WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Fuzzy Logic-Enhanced PMC Index for Assessing Policies for Decarbonization in Higher Education: Evidence from a Public University(MDPI, 2025-10-09) Fidan, Fatma Sener; Şener Fidan, FatmaHigher education institutions play a critical role in the transition to a low-carbon future due to their research capacity and societal influence. Accordingly, the calculation of greenhouse gas (GHG) emissions and the prioritization of mitigation strategies are of particular importance. In this study, a comprehensive campus-level GHG inventory was prepared for a public university in T & uuml;rkiye in alignment with the ISO 14064-1:2018 standard, and mitigation strategies were evaluated. To prioritize these strategies, both the classical Policy Modeling Consistency (PMC) index and, for the first time in the literature, a fuzzy extension of the PMC model was applied. The results reveal that the total GHG emissions for 2023 amounted to 4888.63 tCO2e (1.19 tCO2e per capita), with the largest shares originating from investments (31%) and purchased electricity (28.38%). While the classical PMC identified only two high-priority actions, the fuzzy PMC reduced score dispersion, resolved ranking ties, and expanded the number of high-priority actions to seven. The top strategies include awareness programs, energy-efficiency measures, virtual meeting practices, advanced electricity monitoring, and improved data management systems. By comparing the classical and fuzzy approaches, the study demonstrates that integrating fuzzy logic enhances the transparency, reproducibility, and robustness of strategy prioritization, thereby offering a practical roadmap for campus decarbonization and sustainability policy in higher education institutions.Article Citation - Scopus: 1Information Sources and Congruency Modulate Preference-Based Decision-Making Processes(Routledge Journals, Taylor & Francis Ltd, 2024-07-29) Ozkan, Aysegul; Zhang, JiaxiangPreference-based decisions often need to combine multiple pieces of information. This study investigated how the number of information sources and information congruency affect decision performance. Participants made preference-based choices between two groups of food items. Increasing the number of items in each option led to slower and less accurate decisions. Drift-diffusion modelling showed that more information sources relate to a slower rate of evidence accumulation. Therefore, the additional information impeded rather than improved the decision accuracy. In Experiment 2, each choice option contained either fully congruent information or one piece of incongruent information. Decisions with incongruent information is associated with a lower drift rate than that with congruent information, leading to inferior behaviorual performance. Further model simulations support that the change in attention weighting over information sources leads to the observed effects of item numbers and item congruency. Our results suggest a bounded combination of information sources during preference-based decisions.