IDEAS home Printed from https://ideas.repec.org/a/wly/agribz/v4y1988i1p91-103.html
   My bibliography  Save this article

Developing a marketing strategy for branded, low fat, fresh beef

Author

Listed:
  • Dale J. Menkhaus

    (Department of Agricultural Economics and Professor, Department of Animal Science, University of Wyoming, Laramie)

  • Glen D. Whipple

    (Department of Agricultural Economics and Professor, Department of Animal Science, University of Wyoming, Laramie)

  • Steven J. Torok

    (Department of Agricultural Economics and Professor, Department of Animal Science, University of Wyoming, Laramie)

  • Ray A. Field

    (Department of Agricultural Economics and Professor, Department of Animal Science, University of Wyoming, Laramie)

Abstract

The objective of this article is to report the results of a logistic regression analysis designed to identify factors which are important in influencing purchase and reorder decisions of a branded, low fat, fresh beef product. Health related factors and visual differences significantly influence the probabilities of reordering and purchasing, respectively.

Suggested Citation

  • Dale J. Menkhaus & Glen D. Whipple & Steven J. Torok & Ray A. Field, 1988. "Developing a marketing strategy for branded, low fat, fresh beef," Agribusiness, John Wiley & Sons, Ltd., vol. 4(1), pages 91-103.
    • Handle: RePEc:wly:agribz:v:4:y:1988:i:1:p:91-103
    DOI: 10.1002/1520-6297(198801)4:1<91::AID-AGR2720040110>3.0.CO;2-Z
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Rhonda K. Skaggs & Dale J. Menkhaus & Steven J. Torok & Ray A. Field, 1987. "Test marketing of branded, low fat, fresh beef," Agribusiness, John Wiley & Sons, Ltd., vol. 3(3), pages 257-271.
    2. Collins, Robert A. & Green, Richard D., 1982. "Statistical methods for bankruptcy forecasting," Journal of Economics and Business, Elsevier, vol. 34(4), pages 349-354.
    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. Siskos, Y. & Matsatsinis, N. F. & Baourakis, G., 2001. "Multicriteria analysis in agricultural marketing: The case of French olive oil market," European Journal of Operational Research, Elsevier, vol. 130(2), pages 315-331, April.

    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. Nabeel Al-Milli & Amjad Hudaib & Nadim Obeid, 2021. "Population Diversity Control of Genetic Algorithm Using a Novel Injection Method for Bankruptcy Prediction Problem," Mathematics, MDPI, vol. 9(8), pages 1-18, April.
    2. Dale J. Menkhaus & Glen D. Whipple & Ray A. Field & Shawn W. Moore, 1988. "Impact of a price premium on sales of branded, low fat, fresh beef," Agribusiness, John Wiley & Sons, Ltd., vol. 4(6), pages 521-534.
    3. Kaylen, Michael S. & Devino, Gary T. & Procter, Michael H., 1988. "Optimal Use Of Qualitative Models: An Application To Country Grain Elevator Bankruptcies," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 20(2), pages 1-7, December.
    4. Golaszewski, Richard & Sanders, Matthew, 1991. "Financial Stress in the U.S. Airline Industry," Transportation Research Forum Proceedings 1990s 319097, Transportation Research Forum.
    5. Harper, Susan D. & Wharton, B. Robert & Traylor, Harlon D., 1985. "A Prediction Of Grain Elevator Bankruptcies Using Linear Discriminant Analysis," 1985 Annual Meeting, August 4-7, Ames, Iowa 278559, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Tamara Ayœs, Armando Lenin & Villegas, Gladis Cecilia & Leones Castro, María Cristina & Salazar Bocanegra, Juan Antonio, 2018. "Modelaci—n del riesgo de insolvencia en empresas del sector salud empleando modelos logit || Modeling of Insolvency Risk in Health Sector Companies Using Logit Models," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 128-145, Diciembre.
    7. Gemünden, Hans Georg, 1988. "Defekte der empirischen Insolvenzforschung," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 205, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    8. Haider A. Khan, 2002. "Can Banks Learn to Be Rational?," CIRJE F-Series CIRJE-F-151, CIRJE, Faculty of Economics, University of Tokyo.
    9. Sueyoshi, Toshiyuki & Goto, Mika, 2009. "Methodological comparison between DEA (data envelopment analysis) and DEA-DA (discriminant analysis) from the perspective of bankruptcy assessment," European Journal of Operational Research, Elsevier, vol. 199(2), pages 561-575, December.
    10. Khojasteh, Khosrow, 1992. "Effects of farm characteristics and government disaster assistance on multiple-peril crop insurance purchases by Iowa crop farmers," ISU General Staff Papers 1992010108000010841, Iowa State University, Department of Economics.
    11. Sueyoshi, Toshiyuki & Goto, Mika, 2009. "DEA-DA for bankruptcy-based performance assessment: Misclassification analysis of Japanese construction industry," European Journal of Operational Research, Elsevier, vol. 199(2), pages 576-594, December.
    12. Moutou, Christele & Brester, Gary W., 1998. "Trends In U.S. Wheat-Based Food Consumption: Nutrition, Convenience, And Ethnic Foods," Journal of Food Distribution Research, Food Distribution Research Society, vol. 29(2), pages 1-14, July.
    13. Moshe Leshno & Yishay Spector, 1997. "The effect of training data set size and the complexity of the separation function on neural network classification capability: The two‐group case," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(8), pages 699-717, December.
    14. Capps, Oral, Jr. & Schmitz, John D., 1991. "A Recognition Of Health And Nutrition Factors In Food Demand Analysis," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 16(1), pages 1-15, July.
    15. Goss, Jody & Holcomb, Rodney B. & Ward, Clement E., 2002. "Factors Influencing Consumer Decisions Related To "Natural" Beef In The Southern Plains," Journal of Food Distribution Research, Food Distribution Research Society, vol. 33(1), pages 1-12, March.
    16. Mohammad Mahdi Mousavi & Jamal Ouenniche, 2018. "Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions," Annals of Operations Research, Springer, vol. 271(2), pages 853-886, December.
    17. Yuan, Yan & Capps, Oral, Jr. & Nayga, Rodolfo M., Jr., 2009. "Assessing the Demand for a Functional Food Product: Is There Cannibalization in the Orange Juice Category?," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 38(2), pages 1-13, October.
    18. Haider A. Khan, 2004. "General Conclusions: From Crisis to a Global Political Economy of Freedom," Palgrave Macmillan Books, in: Global Markets and Financial Crises in Asia, chapter 9, pages 193-211, Palgrave Macmillan.
    19. Premachandra, I.M. & Chen, Yao & Watson, John, 2011. "DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment," Omega, Elsevier, vol. 39(6), pages 620-626, December.
    20. Chen, Liang-Hsuan & Chiou, Tai-Wei, 1999. "A fuzzy credit-rating approach for commercial loans: a Taiwan case," Omega, Elsevier, vol. 27(4), pages 407-419, August.

    More about this item

    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:wly:agribz:v:4:y:1988:i:1:p:91-103. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1520-6297 .

    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.