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Factors Affecting Farmers’ Adoption of Agricultural Innovations: A Panel Data Analysis of the Use of Artificial Insemination among Dairy Farmers in Ireland

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  • Peter Howley
  • Cathal O. Donoghue
  • Kevin Heanue

Abstract

The use of artificial insemination (AI) has been of enormous economic benefit for dairy farmers in many countries such as Ireland through the genetic improvement of their stock. Despite these benefits a significant proportion of dairy farmers continue to use natural mating over AI. Previous research has found that the cost of semen, the cost of insemination and success rate all affect the probability of farmers using AI. Using a nationally representative panel dataset, this paper examined if there were any farm or farmer characteristics that affected the probability of dairy farmers using AI. Modelling the farm factors driving the uptake of AI enables the understanding of the differences between various types of landowners which should in turn better equip policymakers to design policies and programs that efficiently promote good reproductive management. The results in this paper suggest that there is significant heterogeneity among farm households in relation to the uptake of AI with both characteristics of the farmer as well as structural farm factors all found to significantly affect the probability of a farmer adopting this agricultural innovation.

Suggested Citation

  • Peter Howley & Cathal O. Donoghue & Kevin Heanue, 2012. "Factors Affecting Farmers’ Adoption of Agricultural Innovations: A Panel Data Analysis of the Use of Artificial Insemination among Dairy Farmers in Ireland," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 4(6), pages 171-171, April.
    • Handle: RePEc:ibn:jasjnl:v:4:y:2012:i:6:p:171
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    References listed on IDEAS

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    1. Adesina, Akinwumi A. & Zinnah, Moses M., 1993. "Technology characteristics, farmers' perceptions and adoption decisions: A Tobit model application in Sierra Leone," Agricultural Economics, Blackwell, vol. 9(4), pages 297-311, December.
    2. Batz, F. -J. & Peters, K. J. & Janssen, W., 1999. "The influence of technology characteristics on the rate and speed of adoption," Agricultural Economics, Blackwell, vol. 21(2), pages 121-130, October.
    3. Akinwumi A. Adesina & Moses M. Zinnah, 1993. "Technology characteristics, farmers' perceptions and adoption decisions: A Tobit model application in Sierra Leone," Agricultural Economics, International Association of Agricultural Economists, vol. 9(4), pages 297-311, December.
    4. F.‐J. Batz & K.J. Peters & W. Janssen, 1999. "The influence of technology characteristics on the rate and speed of adoption," Agricultural Economics, International Association of Agricultural Economists, vol. 21(2), pages 121-130, October.
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    1. Seth Ooko Onyango & Sabina Mukoya-Wangia & Josiah Mwivandi Kinama & Pamela Akinyi Olet, 2024. "Integration of Tsetse Fly and Trypanosomiasis Control Methods From Livestock Farmers’ Perspective: A Multivariate Probit Approach," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 12(10), pages 1-67, April.

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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