The objective of this paper is to propose the use of transaction data, hedonic model and internet‐based technologies to provide potential home buyers and sellers with instant and online property appraisal services by real estate‐related firms.
Hedonic price model is performed to estimate the price index of individual housing estate. The values of the coefficients of the attributes may change in response to a changing environment. A professional judgment should be given by appraisers on time intervals to re‐run the hedonic price models, if needed. Once the algorithms have been updated, authenticated users can connect to the system via a secure socket layer. They can browse and search the valuation reports by entering search criteria of premises into the system that filters the results instantly according to the request of users, and a detailed asset valuation report will be displayed in the browser.
This sort of online services is believed to save consumers' time, by offering timely property appraisal services that facilitate property transactions.
Currently, local large property developers, agencies and surveying firms are still relying on manual processes of providing selected transaction data via the web to their prospective customers. The system proposed and developed as described in this paper is an automatic and self‐learning system that produces reliable and authentic results based on large quantity of historical transaction records. The professional judgments of appraisers add flavor to the final valuation of properties. As well as providing information to individual buyers/sellers, the system is most suitable to investors who own a large portfolio of properties as the total capitalization of the portfolio can be computed easily and quickly. REITs are examples of these portfolio owners.
Mak, S.W.K., Choy, L.H.T. and Ho, W.K.O. (2008), "Hedonic models, internet‐based technologies, and the provision of online property appraisal", Construction Innovation, Vol. 8 No. 2, pp. 92-105. https://doi.org/10.1108/14714170810867023Download as .RIS
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