'From data to value'
in real estate investment management
H.S.A.H. Hassan (TU Delft - Architecture and the Built Environment)
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Abstract
‘Real estate is the largest asset class in the world’ as stated by Harvard business school Professor Arthur Segel. It is also unbeatable driver of individual wealth and overall economy. But on the other hand, it is one of the most imperfect markets, due to the lack of accessibility to valuable information in the limited time of decision making process. Thus, it is crucial to find out what is brought by the state of art that could tackle this problem in such a complex and competitive context.
Since, the main component of information is data which is also the chief resource in the modern world; (big) data could be a hot phenomenon to be adapted within the real estate investment domain for improving the performance of the real estate market.
Thus, the main goal of this research is to bridge the area between real estate investment domain and big data, by leveraging big data methods, predictive analytics and smart tools for achieving informed real estate investment decisions. Consequently, investors will be able to maximize return, achieve better risk diversification and select the right time to invest.
The expected final product of this research is a developed integrated decision making model and flow chart that involves big data methods and techniques for making more informed real estate investment decisions ‘Dutch office market’.