge.

This survey seeks to know the demand about the awareness in the visions of industry and active contractors in different real estate area, through the application of questionnaires to contractors.

Concepts were identified, themes in topics related to the professional activities of real estate, organized in 5 segments: (i) real estate development, (ii) real estate finance, (iii) real estate investment, (iv) real estate economics and (v) real estate management, which one covering different topics.

The selected professionals to apply the questionary were defined in different groups, recognized in: incorporating companies – real estate development; investing companies – only invest don’t operate, has the focus in fund mobilize; and properties companies – holder companies of income commercial properties, focusing in acquisition, leasing, management and sale.

Through the form the individuals attribute levels of importance about the topics, that allowed ranking. Across these attributions was possible to rate the themes.

Three topics accent in terms of relevance, regardless of the business segment or area. They are: (i) the construction of economic-financial models for investment analysis; (ii) the formatting of projects; (iii) the financial market and its behavior expectations.

Public Land Development (PLD) is an active form of land policy that is mainly used in the Netherlands, Finland, Sweden, and China. In PLD, the public authority buys the land in an area of interest, prepares the plan for the area, rearranges the plots, provides infrastructure, and sells the serviced plots to developers for development. Some literature suggests that PLD gives control over land supply, which may lead to more timely plan implementation. However, other work indicates that PLD may not offer better outcomes than other forms of land development policies in terms of timing of development and implementation of housing plans. In this context, the use of PLD as a significant public intervention in the land market is difficult to rationalize.

In this paper, we focus our investigation on the impact of PLD on housing plan implementation. In addition, we investigate if PLD has any advantages compared to other forms of land development policies.

Our empirical analysis focuses on the Netherlands. We construct a panel of approved housing plans in Dutch municipalities from 2010 to 2019 and estimate the impact of PLD on plan implementation using survival models.

This study seeks contribute to the debate on the merits of a hierarchical and centralised approach to housing. Single housing authority (SiHA) was established under Botswana Housing Corporation (BHC) to implement all the housing programmes which are inclusive of the Self-Help Housing Agency (SHHA) Turnkey Loan housing schemes and youth housing. BHC mandate is to provide affordable housing to Batswana but the proportion of houses provided by BHC has decreased from 4.6 % in 2001 to 1.72 % in 2011. In opposite correlation with the 20.5% growth in population from 1,680,863 to 2,024,904, (Central Statistics Botswana, 2014) and the following year of 2012, Botswana Housing Corporation was given responsibility for other housing programmes. This decrease seems to signal that there are inefficiencies in provision of housing and challenges of housing are not sufficiently met. As of the 1990’s the institutions acted separately in providing housing to the low income. The main objective of this study was to find out the whether coalition of housing programmes will influence the rate at which quality housing is produced to meet the needs for low income housing, which included considerations for customer plan preferences and payment plan issues. Causal research design and Quantitative research approach were employed. The study population comprised of Botswana Housing Corporation management, Botswana Housing Corporation customers and Gaborone City Council public housing officers. This was to determine the sample size and stratified random sampling was used to increase the viability of the research. Semi-structured questionnaires were used to collect study data. SPSS version 22 was used to process and analyze the data findings of the study. The data was summarised and categorised according to common themes. The SPSS computer software aided in the analysis as it was user friendly and most appropriate for analysis. The study found out that considerations for user preferences are standardized due to constraints in funding and mandate. The study further found out that the corporation developed a quality assurance system to allow for feedback and appropriate planning. This gives consideration to user preferences in more general approach. The study further revealed that loan rates are adequate although beneficiaries still face issues of default which suggests that the cause of default is not necessarily due to the rates imposed but the income group being served. This shows a need for social housing that is highly subsidized and empowerment alongside facilitation of housing. The study recommended that Botswana Housing Corporation should continually embrace the use of quality assurance systems to provide basis for customer satisfaction and planning to create new products. It was evident that along with supply of housing, property literacy is imperative along with proper management of projects to improve delivery.

Using a micro-level dataset of over 5 million listings, house price indexes for Poland over the period 1996 to 2021 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 each city and then aggregated. The constructed index has some limitations but provides information on the housing market in Poland for much longer than officially published.

