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Multicriterion Analysis of Investment to Real Estate/Inestavimo į nekilnojamąjį turtą variantų daugiakriterinis vertinimas

Author(s):

Medium: journal article
Language(s): Latvian
Published in: Journal of Civil Engineering and Management, , n. 1, v. 4
Page(s): 72-77
DOI: 10.3846/13921525.1998.10531382
Abstract:

It is very important to estimate real estate very exactly in order to choose the right way of investment and to choose strategy of building purpose after restoration. While evaluating the variants of investment into real estate, practically we can meet the problem of establishing the index weight. Subjectivity is inevitable, and having inquired a sufficient number of specialists, we could find real weight of indexes. We have arranged an inquiry for real estate evaluators, specialists of real estate marketing, construction specialists and researchers and formed out the comparative weights of indexes which have the greatest influence on real estate marketing. The aim of the inquiry was to establish the index weights, which would help to choose the most profitable variant. The situation was investigated where the building was bought, repaired and used for some purposes; later it was rented or sold. The general model of reconstruction marketing is given in Fig 1. At the beginning some buildings are chosen for investment. Before buying one of them it must be estimated. There are things that must be taken into consideration: the amount of structures, the degree of wear, the location. Some variants of building utilisation are designed. For example, we can arrange flats, a café or a hotel in the structure. An estimate for each structure must be made. When all the necessary expenditure is found, market calculation should be performed: which variants are cheaper, what profit could be gained having rented or sold the structure, what price of selling must be for having the invested means back and for gaining the foreseen profit. For comparison, possible selling price is estimated. If the credits are to be taken, the stages of credit taking and investment as well as the growth of interes must be foreseen. The best variant is selected according to the best ratio of the means invested and the profit gained. The next stages of activities—the structure is renovated, sold or rented. Having calculated the realisation costs of each variant, the most favourable variants of investment are chosen with the help of expert methods. For the comparison of constructions and their utilisation, a questionnaire for experts has been compiled. It was devoted for establishing the importance of the indexes according to which the variants of investment are estimated. 18 experts took part in the inquiry. Having analysed the questionnaire filled by the experts, the common questionnaire has been arranged with the average meanings of numbers given by the experts (Table 2). The questionnaire is worked out according to twin-comparison method (using program KVADR, arranged at VGTU) and the vector of index importance is gained (Table 1). Then, the way of conciliation of experts' opinions is checked. Having worked up all the experts' questionnaires according to twin-comparison method, the vectors of index importance are gained (Table 3). The priority of indexes established by the experts is shown in Table 4. Having got the vectors of index importance, the coefficient of concordance can be found according to EXPERT programme [1] (author L. Ustinovičius). In case of calculation the importance of concordance coefficient x=64.44, when its normative meaning xnorm=26.22. Therefore the experts opinions are reconciled and can be trusted. The compared indexes lined up in order are shown in Table 5.

Copyright: © 1998 The Author(s). Published by VGTU Press.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10363855
  • Published on:
    12/08/2019
  • Last updated on:
    02/06/2021
 
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