Integrating LODECI Weighting and ALPAS Methods for Raw Material Supplier Selection in the Textile Industry
The selection of raw material suppliers in the textile industry is a complex challenge because it involves various criteria, such as price, delivery timeliness, material quality, color consistency, and production capacity. Subjective decisions or those based on unstructured data often lead to inaccuracies, unfairness, and supply chain disruption risks. This study aims to present an objective and systematic approach by integrating the LODECI method for criteria weighting and ALPAS for alternative ranking. The LODECI method extracts criteria weights rationally from variations in supplier performance, minimizing the influence of subjectivity, while ALPAS combines the criteria weights with the performance data of alternatives to generate final scores and rank suppliers comprehensively. This study involved eleven actual suppliers as alternatives, with performance data reflecting real operational conditions. The ranking results show that alternative A8 has superior and stable performance, followed by A10 and A4, while the sensitivity analysis indicates that changes in criteria weights of ±0.05 do not cause significant shifts in rankings, confirming the model's robustness. These findings demonstrate that the integration of LODECI and ALPAS can enhance the objectivity, consistency, and accountability of supplier decision-making, supporting supply chain efficiency, product quality, and the overall competitiveness of the textile industry.
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