scholarly journals Corporate ownership and technical efficiency analysis in the Spanish real estate sector

2007 ◽  
Vol 4 (2) ◽  
pp. 100-113 ◽  
Author(s):  
Douglas Nanka-Bruce
Keyword(s):  
Real Estate ◽  
Technical Efficiency ◽  
Shadow Economy ◽  
Panel Data Analysis ◽  
Efficiency Analysis ◽  
News Article ◽  
Corporate Ownership ◽  
Spanish Economy ◽  
The Real Estate ◽  
Real Estate Sector

The real estate sector keeps contributing significantly to the Spanish economy. A recent news article reports the existence of inefficiencies in the nature and delivery of new properties. We investigate the technical efficiency of this sector using a non-parametric “reasonable” benchmarking frontier, acknowledging the marked influence of the sector’s shadow economy. We then relate the results applying a panel data analysis to the shareholding concentration and identity of firm ownership. We find no systematic support for the effect of corporate ownership on technical efficiency

scholarly journals Real Estate Sector Efficiency Analysis

2020 ◽  
Vol 18 (2) ◽  
Author(s):  
Tomás José Fontalvo Herrera ◽  
Enrique De la Hoz ◽  
Efrain De la Hoz
Keyword(s):  
Logistic Regression ◽  
Real Estate ◽  
Logistic Regression Model ◽  
Efficiency Analysis ◽  
Data Envelopment ◽  
Average Efficiency ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Real Estate Company ◽  
The City

This research an analysis of the efficiency of the real estate sector of the city of Cartagena - Colombia is developed. For the 46 companies registered as real estate agencies in the city, the techniques of principal components, data envelopment analysis and logistic regression were articulated. The results show an average efficiency of the sector of 42.33%, considering 8 companies as efficient. Five hypotheses were raised about the incidence of each financial item in the efficiency result, evidenced through the logistic regression model how the variable Operational Income is the only significant one (Value-p = 0.028). It was evidenced as an efficient real estate company should not have high values in the items of heritage and plants, property and equipment.

scholarly journals Bringing the User Back in the Building: An Analysis of ESG in Real Estate and a Behavioral Framework to Guide Future Research

2021 ◽  
Vol 13 (6) ◽  
pp. 3239
Author(s):  
Shirley Kempeneer ◽  
Michaël Peeters ◽  
Tine Compernolle
Keyword(s):  
Real Estate ◽  
Social Science ◽  
Environmental Psychology ◽  
Fiduciary Duty ◽  
Future Research ◽  
The Real Estate ◽  
Investment Value ◽  
Real Estate Sector ◽  
Sustainable Investments

Investors are currently obliged to take environment, social, and governance (ESG) issues into consideration as part of their fiduciary duty. As such, it becomes increasingly important to identify sustainable investments that also hold financial value. A sector where this is especially underdeveloped is real estate. This has a lot to do with the obfuscated conceptualization of ESG. The article identifies key gaps in the literature and practice and provides a framework to further the understanding of how ESG factors can add societal and financial value in the real estate sector. A key premise of the article is that the user in the building is grossly overlooked. Drawing on insights from behavioral social science and environmental psychology, the paper explains the role of the user in improving buildings’ ESG, also taking into account the investment value. To conclude, the article makes the case that the transition to user-centered smart real estate is the solution to improving both the environmental (E) and social (S) sustainability of buildings, as well as their investment value. Therefore, practitioners and academics are encouraged to critically evaluate and contextualize the ESG framework they are using as well as the extent to which users are considered and smart technology is employed.

