Empirical evidence on the ownership and liquidity of real estate tokens

To better understand the potential and limitations of the tokenization of real asset mar-kets,empirical studies need to examine this radically new organization of financial mar-kets.In our study,we examine the financial and economic consequences of tokenizing 58 residential rental properties in the US,particularly those in Detroit.Tokenization aims at fragmented ownership.We found that the residential properties examined have 254 owners on average.Investors with a greater than USD 5,000 investment in real estate tokens,diversify their real estate ownership across properties within and across the cities.Property ownership changes about once yearly,with more changes for proper-ties on decentralized exchanges.We report that real estate token prices move accord-ing to the house price index;hence,investing in real estate tokens provides economic exposure to residential house prices.

Research on the intelligent supervision and operation platform of railway real estate

Railway real estate is the fundamental element of railway transportation production and operation.Effective management and rational utilization of railway real estate is essential for railway asset operation.Based on the investigation of the requirements of railway real estate management and operation,combined with Beidou positioning,GIS(Geographic Information System),multi-source data fusion and other cutting-edge technologies,this paper puts forward the multi-dimensional dynamic statistical method of real estate information,the identification method of railway land occupation and the comprehensive evaluation method of real estate development and utilization potential,and build the railway real estate supervision and operation platform,design the function of the platform,so as to provide intelligent solutions for the railway real estate operation.

Architecting the Metaverse: Blockchain and the Financial and Legal Regulatory Challenges of Virtual Real Estate

There has been disagreement over the value of purchasing space in the metaverse, but many businesses including Nike, The Wendy’s Company, and McDonald’s have jumped in headfirst. While the metaverse land rush has been called an “illusion” given underdeveloped infrastructure, including inadequate software and servers, and the potential opportunities for economic and legal abuse, the “real estate of the future” shows no signs of slowing. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the long-term legal and regulatory considerations of capitalizing on the investment, as well as the manner in which blockchain technology can secure users’ data and digital assets, has yet to be properly investigated. With the metaverse still in a conceptual phase, building a new 3D social environment capable of digital transactions will represent most of the initial investment in time in human capital. Digital twin technologies, already well-established in industry, will be ported to support the need to architect and furnish the new digital world. The return on and viability of investing in the “real estate of the future” raises questions fundamental to the success or failure of the enterprise. As such this paper proposes a novel framing of the issue and looks at the intersection where finance, technology, and law are converging to prevent another Dot-com bubble of the late 1990s in metaverse-based virtual real estate transactions. Furthermore, the paper will argue that these domains are technologically feasible, but the main challenges for commercial users remain in the legal and regulatory arenas. As has been the case with the emergence of online commerce, a legal assessment of the metaverse indicates that courts will look to traditional and established legal principles when addressing issues until the enactment of federal and/or state statutes and accompanying regulations. Lastly, whereas traditional regulation of real estate would involve property law, the current legal framing of ownership of metaverse assets is governed by contract law.

Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects.Additionally,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry.However,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks.To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making approach.First,a credit risk assessment index for Chinese real estate enterprises is established.Then,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods.This approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation information.Finally,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility.This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

A Concept about Guide on Hazards for the Real Estate Business-An Example from Bulgaria

The paper is a part of wider investigation related to the application of basic sciences to the sustainable development of society.It deals with the presentation of knowledge to the real estate(fast growing business)about the local natural and man-made hazards in the near vicinity of any structure(inhabitant,recreation area,land,etc.)and their influence to the social safety and human comfort of life.The structure,necessary information and knowledge base for visible or hidden hazards about a guide for the real estate business is included.An example of application the knowledge about seismic hazard and related phenomena simplified to be more available to the non-specialists(such as real estate agents and companies)targeted to Sofia(the largest urban center and capital of Bulgaria)can attract and improve the learning abilities of the real estate for the society’s sake.

