IDEAS home Printed from https://ideas.repec.org/a/ags/jlofdr/26766.html
   My bibliography  Save this article

Retail Meat Feature Pricing: Enhancing Meat-Case Revenues?

Author

Listed:
  • Pritchett, James G.
  • Johnson, Kamina K.

Abstract

Retail meat managers have many pricing tools to encourage product purchase, including the feature price, syndicate price, and the percent discount. Given seasonal demands and a large, diverse set of meat cuts, meat managers may form strategic pricing groups when choosing the feature-price, syndicate-price, and percent-discount levels. This research inductively determines these groups using a principal-components method and examines the role feature pricing plays in determining the volume sold and syndicate price. Seemingly unrelated regression (SUR) models are used to simultaneously estimate the impacts of featuring strategy decisions among cluster groups.

Suggested Citation

  • Pritchett, James G. & Johnson, Kamina K., 2005. "Retail Meat Feature Pricing: Enhancing Meat-Case Revenues?," Journal of Food Distribution Research, Food Distribution Research Society, vol. 36(1), pages 1-7, March.
    • Handle: RePEc:ags:jlofdr:26766
    DOI: 10.22004/ag.econ.26766
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/26766/files/36010144.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.26766?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. Dillon, William R & Mulani, Narendra & Frederick, Donald G, 1989. "On the Use of Component Scores in the Presence of Group Structure," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(1), pages 106-112, June.
    Full references (including those not matched with items on IDEAS)

    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. Tai, Chung-Ching & Lin, Hung-Wen & Chie, Bin-Tzong & Tung, Chen-Yuan, 2019. "Predicting the failures of prediction markets: A procedure of decision making using classification models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 297-312.
    2. Robert Kapłon, 2006. "A retrospective review of categorical data analysis – theory and marketing practice," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(1), pages 55-72.
    3. Zhiliang Ma & Adam Cardinal-Stakenas & Youngser Park & Michael Trosset & Carey Priebe, 2010. "Dimensionality Reduction on the Cartesian Product of Embeddings of Multiple Dissimilarity Matrices," Journal of Classification, Springer;The Classification Society, vol. 27(3), pages 307-321, November.
    4. Mitra, Suman & Yao, Mingqi & Ritchie, Stephen G., 2021. "Gender differences in elderly mobility in the United States," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 203-226.
    5. Maria Warne & Kristen Snyder & Katja Gådin, 2014. "Adaptation and Validation of a Positive Health Scale for Adolescents," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 119(2), pages 1079-1093, November.
    6. Pankaj Patel & Sherry Thatcher & Katerina Bezrukova, 2013. "Organizationally-relevant configurations: the value of modeling local dependence," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 287-311, January.
    7. Gould, Stephen J. & Oakes, Leslie S. & Considine, Judith M., 1997. "Profiling pharmaceutical allergy medications by symptoms and their relief: A study of consumer perceptions," Journal of Business Research, Elsevier, vol. 40(3), pages 199-206, November.
    8. A. Oumlil & Joseph Balloun, 1994. "Some simple structure significance tests for exploratory component analysis with market survey data," Quality & Quantity: International Journal of Methodology, Springer, vol. 28(4), pages 371-381, November.

    More about this item

    Keywords

    Demand and Price Analysis;

    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:jlofdr:26766. 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/fdrssea.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.