Using Hurricane Sandy (‘Sandy’) as a natural experiment, this study investigates whether the occurrence of a major hurricane affects the way flood risk is capitalized in commercial real estate prices. We draw from a detailed property-level commercial real estate transaction data set covering the four major commercial property types – office, retail, industrial, and multifamily. In order to explore various price channels, we investigate both hurricane affected areas and unaffected areas. Rresults vary significantly across property types. In the office submarket, we find a significant price discount for properties located in high flood risk areas directly affected by the hurricane. However, this impact lasted for only two years, and was not found in the hurricane unaffected areas. In the apartment submarket, we document a significant price discount associated with flood risk prior to the hurricane. However, following the hurricane we observe a significant apartment price appreciation across the NYC metropolitan area. Such an impact was not found in hurricane unaffected areas. One possible explanation for this finding is the substitution effect whereby the hurricane leads some households to move from single-family homes to apartments. For retail and industrial properties, we do not find any evidence that Sandy significantly affected prices in hurricane-affected  or unaffected areas. 

The externalities generated by cell phone towers have been discussed in the economic literature since 1990s. Recent development of new generation of wireless infrastructure has drawn public attention to the problem, and risen both health and socio-economic concerns. 

The main goal of the paper is to investigate the impact of cell phone towers on residential property prices in Poland, where problem has not been explored to date. The research was divided on two phases. In the first part we conduct a systematic literature review. As a result of the literature analysis, a total of 11 studies were identified: 4 from the United States, 3 from New Zealand, 2 from Germany and one from Australia and Switzerland. The identification of such a relatively small number of scientific research carried out only in a few countries of the world indicates that the discussed issues are not well not recognized and requires further in-depth research. In the second stage we investigate the impact on cell phone towers in Warsaw (Poland) using spatial hedonic price models. We did not find a statistically and economically significant effect of the proximity of cell phone towers on house prices. The research results contribute to the ongoing debate about the potential negative effects of wireless communication infrastructure on house prices, and have significant policy implications.

The spread of coworking spaces has increased over the last decade with the rise of freelancers, itinerant workers, and commuters. This activity, which is strongly driven by a spirit of sociability, independence, shared values, and synergy, tends more and more to break away from the typical working districts of the city, becoming satellite stations that record a significant growth in mid-sized and small town areas.

The objective of this study was to identify coworking spaces (CSs) in peripheral areas of Germany and find determinants of their real estate markets. 

Based on desk research, we constructed our own database of 1202 CS. In order to identify peripheral areas in Germany we considered the data from a urban hierarchy and real estate perspective. Further, we collected relevant real estate market data by a desk research for the identified regions.

The second-highest number of CSs were found to operate in office market peripheries. This should be explained by a search for lower office rents, which are sought out by CSs. Most CSs in peripheral areas of Germany were only recently established in tourist-oriented regions in the south and north of Germany.

Coworking is a model based on sharing a working environment, typically an office, with other people, but in which workers' activities are carried out individually or in small groups. This working model is often confused with the traditional office space model, but unlike these, the workers do not necessarily belong to the same company or working environment. The spread of these spaces has increased over the last decade with the rise of freelancers, itinerant workers, and commuters. This activity, which is strongly driven by a spirit of sociability, independence, shared values, and synergy, tends more and more to break away from the typical working districts of the city, becoming satellite stations that grow in less predisposed areas of the city, such as: industrial district, rural areas, and residential ones. The literature on coworking spaces has been growing fast during the past year, to date, no literature review has systematically studied the effects of such collaborative-flexible new working spaces on residential areas. To fill the gap in the literature, this paper presents a systematic literature review of the effects of coworking spaces on residential areas and their inhabitants.

The methodological approach is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, also known as PRISMA. By considering the PRISMA checklist items. This study provides different aspects and identifies indicators from various cross-studies published in 10 years (2011-2021).

Results show that USA and Europe exceeds the number of publications on these topics during the past decade, and the main research focus was based on spatial planning. With its ability to foster a community of specialized and well-trained people, CSs enhance the revitalisation of residential areas, create a identity and can provide social services for the municipality, which leads to a higher sense of wellbeing of the residents.

Housing markets display several correlations to multiple economic sectors of an economy. Their enormous impact on economies’ health, wealth, and stability is uncontroversial. Interestingly, the forms of financing residential property vary widely between the different countries in terms of both, the available product types and the institutions offering them. This research examines the implications of different financial intermediaries on housing market cycles with special emphasis on two institutional types, conventional banks and building and loan associations. Introducing a heterogeneous agent-based model, the interactions of buyers, sellers, and the two types of credit institutions are assessed in an artificial economy. It is elaborated whether financial institutions are able to smooth housing market cycles and, therefore, increase stability using different mortgage granting policies.

