Business Data Analytics for Sustainable and Resilient Food Procurement: Integrating Expert Judgment and Objective Weighting under Uncertainty
DOI:
https://doi.org/10.63646/WQGU4851Keywords:
Business data analytics; sustainable procurement; supply chain resilience; fuzzy multi-attribute decision-making; quasirung orthopair fuzzy sets; food supply chainAbstract
Food procurement is becoming a strategic data-analytics problem because decision-makers must balance economic efficiency, environmental responsibility, social fairness, and disruption resilience while operating with vague, partial, and conflicting information. Conventional fuzzy multi-attribute decision-making studies remain limited by two persistent gaps: (i) classical fuzzy extensions cannot accommodate sharply asymmetric expert judgments, and (ii) most studies rely on a single weighting lens, either subjective or objective, which produces fragile rankings. To close these gaps, this article develops an information-driven decision pipeline that operates inside the p,q-quasirung orthopair fuzzy environment. The pipeline first encodes expert linguistic judgments as orthopair pairs with two independent rung parameters, then derives subjective importance through a fuzzy zero-inconsistency procedure, computes objective importance through an envelope-and-slope routine, and finally blends the two streams through a single hybridization coefficient. Suppliers are ranked through a mixed aggregation scheme that combines three normalization views with arithmetic and geometric deviation measures. The pipeline is calibrated against a real Indian bakery and confectionery firm sourcing perishable and non-perishable inputs from six candidate suppliers under twenty-five sustainability and resilience criteria. Sensitivity tests across the hybridization coefficient, the rung parameters, and the weight perturbation envelope all confirm that the leading supplier remains stable. Comparative benchmarking against eight reference methods further supports the analytical robustness of the framework.
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