Search Results (52)

Housing unaffordability and widening socio-spatial polarization continue to pervade US cities today. Driving this phenomenon, in part, is the increasing investment of rental housing stock by corporate landowners who rely on firms like RealPage, Inc. to employ advanced algorithms that determine the highest possible rent to charge tenants. RealPage is currently being sued for violating US antitrust law. This study critically examines the evidence against and in defense of RealPage to identify the firm’s practices as a technologically advanced strategy of pursuing class monopoly rent (CMR). In the process, the study brings scholarship on platform real estate into closer dialogue with land rent theory and criticism of existing antitrust law in the US to establish a more nuanced understanding of intentionality. We argue that the treatment of intentionality by the existing legal framework is limited in terms of recognizing the myriad ways in which CMR is realized in the rental housing sector, especially in contexts where CMR is realized without entailing explicit collusive intent among the market players. Our analysis also reveals that RealPage’s algorithmically enabled pursuit of CMR potentially widens the scale of impact across submarket boundaries that might not have otherwise been possible, exacerbating existing and entrenched patterns of socio-economic segregation and socio-spatial inequality. We conclude by discussing the implications of the study’s findings for policy with an emphasis on the kinds of policies intended (or designed) to suppress the pursuit of CMR in the first place. Full article

The world is characterised by the growing volumes and flow of goods, which, amid benefits to economic development, result in negative externalities affecting the sustainability of cities. Although numerous studies have analysed the locational patterns of logistics facilities in cities, further research is required to examine their real estate patterns and trends. The aim of the paper is, therefore, to analyse the value of land accommodating logistics facilities in the City of Cape Town municipality, South Africa. Given the lack of dedicated geo-spatial data, logistics firms were searched on Google Maps, utilising a combination of aerial photography and street view imagery. Three main attributes of land parcels hosting logistics facilities were thereafter captured from the municipal cadastral information: property extent, street address, and property number. The latter two were used to extract the 2018 and 2022 property market values from the valuation rolls on the municipal website, followed by statistical, spatial, and geographically weighted regression (GWR) analyses. Zones near the central business district and seaport, as well as areas with prime road-based accessibility, had high market values, while those near the railway stations did not stand out. However, GWR yielded weak relationships between market values and the locational variables analysed, arguably showing a disconnect between spatial planning and logistics planning. Towards augmenting sustainable logistics, it is recommended that relevant stakeholders strategically integrate logistics into spatial planning, and particularly revitalise freight rail to attract investment to logistics hubs with direct railway access. Full article

This study investigates how China’s affordable housing policies have shaped the real estate market, using data from 35 major cities between 2010 and 2023. By analyzing housing prices, sales, and investment trends with advanced statistical methods, we found that increasing the supply of affordable housing significantly slows down rising home prices, especially in cities with high housing costs. During the COVID-19 pandemic, these policies also helped stabilize the market by boosting housing sales and reducing price volatility. Our research highlights regional differences: affordable housing works best in economically developed eastern cities to curb prices, while in less-developed central and western areas, it may temporarily increase prices due to land competition. We also show that affordable housing absorbs demand from low- and middle-income buyers, easing pressure on commercial housing markets over time. This study provides practical insights for policymakers to design targeted housing strategies, optimize land use, and enhance urban resilience during crises, like pandemics. By combining real-world data with robust analysis, we offer a clearer picture of how housing security policies can balance market stability and affordability in rapidly urbanizing economies. Full article

This study addresses the vast amount of information held by the banking sector, especially regarding opportunities in tourism development, production, and large residential projects. With advancements in information technology and databases, data mining has become essential for banks to optimally utilize available data. From January 2023 to July 2024, data from the Egyptian Arab Land Bank (EALB) were analyzed using data mining techniques, including rough set theory and the Weka version 3.0 program. The aim was to identify potential units for targeted marketing, improve customer satisfaction, and contribute to sustainable development goals. By integrating sustainability principles into financing approaches, this research promotes green banking, encouraging environmentally friendly and socially responsible investments. A survey of EALB customers assessed their interest in purchasing homes under the real estate financing program. The results were analyzed with GraphPad Prism version 9.0, with 95% confidence intervals and an R-squared value close to 1, and we identified 13 units (43% of the total units) as having the highest marketing potential. This study highlights data mining’s role in enhancing marketing for the EALB’s residential projects. Combining sustainable financing with data insights promotes green banking, aligning with customer preferences and boosting satisfaction and profitability. Full article

