Warner, L. A., Rihn, A.L., Fulcher, A., Schexnayder, S., & LeBude, A. V. (2022). Relating Grower Perceptions and Adoption of Automated Nursery Technologies to Address Labor Needs. Journal of Agricultural Education, 63(2), 150-168. https://doi.org/10.5032/jae.2022.02150
Abstract: This study examined factors that shape how nursery growers perceive automated nursery technologies and evaluate how these perceptions relate to growers’ adoption. We applied Rogers’ (2003) Diffusion of Innovations to understand growers’ perceptions of automated technologies to inform Extension programming serving niche audiences in the nursery and horticulture arenas. Data were collected via a mixed-mode survey and analyzed using descriptive statistics and multiple linear regression. Nursery growers indicated fairly strong perceptions of observability, relative advantage, and compatibility. Automated nursery technologies were not perceived as being complex. Notably, perceptions of trialability were low. Compatibility, complexity, and trialability predicted growers’ current adoption of automated technologies. Relative advantage, complexity, and compatibility predicted the future adoption of automated nursery technologies. Compatibility was the most important predictor of both current use and the likelihood of adopting automated nursery technologies. Extension professionals, researchers, and others who support the nursery industry can use these findings to encourage the adoption of technological innovations. Chiefly, automated nursery technologies need to be designed with compatibility in mind (e.g., adaptable to nursery operations’ existing infrastructure, values, and goals). Uptake could be accelerated by emphasizing compatibility (e.g., conveying how these technologies can be integrated into existing systems and how the current labor force’s skillsets can be applied to new technologies). This study considered a suite of automated nursery technologies to provide a starting point in developing and diffusing these types of innovations. Future research should examine the characteristics of specific technologies to pinpoint precise strategies aimed at behavioral adoption.