Application of FAHP–QFD–NLP Hybrid Decision Model in Assessment of Priority Strategies of Corporate Sustainability

Abstract

This study presents a structured decision-making framework to evaluate and prioritize corporate sustainability actions under the triple bottom line, encompassing economic performance, social value, and environmental responsibility. First, we use fuzzy analytic hierarchy process to determine the relative importance of sub-criteria across TBL dimensions based on expert judgments and selection. Second, we use quality function deployment to translate those weighted priorities into ranked indicators by the house of quality. Finally, using natural language processing, we employ BERT semantic similarity models and assess the alignment between the model’s recommended actions and actual corporate sustainability disclosures across 10 publicly listed companies. The integrated framework enables a systematic comparison between ideal strategic priorities and practical implementation. By aggregating expert-derived priorities and disclosure-based alignment, the model provides a quantitative basis for benchmarking firms and identifying gaps between intention and action. This approach offers a replicable, data-driven method for evaluating corporate sustainability strategies within the TBL structure.