Segmenting CSA members by motivation: Anything but two peas in a pod

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Purpose-The purpose of this paper is to seek to segment CSA members based on their motivations to join a CSA. Design/methodology/approach-Data obtained from an online survey of 565 members belonging to a New York state CSA were analyzed using a combined hierarchical and non-hierarchical cluster analysis. Findings-Based on their motivations to join a CSA results reveal four distinct types of segments among CSA members: No-Frills Member, Foodie Member, Nonchalant Member, and Quintessential Member. Results show all four clusters differ statistically across demographic characteristics including gender, political affiliation, and household income. The clusters differed across psychographic characteristics such as attitudes toward the treatment of animals, treatment of farm workers, pesticide use, the environment, food miles, and limiting factory farm purchases. Quintessential Members emerge as most concerned with food purchasing decisions while No-Frills Members are least concerned. Research limitations/implications-The study employs a non-random purposive sample of CSAs in New York state. Respondents were recruited indirectly to participate in an online survey. The length and complexity of the survey, absence of an email address for respondents, levels of digital fluency, and technical glitches may result in lower participation rates. Practical implications-This paper offers recommendations to farmers for retaining and attracting different types of CSA members. Originality/value-This is the first study that segments CSA members in the USA based on their motivations to subscribe to a CSA, and it differentiates CSA member clusters based on their demographics, psychographics, and food purchasing decisions.

Original languageEnglish
Pages (from-to)1488-1505
Number of pages18
JournalBritish Food Journal
Volume117
Issue number5
DOIs
StatePublished - 5 May 2015

Keywords

  • Cluster analysis
  • Consumer perceptions
  • Consumer purchasing decisions
  • USA

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