Prof. US Dr inż. Hab. Kesra Nermend 1 and Mateusz Piwowarski2
Department of Decision Support Methods and Cognitive Neuroscience
Institute of Management, University of Szczecin, Szczecin, Poland
Email: [email protected] – [email protected]
DOI: 10.23918/ICABEP2022p53
Abstract
This study investigated the effectiveness and the different methodological approaches of the Vector Measure Construction Method (VMCM) and Technique for Order Preference by Similarity Ideal Solution (TOPSIS). These methods are from the area of multiple-criteria decision analysis (MCDA) or multidimensional comparative analysis (MCA) methods. The method from this area is dedicated to the study of complex economic processes described by many factors. Mostly, these methods are used in situations wherein the decision-makers participation is relatively small, e.g. selected problems at the macro level depending on the situation, and the case under consideration. The TOPSIS and VMCM methods are methodologically similar and successfully implemented among others. They rank and classify the analyzed objects providing similar good results if the research does not require the dynamics of change. VMCM method is more sensitive to changes in the data values taken into account in the calculations. It is more effective when we add new data to the study. This must be taken into account in calculations, it does not require recreating the pattern. Because the pattern can be any object among the analyzed objects or outside of those objects, it can even be a real object. The created measure with the VMCM method is not limited – either from the bottom or from the top, which allows for better comparison with the elements that fall outside of the matrix pattern. In addition, the VMCM method allows the dynamics of changes to be studied, and the TOPSIS method does not offer the possibility of obtaining reliable results in this case. The fundamental methodological difference between the two methods is the way of creating a pattern. In the TOPSIS method, the pattern should be the best object for the whole analyzed period. Modifying this period in any way requires the pattern to be recreated from scratch. It also does not allow the use of actual Patterns. In addition, one such limitation of the TOPSIS method is the situations where some data (objects) are significantly distant from the adopted pattern, they may significantly affect the final results of the analysis. These are the so-called non-typical objects.
Keywords: Multidimensional comparative analysis; VMCM; TOPSIS; MCDA; MCA
ICABEP2022
4th International Conference on Accounting, Business, Economics and Politics
Organized by
Tishk International University, College of Administration and Economics, Salahaddin University-Erbil, and
University of Szczecin, Poland.
