Understanding farmers’ preferences for artificial insemination services provided through dairy hubs

Africa has a shortage of animal products but increasing demand because of population growth, urbanisation and changing consumer patterns. Attempts to boost livestock production through the use of breeding technologies such as artificial insemination (AI) have been failing in many countries because costs have escalated and success rates have been relatively low. One example is Kenya, a country with a relatively large number of cows and a dairy industry model relevant to neighbouring countries. There, an innovative dairy marketing approach (farmer-owned collective marketing systems called dairy hubs) has been implemented to enhance access to dairy markets and dairy-related services, including breeding services such as AI. So far, the rate of participation in these dairy hubs has been slow and mixed. In order to understand this phenomenon better and to inform dairy-related development activities by the Kenyan government, we investigated which characteristics of AI services, offered through the dairy hubs, farmers prefer. To do so, we applied a choice experiment (CE), a non-market valuation technique, which allowed us to identify farmers’ preferences for desired characteristics should more dairy hubs be installed in the future. This is the first study to use a CE to evaluate breeding services in Kenya and the results can complement findings of studies of breeding objectives and selection criteria. The results of the CE reveal that dairy farmers prefer to have AI services offered rather than having no service. Farmers prefer AI services to be available at dairy hubs rather than provided by private agents not affiliated to the hubs, to have follow-up services for pregnancy detections, and to use sexed semen rather than conventional semen. Farmers would further like some flexibility in payment systems which include input credit, and are willing to share the costs of any AI repeats that may need to occur. These results provide evidence of a positive attitude to AI services provided through the hubs, which could mean that AI uptake would improve if service characteristics are improved to match farmer preferences. The dairy hubs concept is currently in the implementation phase with most hubs at startup phase, hence understanding which AI service characteristics farmers prefer can inform the design of high-quality and cost-effective AI services in the future.