Since 2016, strict regulatory policies have limited the size and financing channels of China’s urban real estate market. To adapt to the new situation, real estate developers need to adjust their development strategies and adopt more precise investment methods. In this respect, cost reduction, an accurate market positioning, and conducting detailed market research are particularly crucial. Given that the uneven development of the urban housing market has exacerbated urban segregation, urban residential space was subdivided into multiple potential submarkets. This study focuses on the land acquisition and the development of commercial residential projects in Hangzhou, China, from 2003 to 2022. Using the latent class analysis method based on the discrete choice model, the potential submarkets of Hangzhou’s housing development market are identified, and the project positioning and land selection preferences of developers are assessed. The results show that Hangzhou’s residential projects can be divided into five potential market categories: high-rise basic demand dwellings, high-end-improvement-type dwellings, luxury low-density dwellings, primary-improvement-type dwellings, and large-scale mixed-density dwellings. The importance of different land elements for developers when developing various types of projects is evaluated by calculating the willingness-to-pay coefficient. The findings of this study provide a comprehensive perspective for the government, real estate developers, and property owners to better understand the development dynamics on the supply side of the real estate market. Full article

Alongside the economic system reforms and the rapid development of the Chinese economy, wealth gap in China is widening, gradually evolving into an important issue that threatens the sustainable development of China. To comprehensively understand the evolution of wealth disparity in China and the underlying reasons behind its changes, we use CHIP and CFPS datasets to construct time series data of China’s wealth inequality. Based on that, we explore the main reasons of the wealth change through asset decomposition, urban–rural decomposition, and regional decomposition, which is followed by the analysis of the possible role of policies in this process. Our findings reveal a two-stage evolution of wealth inequality in China: from 1995 to 2010, there was a rapid escalation in wealth disparity; after 2010, the rate of increase in China’s wealth disparity was gradually mitigated, yet persisted at a heightened level. Net housing assets, urban–rural disparity, and regional disparity have been pivotal in this evolution. In recent years, financial assets have demonstrated significant substitutability for housing assets, progressively supplanting housing assets as the principal driver of wealth inequality in China. We scrutinize the evolution of it in conjunction with China’s real estate, land, and capital market policies, finding these policies to have played critical roles in shaping the trajectory of inequality evolution. Full article

The preservation of cultural heritage plays a key role in the development of society. To preserve cultural heritage, protection zones are established, which represent an encumbrance on land plots and, therefore, should be taken into account in the valuation process. Currently, there is a problem that mass (cadastral) and individual valuation methods do not necessarily include cultural heritage objects and their zones in cost coefficients. The absence of a mechanism to address their individual characteristics in the real estate valuation system has a significant impact on the value of real estate and leads to unjustifiably inflated market value and, as a consequence, to disputing the results of cadastral valuation. This article is devoted to determining the impact of protection zones of cultural heritage objects on the value of land intended for individual housing construction, using the example of the city of Orenburg. This article considers various methods of identifying patterns of the influence of zones with special conditions of use of the territory on the market value of land and substantiates the use of the method of comparative sales in the conditions of a low-active land market in Orenburg, a statistical analysis of market information, on the basis of which the type of activity of the real estate market in Orenburg was determined. The patterns of the calculation of corrections for the remoteness of the studied land plots from the objects of the transport and social infrastructure of Orenburg were revealed in this work as well. Through the method of paired sales within the framework of an individual assessment of the land plot intended for individual housing construction, the diminishing impact of the zones of protection of cultural heritage objects on the market value of land plots was revealed. This allows for conclusions to be drawn as to whether objects of cultural heritage have an impact on the value of real estate, and as a result, there is a need to modify the applied methods of mass and individual real estate valuation within the boundaries of historical settlements. Full article

