Аннотация
Contemporary supply chains operate under growing pressures of globalization, digital transformation and increasingly complex coordination. Under these conditions, information asymmetry, limited transparency and opportunistic behaviour weaken operational performance and raise legal and organizational risks. The article examines non-manipulable mechanisms in logistics and supply chain management as institutional and technological arrangements that limit such distortions through transparency, verifiability, traceability and protection from unilateral influence. The study aims to determine how these mechanisms affect operational efficiency, customer satisfaction and risk reduction, proceeding from the idea that incentive alignment, transparency and verifiability jointly shape logistics outcomes and should be viewed as a unified governance approach. A mixed-method quasi-experimental comparative design was used. Data were collected from 80 enterprises, with an implementation group (50 companies) and a control group (30 companies). The empirical base includes standardized questionnaires, internal records, semi-structured interviews and comparable before–after indicators. Statistical analysis relied on Student’s t-tests, and qualitative materials were examined using thematic analysis. Enterprises applying non-manipulable mechanisms, compared with those using standard practices, demonstrated shorter order processing times, lower inventory costs, higher customer satisfaction and lower fraud-related and legal risks, as well as better coordination and greater trust among partners. The study integrates mechanism design, transparency-oriented governance and logistics performance into a single analytical framework and provides empirical confirmation of the practical relevance of non-manipulable mechanisms for designing more transparent, resilient and efficient supply chain management systems. Keywords: supply chain management, non-manipulable mechanisms, transparency, efficiency, risks, quantitative analysis, qualitative analysis.