Upgrading current multi-attribute decision-making with a 3-dimensional decision matrix for future-based decisions

Area of Science:

• Operations Research
• Decision Analysis
• Management Science

Background:

• Existing Multi-Attribute Decision-Making (MADM) methods struggle with dynamic expert experience levels.
• Forecasting future scenarios presents a significant challenge for conventional MADM techniques.

Purpose of the Study:

• To identify and address critical shortcomings in current MADM approaches.
• To propose a novel framework that overcomes the limitations of existing MADM techniques.

Main Methods:

• Introduction of a 3-dimensional decision matrix.
• Development of a new methodology to integrate dynamic factors into decision analysis.

Main Results:

• The proposed 3D matrix effectively accommodates fluctuating expert experience.
• Enhanced forecasting capabilities are demonstrated through the new decision-making framework.

Conclusions:

• The 3-dimensional decision matrix offers a significant advancement over traditional MADM methods.
• This innovative approach improves the robustness and accuracy of complex decision-making processes.