Document Type : Research Paper
Authors
1 Department of agricultural extension and education
2 Department of Agricultural Extension & Education- Faculty of Agriculture, Razi university- Kermanshah
3 Department of management and entreprenurship
Abstract
this study adopts an innovative mixed-methods approach to assess the educational needs of agricultural digital marketing professionals by integrating bibliometric analysis and network analysis. In the first stage, a bibliometric analysis was conducted based on Scopus-indexed documents published between 2019 and 2025. The examination of approximately 90 scientific documents and co-occurrence analysis of keywords using VOSviewer revealed the main conceptual clusters and research trends related to the application of artificial intelligence in agricultural digital marketing. This conceptual map provided the basis for the second stage, in which a systemic analysis of skills was carried out. In the next stage, MACTOR analysis was employed to identify relationships of influence, dependency, and strategic importance among the skills. Data for this phase were collected from 48 selected experts using criterion-based sampling. The findings indicated four main dimensions of educational needs: (1) AI literacy and conceptual understanding, (2) interactive and practical chatbot skills, (3) AI-based marketing competencies, and (4) commercialization and value creation. Influence–dependence analysis further showed that “market demand analysis and forecasting” and “consumer behavior analysis” are key driving factors, while skills such as “digital campaign management” serve as intermediary variables linking these drivers to final outcomes such as “customer engagement.” In addition, convergence analysis revealed that “customer data analysis” and “personalized recommendations” exhibit the strongest alignment, highlighting the need for integrated and hybrid training packages.
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