Akademik Veri Yönetim Sistemi
Journal of Cleaner Production, cilt.557, 2026 (SCI-Expanded, Scopus)
Based on the urge to select the most proper food waste treatment technology (FWTT) to alleviate the adverse repercussions of food waste (FW) generated by the hospitality industry on sustainability, and methodological shortcomings of the relevant multi-criteria decision-making (MCDM) research, this research intends to introduce a novel hybrid MCDM model for identifying the most pertinent FWTT adopting the Gaussian–IF–SWARA–LOPCOW–ALPAS framework for the first time. Specifically, this study addresses key methodological gaps by jointly capturing epistemic uncertainty and randomness via Gaussian intuitionistic fuzzy sets, incorporating expert-importance weighting, and systematically integrating subjective and objective criteria weights within a unified framework. The proposed integrated model constitutes a methodological novelty by combining controllable weighting mechanisms, robust normalization schemes, and a stable ranking procedure, thereby enhancing the reliability, transparency, and applicability of FWTT selection under uncertainty. Through a case study based on 13 criteria and involving 10 FWTTs, the applicability of the suggested methodology is also indicated. Referring to the results, incineration is marked as the most pertinent FWTT, followed by gasification and pyrolysis for FW treatment. Further, both sensitivity and comparative analysis also support the robustness of the proposed methodology. The findings enhance decision-makers' awareness in relevant institutions and industries about selecting the appropriate FWTT under uncertainty, offering valuable insights tailored to diverse criteria regarding sustainable aspects of FWTTs.