Investigating consumers' experiences with community supported agriculture: Convergent parallel design methods

PLoS One. 2024 May 13;19(5):e0303184. doi: 10.1371/journal.pone.0303184. eCollection 2024.

Abstract

Community-supported agriculture (CSA) represents a collaborative model where local farms and community members form partnerships to facilitate the direct delivery of fresh produce from farms to consumers. This study primarily investigates the experiences of current CSA members, focusing on the key factors influencing their retention intentions. Employing a convergent parallel mixed methods approach, this study gathers and analyzes both quantitative data (such as factors affecting members' retention intentions) and qualitative data (derived from interviews reflecting members' perceptions of their CSA experiences). The integration of these datasets provides a comprehensive understanding of the factors that shape CSA membership dynamics. The research findings underscore that Convenience, Product Quality, and Positive Interactions are pivotal factors that contribute to members' Intentions to continue their CSA memberships. These insights are crucial for enhancing the services provided to CSA members and hold significant implications for the broader scope of CSA membership research. This study not only fills a critical gap in understanding the Chinese CSA context but also contributes to the global discourse on sustainable agriculture practices and community engagement.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture*
  • China
  • Community Participation
  • Consumer Behavior
  • Farms
  • Female
  • Humans
  • Male

Grants and funding

The author(s) received no specific funding for this work.