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    Integrating Artificial Intelligence into Fuzzy Decision Analytics: A Novel Approach to Mitigating Stereotype Threat in Sustainable Business Environments
    (Research Expansion Alliance (REA), 2025) Czukor, Gergely; Dinçer, Hasan; Eti, Serkan; Yüksel, Serhat; Pamucar, Dragan
    Preventing the threat of stereotyping is critical for business performance improvements. Because of this situation, businesses must take the necessary precautions. However, these actions have an impact on cost increase for the businesses. The number of studies in the literature performing priority analysis for these factors is quite limited. This situation increases the need for a new study that prioritizes the analysis of these variables. Accordingly, this study aims to evaluate the factors against the stereotype threat in the sustainable business environment. An artificial intelligence model is implemented in the first stage to weigh the experts. In the following stage, selected criteria are evaluated with the help of T-Spherical fuzzy DEMATEL. Thirdly, a comparative analysis was performed using different values. Finally, selected industries are ranked by Spherical Fuzzy RATGOS with respect to the stereotype threat. The weights of the experts can be identified in the analysis process. This situation has a strong contribution to the effectiveness of the findings. It is concluded that training activities are critical to minimizing the threat of stereotypes in companies. © 2025, Research Expansion Alliance (REA). All rights reserved.
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    The MEREC-AROMAN method for determining sustainable competitiveness levels: A case study for Turkey.
    (Socio-Economic Planning Sciences, 2023-11-17) Acar, A. Zafer; Kara, Karahan; Yalçın, Galip Cihan; Simic, Vladimir; Konya, Serkan; Pamucar, Dragan
    ABSTRACT: Sustainable competitiveness represents a multifaceted phenomenon encompassing economic, environmental, and social dimensions. Macro-level competitiveness strategies are formulated based on the diverse capitals possessed by individual countries, thereby giving rise to variations in the sustainable competitiveness strategies of each country. This research introduces a novel hybrid method called the method based on the removal effects of criteria (MEREC)? alternative ranking order method accounting for two-step normalization (AROMAN) for determining sustainable competitiveness levels. This study aims to assess Turkey’s sustainable competitiveness position vis-` a-vis its border neighbors. Natural capital, resource efficiency and intensity, social capital, intellectual capital and innovation, economic sustainability, and governance efficiency are the Global Sustainable Competitiveness Index (GSCI) indicators. The GSCI indicators are employed as criteria for determining the sustainable competitiveness scores of countries. The findings show that the “resource efficiency and intensity” criterion has the highest level of significance. The sustainable competitiveness level of Turkey to its neighboring countries is elucidated based on the results. Recommendations are formulated for the development of strategies aimed at determining Turkey’s position in the race for sustainable competitiveness. The introduced MERECAROMAN can be utilized to provide rules of thumb for other countries to improve their sustainable competitiveness. This research offers decision support for the formulation of countries’ sustainable competitiveness strategies and policies, fostering awareness in the planning and establishment of regional collaborations among nations.