Abstract
Simple SummaryMost prototypes of systems to automatically detect lameness in dairy cattle are still not available on the market. Estimating their potential adoption rate could support developers in defining development goals towards commercially viable and well-adopted systems. We simulated the potential market shares of such prototypes to assess the effect of altering the system cost and detection performance on the potential adoption rate. We found that system cost and lameness detection performance indeed substantially influence the potential adoption rate. In order for farmers to prefer automatic detection over current visual detection, the usefulness that farmers attach to a system with specific characteristics should be higher than that of visual detection. As such, we concluded that low system costs and high detection performances are required before automatic lameness detection systems become applicable in practice.Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system’s potential adoption rate.
Highlights
Current dairy research focuses on the development of technologies to detect health problems such as lameness, mastitis, and metabolic disorders [1] to improve farm profitability, animal health, and animal welfare
Potential adoption rates should be estimated in advance to design systems that are useful for the farmer, and commercially feasible [2]
A simulation of potential market shares could provide an insight into these effects, and could be performed based on a utility model describing the usefulness that farmers attach to different technologies with specific characteristics
Summary
Current dairy research focuses on the development of technologies to detect health problems such as lameness, mastitis, and metabolic disorders [1] to improve farm profitability, animal health, and animal welfare. Farmers’ preferences could be diverse for different types of technology and lead to different potential adoption rates. As emerging technologies are not yet used in practice, no real market shares are available to demonstrate the effect of alternating system performances or costs. A simulation of potential market shares could provide an insight into these effects, and could be performed based on a utility model describing the usefulness that farmers attach to different technologies with specific characteristics. Such a utility model can be constructed based on the choice behavior of farmers as explored using discrete choice experiments (DCE). Revealing the preferences of the end user could support a more focused development, as system developers know what farmers expect and can take these expectations into account during development
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