Abstract
Decision-making is the process of carefully considering multiple options and choosing the best one. The EDAS (evaluation based on distance from average solution) method has been studied in many multi-attributes decision-making (MADM) problem which assumes decisionmaking under absolute rationality. However, people usually show the characteristics of bounded rationality in the real decision-making process. Prospect theory (PT) utilizes gains and losses relative to the reference point to explain this phenomenon better. In this paper, an enhancement EDAS method based on PT will be proposed, which shows better properties in practice. We apply the traditional EDAS method and enhancement EDAS method to the same case and we utilize the sensitivity analysis and comparative analysis to analyze their performances. The result shows that our approach has a superiority compared with the traditional EDAS method. The methods we present are of great significance for investment decision-making problems, new product development, design plan selection and supplier selection.
Highlights
Multi-attribute decision-making (MADM) is a decision-making problem in which multiple attributes or indicators are considered, and the best alternatives or alternatives with limited ranking are selected (Rostamzadeh et al, 2017; Tabatabaei et al, 2019; Wang et al, 2021)
This section considers the enhancement EDAS method based on cumulative prospect theory (CPT), which differs from the previous section is the probability weight of alternatives
We use the enhancement EDAS method based on PT1 to illustrate many options for positive distance from average (PDA) and negative distance from average (NDA) (The sensitivity analysis of the parameters in the CPT method is consistent with PT1, so we only present the PT1 method here)
Summary
Multi-attribute decision-making (MADM) is a decision-making problem in which multiple attributes or indicators are considered, and the best alternatives or alternatives with limited ranking are selected (Rostamzadeh et al, 2017; Tabatabaei et al, 2019; Wang et al, 2021). In 1992, Amos Tversky and Daniel Kahneman (1992) extended the original PT based on the hierarchy-dependent utility theory, and proposed the cumulative prospect theory (CPT). It replaced the scattered probability weights in the PT with incremental probability weights, gave a value function, and calculated the probability weight function. To solve the risky multi-attribute problem, Liu and Zhang (2010), Wang and Zhang (2009) and Liu, Jin, Zhang, Su, and Wang (2011) respectively proposed decision-making methods based on PT. (3) Through sensitivity analysis, we know that the enhancement EDAS can demonstrate the bounded rationality effect of PT It has enriched VCs’ decision-making method and made a reasonable demonstration role for the uncertain decision-making in the other field.
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