Knowledge-Driven Logistics: an Agent-Based Model for Enhancing Russia-Tanzania Trade Institutions
摘要
The evolution of global trade within a multipolar framework demands logistics solutions that integrate infrastructure with knowledge flows and institutional coordination. Focusing on the emerging Russia-Tanzania trade axis, this paper develops a knowledge-driven, agent-based modeling (ABM) framework to design and evaluate a multimodal logistics corridor via the International North-South Transport Corridor (INSTC). The methodology integrates trade profiling, agent interaction simulation, and economic-risk assessment. Findings reveal a strategic alignment between Tanzania’s agro-industrial import needs and Russia’s export strengths in wheat and fertilizers, underscoring the role of embedded knowledge in commodity flows. The ABM demonstrates how digital integration, dynamic risk mitigation, and policy interventions, such as joint logistics ventures and free economic zones, can enhance corridor resilience, reduce costs, and support sustainable trade expansion. This research re-conceptualizes trade corridors as adaptive, intelligence-based ecosystems, contributing to the practical implementation of South-South cooperation.