It has been documented in academic literature and grey literature that flexible workspace providers take office space in longer leases. The rationale is straightforward as one of their key profitability components relies on benefitting from the difference between their long-term rights to a space and their short-term offerings, also known as long-short space strategy. Using a dataset of 4,687 leases in New York City extracted from Compstak over the period of 2011-2022, we analyse the overall lease term structure in different economic cycles and compare it with the lease term structure of flexible workspace providers. We also investigate the effects of flexible workspace providers as tenants on effective rents, as previous studies have demonstrated a significant difference in comparison to their peers.

The responsiveness of housing supply to changes in demand, i.e., the price elasticity of housing supply, is a key factor on the housing market. Previous literature has shown that the housing supply elasticity varies significantly across regions, and land use regulations, among other factors such as urban density, level of population, and geographical constraints, have been found to be important predictors of the variation. While the literature has widely acknowledged the negative impact of regulation on new housing supply and thereby an increasing effect on housing prices, an often brought up gap in the existing research is that it relies on rather crude measures of regulatory stringency. Different types of regulatory interventions may, however, have different effects on housing market outcomes, which makes it challenging to interpret the estimated effects of aggregate measures of land use restrictiveness. Moreover, the existing literature has focused mainly on the contexts of US and UK, while less attention has been devoted to examining impacts of land use regulation in the context of countries with statutory planning systems.

This study contributes to the extant empirical research by examining the regional variation of housing supply elasticity and its determinants in the Finnish context. The study utilizes refined measures of land use policy stringency, which reflect the prevalence and stringency of different paths of land use policy interventions. Specifically, a two-step analysis is conducted. First, this paper estimates the housing supply elasticity in the 30 largest Finnish cities. Second, these estimates and the measures of land use policy stringency are used to conduct cross-sectional investigation of the role of different types of land use regulatory interventions – including both land policy and planning interventions – in explaining differences in the housing supply elasticity across cities. The study provides hence information also on the impacts of land policy interventions, such as public land banking and negotiable developer obligations, which have received much less attention in the literature than the impacts of planning interventions.

We demonstrate how society-wide intergenerational transmission of trauma, ignored in economic models drove the Irish property bubble. Ireland’s ‘obsession’ with property owning is a psychic attempt, through repetition compulsion, to transcend the traumatic past and ‘inhabit’ an idealized pre-colonial fantasy land. We also explain why the property bubble is almost inevitably being re-enacted so soon with no apparent learning.

We examine the effect of relaxing land-use regulation on housing supply and rents at the local intra-city level. Constructing a theoretical framework based on the monocentric city model, we obtain theoretical predictions on these effects. Our framework shows that relaxing floor-to-area (FAR) restrictions lead to higher local housing supply and lower rents across the entire city, with no difference in rents between treated and non-treated areas. To bring our conceptual framework to the data, we use detailed geo-coded data from the Canton of Zurich in Switzerland from 1995 to 2020. We apply a staggered difference-in-difference model, exploiting exogenous differences in the treatment timing as identifying variation. We find that upzoning a parcel by 20% or more leads to a 13% increase in housing supply on the treated parcel in the subsequent ten years. Furthermore, changes in zoning do not significantly increase or lower rents on the treated parcels compared to the untreated parcels within the same housing market, confirming the predictions of our framework. Thus, we show that upzoning is an effective policy for increasing the housing supply without increasing rents at the local level.

Anticipated climate change impacts on the real estate sector has the potential for devastating value implications, in both the short and long term. Businesses, organisations, governments, and real estate owners and occupiers are currently tackling a changing policy environment relating to emissions reporting. In addition, a greater understanding of a range of climate change risks and the exposure of assets to a raft of risks is seeing an altering in assessment and action to future proof their businesses and assets. Valuers, in their pivotal role of evaluating real estate markets and assessing market values will need to consider how this changing environment, shifting understanding of traditional risk considerations and how policy and climate and transitional risks are incorporated into valuation practice. This paper presents current valuation practice challenges identified in valuing real estate and consideration of sustainability, emissions and climate change risks.

Policies to reduce residential segregation through the supply of affordable housing in middle- or upper-class neighbourhoods or estates, so-called social mixing policies, have been on top of urban political agendas. Yet the achievements have been rather limited, at least regarding the cases of Greater London and Paris, analysed in this study. 

The paper probes the hypothesis that affordable housing supply suffers from a collective action problem where the outcome may rather reflect neighbourhood opposition, particularly by homeowners, than the general interest. The analysis draws on two novel multi-level datasets for Greater London and the ‘Métropole du Grand Paris’, covering the neighbourhood as well as the municipal level (2010-2018).

