Reverse Logistics Practices and the Performance of Heavy Commercial Logistics Firms in the Western Corridor of the Sugar Belt in Kenya

Abstract

Reverse logistics encompasses the planning and control of material, product, information, and asset flows that move upstream for recovery, reuse, recycling, or appropriate disposition. In transport-intensive agricultural supply chains, reverse-logistics activities can include coordinated return flows, asset recovery, and managed secondary movements, while empty-mile management concerns the reduction and productive use of unladen vehicle capacity. This study examines the relationships between reverse-logistics consolidation, empty-mile management, road infrastructure quality, technology and telematics integration, and operational performance among heavy commercial logistics firms operating in Kenya’s Western Sugar Belt. The study is situated within a regulatory environment in which the Sugar Act, 2024 recognises transporters as value-chain actors and includes transportation and delivery within cane management. Drawing on the Resource-Based View, Institutional Theory, and Sustainable Supply Chain Theory, the study adopted a quantitative cross-sectional explanatory design. Data from 240 valid respondents, comprising logistics managers, dispatchers, drivers, and supply-chain personnel, were analysed using descriptive statistics, Pearson correlation, multiple linear regression, and conditional-process analysis. The results show statistically significant positive associations between each explanatory construct and operational performance. The regression model explained 51.5% of the variance in operational performance (R² = 0.515; adjusted R² = 0.507; p < 0.001). Empty-mile management had the largest standardized coefficient (β = 0.389), followed by technology and telematics integration (β = 0.373), reverse-logistics consolidation (β = 0.347), and road infrastructure quality (β = 0.315), with all coefficients statistically significant at p < 0.001. The interaction between reverse-logistics consolidation and technology/telematics integration was not statistically significant (interaction coefficient = 0.055, p = 0.331). The mediation test produced an indirect effect of 0.042 with a 95% bootstrap confidence interval of [0.000, 0.089]. Because the interval touches zero at its lower bound, the data failed to establish a statistically significant indirect effect for this sample. The findings suggest that firms may improve operational performance by reducing unproductive kilometres, coordinating return flows, strengthening digital visibility, and addressing infrastructure constraints. The study contributes context-specific evidence to reverse-logistics research and offers practical implications for transport firms, sugar-industry stakeholders, and public agencies responsible for transport infrastructure and sector regulation.