Information security in the South Australian real estate industry

2014 ◽  
Vol 22 (1) ◽  
pp. 24-41 ◽  
Author(s):  
Deepa Mani ◽  
Kim-Kwang Raymond Choo ◽  
Sameera Mubarak
Keyword(s):  
Risk Management ◽  
Information Security ◽  
Real Estate ◽  
South Australia ◽  
Security Threats ◽  
The South ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Sector

Purpose – Opportunities for malicious cyber activities have expanded with the globalisation and advancements in information and communication technology. Such activities will increasingly affect the security of businesses with online presence and/or connected to the internet. Although the real estate sector is a potential attack vector for and target of malicious cyber activities, it is an understudied industry. This paper aims to contribute to a better understanding of the information security threats, awareness, and risk management standards currently employed by the real estate sector in South Australia. Design/methodology/approach – The current study comprises both quantitative and qualitative methodologies, which include 20 survey questionnaires and 20 face-to-face interviews conducted in South Australia. Findings – There is a lack of understanding about the true magnitude of malicious cyber activities and its impact on the real estate sector, as illustrated in the findings of 40 real estate organisations in South Australia. The findings and the escalating complexities of the online environment underscore the need for regular ongoing training programs for basic online security (including new cybercrime trends) and the promotion of a culture of information security (e.g. when using smart mobile devices to store and access sensitive data) among staff. Such initiatives will enable staff employed in the (South Australian) real estate sector to maintain the current knowledge of the latest cybercrime activities and the best cyber security protection measures available. Originality/value – This is the first academic study focusing on the real estate organisations in South Australia. The findings will contribute to the evidence on the information security threats faced by the sector as well as in develop sector-specific information security risk management guidelines.

scholarly journals Geographic Scope and Real Estate Firm Performance during the COVID-19 Pandemic

2021 ◽  
Vol 14 (7) ◽  
pp. 309
Author(s):  
Xiaoling Chu ◽  
Chiuling Lu ◽  
Desmond Tsang
Keyword(s):  
Firm Performance ◽  
Real Estate ◽  
Stock Market ◽  
Adverse Impact ◽  
Corporate Diversification ◽  
Market Reactions ◽  
Geographic Scope ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Stock Market Reactions

This study examines the effect of geographic scope in mitigating the adverse impact of the COVID-19 pandemic in the real estate sector. Utilizing the Chinese setting over the two-month period in 2020 from the beginning of the outbreak to the successful containment of the spread of virus, we show that while the pandemic has negatively impacted real estate firm returns, firms with broader geographic scope and more geographically diversified property allocations have managed to better endure the crisis. We further find that firms with higher leverage report lower returns during the pandemic irrespective of their geographic scope, but larger firms can lessen the adverse impact of the pandemic only if they have adopted a more diversified strategy. Overall, our study provides novel evidence on the benefit of diversification by demonstrating the importance of geographic scope and diversification at times of crises. Specifically, we show corporate diversification could be especially useful to mitigate the negative stock market reactions resulting from the pandemic. Moreover, diversification could even become essential for larger firms that are expected by the market to be more diversified.

scholarly journals The work that place does: The London Landed Estates and a curatorial approach to estate management

2021 ◽  
pp. 096977642199976
Author(s):  
Patrícia Canelas ◽  
Mike Raco
Keyword(s):  
Real Estate ◽  
Public Information ◽  
Urban Spaces ◽  
Data Sources ◽  
Local Context ◽  
Socially Responsible ◽  
Land Expropriation ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Property Owners

Writings on urban development and planning in Europe have been dominated by a combination of technical studies of the real estate sector and more structural political economy approaches on land expropriation and financialisation. In this paper we draw on the example of the London Landed Estates, to critically assess how land-owning real estate companies, that we call city-owners, perform their roles and what models and knowledge sources they draw upon in managing and carefully curating urban spaces and places. Data sources include interviews with estate managers, others involved in, or affected by, their management, and other corporate public information. Our theoretical framing draws on performativity theory that we see as a valuable addition to existing research approaches. We describe and analyse the ways these agencies construct narratives and practices of socially responsible and historically established forms of performance, that they label place stewardship, and the specific mechanisms they use to bring places into existence. Collectively, the discussion calls for an increased focus on how models abstracted from local context and politics can be ‘localised’, in the study of the governance of the built environment. Greater attention also needs to be paid to the work that place does in influencing the strategies, tactics and activities of property owners.

