Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain

- A novel MCGDM methodology based on group heterogeneity concept.
- Group heterogeneity established from pair wise preference comparison matrix.
- Biasness of information restricted by consistency check mechanism of AHP.
- The algorithm fits itself in the class of established MCDM techniques.
- Investigation finds the model as a robust and effective decision making tool.

Group decision making (GDM) is more effective in extracting the real case scenarios of the decision problems to add competitive advantages in a supply chain. Group members from wider spectrum of the environment naturally command variation in knowledge level to their respective domain. The degree of heterogeneity of the decision makers in a group plays a crucial role in realistic assessment of both alternatives and selection criteria. This paper proposes a new Multi criteria GDM approach in adroit exploitation of the group heterogeneity during evaluation process and restrict the biasness of information while decision making. The importance of the heterogeneous degree of expertise is established through pair wise preference comparison matrix. To overcome the biasness, the consistency check mechanism of analytical hierarchy process (AHP) is employed. A real case example on warehouse location selection in a supply chain is illustrated to demonstrate the validity and effectiveness of the proposed approach. In order to ensure the applicability, compatibility and validity of the proposed approach, comparative study is carried out with the proven and established MCDM methodologies SAW, MOORA, TOPSIS, VIKOR, ELECTRE II, COPRAS and PROMETHEE. ANOVA, Sensitivity analysis (SA) and other investigations find the proposed approach as a rational, robust, effective and precise decision making aid to the supply chain managers.

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