Spatial weight matrix impact on real estate hierarchical clustering in the process of mass valuation - Sebastian Gnat (Oeconomia Copernicana, 2019)
Research background: The value of the property can be determined on an individual or mass basis. There are a number of situations in which uniform and relatively fast results obtained by means of mass valuation undoubtedly outweigh the advantages of the individual approach. In literature and practice there are a number of different types of models of mass valuation of real estate. For some of them it is postulated or required to group the valued properties into homogeneous subset due to various criteria. One such model is Szczecin Algorithm of Real Estate Mass Appraisal (SAREMA). When using this algorithm, the area to be valued should be divided into the so-called location attractiveness areas (LAZ). Such division can be made in many ways. Regardless of the method of clustering, its result should be assessed, depending on the degree of implementation of the adopted criterion of division quality. A better division of real estate will translate into more accurate valuation results.