Examining the Impact Factors and Strategies to Mitigate Economic Fluctuation in the Real Estate Sector

With the continuous growth of the economy and the rapid pace of urbanization,the real estate sector has assumed an increasingly substantial role within the national economy.Ensuring the stable and sustainable development of the real estate sector to maximize its societal and economic contributions has become a pressing issue.China,presently engaged in an extensive urbanization drive,places real estate development and sales as pivotal components in the broader real estate industry,significantly impacting the overall functionality of the real estate market.Real estate,being a comprehensive system encompassing land,housing,infrastructure,and other key elements,exerts a profound influence on people’s basic needs such as shelter,sustenance,and daily living.Its evolution directly shapes the trajectory of the national economy and social stability.Therefore,to foster the consistent and robust growth of China’s real estate economy,it is necessary to implement effective measures that entail a systematic and thorough analysis of the factors responsible for the fluctuations in China’s real estate economy.

A Review of Domestic and Foreign Research on Real Estate Financial Management

With the tightening of house purchase policies in recent years, the introduction of financial and land restriction policies, as well as the impact of the COVID-19 pandemic, real estate bombshells are common. Real estate is in the critical stage of transformation and upgrading, and industrial development is facing dire challenges and pressure for survival. As an important part of enterprise management, financial management is directly related to the success or failure of enterprise development. Facing the financial risks emerging in the financial management of the real estate industry at this stage, this review begins from financial management personnel training, investment calculation management, budget management, and asset management in the effort of optimizing the real estate financial management operating mechanism under the new situation and ensuring the healthy and stable development of real estate enterprises, while maintaining core competitiveness.

An Intelligent Recommendation System for Real Estate Commodity

Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms,whereas consumers often rely on websites to search and compare prices when purchasing real property. In addition to being time consuming, this search processrenders it difficult for agents and consumers to understand the status changes ofobjects. In this study, Python is used to write web crawler and image recognitionprograms to capture object information from the web pages of real estate agents;perform data screening, arranging, and cleaning;compare the text of real estateobject information;as well as integrate and use the convolutional neural networkof a deep learning algorithm to implement image recognition. In this study, dataare acquired from two business-to-consumer real estate agency networks, i.e., theSinyi real estate agent and the Yungching real estate agent, and one consumer-toconsumer real estate agency platform, i.e., the, FiveNineOne real estate agent. Theresults indicate that text mining can reveal the similarities and differences betweenthe objects, list the number of days that the object has been available for sale onthe website, and provide the price fluctuations and fluctuation times during thesales period. In addition, 213,325 object amplification images are used as a database for training using deep learning algorithms, and the maximum image recognition accuracy achieved is 95%. The dynamic recommendation system for realestate objects constructed by combining text mining and image recognition systems enables developers in the real estate industry to understand the differencesbetween their commodities and other businesses in approximately 2 min, as wellas rapidly determine developable objects via comparison results provided by thesystem. Meanwhile, consumers require less time in searching and comparingprices after they have understood the commodity dynamic information, therebyallowing them to use the most efficient approach to purchase real estate objectsof their interest.

Enhancing the Efficiency of the Management of Real Estate Companies through Organizational Structures

The article represents research on ways to make the management of real estate companies more efficient, starting from their structural organization. The organizational structure of the enterprise is a basic component of the general structure of the company and reflects the “anatomy of the enterprise” and the way of its conception, detailing, and implementation directly influence the activities required to achieve the objectives of the enterprise. On closer examination of a series of organizational charts of real estate management companies, the author observed a tendency to use organizational structures that are inefficient. The main objectives of this article are to bring into the practice of real estate management a model of beneficial organizational structure, both for the real estate management companies and for the construction companies that, besides the building activity, also deal with the management of their own real estate, and to emphasize the particular importance of the organizational structure of the company. The appreciation of the organizational structure represents the process of knowledge, understanding, and explanation of the existing situation through a detailed analysis of the factors that influence its condition through: the enterprise development strategy;the type and complexity of services;the size of the enterprise;the quality of human resources;the changes that take place in the external environment of the company, and last but not least, the legal framework and the statutes of the enterprise.

