Blockchain in Agricultural Cooperative Supply Chains

Data Description for Repository Submission

Research Hypothesis
This study explores how socio-demographic and organizational factors affect the adoption of blockchain-based traceability systems in agricultural cooperatives. It hypothesizes that education level enhances perceived usefulness, age influences adoption priorities, and perceived usefulness mediates the relationship between supply chain challenges and adoption intention. Together, these hypotheses examine how trust, transparency, and capacity-building shape technology acceptance in cooperative structures.

What the Data Show
Evidence from the 15-month blockchain pilot at the S.S. Ödemiş Bademli Agricultural Development Cooperative (Türkiye) supports these assumptions. Education significantly increased perceived usefulness (η² = 0.545, p < .01), while younger members valued traceability and older ones prioritized efficiency. Capacity-building and infrastructure were rated more important than financial incentives. Perceived usefulness strongly correlated with adoption intention (r = 0.78, p < .01). System telemetry confirmed 99.7 % uptime, 94 % fewer manual errors, and 35 % faster task completion compared with pre-blockchain processes.

Interpretation and Notable Findings
Results emphasize that trust, transparency, and digital literacy are key to blockchain adoption in cooperatives. The proposed Community-Enhanced Technology Acceptance Model (CE-TAM) extends traditional TAM by integrating cooperative governance factors such as shared trust and participation. Findings suggest that social cohesion can be as critical as technical infrastructure in digital transformation.

Data Nature and Use
Data were collected through structured surveys (5-point Likert scales), semi-structured interviews, and blockchain system logs (Polygon Amoy testnet + MySQL backend). All participants provided informed consent, and no personal data were stored, ensuring KVKK and GDPR compliance. The dataset includes variable labels, codebook, and a README explaining structure and analysis methods. Researchers can reuse the data for replication, meta-analysis, or benchmarking blockchain performance in cooperative settings. Aggregated datasets are available at the designated repository (DOI forthcoming).