Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302512
Title: Immovable property taxation and the development of an artificial neural network valuation system for residential properties for tax purposes in Cyprus
Author: Panayiotou, Panayiotis Andrea
ISNI:       0000 0001 3466 3548
Awarding Body: University of Glamorgan
Current Institution: University of South Wales
Date of Award: 1999
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Abstract:
The last General Valuation in Cyprus, in 1980, took about twelve years to be completed by the Lands and Surveys Department. The comparison method was adopted and no computerised (mass appraisal) method or tool was used to assist the whole process. Although the issue of mass appraisal was raised by Sagric International, who had been invited to Cyprus as consultants, and recently by DataCentralen A/S with the development of a mass appraisal system based on regression analysis, there has been little literature and no research directly undertaken on the problems and the analysis of immovable property taxation in Cyprus and the development of an artificial neural networks valuation system for houses and apartments. The research project approached the issue of property taxation and mass appraisal through an investigation into Cyprus's needs for an up-dated tax base for equitabileness and for an assessment system capable of performing an effective revaluation at a certain date, with minimum acceptable mean error, minimum data and minimum cost. Investigation within Cyprus and world-wide indicated that this research project is a unique study in relation to Cyprus's property taxation and the development of a computer assisted mass appraisal system based on modular artificial neural networks. An empirical study was carried out, including prototyping and testing. The system results satisfy IAAO criteria for mass appraisal techniques, compare favourably with other studies and established a framework upon which future research into computer assisted mass appraisal for taxation purposes can be developed. In conclusion, the project has contributed significantly to the available literature on the immovable property taxation in Cyprus and the development of a computer assisted mass appraisal system for houses and apartments based on modular artificial neural network method. The proposed approach is novel not only in the context of Cyprus but also world-wide.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.302512  DOI: Not available
Keywords: Artificial Neural Networks ; ANNs ; Valuation System ; Immovable property taxation ; Cyprus ; mass appraisal techniques
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