(In)consistency of the Selection of the Method of Multiplicative Decision-Making
DOI:
https://doi.org/10.7251/ACE1829063RKeywords:
Multi-attributive decision-making, data normalization, weight coefficients, Likert scaleAbstract
The paper analyzes the main causes of the (in)consistency of the selected method of multiplicative decision-making: data normalization, weight coefficients and the application of the Likert scale for the purpose of measuring quantitative attributes. Normalized data in the methods of multitributive decision making represents the substitute for a subjective attribute ratings by decision makers. Since they are calculated on the basis of mathematical transformations of empirical data, one gains the impression that the choices basen on normalized values are „objective”. Therefore, the sensitivity analysis of the results has dealt exclusively with effects of weight coefficients on the final choices so far, while the potential impact of normalization is complitely ignored; meanwhile, the deformations caused by the normalization of data have been attributed to the effects of weight coefficients and their inevitable subjectivism. We intent to point out at the deformations of empirical values that are the result of normalization and which call into question the application of normalized values as a decision base. It can be proven that the normalized values are an unrealiable information base for decision-making. In addition, the (in)consistency of selection methods of multi-attributive decision-making is also influenced by changes in the method of measuring and formulating attributes.
References
Acuña, C., Liern, V., Pérez-Gladish, B. (2018). Normalization in TOPSIS-based approaches with data of different nature: application to the ranking of mathematical videos. Annals of Operations Research, DOI: 10.1007/s10479-018-2945-5. Available at: https://www.uv.es/liern/LABIPE/Annals.pdf
Cables, E., Lamata, M.T., Verdegay, J.L. (2016). RIM-reference ideal method in multicriteria decision making. Information Sciences, 337-338, 1-10, Available at: https://doi.org/10.1016/j.ins.2015.12.011
French, S. (1988). Decision Theory – An introducion to the mathematics of rationality. New York: John Wiley&Sons.
Jassbi, Ј., Camarinha-Matos, L., Barata, Ј. (2015). A Framework for Evaluation of Resilience of Disaster Rescue Networks. Springer, Cham, 146–158, DOI:10.1007/978-3-319-24141-8_13
Kahneman, D., Tversky, A. (2000). Choices, Values and Frames. Cambridge: Cambridge University Press.
Karande, P., Zavadskas, E., & Chakraborty, S. (2016). A study on the ranking performance of some MCDM methods for industrial robot selection problems. International Journal of Industrial Engineering Computations, 7(3), 399-422, DOI: 10.5267/j.ijiec.2016.1.001
Mathew, М., Sahu, С., Upadhyay, А, К. (2017). Effect Of Normalization Techniques In Robot Selection Using Weighted Aggregated Sum Product Assessment. International Journal of Innovative Research and Advanced Studies (IJIRAS), Vol. 4 Iss. 2. Available at: http://www.ijiras.com/2017/Vol_4-Issue_2/paper_12.pdf
Ouenniche, J., Pérez-Gladish, B., Bouslah, K. (2017). An out-of-sample framework for TOPSIS-based classifiers with application in bankruptcy prediction. Technological Forecasting and Social Change, in press, Available at: https://doi.org/10.1016/j.techfore.2017.05.034
Pavličić, D. (2001). Normalisation Affectes the Results of MADM Methods. Yugoslav Journal of Operational Research, Vol. 11, No 2.
Солдић-Алексић, Ј., Chroneos Красавац, Б. (2009). Квантитативне технике у истраживању тржишта. Београд: Економски факултет.
Vafaei, N., Ribeiro, R.A., Camarinha-Matos, L.M. (2018). Selection of Normalization Technique for Weighted Average Multi-criteria Decision Making. Technological Innovation for Resilient Systems, DoCEIS 2018. IFIP Advances in Information and Communication Technology, vol 521. Springer, Cham, DOI: 10.1007/978-3-319-78574-5_4, Available at: https://link.springer.com/chapter/10.1007/978-3-319-78574-5_4
Vafaei, N., Ribeiro, R.A., Camarinha-Matos, L.M. (2016). Normalization Techniques for Multi-Criteria Decision Making: Analytical Hierarchy Process Case Study. IFIP Advances in Information and Communication Technology Technological Innovation for Cyber-Physical Systems, 261–269, DOI:10.1007/978-3-319-31165-4_26