This paper investigates the relevance of investment ratings of German (semi-)open-end real estate funds (GOEREFs) from a capital markets perspective. GOEREFs are investment vehicles which, under normal circumstances, offer their investors a permanent redemption option at their estimated net asset values (NAVs) while their shares are also floating on secondary markets. However, share redemptions are suspended when investors’ redemption demands exceed liquid assets. This setting provides a unique opportunity to study the information content of investment ratings when there is uncertainty with respect to the estimation of NAVs and the risk of “runs on the bank” (i.e., runs on the fund). Using a comprehensive hand-collected sample of 409 rating announcements for 49 funds and information from annual reports during the period 2004-2020, this study finds that whereas the predictive power of ratings for future fund returns does not exceed the predictive power of readily available publicly available information, ratings correlate significantly with the likelihood of future redemption suspensions. An event study shows that the spread between NAVs and secondary market share prices as well as trading volume react significantly to rating changes. The reactions of spreads are particularly pronounced when share redemptions are suspended, whereas trading volume is comparatively lower. The impact on spreads reverses only partially in the long run. The results do not show evidence for rating changes having an impact on contemporaneous or near-term monthly net funds flows. However, the impact of downgrades on net fund flows might be masked by downgrades being more frequently followed by redemption suspensions.

The purpose of this paper is to try to understand if investments in the "green" lead to benefits for real estate investors and therefore if these benefits outweigh the costs. Therefore, attention was paid (i) to the classification and numerosity census of real estate (RE) investments screening for environmental, social and governance (ESG) criteria based, within the ESG-framework, on their compliance score with environmental factors; (ii) to the effect that green property criteria have on the property value and expected yield considering implied risk. The survey of “green” RE investments and their performance characteristics contributes to the analysis of the role of sustainable investments in the strategic asset allocation decisions and portfolio diversification in the context of variance-minimizing investments. The analysis was carried out by comparing sustainable investments made in the EU member countries over the last decade.

The purpose of this article is to determine the revealed preferences of buyers in the secondary housing market in Poznań in 2010-2018 by age, gender, and marital status. The study was conducted based on data on transactions of real estate premises made on the secondary market in 2010-2018 in Poznań. These data were supplemented with the information contained in the Land Register (section II - ownership), in the real estate cadastre and using Google Street View. Based on hedonic models and unique datasets of over 30 thousand observations, the revealed preferences were investigated more thoroughly than before.

Pension funds aim to hold assets that match their future liabilities.  We expand extant research by considering a long period encompassing various economic regimes.  Using return data for four asset classes in Sweden over a 145-year period, we investigate the out-of-sample performance of portfolios optimized using several approaches and compare them with that of a naïve allocation.  We then turn to analyzing the drivers of asset allocations, in particular multi-family properties, over time.  The usefulness of holding residential real estate to hedge pension liabilities is assessed.  Our analyses make it possible to gauge the benefits of holding residential properties in various economic environments.

We often observe substantial delays in the development of land. The literature lists a number of reasons: from risk and uncertainty to problems with the specific plot to land banking and speculation by investors. In an earlier, quantitative analysis for the GZM metropolis in Poland (Reyman, Maier, 2022), we applied survival analysis to the development process and found strong influence of institutional factors. 

This research extends and complements the earlier study with qualitative interviews with developers and city officials, two important actors in this process. We believe that clashing perspectives of those two actors will provide us with meaningful insights into institutional and behavioural factors that influence the time of land development in GZM. After four trial qualitative in-depth interviews with city officials, we re-think questions and intend to talk to a total of five city officials and five investors. We will select interview partners from different cities (big, small, rural counties), and different investors’ types (big – small, local – country/Europe level). 

In this presentation, we will report the results of the trial interviews. Some first preliminary observations are that city officials 

• show a strong pro-investor attitude;
• do not see land speculation as a problem in their area;
• face competition from neighbouring cities for investors;
• observe some ownership problems caused by inheritance negligence or inhabitants’ emigration.

The practice has shown that greenhouse gases other than CO2 have received far too little attention, even though they make a significant contribution to global warming. The paper focuses on the status quo of the so-called F-gases (expressed as CO2 equivalent / CO2e), which are used as coolants for air conditioning systems and industrial or commercial refrigeration. F-gases are still used today in the retail real estate sector, which have a more than 3,000 times greater impact than CO2. From a technical point of view, the use of F-gases is not in itself harmful to the climate, as they are in a closed cycle. However, despite regular maintenance, leaks do occur during use, releasing harmful CO2e into the environment. Operators seem to have become aware of this problem and switch little by little to alternative coolants, but this is hardly an issue in the wider property market. Even leading benchmarking tools, such as GRESB, do not take F-gases into account. This can, under certain circumstances, massively distort the emission reduction targets of property owners.

