CADASTRAL REGISTRATION OF REAL PROPERTY WITH DATA DIGITALIZATION

Problem statement. The transition in Ukraine from registration and accounting of land in the State Land Cadastre to registration and accounting of real estate in the multi-purpose cadastre requires research aimed at optimizing the information of the multi-purpose cadastre and the form of data representation based on their digitalization to limit the size of the database by technological support. The composition and scope of real estate accounting information data determine the purpose and functions of the multi-purpose cadastre. The problem is the huge amount of information about real estate and the great variety of objects. The difficulty of formalizing too much data for a multi-purpose cadastre information system makes it necessary to explore ways to reduce the amount of software memory involved by digitizing the data. Purpose of the article. Solving the problem of reducing the amount of memory for the database of registration and accounting of real estate through digitalization requires research on the composition of the necessary information about real estate in the multi-purpose cadastre to ensure the functions of the cadastre based on analysis of users' needs. In order to move from the information on real estate determined by the results of analysis to the basic and thematic geospatial data of the cadastre, it is necessary to perform multilevel structuring of cadastral objects at the level of real estate classification, including land plots, construction objects by characteristic legal, technical and value features. A significant reduction in the amount of memory used in the database of information technology support of the multi-purpose cadastre was achieved by coding the characteristics of real estate, including land, construction objects and other land improvements that are part of real estate. Conclusion. Digitization of real estate data in the multi-purpose cadastre allows you to: significantly reduce the amount of database memory used on the server; provide easy access to data on real estate properties; significantly increase the protection of identification of cadastral objects and their properties; opens new opportunities for real estate management, control over compliance with the law, the application of targeted measures to stimulate the desired development of real estate and prevent adverse use of territories.

USING SVR AND MRA METHODS FOR REAL ESTATE VALUATION IN THE SMART CITIES

Determination of real estate value plays a very critical role in economic development and basic needs of people. Increasing demand for real estate together with population growth is making it difficult to determine real estate value. In applications where real estate is the main subject, such as urban activities, smart cities and urbanization, urban information system and valuation systems, model-based value estimations are essential for effective land/real estate policy. The type of real estate and impact degree of features depending on the type should be known as well as value estimation. It will be beneficial to follow a method that both determines the real estate value and factor impact degree. With the studies to be carried out using such methods, both region-specific valuation models can be created and the model is established with the optimum variable. This paper aimed to determine real estate value by using Support Vector Regression (SVR) and Multi Regression Analysis (MRA) methods for effective real estate management. Besides, both methods were examined by revealing the impact degrees of features that affect the value. The methods were applied to 319 parcels in Konya. For each parcel, 31 land features and market values were collected. The parcel data collected since 2018 were included in the models. From the results, the RBF-SVR model reached the highest R2 value with 0.88, while the MRA model reached 0.86.

Data intelligence and real estate – machines are the real game changer

PurposeThe paper shows with two concrete examples about how algorithms are used in active real estate management. The paper also highlights that the discussion about the adoption of new technologies is crucial for market players.Design/methodology/approach The authors review the current status quo about new technologies in real estate and provide two examples of how algorithms can be used to understand locations and the value drivers of rents.FindingsLocation, location, location is nowadays data, data, data coupled with the knowledge of how to create life out of data. Algorithm can help to understand the value drivers of rents and can also help to evaluate the attractiveness of a location.Practical implicationsReal estate management will adapt to new technologies fast. This change has the potential to disrupt exiting strategies due to the increase in efficiency, insights, transparency and location knowledge. Investment managers walking this talk will definitely benefit in future.Originality/valueThe paper makes usage of the latest machine learning technologies applied to real estate investment cases. This is a unique opportunity on bringing light on the discussion about transparency in real estate.

Organizational workplace relocation: assessment of facilities and real estate managers' practices

PurposeThis research investigates the literature and perspectives of bilateral domains of experts, the facilities management (FM) and real estate management (REM) professionals. It provides insights towards a comprehensive understanding of office facilities relocation as organizational workplaces.Design/methodology/approachAn investigation of the literature was conducted, to identify design aspects, drivers, challenges, and technical and functional considerations of the workplace relocation. A structured survey was utilized, as face-to-face interviews with 32 FM and 32 REM professionals, to explore and compare their perspectives and expertise.FindingsThe study identified key aspects for workplace relocation that were rarely focused on, holistically, in the literature. The research led to identifying the drivers, challenges, considerations, scenarios, and design needs pertaining to the implementation, acquisition, and occupation of the workplace in times of relocation. There is a dispersed view on workplace relocation between FM and REM, which requires alignment. FM and REM experts' perspectives were intrinsically discussed to ascertain the identified key areas.Practical implicationsWorkplace relocation is a change that disturbs almost every workplace around the globe, at least once in its life cycle. This study enlists comprehension of the knowledge obtained from a review of the international literature, to provide a holistic guide for organizational decision makers, and interlink FM and REM professionals' perspectives, for enhanced decision-making.Originality/valueThis article reviews the literature on workplace relocation, covering FM and REM domains perspectives to advance the organizational workplace relocation practices.

Corporate real estate and green building: prevalence, transparency and drivers

Purpose Green building is a megatrend in corporate real estate management. This paper aims to document the prevalence of green building reporting in public firms, assess how well firms apply good practices of green building and show which firms, countries and industry sectors are particularly advanced in the application of green building technologies. Design/methodology/approach The study uses data on green building reporting, green building scores and firm characteristics of 1,281 publicly traded firms from different industries in Organisation for Economic Co-operation and Development countries over a 5-year period. Regression analysis is used to relate the adoption of green building reporting and excellence in green building to firm characteristics. Findings The results indicate that there is a huge variation in green building activities and reporting in corporate real estate management across countries and industries. The study finds that firms in the financial and health-care sectors are leading in green building reporting. Environmental, social and corporate governance-oriented, profitable and large firms receive the highest green building scores. Research limitations/implications The results in this paper rely on the reported but not inevitably monitored green building activities. There may also be companies that use green building technologies but do not report on them. The conclusions are largely based on correlations and do not allow for causal statements (endogenous variables). Practical implications The results in this paper are crucial for practitioners in corporate real estate to benchmark their green building activities and reporting. Additionally, the paper sheds light on how information on green building is propagated in the financial market. Originality/value The paper looks at the drivers and barriers of green building for 25 countries and across all industry sectors (1,281 firms). In contrast to that most of the existing literature focuses on single countries and limits the analysis to companies in the real estate and construction industry. Additionally, the paper has a joint focus on publicly available green building reporting and green building scores.