Search Results (130)

This study examines the integration of multi-real-option valuation and security token offering (STO) as an innovative approach to real estate project financing. The case study of Aspen Resort Development serves to illustrate this methodology. The traditional discounted cash flow (DCF) method is frequently ill-suited to the dynamic and uncertain nature of long-term real estate projects, particularly in regard to the ability to adapt to market fluctuations. In order to address these limitations, this study employs a multi-real-option model with a binomial lattice framework, thereby facilitating flexible decision-making in various investment stages. The analysis demonstrates that the STO-based project financing (STO-PF) model offers enhanced financial performance and strategic advantages in comparison to the conventional DCF approach. Furthermore, the STO-PF model has the effect of increasing liquidity, expanding investment accessibility, and improving risk management through the utilization of digital platforms. By quantifying the project’s extended net present value (ENPV), the integration of STOs with real-options models can facilitate optimal investment decisions in the context of a high level of market volatility. Consequently, the STO-PF model is determined to yield a project value (E) of USD 7.34 million and a real-options value (ROV) of USD 3.69 million. This is markedly higher than the net present value (NPV) of USD 3.65 million derived from the traditional project finance (PF) model. Furthermore, the put option for the second investment stage contributes USD 16.45 million to the overall value of the project, thereby demonstrating the flexibility and strategic advantages of the STO framework in comparison to static NPV analysis. The Aspen project serves as a case study, demonstrating the financial viability of phased investments in dynamic market conditions. It contributes to the theoretical understanding of STO-based financing and provides practical insights for developers seeking flexible and innovative financing solutions in the real estate sector. Further research is required to confirm the applicability of STOs in diverse market environments and regulatory contexts. Additionally, in-depth research is necessary to integrate emerging technologies, such as artificial intelligence and machine learning, into multi-real-option-based financial platforms. This integration aims to enhance financial modeling and decision-making processes, as well as to facilitate the integration of digital technologies in this field. Only then can the development and implementation of smart construction development advance. Full article

This study aims to identify the added value of smart city technologies in real estate development, one of the most significant factors that would transform traditional real estate into smart ones. In total, 16 technologies utilized at both levels have been investigated. The research followed an integrative review methodology; the review is based on 168 publications. The compiled results based on metadata analysis displayed the state of each technology’s added values and usage in both scales. A total of 131 added values were identified. These added values were categorized based on the real estate life cycle sub-phases and processes. Moreover, the value of the integration between these technologies was revealed. The review and results proved that these technologies are mature enough for practical use; therefore, real estate developers, city management, planners, and experts should focus on implementing them. City management should invest in Big Data and geodata and adopt several technologies based on the aspects required for development. This study can influence stakeholders, enhance their decision-making on which technology would suit their needs, and provide recommendations on who to utilize them. Also, it provides a starting point for stakeholders who aim to establish a road map for incorporating smart technologies in future smart real estate. Full article

Real estate plays a pivotal role in the contemporary world, accounting for over half of global wealth and significant employment and GDP shares. This essay examines three key events—the 2007–2008 Global Financial Crisis (GFC), the COVID-19 pandemic, and recent technological revolutions—to place real estate’s centrality. By analyzing housing price indexes in major economies, the paper identifies global trends and regional nuances, as well as highlights real estate’s dual role as both a reflection and a driver of economic cycles. Then, I explore in detail the GFC, the urban roots of COVID-19 and its effects on real estate markets, and the relationship between new techno-economic paradigms and cities and real estate. Future research directions on real estate are also pointed out. Full article

The visual perception of interior architecture plays a crucial role in real estate marketing, influencing the decisions of buyers, interior architects, and real estate agents. These professionals rely on personal assessments of space, often drawing from their experience of using décor to influence how interiors are perceived. While intuition may validate some approaches, this study explores an under-examined aspect of interior design using a mobile eye-tracking device. It investigates how decorative elements affect spatial perception and offers insights into how individuals visually engage with interior environments. By integrating décor into the analysis of interior architecture, this study broadens the traditional scope of the field, demonstrating how décor composition can modulate spatial perception using eye-tracking technology. Results show that effective styling can redirect attention from key architectural elements, sometimes causing them to be overlooked during the critical first moments of observation commonly known as the “first impression”. These findings have important implications for interior design practice and architectural education. Full article

