A Hybrid TOPSIS–PIV Method with Compromise Weighting of SWARA and MEREC for Supplier Selection in the Indonesian Leather Industry

Abstract

Supplier selection constitutes a critical decision in the leather industry, as supplier performance directly influences material quality, production continuity, cost, and product competitiveness. Nevertheless, supplier evaluation in this sector involves multiple, often conflicting criteria, which complicates efforts to obtain reliable rankings through a single weighting or ranking method. Existing approaches tend to rely either on subjective expert judgments or objective data characteristics, neither of which fully captures the complexity inherent in supplier selection. This study addresses this gap by offering an integrated supplier selection framework that combines subjective and objective weighting with complementary ranking techniques. The proposed framework integrates the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Proximity Indexed Value (PIV) methods with a compromise weighting scheme derived from the Stepwise Weight Assessment Ratio Analysis (SWARA) and the Method based on the Removal Effects of Criteria (MEREC). The Delphi method identifies and validates the supplier evaluation criteria. A case study in an Indonesian leather manufacturing company demonstrates the framework's applicability. The findings indicate that the hybrid approach yields consistent supplier rankings and facilitates more robust decision-making by integrating expert judgments with objective data characteristics. The proposed framework thus offers a practical and reliable decision-support tool for supplier selection in the leather industry.