This paper aims to show the status quo of the food retail real estate market regarding F-Gas emissions in Germany. Furthermore, these results will point out to property owners what costs they should expect in the future and, under certain circumstances, how a so-called "stranding point" can be prevented. With the CRREM Risk Assessment Tool, various sample assets (German supermarkets) are evaluated in terms of their CO2 and CO2e emissions. Afterward, the results are compared and evaluated with the country- and asset-type-specific benchmarks of CRREM. As the last step, the influence of F-gases is considered in isolation, and recommendations for action are specified. Given the increasing regulations and the growing awareness of sustainability, especially an evaluation of the CO2e emissions is urgently needed. If this is ignored, the transitory risks of buildings will increase. Action is also required as physical risks such as heatwaves are steadily growing, driving the use of increasingly expensive refrigerants. If owners are not aware of these risks, they may face high costs.

Field trip has become increasingly important in real estate education as it not only improves student’s observation skills, but also enhances their perception about the space. Previous studies suggested that field trip can enhance students’ learning experience by transforming information into personal context. It has therefore been widely used in various disciplines, such as in science, history and business. It has also been adopted in the field of geography and built environment. By just showing photos of a building or a drawing plan is not adequate, as the actual three-dimensional space are completely different from the two-dimensional drawings. Field trip is thus essential in this field. 

For the last two years, it has been difficult to organize a field trip. The COVID-19 pandemic has forced students to attend online lessons, while the field trip has been cancelled which critically affect students’ observation skills and awareness of the space. To achieve a similar learning experience, some educators have adopted virtual field trip to substitute physical field trip. Some has used traditional video to show students the buildings and its surroundings, while others started using virtual reality (VR) technology to engage the students. VR360 panorama tour is in fact a good alternative to show three-dimensional space. Although it is different from the physical field trip which activity taking outside the classroom, the students are brought into the virtual world which allow them to see and interact. This can engage the students and enrich their learning experience. 

The purpose of this study is to examine whether the use of VR as a virtual field trip can enhance students’ understanding on a retail building management. We develop VR360 panorama tour with a walkthrough interactive function named “VR Central Market” to substitute the physical field trip. The students need to find the information about Central Market in this VR tour. The VR tour can be carried out online and the students can learn at their own pace. In our study, the students are required to complete the pretest and posttest questions to examine whether their understanding has been enhanced after viewing the VR tour. The questionnaire survey is also provided to the students to understand their perception on adopting VR as a virtual field trip. Our study contributes to the literature of real estate education, as well as innovation in education.

The valuation of property interiors is highly dependent on subjective and implicit decisions of the analyst, which can be a significant limitation in practice. 

The descriptions of the interior features often do not reflect the quality truthfully (e.g., the quality of two new kitchens may differ significantly) or are intentionally formulated in a positive way in order to arouse the interest of the users.

One way to address this issue would be to use complementary information as the key to more robust information extraction and higher data quality.

We conducted an experimental approach to determine the quality of property interiors based on iterative cognitive voting of image pairs with multiple visual modalities utilizing the Elo scoring system.  

Using the obtained Elo values, we derived the inference for our experiment by predicting the rental and purchase prices along with additional explanatory variables. 

The study shows that incremental evaluation of indoor images by independent persons in the sense of  active learning can serve as a control variable for price, thus demonstrating that the Elo rating system, which has not yet been used in hedonic evaluation, has potential for further investigation.

The European Green Deal's Renovation Wave of the building stock opens up opportunities to companies in the real estate sector. The use of energy efficient lighting technologies and intelligent control systems significantly contributed to electricity savings and reducing carbon dioxide emissions in the construction sector without requiring deep interventions inside the buildings. To assess the economic revenue of the investment, it is necessary to consider both the financial savings related to electricity consumption and the resulting impact on heating and cooling consumption. Despite the wide acceptance of energy-efficient lighting, the thermal effect on the buildings in terms of heating and cooling load has not been investigated. 

This study addresses the impact of lighting efficiency interventions on heating and cooling consumption in different types of buildings within various climate zones through dynamic simulations compliant with the UNI EN 52016:2018 standard. The research outcomes provide a set of regression models valuable for carrying out simplified feasibility studies considering electric and thermal impacts of lighting renovation measures.