The Applicability of the Maximum Global Utility Method in the Activity of the Real Estate Consulting Service

The real estate sector is vital for ensuring human needs for living and activity. This fact conditioned the formation of a legal, normative and methodological framework specific to real estate, but also the investment attractiveness of the field. Thus, the real estate consultant often solves technical, economic, legal, organizational problems, but the biggest responsibility rests with investment consulting. The applied methodologies, focused on evaluating the efficiency of investments, are not sufficient to propose to the investor a reasoned conclusion regarding the investment priority. In this article, the authors propose a useful tool for real estate consultants in order to reason the decision regarding the investment of funds in commercial real estate for the purpose of renting it out—the Maximum Global Utility (MGU) method. It is proposed to include in the analysis and the way of calculating the indicator “importance level of the real estate” which reflects the criterion of the best use. This indicator ensures the flexibility of the decision depending on the quality characteristics of the real estate.

Real Estate Management via a Decentralized Blockchain Platform

Blockchain technology is one of the key technological breakthroughs of the last decade.It has the ability to revolutionize numerous aspects of society,including financial systems,healthcare,e-government and many others.One such area that is able to reap the benefits of blockchain technology is the real estate industry.Like many other industries,real estate faces major administrative problems such as high transaction fees,a lack of transparency,fraud and the effects of a middleman including undue influence and commissions.Blockchain enables supporting technologies to overcome the obstacles inherent within the real estate investment market.These technologies include smart contracts,immutable record management and time-stamped storage.We utilize these key properties of blockchain technology in our work by proposing a system that has the ability to record real estate transactions in a private blockchain,using smart contracts.The immutability of the blockchain ledger and transactions can provide a safe space for the real estate business.Blockchain technology can also assist the authentication process by hastening background checks.Personal digital keys are provided to parties that are involved in a contract,thus minimizing the risk of fraud.We also discuss the rationale behind the advantages of using a blockchain in this manner,and how we selected the consensus mechanism for our proposed system.

A group consensus model for evaluating real estate investment alternatives

Background:Individual decision-making largely influences the effectiveness of decisions and benefits of investments.Methods:In this article,a consensus model for group decision-making(GDM),based on the analytic hierarchy process(AHP),is developed to gather group ideas and analyze the real estate investment environment under multi-criteria problems.Twelve evaluation procedures of the developed model,which increase the convergence of the opinions of multiple experts,are proposed.Results:An empirical case about the real estate investment environment is applied to certify the feasibility of this developed model.Conclusions:the evaluation procedures have been fully observed with several rounds of discussions,and have manifested the experiences of experts.Besides,the evaluation results are in accordance with real-world situations,which demonstrates that our developed model is a feasible analysis tool for real estate investors to obtain better profits and lower risk.

Research on the Effect of Artificial Intelligence Real Estate Forecasting Using Multiple Regression Analysis and Artificial Neural Network: A Case Study of Ghana

To transition from conventional to intelligent real estate, the real estate industry must enhance its embrace of disruptive technology. Even though the real estate auction market has grown in importance in the financial, economic, and investment sectors, few artificial intelligence-based research has tried to predict the auction values of real estate in the past. According to the objectives of this research, artificial intelligence and statistical methods will be used to create forecasting models for real estate auction prices. A multiple regression model and an artificial neural network are used in conjunction with one another to build the forecasting models. For the empirical study, the study utilizes data from Ghana apartment auctions from 2016 to 2020 to anticipate auction prices and evaluate the forecasting accuracy of the various models available at the time. Compared to the conventional Multiple Regression Analysis, using artificial intelligence systems for real estate appraisal is becoming a more viable option (MRA). The Artificial Neural network model exhibits the most outstanding performance, and efficient zonal segmentation based on the auction evaluation price enhances the model’s prediction accuracy even more. There is a statistically significant difference between the two models when it comes to forecasting the values of real estate auctions.

