Producers’ adoption behaviors for precision agriculture (PA) technologies to improve nitrogen use efficiency: Diffusion of Innovations theory as an explanatory lens

Authors

DOI:

https://doi.org/10.37433/aad.v3i3.205

Keywords:

innovation decisions process, nitrogen fertilizer, sustainability

Abstract

Advancements in precision agriculture technologies enable producers to achieve higher yields; however, in some cases, these innovations have not reached widespread adoption despite years of availability. We sought to understand producers’ adoption experiences with two precision agriculture technologies: Nitrogen (N)-Rich Strips and the Sensor Based Nitrogen Rate Calculator (SBNRC). These technologies can help producers optimize their application of nitrogen fertilizer on growing crops, especially small grains such as wheat. Using Rogers’ (2003) diffusion of innovations theory as an explanatory framework, this descriptive-exploratory study examined the adoption behaviors of producers from two midwestern states. Rogers’ (2003) theoretical lens guided instrument development and interpretation of results. To better understand the effects of change agents’ actions and potential adopters’ behaviors during the innovation-decision process, more research is needed regarding disenchantment discontinuance and replacement discontinuance, the potential for pro-innovation bias, and of the innovation attribute compatibility. The future development of precision agriculture technology with the perceptions of potential adopters in mind, especially those averse to adoption and continuance, may assist in overcoming barriers to widespread diffusion.

Downloads

Download data is not yet available.

References

Camp, W. G. (2001). Formulating and evaluating theoretical frameworks for career and technical education research. Journal of Vocational Education Research, 26(1). https://doi.org/10.5328/JVER26.1.4

Desta, B., Arnall, B., & Raun, B. (2017, April). The evolution of reference strips in Oklahoma – Oklahoma State University. https://extension.okstate.edu/fact-sheets/the-evolution-of-reference-strips-in-oklahoma.html

Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys: The tailored design method (3rd edition). John Wiley & Sons.

Hill, P., Mills, R., Peterson, G., & Smith, J. (2013). Breaking the code: The creative use of QR codes to market Extension events. Journal of Extension, 51(2). https://archives.joe.org/joe/2013april/tt4.php

Johnson, R. B., & Christensen, L. (2017). Educational research: Quantitative, qualitative, and mixed approaches (6th edition). SAGE.

Lee, C. L., Strong, R., & Dooley, K. E. (2021). Analyzing precision agriculture adoption across the globe: A systematic review of scholarship from 1999–2020. Sustainability, 13(18), 10295. https://doi.org/10.3390/su131810295

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). The Free Press.

Downloads

Published

2022-09-16

How to Cite

Looney, L., Montgomery, P., Edwards, M. C., Arnall, B., & Raun, W. R. . (2022). Producers’ adoption behaviors for precision agriculture (PA) technologies to improve nitrogen use efficiency: Diffusion of Innovations theory as an explanatory lens. Advancements in Agricultural Development, 3(3), 40–50. https://doi.org/10.37433/aad.v3i3.205

Issue

Section

Articles