This study explores the impact of accessibility on property pricing and land economies by advanced spatial analysis techniques, focusing on Shanghai as a representative metropolis. Despite the impact of metro systems on residential property values, which has been frequently assessed, a research gap exists in understanding this phenomenon in Asian, particularly Chinese, urban contexts. Addressing this gap is crucial for shaping effective urban land use policy and improving the land economy rationally in China and similar settings facing urban challenges. To assess the impact of metro station accessibility on property prices in Shanghai, with extensive rail transit, and to deeply explore the overall impact of land value varieties driven by metro on urban development, we conducted a comprehensive analysis, with discussion about future aspirations for land planning and management along with landscape and facility design, and measures to improve land economy. The procedures involved creating neighborhood centroids to represent accessibility and using the Euclidean distance analysis to determine the shortest paths to metro stations. Our evaluation incorporated a hedonic pricing model, considering variables like neighborhood characteristics, housing attributes, and socio-economic factors. Advanced spatial analysis encompassing Ordinary Least Squares (OLS) regression and XGBoost analysis were employed to explore spatial effects, and Geographically Weighted Regression (GWR) helped examine spatial patterns and address autocorrelation challenges. Results revealed a negative association between distance to metro station and property prices, indicating a non-linear and spatially clustered relationship and heterogeneous spatial pattern. We dissected the non-linear results in detail, which complemented the conclusion in existing research. This study provides valuable insights into the dynamic interplay between metro accessibility and housing market behaviors in a significant Asian urban context, offering targeted suggestions for urban planners and governors to decide on more reasonable land use planning and management strategies, along with landscape and infrastructure design, to promote not only the healthy growth of the real estate market but also the sustainable urban development in China and similar regions. Full article

Drastic shifts in prices and housing market trends in recent years, representing shocks to the housing system, have led many residential developers to pause or cancel their projects. In the already heated housing markets of the Greater Toronto Area (GTA), these supply frictions can have ramifications for affordability. Our study formulates a standardized “proforma” model of the profitability of a hypothetical condominium project in the city of Toronto, Canada, scheduled between 2019 to 2023, to explore the combined effect of developers’ price expectations and market volatility on developers’ decisions. Using the proposed proforma, we first identify the key drivers of development decisions. We then evaluate the impact of the expectation formation of key factors influencing perceived development profitability, including construction costs, sales prices, and interest rates, on the financial feasibility of potential developments. The results highlight that boundedly rational expectations can cause variations in profitability perceptions and potentially reverse development decisions in volatile market conditions. Our results highlight the sources of risk and uncertainty in development decisions, facilitating the recognition of possible solutions to mitigate these risks and increase affordable housing supplies. The proposed model can also enhance the realism of decision models in agent-based representations of land and housing markets. Full article

The present study is part of the context in which Romania adopted the European Parliament Directive 2007/60/EC on flood risk assessment and management. Therefore, the aim of this research is to assess the risk induced by a hydrological hazard, expressed by a financial value estimation, for the Turcu River in the northern sector of the Bran–Dragoslavele transcarpathian corridor (Romania), an important tourist axis where the pressure on land has increased considerably. As a result, the intra-village areas of Moieciu de Sus, Cheia, Moieciu de Jos, Bran and Tohanu Nou have also expanded into areas vulnerable to flooding. There are currently no studies on the areas potentially affected as well as the extent of the possible damage. For this reason, we proceeded to model the water level corresponding to the maximum flow value with a probability exceeding 1%, using HEC-RAS and ArcGIS software. The results of the implementation of the spatial analysis model resulted in the delineation of the floodplain and the assessment of the potential financial loss related to the minimum market value of the land with the related real estate infrastructures. The research reveals that in the 1% band area (78.7841 ha) with water depth > 0.5 m, more than 433 infrastructures are at high risk of flooding, most of them with high real estate value, i.e., 5.61 km of roads for which a cost of EUR 3,402,666.90 was calculated for restoration. A knowledge of financial vulnerability to flooding becomes important for the community; local authorities involved in making decisions for insuring real estate at risk and planning/managing investments work to prevent/combat the effects of flooding. Full article