Career choice of real estate students in Nigeria

2019 ◽  
Vol 37 (1) ◽  
pp. 154-176 ◽  
Author(s):  
Timothy Oluwafemi Ayodele
Keyword(s):  
Real Estate ◽  
Career Choice ◽  
Third Party ◽  
Southwestern Nigeria ◽  
Test Analysis ◽  
Content Type ◽  
The Real Estate ◽  
Factors Influencing ◽  
Real Estate Sector ◽  
Career Preferences

Purpose The purpose of this paper is to examine the career preferences of real estate students and the predisposing factors influencing the choice of career. The study also analysed the gender and socioeconomic variations with respect to the career preferences and factors influencing the career choice of real estate students in an emergent market like Nigeria. Design/methodology/approach Closed-ended questionnaires were administered on final year real estate students in the three Federal universities offering real estate in Southwestern Nigeria. Data were analysed using frequency counts, percentages, mean ranking, independent t-test, analysis of variance and correlation analysis. Findings The findings showed that the predominant individual factors influencing career choice of real estate students were personal career interest, the magnitude of initial salary, future financial prospects and job security. Furthermore, while intrinsic and economic/financial factors were the major themes influencing respondents’ career choice, the influence of a third party was less a likely determinant. Analysis of gender differences showed that there was a statistical difference between the male and female respondents with respect to the intrinsic and career exposure factors. Research limitations/implications The study has implications for real estate students, career advisers/academic counsellors, organisations employing the services of real estate graduates, and educational institutions and policy stakeholders in the real estate sector. The study also has implication for real estate professional bodies in Nigeria and other emergent markets. Originality/value This is perhaps the first attempt that examined the factors influencing the career choice of real estate students in an emergent market like Nigeria, especially from the perspectives of gender and socioeconomic variations.

scholarly journals Deep Learning Classification of Building Types in Northern Cyprus

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Mubarak Muhammad ◽  
Sertan Serte
Keyword(s):  
Deep Learning ◽  
Real Estate ◽  
Smart Cities ◽  
House Price ◽  
Training Dataset ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Northern Cyprus ◽  
Second Category

Among the areas where AI studies centered on developing models that provide real-time solutions for the real estate industry are real estate price forecasting, building age, and types and design of the building (villa, apartment, floor number). Nevertheless, within the ML sector, DL is an emerging region with an Interest increases every year. As a result, a growing number of DL research are in conferences and papers, models for real estate have begun to emerge. In this study, we present a deep learning method for classification of houses in Northern Cyprus using Convolutional neural network. This work proposes the use of Convolutional neural networks in the classification of houses images. The classification will be based on the house age, house price, number of floors in the house, house type i.e. Villa and Apartment. The first category is Villa versus Apartments class; based on the training dataset of 362 images the class result shows the overall accuracy of 96.40%. The second category is split into two classes according to age of the buildings, namely 0 to 5 years Apartments 6 to 10 years Apartments. This class is to classify the building based on their age and the result shows the accuracy of 87.42%. The third category is villa with roof versus Villa without roof apartments class which also shows the overall accuracy of 87.60%. The fourth category is Villa Price from 10,000 euro to 200,000 Versus Villa Price from 200,000 Euro to above and the result shows the accuracy of 81.84%. The last category consists of three classes namely 2 floor Apartment versus 3 floor Apartment, 2 floor Apartment versus 4 floor Apartment and 2 floor Apartment versus 5 floor Apartment which all shows the accuracy of 83.54%, 82.48% and 84.77% respectively. From the experiments carried out in this thesis and the results obtained we conclude that the main aims and objectives of this thesis which is to used Deep learning in Classification and detection of houses in Northern Cyprus and to test the performance of AlexNet for houses classification was successful. This study will be very significant in creation of smart cities and digitization of real estate sector as the world embrace the used of the vast power of Artificial Intelligence, machine learning and machine vision.

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