A Behavioral-Aware Hybrid Multi-Criteria Decision-Making Framework Integrating BAHP, BTOPSIS, and BVIKOR for Industrial Decision Support

Multi-Criteria Decision-Making (MCDM) methods are widely employed in industrial engineering to support complex decision problems involving multiple conflicting criteria. Conventional MCDM techniques generally assume that decision makers behave rationally throughout the evaluation process. However, empirical evidence from behavioral science indicates that cognitive biases frequently influence judgment, resulting in distorted criteria weighting and unreliable alternative rankings. this paper proposes a novel Behavioral-Aware Hybrid Multi-Criteria Decision-Making (BAH-MCDM) framework that integrates behavioral decision-making concepts with three classical MCDM techniques: Behavioral Analytic Hierarchy Process (BAHP), Behavioral TOPSIS (BTOPSIS), and Behavioral VIKOR (BVIKOR). The proposed framework incorporates eight major cognitive biases into both the weighting and ranking stages of the decision-making process. Furthermore, two new behavioral indicators, namely the Bias Severity Index (BSI) and the Decision Reliability Index (DRI), are introduced to quantify behavioral distortions and evaluate decision reliability. A hypothetical supplier-selection case study is presented to demonstrate the applicability of the proposed framework, followed by a sensitivity analysis to evaluate its robustness under different behavioral conditions. The results indicate that incorporating behavioral information improves the interpretability and reliability of decision support while maintaining ranking stability. The proposed framework provides a promising foundation for future behavioral decision-support applications in industrial engineering and operations management.

کلیدواژه ها:

Behavioral decision making ، Multi criteria decision making (MCDM) ، Behavioral AHP ، Behavioral TOPSIS ، Behavioral VIKOR ، Cognitive bias ، Decision reliability