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I identify the effect of financial constraints on product prices using granular data on home-builder housing developments from the 2006–2009 housing crisis. Builders who experience losses in one area subsequently sell homes in unaffected areas at a discount to raise cash quickly. When builders cut prices, they sell homes faster and builders cut prices more in areas in which price cuts produce larger declines in time-to-sale. Financially constrained firms are more likely to cut prices of homes in healthy areas following losses elsewhere. Firms cut prices following losses in other projects only during the crisis, not during the boom. [ABSTRACT FROM AUTHOR]

Purpose: Though alternative building technologies (ABTs) have been encouraged to address accessible and affordable issues in low-cost housing (LCH) provision, their adoption is still overwhelmed with encumbrances. The encumbrances that hinder ABT adoption require an in-depth study, especially in developing countries like Nigeria. However, studies regarding ABT and its role in improving Nigeria's LCH to achieve Sustainable Development Goal (SDG) 11 are scarce. This research investigates encumbrances to ABT adoption in Nigeria's LCH provision and suggests feasible measures to prevent or reduce the encumbrances, thereby improving achieving SDG 11 (sustainable cities and communities). Design/methodology/approach: This research utilised qualitative research and adopted a face-to-face interview as the primary data collection. The interviewees comprised ABT practitioners and end users in Nigeria who were chosen by a convenient sampling technique. The study's data were analysed manually through a thematic approach. Findings: This study shows that stakeholders should embrace ABT in LCH provision to improve achieving SDG 11 in Nigeria. Also, it clustered the perceived 20 encumbrances to ABT adoption in LCH provision into government/policymaker, housing developers/building contractors, ABT users and ABT manufacturers-related issues in Nigeria's context. This study suggested mechanisms to mitigate encumbrances to ABT adoption in LCH provision, thereby improving achieving SDG 11. Originality/value: This research adds to the limited literature by analysing ABT adoption encumbrances in Nigeria's LCH provision, which could assist policy formulation for the uptake of ABT in LCH provision and improve achieving Goal 11. [ABSTRACT FROM AUTHOR]

In many cities, incentives and regulations lead developers to integrate low-income housing into market-rate buildings. How cost-effective are these policies? I study take-up of a tax incentive in New York City using a model in which developers trade off between tax savings and pretax income. Estimating the model using policy variation and microdata on development from 2003 to 2015, I find a citywide marginal fiscal cost of $1.6 million per low-income unit. Differences in neighborhoods, not developer incidence, explain the cost premium over other housing programs. Weighing costs against estimates of neighborhood effects, I conclude middle-class neighborhoods offer "opportunity bargains." [ABSTRACT FROM AUTHOR]

Research shows that most households in developing economies rely on informal housing finance and self-help because of the challenges imposed by the underdeveloped capital markets. How housing developers navigate these challenges is less well understood, but this understanding is necessary to develop innovative financing solutions that efficiently meet the escalating housing demand in these economies. We fill this gap by examining the entrepreneurial adaptative financing of developers in Ghana. Our interest is the alternative financing mechanisms developers are innovating to economize the transaction costs (TCs) of accessing capital. These are examined through the lens of TC economics. Instead of debt (only 1.2% of developers used exclusively formal financing sources), we observe private developers' efforts to coordinate finance hierarchically, in some cases adopting the roles of traditional banks. For most financing mechanisms, the homebuyer either co-creates or temporarily co-owns the property with the developer. The eight identified adaptive financing models economize TCs and traditional financing usage and support housing consumption, offering buyers pathways to homeownership without conventional mortgages. However, they do not support volume development and expose homebuyers to significant ex-post contractual hazards. Our study provides insights into creating responsive policies that increase housing finance accessibility, while protecting homebuyers. [ABSTRACT FROM AUTHOR]

