BLOCKCHAIN ADOPTION IN THE LOGISTICS SECTOR: A FIT-VIABILITY AND TASK-TECHNOLOGY FIT PERSPECTIVE

Abstract

This study examines the determinants of blockchain adoption in the logistics sector by integrating the Fit-Viability Model (FVM) and Task-Technology Fit (TTF) theory. Using data collected from 364 logistics managers operating in maritime, transport, and warehousing firms in Mersin, T & uuml;rkiye, the research empirically tests how organizational alignment, transparency, integration, and resilience affect operational fit (TTF), and how sustainability dimensions-economic, environmental, and social-influence strategic fit (STF). Structural Equation Modeling (SEM) via SmartPLS was employed to evaluate the relationships among these constructs. The findings demonstrate that both TTF and STF significantly predict blockchain adoption, with STF (beta = 0.453, p < 0.001) showing a stronger influence than TTF (beta = 0.282, p < 0.001). This indicates that sustainability objectives may be a more decisive factor in driving blockchain uptake than operational fit alone. The study also reveals that transparency and integration are particularly critical in shaping TTF. Conversely, agility did not significantly moderate the relationship between TTF and adoption, suggesting that internal adaptability may be insufficient without external readiness and regulatory support. By validating the dual-fit framework, this study contributes original insights to the literature on emerging technology adoption in logistics. It highlights the complementary role of sustainability and technological alignment in driving blockchain implementation. Managerial implications emphasize the need for strategic ESG alignment, supply chain transparency, and system integration. Policy recommendations include standardization of platforms, incentive schemes for SMEs, and targeted capacity-building initiatives. The study sets a foundation for future research into the moderating effects of digital maturity and institutional factors on technology adoption in complex logistics ecosystems.