Diverse human activities are carried out in real estate, suggesting its significant contribution to global warming. This study examines how cognizant managers of real estate are about the potential benefits of vertical greening systems (VGSs). The research questionnaire was administered to real estate managers. The real estate managers were those under the employment of registered estate surveying and valuation firms in Lagos. They were sampled using the simple random method, with one real estate manager selected per firm. Of the total of 282 real estate managers, only 127 responded to the questionnaire, and 121 (representing 42.9%) were found to be of use in the data analysis. With the aid of the Statistical Package for the Social Sciences (SPSS v.20). The analysis of the data collected was done using the fuzzy synthetic evaluation method. The study found a generally low level of cognizance among the real estate managers (overall cognizance index = 2.60). However, based on the categories of the different benefits of VGSs, the results showed that the real estate managers' cognizance of the environmental benefits of VGSs is more than that of its social and economic benefits. Real estate managers not being fully cognizant of the potential benefits of VGSs would prevent them from giving an appropriate recommendation to the government on the need to form a policy that would mandate the installation of vegetation on buildings. We conclude that the cognizance of the real estate managers would assist the government in the formulation of policies to foster the achievement of sustainable development goals.

The following article briefly reflects the author’s progress in their complex research of specific Ukrainian problems of total housing privatization resulting in utility debts and housing stock degradation together with rising subsidies, as well as deformed condominium model without real estate object and weak residential building management. The aim of the article is to show the root of the problem which is connected with wrong property relations and to find common way out. Unlike other authors from East European countries, we base our methodology on the proof that significant part of citizens cannot afford maintenance, operation and renovation of their housing and that the public funding of homeowners is unfair and must be transformed into property exchange instead of subsidizing. To simplify this process Ukrainian wrong condominium model with ownership on individual apartment has to be transformed into housing corporation with shared ownership on land plot and whole building. Next, the shares of the company could be divided on virtual tokens represented the part of the property which could be exchanged for money. The proposed mechanism has additional advantages in case of construction and reconstruction financing, social and private renting housing development, housing management companies stimulating. The model  could be used in other East European countries with the similar problems.The problem has acquired particular importance in connection with the destruction of a significant part of residential buildings during the Russian aggression in Ukraine in 2022. New construction and restoration of housing will require fundamentally new property relations, free from existing shortcomings.

In 2020, MeilleursAgents was estimating that 2 years and 10 months were needed by a French household to amortize the cost of buying versus renting on average in France. At the same time, in Paris, the same household would have to wait 6 years and 11 months to amortize its costs. These figures are of utmost importance for households to help them decide whether they should buy or rent their main residence.

From an operational perspective, estimating this time is made possible by a precise knowledge of rent to price ratios. The main objective of this contribution is estimating those ratios on the whole French territory using observations of rent and transaction prices for the same housing between 2010 and 2021. Once those ratios are estimated, we highlight the factors that determine them using machine learning methods.

Using a coarsened exact matching, we estimate rent to price ratios on the whole territory. Then we compare two different approaches to identify the determinants of these ratios.  The first approach consists in explaining the ratios using a linear regression model to predict them using housing characteristics and geographical amenities. The second approach uses a gradient boosting decision tree model to predict the ratios. Hence, we can explain the role of each feature of the model thanks to explainability methods associated with tree models: feature importance and shape values. In order to proceed with this study, we use rental listings from MeilleursAgents platform that have geolocation at the address level. This use of such listings is inspired by Chapelle&Eymeoud(2018)1 which shows that web scrapped listings are unbiased compared to survey data such as the ones from the “Observatoire Locaux des Loyers” (OL) in France. Moreover, these surveys are limited to certain dense areas whereas our study aims at comparing mechanisms on the whole French territory.

These listings are matched with the national DV3F French database which provides us with a parcel geolocation level. Matching these two sources between 2010 and 2021 provides us with 85’000 matched ratio observations. The (rent, price) couples are used to estimate rent to price ratios and to highlight the differences in the influence of each factor depending on the territory but also thanks to our precise geolocation, inside urban areas.

Our study has a double contribution. First, from a methodological point of view, using a gradient boosting model to estimate and explain rent to price ratios has never been done. The main advantage of this method compared to classic methods is a better handling of interactions and effect heterogeneity. The second contribution leans on the precise geolocation level of our observations. These ratios are most of the time studied using ratios of average rent and average prices because of the scarcity of precisely geolocated data. Yet, Hill&Syed(2016)2 showed that such an approximation can lead to an error up to 20% when estimating the ratio. Therefore, they advise to use housing level matching to control feature heterogeneity between rented and sold housing. Our study is thus the first study in France that allows an exact matching outside of the dense areas covered by the “Observatoire Locaux des loyers” on this topic.