Objective: To analyze the factors that contribute to the reduction of vegetable production in the San Vicente Chicoloapan ejido. Design/Methodology/Approach: Sixty out of a total of 150 ejidatarios who produced vegetables in 2022 participated in a convenience sampling. Producers who agreed to be surveyed were interviewed in their plots. Results: The ejidatarios have an average of 1.47 agricultural ha (minimum: 1 ha; maximum: 5 ha), considering both irrigated and rainfed lands. The use of the sample studied was divided as follows: 43.3% of the owners sold their land to developers who built housing units and new houses; 38.3% cultivated their own land or those they rented; and 18.3% rented out their lands. The ejidatarios suffer from vegetable theft, particularly pumpkin (45.0%), artichoke (31.7%), onion (13.3%), chard (8.3%), and cabbage (1.7%). Study Limitations/Implications: Designing a random sample was impossible given the lack of access to a register of ejidatarios. Estimating the harvested area or estimating yield based on the production volume was impossible, since producers grow several crops in their plots, besides vegetables. Findings/Conclusions: Vegetable production in the San Vicente Chicoloapan ejido, State of Mexico, is at risk of disappearing, as a consequence of economic and social issues and a lack of support. The ejidatarios who still grow vegetables have tried to mitigate these problems; however, their future as producers is severely limited and older people have chosen to sell their land, which are used by developers to build houses. [ABSTRACT FROM AUTHOR]

In many countries of the world, the problems related to housing, which is one of the basic needs of people, have not been fully solved. In Turkey, different problems arise in the housing production and marketing process. The aim of this study is to categorize and discuss the types of problems encountered in the housing production and marketing process in Turkey within the framework of the relevant literature. Within this framework, secondary data were analyzed and concepts and terms related to these problems were explained. In this way, the research has an exploratory characteristic. As a result of the secondary data analysis of the research, it is understood that housing production is faced with problems arising from land supply, increases in construction material costs and local governments as well as financial problems. Another important finding emerging from the data analysis is that housing developers are inadequate in using marketing automation and digital techniques in their advertising efforts. It is evaluated that the results will be useful in the correct decision-making processes of those who supply and demand housing, give readers the opportunity to reason, help them to satisfy and motivate them, and guide future studies. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the article is to continue research on the resilience of participants in the housing market to economic shocks and disruptions-in this case, the supply side of the market, i.e., the developer. The goal is also to answer research questions such as: does the developer, as a professional market entity, demonstrate resilience in this regard? Previous research results have shown that the demand side of the market is not resilient to such negative phenomena. Design/methodology/approach: The study is based on the existing literature on resilience concepts and the compilation of statistical data on developers and market conditions during the period of 2018-2023. By analyzing the sales revenues of 32 publicly traded developers during the studied period, their resilience to economic shocks and disruptions was assessed. Findings: The research found that most developers (about 70%) showed resilience to the effects of the pandemic, the outbreak of the war in Ukraine, and rising inflation. It can be inferred that this resilience is related to the long-term investment process and the specifics of the housing market. Research limitations/implications: The study’s results provide a valuable source of information about resilience of developers in real estate market and partially complements existing research in this area. Originality/value: The conducted research provides new insights into the resilience of enterprises to economic shocks – in this case, developers in the housing market. The article is primarily aimed at individuals interested in real estate market research as well as those interested in the concept of enterprise resilience. [ABSTRACT FROM AUTHOR]

This study investigates the effectiveness of four machine learning models for predicting house prices: Linear Regression (LR), Artificial Neural Networks (ANNs), Random Forest Regressor, and Support Vector Regression (SVR). As the demand for housing continues to rise due to population growth, the housing business has become one with high long-term potential. This is evidenced by an upward trend in house prices in Indonesia and other regions. For instance, in the United States, new single-family home sales climbed 8.8% to 693,000 units (SAAR) in March 2024, marking the fastest pace since September 2023 and an 8.3% year-over-year increase. Property values are influenced by various internal factors, such as area and number of rooms, as well as external factors like inflation rates and government policies. Linear Regression (LR) is known for its simplicity and ease of interpretation, providing high accuracy with low computational cost. In contrast, Artificial Neural Networks (ANNs) excel at capturing non-linear relationships, making them suitable for more complex datasets. Random Forest Regressor, an ensemble learning method, enhances predictive performance by averaging multiple decision trees and controlling overfitting, while SVR is effective in high-dimensional spaces and can model non-linear relationships using kernel functions. We employ the Boston housing dataset, a widely used benchmark for house price prediction tasks, to compare these models. The dataset is split into 70% for training and 30% for testing. The performance of the models is evaluated using Mean Squared Error (MSE), R-squared, and Mean Absolute Error (MAE). The results show that Linear Regression achieves an MSE of 0.0106, R-squared of 0.67, and MAE of 0.075. The Artificial Neural Network achieves an MSE of 0.0046, R-squared of 0.86, and MAE of 0.047. The Random Forest Regressor achieves an MSE of 0.0060, R-squared of 0.81, and MAE of 0.050, while the SVR achieves an MSE of 0.0054, R-squared of 0.83, and MAE of 0.056. By comparing these models, we find that the Artificial Neural Network (ANN) achieves the highest accuracy, followed by SVR, Random Forest Regressor, and Linear Regression. These findings provide valuable insights for buyers, sellers, and developers in the housing market, highlighting the potential of advanced machine learning models in accurately predicting house prices. [ABSTRACT FROM AUTHOR]

