Enhancing logistics performance has been widely recognized as a critical pathway for accelerating economic development in emerging economies. In this context, a rigorous and objective assessment of national logistics performance remains essential. Accordingly, an integrated multi-criteria decision-making (MCDM) framework based on the Skewness Impact Through Distributional Evaluation (SITDE) method and the Multi-Attributive Border Approximation Area Comparison (MABAC) method was proposed for the systematic evaluation of logistics performance across the Emerging Seven (E7) economies. Within this framework, criterion weights were objectively derived using the SITDE method by capturing the distributional characteristics and skewness effects inherent in logistics performance indicators, thereby minimizing subjectivity in the weighting process. Subsequently, the MABAC method was employed to rank countries by quantifying their distances from criterion-specific boundary approximation areas. The empirical analysis focused on the E7 countries—China, India, Brazil, Russia, Indonesia, Mexico, and Türkiye—using the Logistics Performance Index (LPI) indicators obtained from the World Bank database. The results demonstrated that timeliness emerged as the most influential determinant of overall logistics performance. Among the E7 countries, China was identified as exhibiting the highest logistics performance, whereas Russia recorded the lowest performance level. Notably, Türkiye was ranked second, despite its comparatively lower level of economic development relative to several other E7 economies. The robustness and stability of the proposed SITDE–MABAC framework were further confirmed through comprehensive sensitivity and comparative analyses. Beyond methodological advancement, the findings offer important managerial, policy-oriented, and region-specific insights, providing evidence-based guidance for policymakers and logistics practitioners seeking to enhance logistics efficiency, resilience, and international competitiveness in developing economies.
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