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Ferreira, F., Spahr, R. & Sunderman, M. (2016). Using multiple criteria decision analysis (MCDA) to assist in estimating residential housing values. International Journal of Strategic Property Management. 20 (4), 354-370
F. A. Ferreira et al., "Using multiple criteria decision analysis (MCDA) to assist in estimating residential housing values", in Int. Journal of Strategic Property Management, vol. 20, no. 4, pp. 354-370, 2016
@article{ferreira2016_1731867504260, author = "Ferreira, F. and Spahr, R. and Sunderman, M.", title = "Using multiple criteria decision analysis (MCDA) to assist in estimating residential housing values", journal = "International Journal of Strategic Property Management", year = "2016", volume = "20", number = "4", doi = "10.3846/1648715X.2015.1122668", pages = "354-370", url = "https://journals.vgtu.lt/index.php/IJSPM/article/view/2096" }
TY - JOUR TI - Using multiple criteria decision analysis (MCDA) to assist in estimating residential housing values T2 - International Journal of Strategic Property Management VL - 20 IS - 4 AU - Ferreira, F. AU - Spahr, R. AU - Sunderman, M. PY - 2016 SP - 354-370 SN - 1648-715X DO - 10.3846/1648715X.2015.1122668 UR - https://journals.vgtu.lt/index.php/IJSPM/article/view/2096 AB - Considerable literature exists regarding the complexity of the residential real estate appraisal process and the methods employed to determine initial listing prices as estimates of intrinsic market prices. Deviations in residential real estate intrinsic values occur due to a multiplicity of attributes and explanatory factors requiring consideration. We conduct a panel study using a Multiple Criteria Decision Analysis (MCDA) based framework that utilizes the skills and knowledge of a panel of residential real estate professionals (i.e. appraisers and realtors). We demonstrate how cognitive mapping and the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) may assist in estimating appropriate offer/sale prices and strengthening current valuation approaches such as using comparables and/or hedonic modeling. The managerial implications of our MCDA-based framework and some avenues for future research are also presented. ER -