Grounded Theory Model for Social Media Integration in Agricultural Extension

Articles in Press

Document Type : Original Research

Authors
M. Baharestani 1
A. Poursaeed 2
M. Vahedi 2
1 PhD Student, Department of Agricultural Extension and Education, Ilam Branch, Islamic Azad University, Ilam, Iran
2 Assistant Professor, Department of Agricultural Extension and Education, Ilam Branch, Islamic Azad University, Ilam, Iran
Abstract
The rapid spread of digital technologies has created new opportunities for strengthening agricultural extension, yet the systematic integration of social media into extension systems remains poorly understood. This study aimed to develop a grounded theoretical model that explains the drivers, barriers, and strategies for enabling social media adoption in agricultural extension. Eleven semi-structured interviews were conducted with subject-matter experts from extension institutions and digital communication units in Iran, and data were analyzed using open, axial, and selective coding procedures. The coding process generated 57 concepts and 23 categories, which were synthesized into a paradigmatic model encompassing causal, contextual, and intervening conditions, as well as strategies and outcomes. Results showed that policy coordination, institutional collaboration, infrastructure investment, and digital capacity-building are essential conditions for effective adoption. Key barriers identified include weak rural internet coverage, limited digital literacy among farmers, insufficient financial resources, and fragmented policy frameworks. The study also revealed that social media supports faster knowledge dissemination, real-time farmer engagement, and adoption of sustainable agricultural practices. The theoretical model contributes to extension scholarship by linking institutional and contextual enablers to practical outcomes, thereby complementing existing technology-adoption frameworks. Practically, the findings emphasize the need for evidence-based policy frameworks, public–private partnerships, and investments in localized content and farmer training. Strategic use of emerging tools such as big data, IoT, and artificial intelligence can further enhance the effectiveness of social media-based extension. The model provides actionable guidance for policymakers and practitioners to strengthen rural innovation and sustainable agricultural development.

Keywords

Subjects

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Journal of Agricultural Science and Technology

Articles in Press, Accepted Manuscript
Available Online from 18 October 2025