A Framework for Sustainable Supplier Selection Integrating Grey Forecasting and F-MCDM Methods: A Case Study

Abstract

Selecting appropriate suppliers is critical for healthcare organizations to ensure high-quality, reliable, and sustainable patient care services. In an increasingly competitive environment, hospitals must optimize supplier selection not only based on economic factors but also by integrating environmental and social sustainability considerations. This study aims to create a strong system for choosing sustainable suppliers in healthcare by combining fuzzy-based multi-criteria decision-making (MCDM) methods with Grey Forecasting GM(1,1) to handle uncertainty and changes in performance over time. The proposed framework applies the Fuzzy Best-Worst Method (F-BWM) to determine the relative importance of sustainability criteria, while the Fuzzy Additive Ratio Assessment (F-ARAS) method is used to rank suppliers based on these weighted criteria. Grey Forecasting GM(1,1) is employed to predict supplier performance for future periods, with forecasting accuracy evaluated through Mean Absolute Percentage Error (MAPE). All supplier forecasts achieved MAPE values below 5%, indicating very high prediction reliability. Empirical results from a case study at a general hospital in Indonesia confirm that social aspects, such as patient safety and reputation, are prioritized over economic and environmental considerations. Practically, the proposed framework enables healthcare institutions to holistically evaluate suppliers, specifically reducing risks related to supply disruptions and quality inconsistencies. The model performs best under conditions of limited or uncertain data availability, where supplier historical performance trends can be leveraged to forecast future reliability and sustainability outcomes. The prioritization of sustainability criteria yields social criteria (weight = 0.3703) as the most important, followed by economic (0.3609) and environmental (0.2688) criteria.