A Hybrid BWM-Entropy-VIKOR Model for Assessing Logistics System Maturity in Large-Scale Steel Industry

Logistics maturity assessment in large-scale industries requires simultaneous consideration of managerial priorities and operational performance—a challenge inadequately addressed by existing single-source weighting models. This study develops a hybrid Best–Worst Method (BWM)–Entropy–VIKOR framework to evaluate logistics maturity across five units of Mobarakeh Steel Company. Five dimensions—Inventory Management, Transportation, Logistics Information Technology, Human Resources, and Financial Performance—were identified through systematic literature review and validated by ۱۵ experts (Content Validity Ratio = ۰.۶۲–۰.۸۸; Content Validity Index = ۰.۸۱–۰.۹۴; Cronbach's α = ۰.۸۹). To overcome subjectivity bias and inconsistency limitations of conventional pairwise comparisons, subjective weights were derived via the BWM and objectively integrated with Entropy-based weights from operational performance data of ۶۰ logistics units. Final hybrid weights identify Inventory Management (۰.۲۹۵) and Transportation (۰.۲۵۰) as dominant maturity drivers. Units ranked via VIKOR—which balances group utility and individual regret under conflicting criteria—reveal central warehouse as highest maturity (Q = ۰.۲۱۵) and finished goods warehouse as lowest (Q = ۰.۵۲۶), yielding a significant performance gap (ΔQ = ۰.۳۱۱). Unlike prior fuzzy-based models, the proposed framework provides a replicable, data-driven diagnostic tool integrating strategic priorities with empirical variability. Findings enable evidence-based resource allocation and targeted improvement planning in capital-intensive manufacturing contexts.

کلیدواژه ها:

Logistics maturity ، Large-scale Steel Industry ، best-worst method ، Entropy