One of the key elements in real estate appraisal of residential buildings is the usable area. To determine the monetary value of real estate, appraisers in Poland often rely on transaction data registered in the Real Estate Price Register (REPR). However, the REPR may contain meaningful gaps, particularly on information concerning usable areas. This may lead to difficulties in finding suitable comparative properties, resulting in mispricing of the property. To address this problem, we used linear and nonlinear models to estimate the usable area of buildings with multi-pitched roofs. Utilizing widely available data from the Topographic Objects Database (BDOT10k) based on LiDAR technology, we have shown that three parameters (building’s covered area, building’s height, and optionally the number of storeys) are sufficient for a reliable estimate of the usable area of a building. The best linear model, using design data from architectural offices, achieved a fit of 95%, while the best model based on real data of existing buildings in the city of Koszalin, Poland achieved 92% fit. The best nonlinear model achieved slightly better results than the linear model in the case of design data (better fit by approximately 0.2%). In the case of existing buildings in Koszalin, the best fit was at 93%. The proposed method may help property appraisers determine a more accurate estimation of the usable area of comparative buildings in the absence of this information in the REPR. Full article

The Green Building Evaluation Standard (ESGB) has become an important support for China’s building sector in realizing the “double carbon” goal. However, there remains a lack of comprehensive research on the historical evolution and development status of the ESGB. This study firstly analyzes the updating logic and development strategy of the three versions of the ESGB, then compares the differences between ESGB 2019, CASBEE-NC 2014, and LEED O+M v4.1 from the perspective of the index system, and further examines the current international application status of the ESGB. The results show that LEED focuses on decarbonization and ecological protection, while CASEBB focuses on the concept of humanization and positively influences the local real estate market, and ESGB 2019 contains more health and comfort considerations than its previous version and is close to the internationally advanced level in terms of provision setting and international application. This study offers valuable insights into the potential for further refinement of green building standards in China and highlights areas for future research, including enhancing the ESGB’s adaptability and integration with emerging technologies to promote global sustainable development. Full article

This paper explores different building maintenance strategies in commercial buildings in Sydney, Australia, focusing on corrective maintenance (CM) and preventive maintenance (PM). While CM involves rectifying issues after they occur, PM aims to enhance productivity by anticipating potential issues. Although PM seems more logical, the decision to implement this type of maintenance strategy are typically made based on item reliability, failure frequency, and downtime cost, commonly found in manufacturing facilities or critical environments. However, as found in the selected/surveyed commercial real estate buildings, CM was more frequently adopted in aged facilities with older infrastructure, and PM was favoured for buildings without structural deficiencies; however, operating equipment failures were common. However, in many cases, decision makers did not consider the broader effects of downtime beyond direct financial losses, costs associated with customer satisfaction, worker efficiency, rent abatements, and reputation damage. While each building is unique and may require a bespoke maintenance schedule, this study’s insights may help managers select the most appropriate maintenance strategy. Nonetheless, further research is needed to investigate the role of innovative technologies (such as machine learning and artificial intelligence) in enhancing maintenance efficacy and explore the influences of economic shifts, corporate and financial objectives, and the availability of technical resources. Full article

The traditional concept of real estate, rooted in physical attributes—including land, buildings, and infrastructure—has undergone significant transformation in the digital age. This paper repositions real estate as a foundational platform within the broader digital ecosystem, serving as an integrative node that connects various digital platforms. By examining processes such as informatization, servicization, automatization, e-spatialization, dematerialization, and humanization, this study demonstrates how these elements collectively embed economic, social, and environmental value states into the digital framework of real estate. Leveraging advanced technologies and interdisciplinary methodologies, this paper constructs a comprehensive framework for understanding real estate’s digital evolution. The findings highlight real estate’s pivotal role in providing essential spatial and digital infrastructure that support the integration and operation of other platforms. It contributes to the discourse on platformization by offering a new model for understanding and utilizing real estate in a digitally driven society while proposing strategies crucial for its successful implementation in the ongoing digital transformation. Full article

