Agripreneurial Matching: Worker-Centric Digital Platforms for Displaced Farm Workers in Southwest Cameroon

Purpose: This study examines how worker-centric digital platforms facilitate agripreneurial matching among conflict-displaced farm workers in Southwest Cameroon, focusing on technology-enabled employment pathways in conflict-affected agricultural markets.
Research Methodology: A mixed-methods design was employed. Quantitative data were collected from 385 displaced farm workers and 45 agricultural employers through structured questionnaires and analyzed using descriptive statistics and multiple regression. Qualitative data were obtained from 25 key informants through semi-structured interviews and analyzed using Braun and Clarke’s six-phase thematic analysis. Findings were integrated through an explanatory sequential approach.
Results: Platform accessibility, digital literacy, and trust significantly predicted agripreneurial matching outcomes, explaining 54.2% of the variance. Trust was the strongest predictor (β=0.398, p<0.001), followed by platform accessibility (β=0.342) and digital literacy (β=0.287). Qualitative findings showed that displaced workers prioritized transparent wage information and accessible dispute-resolution mechanisms.
Conclusions: Worker-centric digital platforms can facilitate agripreneurial matching when accessibility, digital literacy, and institutional trust are adequately addressed.
Limitations: The study focused on Southwest Cameroon, limiting generalizability, while its cross-sectional design restricts causal inference.
Contributions: This study extends technology acceptance and social capital perspectives to conflict-induced displacement and proposes a worker-centric framework for inclusive digital employment platforms in humanitarian settings.