<![CDATA[Evaluation of sales team performance is essential for measuring the effectiveness of marketing strategies and achieving corporate goals. The main problem in evaluating sales team performance lies in the high subjectivity of assessments, unclear performance indicators, and difficulties in determining objective and consistent criteria weights. This situation results in evaluation outcomes that are unstable and potentially lead to suboptimal managerial decisions. To address this, the study applies a hybrid approach combining Entropy weighting and Multi-Attribute Utility Theory (MAUT). Entropy objectively derives criterion weights from data variability, while MAUT systematically transforms performance scores into utility values, enabling more consistent comparisons than traditional assessment methods. The research results show that the proposed model produces stable and quantitatively consistent rankings, with a utility score range between 0 and 1.0048 reflecting measurable performance differentiation among teams. Team G achieved the highest score of 1.0048, while Team D scored 0, indicating a significant performance gap. Compared to conventional methods, which tend to yield more homogeneous values, this hybrid approach is more effective in minimizing bias, enhancing discriminative power, and strengthening the reliability of managerial decision-making. This research makes a significant contribution to the development of scientific knowledge by presenting an innovation in the form of integrating the Entropy and MAUT methods in the context of sales team performance evaluation that is more objective, systematic, and data-based.]]>
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