Real estate mass appraisal is increasingly gaining popularity as a critical issue, reflecting its growing importance and widespread adoption in economic spheres. And data-driven machine learning methods have made new contributions to enhancing the accuracy and intelligence level of mass appraisal. This study employs python web scraping technology to collect raw data on second-hand house transactions spanning from January 2015 to June 2023 in China. Through a series of data processing procedures, including feature indicator acquisition, the removal of irrelevant sample cases, feature indicator quantification, the handling of missing and outlier values, and normalization, a dataset suitable for direct use by mass appraisal models is constructed. A dynamic neural network model composed of three cascaded sub-models is designed, and the optimal parameter combination for model training is identified using grid searching. The appraisal results demonstrate the reliability of the dynamic neural network model proposed in this study, which is applicable to real estate mass appraisal. A comparison with the common methods indicates that the proposed model exhibits a superior performance in real estate mass appraisal. Full article

The concept of homogeneity in the real estate market is a well-known analysis aspect, yet it remains a significant challenge in practical implementation. This study aims to fill this research gap by introducing the HELIOS concept (Homogeneity Estate Linguistic Intelligence Omniscient Support), presenting a new approach to real estate market analyses. In a world increasingly mindful of environmental, social, and economic concerns, HELIOS is a novel concept grounded in linguistic intelligence and machine learning to reshape how we perceive and analyze real estate data. By exploring the synergies between human expertise and technological capabilities, HELIOS aims not only to enhance the efficiency of real estate analyses but also to contribute to the broader goal of sustainable and responsible data practices in the dynamic landscape of property markets. Additionally, the article formulates a set of assumptions and suggestions to improve the effectiveness and efficiency of homogeneity analysis in mass valuation, emphasizing the synergy between human knowledge and the potential of machine technology. Full article

Traditionally, studies analyzing consumer preferences in real estate have focused on measuring subjective user responses, neglecting associated physiological responses. This study investigates the relationship between visual attention patterns and subjective evaluations of home sales information. Eye-tracking technology was used to record two characteristics of 21 participants’ visual behavior while viewing stimuli containing information about home sales (First Fixation Time and Total Fixation Duration). Additionally, participants evaluated their level of satisfaction with nine dwelling characteristics based on a questionnaire adapted for this research (1, quality and finishes of the dwelling; 2, size of the dwelling; 3, dwelling floor level; 4, bright and outdoor orientation of the dwelling; 5, flexible layout; 6, peaceful atmosphere; 7, smart and secure character; 8, privacy; and 9, original and luxurious character). The results demonstrated significant correlations between fixation time on specific areas of the stimulus and subjective ratings of features such as size, quality, finishes, layout, and orientation of the homes. Furthermore, differences based on gender and participants’ architecture experience level were observed in visual behavior during image observation. These findings underscore the importance of visual design and presentation in home marketing, as visual attention can influence perceptions of home characteristics and, ultimately, purchase decisions. Full article

Around 35% of the total housing stock of the European Union is more than half a century old. The shortage of funds for new construction, combined with rapidly changing economic, social, and technological factors, has led to significant obsolescence. Additionally, this situation makes it difficult to satisfy the owners’ energy, functional, and socio-economic needs. This research aims to develop an innovative retrofit approach that brings multiple benefits to assessing retrofit designs for social housing, with specific emphasis on volumetric envelope additions toward the nearly zero energy buildings target (nZEBs). To achieve the purpose of this study, the research through design methodology was chosen. The research methodology consisted of two phases: design and simulation. First, the design phase focused on re-designing and retrofitting social housing to address various aspects of the functional requirements in developing rational solutions. Second, the simulation phase focused on computational modeling and analysis of energy performance to assess the nZEBs target. The results show that the use of high-efficiency Heating, Ventilation, and Air Conditioning (HVAC) systems and improved material envelopes cut electricity consumption use by 43% and primary energy use by 40% compared to the base case. Photovoltaics (PV) production can meet the total electricity demand for six months. This approach can encourage residents and tenants to actively participate in the retrofit process and increase the real estate value of buildings through improvements in energy efficiency and housing function. Full article

