This study identifies which traceability data elements should be prioritized to deter honey fraud and support credible assurance and examines how producer heterogeneity shapes readiness for differentiated traceability requirements.
An exploratory sequential mixed-methods design was employed. Expert interviews (n = 30) specified traceability data elements and their assurance roles; a survey of Polish beekeepers (n = 949) assessed perceived importance and producer characteristics. Survey analysis combined descriptive statistics, K-modes clustering, non-parametric between-cluster tests and multinomial logistic regression.
Experts structured traceability into four domains and 21 data elements, operationalizing traceability as a layered governance architecture separating enforceability-critical core elements from conditional, verification-intensive tiers. The core baseline comprises identifiers, coarse provenance and producer-stage event records, whereas tiered mechanisms (e.g. testing and sensitive husbandry records) strengthen fraud deterrence under elevated risk. The survey results reveal broad support for traceability alongside systematic heterogeneity: data-cautious, data-aware and data-driven profiles differ in verification-oriented priorities and digital engagement, supporting pathway-based proportional implementation.
This study operationalizes traceability as a structured set of data elements linked to verification functions and empirically grounds a core-versus-tiered assurance model calibrated for producer heterogeneity. While empirically grounded in honey, the governance logic is transferable to other authenticity-sensitive food sectors with fragmented production, such as olive oil, spices, wine and origin-labeled products.
