Özet:

In today's fast-paced and ever-changing business landscape, effective decision-making is paramount to achieving success and maintaining a competitive edge. This holds particularly true in the aviation sector, where Human Resource Management (HRM) plays a pivotal role in optimizing workforce performance and ensuring operational efficiency. However, HRM decision-making processes are often confronted with multifaceted challenges that encompass various criteria and encompass both objective and subjective factors. To tackle this complexity, a novel and adaptive approach is needed. In this study, we employ a Fuzzy Logic Approach to analyze the criteria influencing decision-making processes in HRM within the aviation sector, aiming to provide a comprehensive and flexible decision-support system for HRM practitioners and contribute to the sector's overall performance and success. The contribution of this study lies in its innovative application of Fuzzy Logic to HRM decision-making in the aviation sector. By capturing the inherent uncertainties and vagueness that HRM practitioners encounter, the proposed Fuzzy Logic-based model offers a more robust and context-sensitive decision-support system. Based on the Fuzzy Logic application and sensitivity analysis, the findings reveal the significance of employee satisfaction as the most influential criterion in HRM decision-making within the aviation sector. The Fuzzy Logic model demonstrated a strong positive correlation between high employee satisfaction levels and favorable HRM Decision Outcomes. This finding emphasizes the pivotal role of employee satisfaction in shaping HRM strategies and outcomes within aviation organizations.

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