Will the gig work model work for agriculture? An initial exploration

Purpose We examine how a platform-mediated gig work employment model would function for agriculture, addressing two distinct labor market trends: the growing prominence of the gig worker and the pervasive labor struggles for agricultural operations. The main objective of this study is to test the economic viability of this model from the perspective of potential agricultural gig employees. In doing so, we examine two barriers to adoption: producer perspectives and the practical functionality of existing platforms that connect employees and employers. Our paper concludes by providing policy implications and practical strategies for developing this kind of workforce. Design/methodology/approach The study combines self-collected data from a survey of potential gig workers, data scraped from online postings by current gig workers on agriculture-focused platforms, and administrative data to provide a comprehensive descriptive analysis of workers’ interest in gig work and their earning potential. We describe heterogeneity in the latter across a variety of tasks gig workers might perform on an agricultural operation and the characteristics of those tasks. This analysis is complemented by qualitative data from structured roundtable conversations with producers (i.e. potential employers) about their perspective on the promise and pitfalls associated with this employment model. Findings Our results examine workers’ preferences for agricultural gig work and their earning potential. Enthusiasm for gig work among our sample of potential employees was high. We observe notable wage growth for “ideal” gig tasks, which are characterized by high urgency and low trust, over time. Workers’ earning potential is augmented most by moving into tasks that are higher trust rather than higher skill. On the other hand, we observe comparably low returns to workers doing high-urgency tasks. Our exploration of barriers to adoption urges caution: we find marked reticence among potential employers and current platforms lack mechanisms that promote trust. Originality/value This paper is among the first to consider the implications of the gig work platform model for agriculture. It provides a cohesive summary of the overlap between the agricultural labor market and the gig economy and uses a coordinated combination of quantitative and qualitative data from both sides of this labor market. These complementary sources drive our ability to make unique insights about this employment model in the agricultural space. By testing the viability of platform-mediated gig work in the agricultural sector, we explore a creative and potentially actionable solution to the sector's growing need for a skilled and flexible workforce.

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Publication Details

Journal
Agricultural Finance Review
Published
2026-11-04
DOI
https://doi.org/10.1108/afr-12-2025-0232
Primary Topic
Digital Economy and Work Transformation
Type
article
Field-Weighted Citation Impact
0.00
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article

Will the gig work model work for agriculture? An initial exploration

Margaret Jodlowski, Zheng Hou, Brian Gwin, Kristina Boone et al.
Agricultural Finance Review
Digital Economy and Work Transformation
article

Will the gig work model work for agriculture? An initial exploration

Margaret Jodlowski, Zheng Hou, Brian Gwin, Kristina Boone, Jacqueline Wilkins
article en

Abstract

Purpose We examine how a platform-mediated gig work employment model would function for agriculture, addressing two distinct labor market trends: the growing prominence of the gig worker and the pervasive labor struggles for agricultural operations. The main objective of this study is to test the economic viability of this model from the perspective of potential agricultural gig employees. In doing so, we examine two barriers to adoption: producer perspectives and the practical functionality of existing platforms that connect employees and employers. Our paper concludes by providing policy implications and practical strategies for developing this kind of workforce. Design/methodology/approach The study combines self-collected data from a survey of potential gig workers, data scraped from online postings by current gig workers on agriculture-focused platforms, and administrative data to provide a comprehensive descriptive analysis of workers’ interest in gig work and their earning potential. We describe heterogeneity in the latter across a variety of tasks gig workers might perform on an agricultural operation and the characteristics of those tasks. This analysis is complemented by qualitative data from structured roundtable conversations with producers (i.e. potential employers) about their perspective on the promise and pitfalls associated with this employment model. Findings Our results examine workers’ preferences for agricultural gig work and their earning potential. Enthusiasm for gig work among our sample of potential employees was high. We observe notable wage growth for “ideal” gig tasks, which are characterized by high urgency and low trust, over time. Workers’ earning potential is augmented most by moving into tasks that are higher trust rather than higher skill. On the other hand, we observe comparably low returns to workers doing high-urgency tasks. Our exploration of barriers to adoption urges caution: we find marked reticence among potential employers and current platforms lack mechanisms that promote trust. Originality/value This paper is among the first to consider the implications of the gig work platform model for agriculture. It provides a cohesive summary of the overlap between the agricultural labor market and the gig economy and uses a coordinated combination of quantitative and qualitative data from both sides of this labor market. These complementary sources drive our ability to make unique insights about this employment model in the agricultural space. By testing the viability of platform-mediated gig work in the agricultural sector, we explore a creative and potentially actionable solution to the sector's growing need for a skilled and flexible workforce.

Agricultural Finance Review
Southern Illinois University Carbondale (US), The Ohio State University (US)
Openalex Percentile: Top 8%
Digital Economy and Work Transformation
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