IDEAS home Printed from https://ideas.repec.org/p/ags/saea14/162422.html
   My bibliography  Save this paper

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

Author

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

Abstract

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
    DOI: 10.22004/ag.econ.162422
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/162422/files/SAEA%20BestWorst%20Final.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.162422?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Office of Health Economics, 2007. "The Economics of Health Care," For School 001490, Office of Health Economics.
    5. Lusk, Jayson L. & Briggeman, Brian C., 2008. "AJAE appendix for “Food Values”," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 91(1), pages 1-12, February.
    6. 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.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lai, John & Olynk Widmar, Nicole J. & Gunderson, Michael A. & Widmar, David A. & Ortega, David L., 2018. "Prioritization of farm success factors by commercial farm managers," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(6), July.
    2. Elizabeth S. Byrd & Nicole J. Olynk Widmar & Benjamin M. Gramig, 2018. "Presentation matters: Number of attributes presented impacts estimated preferences," Agribusiness, John Wiley & Sons, Ltd., vol. 34(2), pages 377-389, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Danny Campbell & Seda Erdem, 2015. "Position Bias in Best-worst Scaling Surveys: A Case Study on Trust in Institutions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(2), pages 526-545.
    2. Sackett, Hillary & Shupp, Robert & Tonsor, Glynn, 2016. "Differentiating “Sustainable” From “Organic” And “Local” Food Choices: Does Information About Certification Criteria Help Consumers?," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 4(3), pages 1-15, July.
    3. McKendree, Melissa G.S. & Tonsor, Glynn T. & Wolf, Christopher A., 2015. "Similarities and Differences of Animal Welfare Perceptions between U.S. Cow-Calf Producers and the Public," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205433, Agricultural and Applied Economics Association.
    4. Ward, Patrick S. & Ortega, David L. & Spielman, David J. & Singh, Vartika, 2014. "Heterogeneous Demand for Drought-Tolerant Rice: Evidence from Bihar, India," World Development, Elsevier, vol. 64(C), pages 125-139.
    5. Muunda, Emmanuel & Mtimet, Nadhem & Schneider, Franziska & Wanyoike, Francis & Dominguez-Salas, Paula & Alonso, Silvia, 2021. "Could the new dairy policy affect milk allocation to infants in Kenya? A best-worst scaling approach," Food Policy, Elsevier, vol. 101(C).
    6. 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.
    7. Erdem, Seda & Rigby, Dan, 2011. "Using Best Worst Scaling To Investigate Perceptions Of Control & Concern Over Food And Non-Food Risks," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108790, Agricultural Economics Society.
    8. Marti, Joachim, 2012. "A best–worst scaling survey of adolescents' level of concern for health and non-health consequences of smoking," Social Science & Medicine, Elsevier, vol. 75(1), pages 87-97.
    9. Soto, José R. & Adams, Damian C. & Escobedo, Francisco J., 2016. "Landowner attitudes and willingness to accept compensation from forest carbon offsets: Application of best–worst choice modeling in Florida USA," Forest Policy and Economics, Elsevier, vol. 63(C), pages 35-42.
    10. Sackett, Hillary M. & Shupp, Robert & Tonsor, Glynn, 2013. "Consumer Perceptions of Sustainable Farming Practices: A Best-Worst Scenario," Agricultural and Resource Economics Review, Cambridge University Press, vol. 42(2), pages 275-290, August.
    11. Sackett, Hillary M., 2011. "Consumer Perceptions of Sustainable Farming Practices: A Best-Worst Scenario," Graduate Research Master's Degree Plan B Papers 115966, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    12. Ortega, David L. & Hong, Soo Jeong & Olynk Widmar, Nicole J. & Wang, H. Holly & Wu, Laping, 2015. "Chinese aquaculture farmers’ value system and on-farm decision making," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 4(3), April.
    13. Soto, José & Escobedo, Francisco & Adams, Damian, 2016. "Public and Private Preferences for Urban Forest Ecosystem Services," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236232, Agricultural and Applied Economics Association.
    14. Kreye, Melissa M. & Adams, Damian C. & Escobedo, Francisco J. & Soto, José R., 2016. "Does policy process influence public values for forest-water resource protection in Florida?," Ecological Economics, Elsevier, vol. 129(C), pages 122-131.
    15. Glenk, Klaus & Eory, Vera & Colombo, Sergio & Barnes, Andrew, 2014. "Adoption of greenhouse gas mitigation in agriculture: An analysis of dairy farmers' perceptions and adoption behaviour," Ecological Economics, Elsevier, vol. 108(C), pages 49-58.
    16. Yoo, Hong Il & Doiron, Denise, 2013. "The use of alternative preference elicitation methods in complex discrete choice experiments," Journal of Health Economics, Elsevier, vol. 32(6), pages 1166-1179.
    17. Qingmeng Tong & Lu Zhang & Junbiao Zhang, 2017. "Evaluation of GHG Mitigation Measures in Rice Cropping and Effects of Farmer’s Characteristics: Evidence from Hubei, China," Sustainability, MDPI, vol. 9(6), pages 1-14, June.
    18. Wolf, Christopher A. & Tonsor, Glynn T., 2013. "Dairy Farmer Policy Preferences," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(2), pages 1-15, August.
    19. Costanigro, Marco & Deselnicu, Oana & Kroll, Stephan, 2012. "Truthful, Misguiding Labels: The Implications of Labeling Production Processes rather than their Outcomes," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124615, Agricultural and Applied Economics Association.
    20. Ortega, David L. & Wang, H. Holly & Wu, Laping & Hong, Soo Jeong, 2015. "Retail channel and consumer demand for food quality in China," China Economic Review, Elsevier, vol. 36(C), pages 359-366.

    More about this item

    Keywords

    Farm Management;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:saea14:162422. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/saeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.