New model for determining criteria weights: Level based weight assessment (lbwa) model

Abstract

This paper presents new subjective model for determining weight coefficients in multi-criteria decision-making models. The new Level Based Weight Assessment (LBWA) model enables the involvement of experts from different fields with the purpose of defining the relations between criteria and providing rational decision making. The method can be applied in practical cases in specialized decision-making support systems, as well as in alternative dispute resolutions in virtual environment. The LBWA model has several key advantages over other subjective models based on mutual comparison of criteria, which include the following: (1) the LBWA model allows the calculation of weight coefficients with small number of criteria comparisons, only n-1 comparison; (2) The algorithm of the LBWA model does not become more complex with the increase of the number of criteria, which makes it suitable for use in complex multi-criteria (MCDM) models with a large number of criteria; (3) By applying the LBWA model, optimal values of weight coefficients are obtained with simple mathematical apparatus that eliminates inconsistencies in expert preferences, which are tolerated in certain subjective models (Best Worst Method - BWM and Analytic Hierarchy Process - AHP); (4) The elasticity coefficient of the LBWA model enables, after comparing the criteria, additional corrections of the values of the weight coefficients depending on the preferences of the decision makers. This feature of the LBWA model enables sensitivity analysis of the MCDM model by analyzing the effects of variations in the values of the weights of criteria on final decision.