Recent literature has highlighted the critical issue of urban land value and cost; properly assessing land use costs, particularly for residential and commercial purposes, is crucial in influencing urban development and investments. Therefore, the objective of this research is to create a model for land pricing that considers the urban street networks and hierarchy; by analyzing the spatial plan of the city using space syntax and evaluating the economic impact on land value, the study aims to identify the factors that influence land prices. Furthermore, the study intends to investigate the correlation between urban spatial networks, street hierarchy, and land price to create a predictive model for urban spatial land pricing. Ultimately, the study has successfully built a model for predicting the price of urban land. The case selected is evaluated and compared in three aspects of the analysis, including the urban axial assessments and urban street width, to find out their impacts on the real estate’s land price in the context of the land use distributions, which are predominantly residential and commercial types of uses. Depth map X8, SPSS, and QGIS 3.16 were used for the study evaluations and assessments. The study found that land prices are influenced by factors such as integration, connectivity, and street width. Commercial zones with good integration and wider roads tend to command higher prices, while narrow local roads generally have lower prices. This result can enhance future urban design regarding urban economy improvements and land costs. Full article

Krakow has a permanent population of over 800,000. The number of inhabitants is increasing year on year due to the influx of working people and students, who often settle in Krakow permanently. This is leading to increased demand and consequently more flats and houses being put into use by developers. The increasing environmental awareness of the population and the resulting financial benefits—particularly evident in 2022—have meant that the classic, or rather ill-considered, building industry is gradually being replaced by better, environmentally friendly solutions. In the first part of the article, the authors focus on smart buildings, and in the second part, they combine them with financial changes in the real estate market. The aim of the publication is to draw conclusions from the changes in the real estate market in Krakow that have taken place in the last decade and to assess these activities from the point of view of environmental solutions. The data are mainly derived from official statistics and trade reports published by research institutes, marketing agencies operating in the real estate sector in Poland, as well as specialist portals and publications dealing with real estate market analysis. The publication analyzes changes in the real estate market in terms of changes in unit prices, number of transactions, and availability. The analysis covers landed property, the primary and secondary premises market, developed property, and tenement buildings. Full article

This research study explored the impact of an urban spatial plan on land value; it drew on the value model based on space syntax as a systematic technical piece of software that explains and analyzes the relationship between land use and land value. The study proposes a framework based on the urban spatial network. We selected the Kirkuk city master plan for evaluation purposes and hypothesized that there would be a relationship between the space syntax of the essence of urban spatial integration and the price of land. Therefore, the case selected was evaluated in three aspects of analysis: the urban spatial function, which involves the integration rates of the city’s street network and connectivity; the urban land price assessments in the context of the city’s spatial grids; and the expansion of land use distribution, including residential and commercial grounds, to explain the changing economic value of the spatial relationship in the land market. OSM, AutoCAD, depth map X8, QGIS 3.16, and SPSS were used for data cluster analysis, spatial network preparation and analysis, and correlation analysis. The results showed that the urban spatial plans and comprehensive urban socioeconomic and environmental factors had a significant impact on land price. This result can enhance the future spatial design and the economy of metropolitan areas. Full article

This study aims to review the off-plan sales program to identify the financial and marketing challenges being faced by such programs in Saudi Arabia and formulate consensus-based measures to overcome these challenges. The study implies an analytical descriptive method to achieve its objectives, based on the opinion of experts involved in the off-plan sales program and analyzing the data using the Delphi technique. Various statistical parameters were calculated to validate the obtained results. The study found several challenges being faced by off-plan sales programs, including financing challenges such as mortgaging on the land deed, as well as marketing challenges, including low turnout of the buyers due to the long duration of project implementation. The study concludes with several suggested measures, the most important of which is to find an alternative to the condition of mortgaging the land deed, such as putting insurance on the project or providing a financial bank guarantee. The study contributes to the improvement of the real estate sector of Saudi Arabia and would benefit the construction and development sectors as well. Full article

Numerous studies have focused on the ripple effect in housing markets; however, these studies often fail to grasp the critical role of commercial real estate land use when forming a real estate portfolio. We argue that spreading an investment across various land-use assets—namely, diversification—may be effective in stabilizing and balancing China’s housing market through the introduction of the ripple effect. In six Chinese mega-cities, the cointegration system is initially used to prove the existence of ripple effects. A causality test can then identify the source cities: Beijing and Chongqing in the residential market, and Shenzhen and Chongqing in the commercial market. Finally, the authorities should enforce the differentiated measures by “depressing the housing market while encouraging the commercial market” in the respective target cities; this approach could efficiently ripple out to other cities. It is believed that the policy of land resources diversification can enable the Chinese real estate market to achieve more sustainable development. Full article