Duration analyses of precision agriculture technology adoption: what's influencing farmers' time-to-adoption decisions?

Purpose - Precision technologies have been available at the farm level for decades. Some technologies have been readily adopted, while the adoption of other technologies has been slower. The purpose of this study is to examine the factors influencing farmers' time-to-adoption decisions as duration between year of commercialization of precision agriculture (PA) technologies and year of adoption, at the farm level. Design/methodology/approach - Time-to-adoption, which is the difference in years between technologies becoming commercially available and the year of adoption was determined using non-parametric duration analysis, and the impact of specific farm/farmer characteristics on time-to-adoption were estimated using a semi-parametric Cox proportional-hazard (CPH) model, based on a panel dataset of 316 Kansas farms from 2002 to 2018. Findings - The findings indicate that, time-to-adoption for embodied-knowledge technologies such as automated guidance and section control were statistically shorter than for information-intensive technologies such as yield monitors, precision soil sampling and variable rate fertility. Duration was indirectly (directly) proportional to commercialization date of embodied-knowledge (information-intensive) technology. More so, time-to-adoption statistically differed among technologies within these two broad categories. Time-to-adoption varies across farm location and between both types of technologies. Millennial farmers are more likely to adopt both types of technologies sooner compared to baby boomers. Net farm income, percentage changes in debt-to-asset ratio, corn to total crop acres and machinery investment had no significant impact on the time-to-adoption for both information-intensive and embodied-knowledge technologies. On the other hand, while variations exist, time-to-adoption of PA technologies is mainly driven by location of farm, generation of farmer, number of workers, years of farming experience, total acres cropped and the cost of crop insurance. Originality/value - This study investigates how the financial position of farms, amongst other important factors might influence time-to-adoption of PA technologies. Results are useful to extension personnel and retailers for planning marketing or farm outreach programs taking into consideration that, time-to-adoption differs across regions and by specific characteristics, key amongst them: generation of farmer, number of workers, years of farming experience, total acres cropped and the cost of crop insurance.