Author
Abstract
Social platforms have become an important force in driving consumer decisions through content marketing, due to their wide reach and precise targeting. Based on Philip Kotler’s consumer decision making process, this study uses the LDA topic model to identify types of content marketing for agricultural products and key factors that influence consumer behavior at the advocate stage. It also applies grounded theory to explore the internal mechanisms of interaction across the aware, appeal, ask, act, and advocate stages in content marketing for agricultural products on social platforms. A theoretical model of key influencing factors and impact pathways is developed. The results show that common types of content marketing for agricultural products include the origin traceability type, daily situational type, product recommendation type, key opinion leader type, and selling pitiful type. Different content marketing types influence consumers’ source credibility awareness and flow content during the aware and appeal stages. This triggers either emotional identification or psychological reactance, which affect perceived risk at the ask stage and purchase behavior at the act stage. Consumer planned behavior moderates the relationship between perceived risk and purchase decisions, with some consumers bypassing risk perception and purchasing directly. At the advocate stage, emotional identification motivates consumers to share and recommend content according to their consumer demand hierarchy, shaping their ongoing behavior. Consumer feedback on product sensory characteristics, logistics, pricing, service attitude, and repeat purchase recommendations supports continuous improvement of content marketing strategies. The conclusions offer strategic guidance for content marketing of agricultural products on social platforms and support a sustainable content marketing ecosystem.
Suggested Citation
Moran Fan & Chunling Zhang, 2025.
"Key Factors and Influence Pathways of Agricultural Product Content Marketing on Social Platforms: A Mixed-Method Approach With LDA and Grounded Theory,"
SAGE Open, , vol. 15(3), pages 21582440251, September.
Handle:
RePEc:sae:sagope:v:15:y:2025:i:3:p:21582440251379295
DOI: 10.1177/21582440251379295
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