This paper analyses planning responses to middle-income informalities in Nairobi city, an increasingly significant element of informal urban development focusing on ad hoc zoning practices and regularisation. The findings highlight aspects of fractured governance, negotiated planning, and power struggles involving middle-income housing developers and other actors that exacerbate housing informalities rather than ameliorate them. The article reveals how different rationalities drive the different spheres of government functionaries, some of whom use planning systems for financial and political gain. Building on debates around 'conflicting rationalities' in planning, the paper proposes the concept of 'entangled rationalities,' which has scope to highlight the nuanced, multi-actor and non-binary nature of interactions between planning, political and development practice characterising responses to middle-income informalities in the global south cities and how this shapes urban outcomes. [ABSTRACT FROM AUTHOR]

Purpose: The increasing growth of urbanisation, especially in developing countries, coupled with affordable housing leakages, may thwart achieving Sustainable Development Goal (SDG) 11 (sustainable cities and communities). Studies regarding affordable housing leakages and their aftermath to Goal 11 in one study are scarce in Malaysia. The study investigated Malaysia's low-cost housing (LCH) leakages and their aftermath to Goal 11 and proffered measures to achieving Goal 11 and its targets. The purpose of this paper is to address these issues. Design/methodology/approach: The researchers covered four of Malaysia's major cities via a qualitative approach. The study used 40 participants via semi-structured virtual interviews, and saturation was achieved. The study adopted a thematic approach for the collected data and honed them with secondary sources. Findings: Findings group Malaysia's LCH leakages into government/agencies/departments in housing, housing developers/building contractors and client/building owners' root causes in Malaysia's context. It shows a threat from Malaysia's LCH leakages to achieving Goal 11 and proffered measures to enhance achieving Goal 11. Achieving Goal 11 will strengthen and improve Malaysia's many SDGs accomplishments because of their link. Originality/value: Apart from proffering measures to mitigate long-standing issues (leakages) in Malaysia's LCH delivery from achieving Goal 11, findings will stipulate the accomplishment of other SDGs related to housing delivery. [ABSTRACT FROM AUTHOR]

This research uses difference-in-difference (DID) and other empirical methods to analyze firm-level real estate data to discover how heterogeneous firm characteristics affect managers' decision-making about development expansion when a firm faces a temporary negative sales shock in the Chinese housing market. The manager's decision is a utility maximization problem under uncertainty, determined by their risk aversion levels, which managers choose to optimize by considering other factors of interest, including career risk and personal wealth. Also, the advance payment rule encourages real estate developers to maintain high turnover, since new projects allow developers to collect cash first. The results show that state-owned enterprises (SOEs) are much more conservative than other types of developers. SOEs tend to focus on current developing projects. Firms with more concentrated management pursue expansion and seek to use new project sales to compensate for their slower growth. Larger developers with headquarters in large cities tend to slow their development speed when they observe negative signals, as they can quickly engage in new projects given these firms' easy access to financial resources such as bank loans. This study makes a novel contribution to the literature since previous research has tended to focus on the macro market level rather than the firm level. The findings also have strong policy and regulation value. The results indicate that higher cashflow monitoring needs, especially to monitor family-owned developers, to prevent misuse and excessive project expansion. [ABSTRACT FROM AUTHOR]

