Date of Award
Master of Science in Information Systems and Technology
Information and Decision Sciences
First Reader/Committee Chair
This Culminating Experience Project explored the application of big data in the real estate industry in order to address the problem of analyzing the accurate property estimates value. The research questions were: (Q1): What are the benefits and advantages of utilizing big data in the real estate market? (Q2): What are the trends in the application of big data in the real estate market? (Q3): What are the challenges in applying big data in the real estate market? (Q4): What are the methods and processes of applying big data in appraisal of assets in the real estate market? To answer these four questions, this study used qualitative and quantitative methodology, content analysis conducted on data collected through Google Scholar, and One Search for industry reports, conference papers, and select literature about big data adoption trends in the real estate industry. The findings were as follows: (Q1): The benefits of using big data analytics are to help clients to make the right decisions and advice, have higher efficiency for appraisals, better risk evaluation of risk in the real estate industry simplifying applications in valuations and pricing. (Q2): there is anecdotal evidence that real estate has already started adopting big data. Adoption is most likely to be beneficial for first mover industry players at the top of the industry pyramid including investment banks, commercial banks, and mortgage banks that hold the highest interest in the real estate industry. (Q3): complexity of big data solutions and the costs of implementation are a major challenge while smaller players such as real estate agents and brokers do not find utility or justification for the huge investment in big data. (Q4): the development of algorithms remains as the main process of applying big data solutions as there are no off-the-shelf big data solutions for the real estate industry. Adoption of Machine learning (ML) and Artificial Intelligence (AI) in real estate would help buyers and sellers to learn from data and make informed decisions. The conclusions of the culminating experience project are Real Estate Industry has a low adoption of big data solutions because many of the players in the industry have not yet learned how to translate big data to business objectives. Areas of further studies include the development of models and algorithms for use by the real estate industry.
Xiao, YongLin, "BIG DATA FOR COMPREHENSIVE ANALYSIS OF REAL ESTATE MARKET" (2022). Electronic Theses, Projects, and Dissertations. 1596.
Business Intelligence Commons, Management Sciences and Quantitative Methods Commons, Real Estate Commons