A Multi-Criteria Decision Approach for Composting of Food Waste in the Hospitality and Tourism Industry

Abstract

Considering the importance of Responsible Consumption and Production (SDG-12) and circular economy principles, this study proposes an integrated experimental and decision support framework for evaluating the composting suitability of selected food waste generated in the hospitality and tourism (H&T) industry. In the first stage, a controlled small-scale composting experiment was conducted using pineapple peel, carrot peel, banana peel, coffee waste, and tea waste, and key operational parameters namely temperature, pH, and moisture content. These were systematically monitored over a 20-day period. The temperature dropped to room temperature from day 5 and remained constant thereafter. Moisture dropped below 20% in the 2nd, 5th, 6th, 7th, 16th, 17th, 18th, 19th, and 20th samples and even to zero in the 7th sample. In the second stage, the Comprehensive Normalization Technique with Mixed Collection (MACONT) method, one of the Multi-Criteria Decision-Making (MCDM) methods, was applied to rank food waste based on their composting performance. To validate the robustness of the result, a comprehensive sensitivity analysis was performed. The findings indicate that pineapple peel and tea waste exhibit superior composting performance under the specific experimental conditions, while coffee waste demonstrates limited suitability and may require alternative valorization pathways. The proposed framework offers a practical decision support tool for environmental managers and practitioners in the H&T industry, enabling evidence-based selection of food streams for composting applications and contributing to sustainable waste management strategies.