Appalled by the low uptake of building information modelling (BIM) in the housing sector, this study investigates the factors influencing the adoption of BIM for residential property development in Nigeria, an emerging market. The primary data utilized were elicited with the aid of a questionnaire served on the officials of real estate development firms in Nigeria. The obtained data were analyzed using statistical tools such as mean ranking, frequency distribution and principal component analysis (PCA). Based on mean ranking analysis, high cost of implementing BIM (MS = 4.38), cost of hardware installation (MS = 4.24) were found as the most influential inhibiting factors. On further analysis, the results of the PCA revealed that the factors influencing BIM adoption can be grouped into operating environment and regulatory factors, cost of acquisition/usage factors, firm management factors, usage capability factors and client demand factors, with variances of 26.834%, 18.792%, 13.439%, 6.275% and 2.909% respectively. The study concluded that issues surrounding operating environment constraints and cost of acquisition and deployment significantly underpin the uptake of BIM technology in emerging economies like Nigeria. Hence, it is imperative that real estate development organizations embrace industry collaboration and efforts made to reduce BIM acquisition and deployment cost. [ABSTRACT FROM AUTHOR]

In the application, there are several inhibiting factors in applying this balanced residential concept, including related to the lack of land availability so that the price of available land becomes expensive and currently not many developers are applying the concept of balanced residential, especially in the Jakarta area. In a housing area, it is definitely determined by the price of land in addition to the location, including the completeness of facilities in the housing area. Land prices in Jakarta city centers are already relatively high so that many developers only build expensive housing for the upper middle class. To prevent this, the government created the Land Bank concept. The main purpose of Land Banking is to acquire land which is then used for the benefit of the welfare of the community, especially in meeting the needs of a house. However, in practice, the Land Bank Concept is still not widely recognized in the wider community, especially housing developers, so there are still few developers who apply the Balanced Residential Concept using the Land Bank System, especially in Jakarta because the rules and regulations of the Land Bank System are relatively new. And if people want to sell or buy a land or residential land then they will look for services in brokers or property developers only. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic added an additional layer of pressure onto an already stressed housing system in Southeast Queensland (SEQ). Housing is a complex system and we argue that thinking about the separate components of housing in isolation, we are unable to consider the resiliency of housing as a whole system. The purpose of this paper is to inform and help structure resilient housing policy and strategy development in SEQ. Using qualitative methodologies, data were collected by conducting semi-structured interviews with 18 participants associated with the housing sector in SEQ, during the pandemic period. Participants were invited from five groups: community, government, consultants, developers and peak housing bodies. We found that rather than relying on reactive mechanisms, there needs to be a commitment from governments to work with other sectors to strategically plan for proactive and resilient-led approaches and policies to prepare for shocks. There is an opportunity at local, state and federal level governments to learn from this study to better understand what makes a housing system more resilient. [ABSTRACT FROM AUTHOR]

Urban parks are important for improving the quality of living environments. Although the impact of parks on housing prices has been well documented, the effects of the COVID-19 pandemic remain vague. This paper analyzes the housing prices of neighborhoods around Meixi Lake park in Changsha, at the initial stage of the COVID-19 pandemic in June 2020 and the stable stage of the recovery period in June 2023, which demonstrates the impacts of urban parks on property pricing and housing choice based on residential transaction data. The results indicate that urban parks are given a high priority in determining people's choices. In June 2020, the risk of epidemic transmission and noise interference lowered the price of property that is close to public parks and recreational facilities. However, good management and social services in residential areas increase housing prices. However, when the pandemic ended, the strong demand for outdoor activities led to a price rise in the properties near Meixi Lake park. People are most likely to choose houses in a neighborhood characterized by good educational facilities and a high-quality living environment. More specially, the houses with a short distance to parks and where residents can enjoy the view of a lake or mountains are preferable to any others. A residential area adjacent to a super large park paired with a small park is the most valuable consideration for property developers and housing consumers. [ABSTRACT FROM AUTHOR]

This study aims to present a comprehensive depiction of the factors influencing the decision-making process regarding the purchase of subsidized housing, focusing specifically on variables such as building quality, strategic location, and price. The research objectives include identifying the key variables impacting the choice of acquiring subsidized housing in the Cileungsi region through a quantitative descriptive approach. Utilizing purposive sampling, the study surveyed one hundred local residents who recently acquired homes through government assistance programs. Structural Equation Modeling (SEM) employing variance-based methods or component-based structural equation modeling, specifically Partial Least Squares (PLS), was utilized for data analysis. The anticipated outcomes of this investigation are expected to contribute significantly to understanding consumer behavior in the context of subsidized housing purchases in Cileungsi. Moreover, the application of PLS analysis methods is poised to provide an in-depth comprehension of the interrelationships among variables within the tested model and furnish strategic recommendations for developers of subsidized housing and pertinent stakeholders to enhance product appeal. [ABSTRACT FROM AUTHOR]