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Re-thinking Commercial Real Estate Market Segmentation


  • Franz Fuerst

    () (School of Real Estate & Planning, University of Reading Business School)

  • Gianluca Marcato

    () (School of Real Estate & Planning, University of Reading)


Investments in direct real estate are inherently difficult to segment compared to other asset classes due to the complex and heterogeneous nature of the asset. The most common segmentation in real estate investment analysis relies on property sector and geographical region. In this paper, we compare the predictive power of existing industry classifications with a new type of segmentation using cluster analysis on a number of relevant property attributes including the equivalent yield and size of the property as well as information on lease terms, number of tenants and tenant concentration. The new segments are shown to be distinct and relatively stable over time. In a second stage of the analysis, we test whether the newly generated segments are able to better predict the resulting financial performance of the assets than the old dichotomous segments. Applying both discriminant and neural network analysis we find mixed evidence for this hypothesis. Overall, we conclude from our analysis that each of the two approaches to segmenting the market has its strengths and weaknesses so that both might be applied gainfully in real estate investment analysis and fund management.

Suggested Citation

  • Franz Fuerst & Gianluca Marcato, "undated". "Re-thinking Commercial Real Estate Market Segmentation," Real Estate & Planning Working Papers rep-wp2010-12, Henley Business School, Reading University.
  • Handle: RePEc:rdg:repxwp:rep-wp2010-12

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    References listed on IDEAS

    1. Steven Devaney & Colin Lizieri, 2005. "Individual Assets, Market Structure and the Drivers of Return1," Journal of Property Research, Taylor & Francis Journals, vol. 22(4), pages 287-307, December.
    2. Martin Hoesli & Colin Lizieri & Bryan MacGregor, 1997. "The Spatial Dimensions of the Investment Performance of UK Commercial Property," Urban Studies, Urban Studies Journal Limited, vol. 34(9), pages 1475-1494, August.
    3. Stephen L. Lee, 2001. "The Relative Importance of Sector and Regional Factors in Real Estate Returns," ERES eres2001_206, European Real Estate Society (ERES).
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    More about this item


    market segmentation; commercial real estate; financial performance measurement; cluster analysis; neural network analysis; risk diversification;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • R33 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Nonagricultural and Nonresidential Real Estate Markets


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