Research on the Impact of Market Concern for Real Estate Policy on Housing Prices: Evidence from Internet Search and Hedonic Price Theory

To avoid the effects of systemic financial risks caused by extreme fluctuations in housing price,the Chinese government has been exploring the most effective policies for regulating the housing market.Measuring the effect of real estate regulation policies has been a challenge for present studies.This study innovatively employs big data technology to obtain Internet search data(ISD)and construct market concern index(MCI)of policy,and hedonic price theory to construct hedonic price index(HPI)based on building area,age,ring number,and other hedonic variables.Then,the impact of market concerns for restrictive policy,monetary policy,fiscal policy,security policy,and administrative supervision policy on housing prices is evaluated.Moreover,compared with the common housing price index,the hedonic price index considers the heterogeneity of houses and could better reflect the changes in housing prices caused by market supply and demand.The results indicate that(1)a long-term interaction relationship exists between housing prices and market concerns for policy(MCP);(2)market concerns for restrictive policy and administrative supervision policy effectively restrain rising housing prices while those for monetary and fiscal policy have the opposite effect.The results could serve as a useful reference for governments aiming to stabilize their real estate markets.

Real Estate in Chongqing as a Pillar Industry: A Quantitative Analysis

The definition of pillar industry is stated and its indicators, including the proportion of added value in the GDP, the degree of industry correlation, the income elasticity of demand, and the growth rate of employment will be discussed. And then index weighing is determined based on the degree of importance. The result of the quantitative analysis of real estate industry in Chongqing suggests that its first three evaluating indicators live up to the index requirement of a pillar industry while its degree of industry correlation is not satisfactory. An overall evaluation indicates that the real estate industry in Chongqing meets the requirements of pillar industry.

Cost control for real estate development projects in China - Part 1: Literature review

The background and purpose, and the current situation of the cost control theory of real estate development project are disscussed in the paper. Problems of cost control for real estate development projects in China are analyzed and summarized. According to the real estate development project cost control problems and related factors, a cost control index system of real estate development enterprise, and a cost control factors index system of real estate projects are constructed respectively. Cost control in the five stages of a real estate development project is introduced and summarized respectively. The five stages include: the investment decision-making, planning and design stage, the bidding phase, project implementation stage, and rental or sale.

Study on Tourism Landscape Real Estate in China

Landscape real estate is a high-grade product of tourism development and real estate industry, and a new real estate development mode integrating both investment and consumption. This paper, based on analyzing concepts and characteristics of tourism landscape real estate, elaborated basic principles of landscape real estate development by taking Guosetianxiang in Chengdu City for example, and proposed suggestions for the future development of tourism landscape real estate.

Reflection on the Development of Real Estate in the Context of Block System Reform

Last year, the State Council issued the Several Opinions on Further Strengthening the Management of Urban Planning. The guideline on urban planning has sparked heated debate among Internet users over opening up gated residential communities to public road system. This paper, based on the analysis of the background and contents of block system reform, explored the problems of the implementation of the block system reform and the impact of the block system reform on the real estate in China from 3 aspects, the selling points of the high-end communities, future property management and the community elderly care model.

Study on the Theory and Method of Real Estate Property Right Appraisal

This paper first introduces the overview of real estate appraisal theory,the basic situation of real estate appraisal,the basic principles and characteristics of real estate appraisal,and three main appraisal methods.On this basis,the specific use scope of each method,the meaning of each parameter,and the influencing factors are analyzed.Then,based on the in-depth study of various existing appraisal theories and methods,a new appraisal method is proposed:the appraisal analysis method based on fuzzy analytic hierarchy process.

China's Real Estate Finance:Undergoing Directional Change

Influenced by a host of new policies on real property loans and foreign investment restrictions, real estate finance is in the midst of directional change characterized by fluctuations in domestic and overseas financing arrangements. The long-