Qualitative research on precision agriculture adoption and farm work transformation
Cornell University researcher Diane Bailey offers qualitative research expertise examining how precision agriculture fits with farmers' existing work practices, beliefs, and identities. Drawing on established theory about technology and work, the research investigates adoption barriers, benefits, and generational appeal among fruit growers in New York State.
Overview
This offering provides qualitative research services focused on understanding the human and organizational dimensions of precision agriculture adoption. The research addresses how farmers integrate data-driven technologies into their existing work practices, how their daily routines change with adoption, what benefits and obstacles emerge post-implementation, and how precision agriculture appeals across generational lines. The work is grounded in established scholarship showing that work, technology, skills, and identity are deeply interconnected, meaning that introducing new technologies often produces unanticipated consequences as farmers adjust their practices, beliefs, and self-understanding in response.
Technical specifications
Research approach:
- Semi-structured interviews enabling detailed, open-ended responses from participants
- Snowball sampling methodology to build a robust participant pool of 30 to 40 farmers
- Standard qualitative coding techniques to analyze data and build theory
- Site visits to farms for direct observation of work practices
Current sample composition:
- Over a dozen New York farmers interviewed to date, primarily fruit growers
- Mix of early adopters, mid-adopters, and uninterested farmers
- Range of younger and older farmers represented
- Recruitment supported through Cornell's statewide extension program
Theoretical foundation:
- Prior research documenting how computational and AI-based technologies shift work from physical to analytical skills
- Framework examining new relations between physical and virtual work artifacts
- Insight into global outsourcing patterns that may emerge in agricultural contexts
Technology readiness level
The research is actively underway with initial interviews already completed and analysis in progress. The methodology has been validated through prior studies in non-agricultural settings such as offices and factories, and is now being extended to agricultural contexts where data-driven technologies are rapidly emerging. The next phase involves expanding the sample to 30 to 40 interviews and completing theory-building analysis. Findings will generate actionable insights for technology designers, agricultural extension programs, and industry partners seeking to improve adoption outcomes and anticipate the broader consequences of precision agriculture deployment.
About Cornell University
Cornell University is a comprehensive private, land-grant research university with campuses in Ithaca and New York City, combining significant scale with cross-disciplinary breadth. Industry connects through open-access user facilities and prototyping labs, pilot-scale testbeds, and a research and technology park that provide pathways from discovery to demonstration. A statewide extension network and integration with a major hospital system enable real-world deployment, while a graduate campus embedded in New York City’s tech corridor provides direct access to startups, venture investors, and corporate R&D teams. Research is supported by competitive federal funding from agencies such as the National Science Foundation, National Institutes of Health, the Department of Energy, and the U.S. Department of Agriculture. A dedicated technology transfer office streamlines IP management, licensing, startup formation, and corporate partnerships across campuses.
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