Abstract
Evolutionary economics has begun to replace—or at least complement—neoclassical economics as the most widely accepted framework for economic modeling. Evolutionary frameworks are nonlinear and iterative: they take their starting point in the divergence of routines and outcomes of business activity over time, and work on the assumption that this diversification subsequently leads to a selection-of-the-fittest mechanism. In real estate analysis the issue is about market outcome and the behavior of actors such as developers and investors. Thus, a feasible method needs to apply both real estate transaction price data and expert interviews about actor motivations and tendencies. On top of the price development target, urban sustainability is incorporated as a more qualitative target, as the aim is to compare the price development with various sustainability aspects across different locations and typical market segments. This demonstration is based on a modeling approach known as the self-organizing map (SOM).
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The paper is based on a presentation held on 12 April 2012 in Vienna, for the EMCSR conference, symposium K. The author is thankful for the comments received from that session.
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Kauko, T. (2014). Towards Evolutionary Economic Analysis of Sustainable Urban Real Estate: Concept of a Research Strategy Exemplified on House Price Modeling Using the Self-Organizing Map, Interviews and Field Inspection. In: Walloth, C., Gurr, J., Schmidt, J. (eds) Understanding Complex Urban Systems: Multidisciplinary Approaches to Modeling. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-02996-2_5
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