We highlight the strong heterogeneity of rent to price ratios inside dense urban areas but also at a larger scale. To our knowledge, this study is the first to bring this phenomenon out at this national scale.

• 1. Chapelle G., Eymedoud J.-B., « Can Big Data Increase Our Knowledge of Local Rental Markets? Estimating the Cost of Density with Rents », SciencesPo Mimeo, 2018
• 2. Hill R.J., Syed I.A, « Hedonic price–rent ratios, user cost, and departures from equilibrium in the housing market», Regional Science and Urban Economics, pp 60-72, 2016

This paper presents stylized facts on urban housing development and neighborhood change using parcel level registry data from the Netherlands between 2013-2020. We propose a methodology to detect and subsequently classify development clusters over space and time. Using this approach, we are able to provide a number of novel insights on urban housing development. First, we find that urban housing supply mostly results in densification of urban areas. This is the result of both infill development and the redevelopment of residential and non-residential areas in higher densities. Second, urban housing development is highly heterogeneous and different types of development occur in distinctly different neighborhoods. We find, for example, that housing development in neighborhoods with a lower socio-economic status almost exclusively consists of development as part of urban renewal schemes. Finally, we also find that urban housing development is highly concentrated, with 20% of the largest development clusters supplying roughly 80% of new urban housing units.

The usage of Automated Valuation Models for taxation purposes has been discussed extensively at the past. Here we work in detail such an approach for Greece. In Greece, taxation is based on a system of zones. Each property belongs to one and only zone, and then from an initial objective value per square meter and with the use of certain coefficients one adjusts and calculates the objective value for each property. This value is used further for taxation and other purposes.  There is always a big question/debate whether such values represent the market values of the properties (or they approach them at least) leaving aside of course discussion about taxation policies of the government. Triggered by the recent update of the zone values, we attempt to compare those values with market values obtained, based on historical data,  via our AVM. The scope is to examine the plausibility and realism for the existing system as well as to demonstrate potential improvement if somebody needs to keep using such an approach. Our results show that there is a huge number of zones with rather impossible low values, below the average cost of building a new property as well as problems in the coefficients used to adjust the characteristics of the property. In general the objective values underestimate the market values in a great extend. Further discussion and suggestions for improvements is made.

Descriptive and diagnostic analysts more frequently utilize data visualization techniques to help frame and answer two key questions: “what happened?” and “why did it happen?” To comprehensively assess the quality of life in two neighboring Coastal Alabama counties, regional civic leaders identified 17 metrics that could help them interpret how the community is performing as a whole (the “what happened” question) and offer insights into areas needing improvement (the “why it happened” question), all with an eye toward long-term support of the community and its real estate values. A few examples of included metrics are crime, housing, poverty, high school graduation, obesity, infant and childhood mortality, and water and air quality. Our business research and services center, the South Alabama Center for Business Analytics, Real Estate, and Economic Development, joined the effort by developing and hosting a series of web-based, interactive, dynamic dashboards. We created multiple visualizations to address each metric using publicly available data sources to answer the “what happened” question. More importantly, because the community initiative’s goal is to spur conversations about addressing areas needing improvement, we took great care to design all dashboard visualizations to motivate and inform community improvement discussions that focus on “why it happened.” We did so by streamlining data comprehension and minimizing misinterpretation, offering a single question as the title of each visualization. Additionally, considering carefully the core visualization component techniques of spatialization and pre-attentive attributes, we worked to ensure that each visualization within the dashboard “family” had the same look and feel so that community leaders could spend their time working on discussing and promoting real community-based solutions rather than trying to interpret and explain differing visualization interfaces. We contend that better solutions to community problems help to ensure better community outcomes and help to ensure the values of real estate within a community.

The paper builds the cycles of transactions and prices in the short term rental market from 2015 to 2021 for 46 European and Asian cities to understand how short-term tenants move across the cities. Having the cycles at the city level, the paper builds a panel and estimates a supply-demand model for the short-term rental market and analyses the endogenous relationship and ripple effect among cities using the VECM framework. Results suggest the existence of links between cities, both in short-term rental contracts and prices, supporting the hypothesis that short-term rental market visitors choose cities clustered in networks and that those networks compete with each other as alternative destinations. The evidence suggests that, through the technological platforms and individually, a particular city network is chosen as an alternative to others, revealing tastes changes and inducing segmentation in rental price growth and investment.

