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Understanding Producer Strategies: Identifying Key Success Factors of Commercial Farms in 2013


  • Holland, Jacqueline K.
  • Olynk Widmar, Nicole J.
  • Widmar, David A.
  • Ortega, David L.
  • Gunderson, Michael A.


Farm management is a series of complex processes incorporating a variety of dynamic factors, including biological aspects, resource allocation and management, and the management of increasingly complex financial/economic systems, which managers are constantly asked to prioritize and allocate management effort amongst. This work determines which success factors, from five predetermined factors (managing production; managing land, equipment, and facilities; controlling costs; managing output prices; and managing people) commercial producers identified as most important for the success of their operation. A total of 28.6 % of respondents selected controlling costs and 27.3% selected managing production as most important factors. From producer-specific estimates of a mixed logit model, correlations between the success factors were estimated; the strongest correlation observed was the negative relationship between managing production and controlling costs. Implications for self-identified success factors of commercial agricultural producers are far reaching, potentially influencing sales, marketing, and decision support for these operations, as well as driving research and programmatic focus to provide relevant information to these producers moving forward.

Suggested Citation

  • Holland, Jacqueline K. & Olynk Widmar, Nicole J. & Widmar, David A. & Ortega, David L. & Gunderson, Michael A., 2014. "Understanding Producer Strategies: Identifying Key Success Factors of Commercial Farms in 2013," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162422, Southern Agricultural Economics Association.
  • Handle: RePEc:ags:saea14:162422

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    References listed on IDEAS

    1. Lusk, Jayson L. & Briggeman, Brian C., 2009. "AJAE appendix for “Food Valuesâ€," American Journal of Agricultural Economics Appendices, Agricultural and Applied Economics Association, vol. 91(1), February.
    2. Jayson L. Lusk & Brian C. Briggeman, 2009. "Food Values," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 184-196.
    3. Erdem, Seda & Rigby, Dan & Wossink, Ada, 2012. "Using best–worst scaling to explore perceptions of relative responsibility for ensuring food safety," Food Policy, Elsevier, vol. 37(6), pages 661-670.
    4. Flynn, Terry N. & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2007. "Best-worst scaling: What it can do for health care research and how to do it," Journal of Health Economics, Elsevier, vol. 26(1), pages 171-189, January.
    5. Ortega, David L. & Wang, H. Holly & Olynk Widmar, Nicole J. & Wu, Laping, 2014. "Reprint of “Chinese producer behavior: Aquaculture farmers in southern China”," China Economic Review, Elsevier, vol. 30(C), pages 540-547.
    6. Ortega, David L. & Wang, H. Holly & Olynk Widmar, Nicole J. & Wu, Laping, 2014. "Chinese producer behavior: Aquaculture farmers in southern China," China Economic Review, Elsevier, vol. 28(C), pages 17-24.
    7. Nicole J. Olynk & Christopher A. Wolf & Glynn T. Tonsor, 2012. "Production technology option value: the case of rbST in Michigan," Agricultural Economics, International Association of Agricultural Economists, vol. 43, pages 1-9, November.
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    More about this item


    Farm Management; Success; Best Worst; Modeling; Correlations; Choice Experiment; Farm Management; Q12; C25;

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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