A Competitive Multiattribute Group Decision-Making Approach for the Game between Manufacturers.

Area of Science:

• Operations Research
• Decision Sciences
• Game Theory
• Evidence Theory

Background:

• Competitive market environments necessitate sophisticated decision-making strategies for manufacturers.
• Existing multiattribute group decision-making models often struggle with imprecise expert evaluations.
• Game theory and evidence theory offer frameworks for analyzing strategic interactions and uncertainty.

Purpose of the Study:

• To propose a novel approach for competitive multiattribute group decision-making (CMAGDM).
• To integrate game theory and evidence theory for analyzing manufacturer competition.
• To handle expert evaluations using 2-dimension 2-tuple linguistic variables.

Main Methods:

• Utilized evidence theory to aggregate 2-dimension 2-tuple linguistic variables from expert evaluations.
• Applied a second aggregation using evidence theory to derive overall situation values.
• Constructed a game matrix and employed game theory to determine the Nash equilibrium point.

Main Results:

• Successfully aggregated imprecise expert evaluations into meaningful attribute and overall situation values.
• Formulated a game matrix representing the competitive decision problem.
• Identified the Nash equilibrium point, providing a strategic solution for decision-makers.

Conclusions:

• The proposed approach effectively addresses competitive multiattribute group decision-making problems.
• Demonstrated applicability and effectiveness through a practical case study in a duopoly setting.
• Offers a robust method for strategic decision-making under competitive market conditions.