Autoregressive heteroscedastic effects in financial time series have been subject to a broad field of applied econometrics. Both academic research, as well as the industry, apply GARCH processes to real estate data with previous investigation mostly focused on securitized real estate positions. So far, the common approach in the literature has been to assume normal distribution of the innovation term for the GARCH modelling of direct real estate markets (Miles, 2008). The specified assumption of normality however falls short of the data characteristics exhibited by direct real estate markets, such as returns of real estate prices explicitly not normally distributed and better characterized by a more leptokurtic, skewed distribution (Schindler, 2009). Ghahramani and Thavaneswaran (2007) point out that typically the innovation distribution is selected without further justification (also see Pin-te & Fuest (2014) footnote for a simple switch to student-t without further justification). Consequently, the omission of a priori assumptions about the innovation term distributions being fit to direct real estate leading to misspecification and -parameterization of GARCH models is the research aim of this study. The employed analysis will utilize monthly transaction-based data for ten US property market subsets, whilst observing a window of time to encompass different market conditions and volatility regimes (Perlin et al., 2021). Determining how ARCH effects might differ across different US real estate submarkets as well as major and non-major markets builds on and extends previous research focused on geographical disaggregation (see Crawford and Fratantoni, 2003; Dolde and Tirtioglu, 1997; Miles, 2008; Schindler, 2009). Subsequently fitting and estimating each data subset with a conditionally normally distributed GARCH model will be juxtaposed by employing a variety of innovation distributions to the data. It follows the central hypothesis of this paper, that the goodness of fit for GARCH models can be improved by allowing for the conditional distribution to be modeled as a flexible a priori assumption. Investigating the differing goodness of fit for the models and employing the most appropriate models to re-estimate the GARCH parameters will allow an analysis of the differences in volatility clustering effects to the model employing normally distributed innovations. The aim is to show empirically, that non-normal innovation term distribution leads to a potentially better goodness of fit of the GARCH model. The utilization of a priori assumptions of GARCH model specification is of high importance not only for portfolio management of investors, but also risk management for economic institutions such as central banks and mortgage banks (Schindler, 2009). To the best of the authors’ knowledge, there is no study which scientifically examines the innovation term distribution of GARCH models of direct real estate investments. This paper aims to provide a better understanding of the influence a priori assumptions of the innovation term can take to increase the validity of volatility models for direct real estate investments.

There is a broad consensus in international statistical organizations such as Eurostat, the European Central Bank, and the International Monetary Fund that price indices should be constructed using transaction data. However, transaction data often lag behind actual market developments in the housing market for new-built properties as prices are typically set months or years before transactions are finalized. We find that for two large Polish cities (Warsaw and Poznan), house price indices (HPIs) for existing properties lead indices for new builds by, on average, eight quarters. In Poland and other countries with large markets for new-builds, this lag can dramatically distort National HPIs. The lag also affects the European Union’s flagship measure of inflation, the Harmonized Index of Consumer Prices (HICP). This is because the HICP includes owner-occupied housing (on an experimental basis) using exclusively transaction data for new-built properties. We illustrate here that the timeliness issue in the price index for new-built properties disappears when preliminary agreements are used instead of transactions in the compilation of the index.

We explore investor expectations about the effects of work from home (WFH) for the commercial real estate sector. We assess how differences in WFH exposure of listed real estate investment trusts (REITs) in the largest European economies – Germany, France and the UK – during the early stages of the Covid-19 pandemic affect their abnormal returns. We measure WFH exposure as REIT’s exposure to the office sector, central business districts (CBDs) and WFH tenants. To capture tenant’s strong commitment to working from home in the future, we construct a variable for tenant WFH intensity using tenant WFH announcements between March and June 2020. We show that REITs with higher WFH exposure have significantly negative abnormal returns independently of their domicile, sector specialization or CBD exposure. Equity investors look at REIT portfolio composition and WFH announcements by tenants to assess the likelihood of WFH in the long term and the associated drop in office demand.

The purpose of this paper is to evaluate the impact of beneficial externality generated by the World Heritage List (WHL) on residential property values in order to offer new insights into heritage discourses. The study uses the hedonic price model to estimate empirically the difference in prices for residential properties located in the Old Rauma World Heritage. The study uses residential sales transaction data from the City of Rauma from January 2005 to September 2012 drawn from an online database called KVKL Hintaseurantapalvelu managed by the Central Federation of Finnish Real Estate Agencies. The research results indicate a positive, but insignificant, relationship between the property sale prices (Euros/sqm) and heritage designation. However, the total sale prices are higher in Old Rauma as the residential properties are significantly larger in Old Rauma compared to other properties in Rauma.