Business Intelligence Framework Design and Implementation: A Real-estate Market Case Study

This article builds on previous work in the area of real-world applications of Business Intelligence (BI) technology. It illustrates the analysis, modeling, and framework design of a BI solution with high data quality to provide reliable analytics and decision support in the Jordanian real estate market. The motivation is to provide analytics dashboards to potential investors about specific segments or units in the market. The article ekxplains the design of a BI solution, including background market and technology investigation, problem domain requirements, solution architecture modeling, design and testing, and the usability of descriptive and predictive features. The resulting framework provides an effective BI solution with user-friendly market insights for investors with little or no market knowledge. The solution features predictive analytics based on established Machine Learning modeling techniques, analyzed and contrasted to select the optimum methodology and model combination for predicting market behavior to empower inexperienced users.

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Application of Creative Experiential Marketing in Vanke Real Estate

Journal of Economics and Public Finance ◽

10.22158/jepf.v4n4p296 ◽

2018 ◽

Vol 4 (4) ◽

pp. 296

Author(s):

Wei Bi ◽

Jun Wu ◽

Yang Gao ◽

Rungtai Lin

Keyword(s):

Real Estate ◽

Emotional Experience ◽

Real Estate Market ◽

Experience Economy ◽

Experiential Marketing ◽

The Real Estate ◽

Product Experience ◽

Real Estate Marketing ◽

User Friendly ◽

Interactive Experience

<p><em>With the continuous development of China’s real estate market and the continuous improvement of people’s living standards, the home buyers’ demand for emotional experience has been constantly aroused, thus making emotional experiential marketing more important in customer behavior. In the era of pursuing personalized experience, experiential marketing has become a powerful means for enterprises to achieve stRung competitiveness. It is usually connected with the creation of an atmosphere, an environment and a situation, the completion of a process and the making of a commitment, and sometimes it needs a customer’s active participation. This paper is based on Vanke’s real estate marketing, first gives a detailed introduction to the real estate experience in terms of the experience economy, experiential marketing and emotional experience, and then analyzes the application of experiential marketing in real estate marketing from product experience, user-friendly experience, scene setting experience and theme interactive experience to discuss how experiential marketing is implemented in Vanke’s real estate, learn from it and provide reference of effective experience for future researches.</em></p>

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Price Bubbles in the Real Estate Markets - Analysis and Prediction

WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS ◽

10.37394/23207.2022.19.27 ◽

2022 ◽

Vol 19 ◽

pp. 292-303

Author(s):

Paweł Dec ◽

Gabriel Główka ◽

Piotr Masiukiewicz

Keyword(s):

Real Estate ◽

Predictive Analytics ◽

Real Estate Market ◽

Point Of View ◽

Subprime Crisis ◽

The Real ◽

The Real Estate ◽

Price Bubbles ◽

The Real Estate Market ◽

The Government

The article concerns the issue of price bubbles on the markets, with particular emphasis on the specificity of the real estate market. Up till now, more than a decade after the subprime crisis, there is no accurate enough method to predict price movements, their culmination and, eventually, the burst of price and speculative bubbles on the markets. Hence, the main goal of the article is to present the possibility of early detection of price bubbles and their consequences from the point of view of the surveyed managers. The following research hypothesis was verified: price bubbles on the real estate market cannot be excluded, therefore constant monitoring and predictive analytics of this market are needed. In addition to standard research methods (desk research or statistical analysis), the authors conducted their own survey on a group of randomly selected managers from Portugal and Poland in the context of their attitude to crises and price bubbles. The obtained results allowed us to conclude that managers in both analysed countries are different relating the effects of price bubbles to the activities of their own companies but are similar (about 40% of respondents) expecting quick detection and deactivation of emerging bubbles by the government or by central bank. Nearly 40% of Polish and Portuguese managers claimed that the consequences of crises must include an increased responsibility of managers for their decisions, especially those leading to failures.

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Predictive analytics using Big Data for the real estate market during the COVID-19 pandemic

Journal Of Big Data ◽

10.1186/s40537-021-00476-0 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Andrius Grybauskas ◽

Vaida Pilinkienė ◽

Alina Stundžienė

Keyword(s):

Big Data ◽

Real Estate ◽

Predictive Analytics ◽

Real Estate Market ◽

Gradient Boosting ◽

The Real Estate ◽

Time On The Market ◽

Extreme Gradient Boosting ◽

The Real Estate Market ◽

The Difference

AbstractAs the COVID-19 pandemic came unexpectedly, many real estate experts claimed that the property values would fall like the 2007 crash. However, this study raises the question of what attributes of an apartment are most likely to influence a price revision during the pandemic. The findings in prior studies have lacked consensus, especially regarding the time-on-the-market variable, which exhibits an omnidirectional effect. However, with the rise of Big Data, this study used a web-scraping algorithm and collected a total of 18,992 property listings in the city of Vilnius during the first wave of the COVID-19 pandemic. Afterwards, 15 different machine learning models were applied to forecast apartment revisions, and the SHAP values for interpretability were used. The findings in this study coincide with the previous literature results, affirming that real estate is quite resilient to pandemics, as the price drops were not as dramatic as first believed. Out of the 15 different models tested, extreme gradient boosting was the most accurate, although the difference was negligible. The retrieved SHAP values conclude that the time-on-the-market variable was by far the most dominant and consistent variable for price revision forecasting. Additionally, the time-on-the-market variable exhibited an inverse U-shaped behaviour.

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Digitalization Real Estate on American Real Estate Society 2018: A Dramatic and Irreversible Shift in Real Estate Systems

Journal of Business and Economics ◽

10.15341/jbe(2155-7950)/05.10.2019/002 ◽

2019 ◽

Vol 10 (5) ◽

pp. 380-386

Author(s):

Jan Veuger ◽

Keyword(s):

Real Estate ◽

Capital Flows ◽

Global Economy ◽

Real Estate Market ◽

Educational Models ◽

Annual Congress ◽

Real Estate Education ◽

Demographic Effects

The 34th annual congress of April 10-14 this year took place in Bonita Springs (Florida) where the professionals in real-estate education and research discussed six themes: global economy and capital flows, real estate market cycles, demographic effects, future-proof real estate, disruption in technology and future educational models.

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