After the announcement of the outbreak of the COVID-19 pandemic, people around the world had to adopt online education, working from home and social-distancing policies in an effort to stop the spread of COVID-19. The lockdowns and home isolation brought to the surface the current limitations of the existing housing stock as people needed to re-organize their home space to host various daytime functionalities. Therefore, one could question whether the priorities of potential homebuyers have been changed due to technology, health, and socialization alteration? This study explores the preferences for housing attributes and trends in Cyprus post-COVID-19 pandemic and compares these against the views of real estate professionals who represent the Cypriot residential demand prior the pandemic. Data were gathered via qualitative surveys from 117 potential homebuyers and 36 real estate professionals from across Cyprus. A survey methodology with questionnaires was used to analyze the changes in the real estate demand between the pre- and post-COVID-19 periods. Descriptive statistics were used to determine the mean importance of the housing attributes and to compare the results from the pre- and post-COVID-19 pandemic periods. The analysis found a shift toward houses rather than apartments, and the results suggest that new housing should contain more capacity for private use spaces, and at the same time, it should be designed with flexible and adaptive layouts to accommodate more activities. This study discusses whether these shifts are likely to be temporary or permanent and the implications for real estate professionals. Full article

In the face of pressing global challenges such as climate change, socioeconomic inequalities, and rapid urbanization, ensuring sustainable development in the regions has become essential. The COVID-19 pandemic has highlighted how vulnerable cities are to unforeseen crises and underscored the urgent need for proactive urban planning strategies capable of navigating dynamic and unpredictable futures. In this context, the use of geographic information systems (GIS) offers researchers and decision makers a distinct advantage in the study of spatial data and enables the comprehensive study of spatial and temporal patterns in various disciplines, including real estate valuation. Central to the integration of modern technology into real estate valuation is the need to mitigate the inherent subjectivity of traditional valuation methods while increasing efficiency through the use of mass appraisal techniques. This study draws on extensive academic literature comprising 103 research articles published between 1993 and January 2024 to shed light on the multifaceted application of GISs in real estate valuation. In particular, three main areas are addressed: (1) hedonic models, (2) artificial intelligence (AI), and mathematical appraisal models. This synthesis emphasizes the interdependence of numerous societal challenges and highlights the need for interdisciplinary collaboration to address them effectively. In addition, this study provides a repertoire of methodologies that underscores the potential of advanced technologies, including artificial intelligence, GISs, and satellite imagery, to improve the subjectivity of traditional valuation approaches and thereby promote greater accuracy and productivity in real estate valuation. By integrating GISs into real estate valuation methodologies, stakeholders can navigate the complexity of urban landscapes with greater precision and promote equitable valuation practices that are conducive to sustainable urban development. Full article

Price markups and firms’ Tobin’s Q ratios are widely believed to have been increasing in the past several decades. Various models for the calculation of price markups have been developed, each relying on the historically held definition of the ratio of price to marginal cost; however, all of these have methodological drawbacks, and some of the results they have produced have been poorly reflective of the near past wider macroeconomic experience. This paper defines a new approach for the definition and measurement of markup pricing, and it also avoids some of the issues surrounding the marginal cost approaches by using the measure of economic rent and the capital asset pricing model. The results show limited markup pricing for the UK’s FTSE 100 companies (2018–2023), but that certain real estate, technology/media and financial services/equity investment firms have enjoyed higher price markup levels. An analysis of the business models of these firms is used to qualitatively propose explanations for such markups. This work offers formal proof that that the expected price markup is equal to Tobin’s Q and finds that the empiric market level of markup is near equivalent to the market Tobin’s Q; the differences between the markup and Tobin’s Q at the level of the firm are equally assessed. This work challenges the general consensus that price markups are above one and have been increasing; it may also aid policy makers with respect to taxation policy and regulatory measures, as well as the financial management of firms in decisions concerning capital deployment and portfolio management. The method merits expansion to wider data sets, as well as to those from outside of the UK. Full article