Comparative innovative logistics performance analysis of G7–BRICS countries using SWARA–MEREC based EDAS methodology

In today's world, where globalization and digitalization are accelerating, the logistics sector has become a strategic element in determining countries' economic competitiveness. The increasing complexity of logistics and the rapid evolution of trade networks require innovative, adaptive logistics structures. In this process, innovation stands out as a key factor that increases the efficiency and sustainability of logistics systems. In particular, broad innovation capacity and supportive institutional environments significantly shape the development of modern logistics systems. A logistics infrastructure strengthened by innovative approaches both increases operational efficiency and supports environmental sustainability. This study proposes a new index measuring countries' Innovative Logistics Performance (ILP) by integrating data from the Global Innovation Index (GII) and the Logistics Performance Index (LPI). By combining these two widely recognized indices, the study offers a multidimensional perspective on the innovation–logistics nexus. The index provides a systematic tool to assess how innovation dynamics translate into logistics competitiveness at the national level. In this respect, the study introduces a new conceptual framework in the literature and presents a measurable structure for analyzing this relationship. The study's unique feature is its hybrid methodological approach, combining SWARA, MEREC, and EDAS for the first time. This multi-method approach allows for a more comprehensive evaluation compared to traditional single-method analyses. The proposed model integrates both subjective and objective weighting techniques, ensuring balance and reliability in the evaluation process. The findings indicate that the "Institutions" criterion is the most influential determinant of ILP, followed by "Customs" and "International Shipments." The United States, Germany, and Canada stood out as the top-performing countries. Furthermore, a sensitivity analysis was conducted to assess the model's reliability, confirming its robustness and consistency in the evaluation results.