Abstract
PurposeThe purpose of this paper is to explore the application of fuzzy logic in real estate investment in Hong Kong. There have been sufficient debates on the literature, providing the theoretical background on real estate investment decisions but there has been a lack of empirical support in this regard. This paper attempts to fill the gap between theorem and application.Design/methodology/approachThe fuzzy logic system is adopted to evaluate the situation of a real estate market with imprecise and vague information. An indicator‐portfolio, rather than a specific indicator/index usually employed by practitioners, is explored to assist investors in risk management. The result derived from this framework is then compared to the property price index. This approach provides a framework in understanding the market without statistical and mathematical models. It tries to stimulate the complex human cognitive process involving decision making.FindingsThe housing‐indicator portfolio composition produces an outcome value which is able to reflect the complexities of both the real estate market and investors' expectations. An increase of this value implies that the investment condition is becoming more positive.Research limitations/implicationsThe paper reveals that fuzzy logic can provide some insights in an intuitive manner and is capable of obtaining information not found in market data. It is particularly useful to investors without experience in mathematical modeling.Practical implicationsThis paper establishes a basic framework of fuzzy logic for real estate investment on which a base is formed as a reference for practitioners and investors. However, they should make references to the specific housing‐indicator portfolio composition in their own regions.Originality/valueThis paper has used a fuzzy logic system to assist practitioners as well as investors on decision making in real estate investment with imperfect market information. With the aid of the system, practitioners and investors are able to enhance their investment decision‐making quality by reducing the risk incurred by such uncertainties.
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