IDEAS home Printed from https://ideas.repec.org/a/inm/orited/v25y2025i3p203-206.html

Case Article–Forecasting at FoodMart: A Case on Cultural Diversity in Supply Chain Management

Author

Listed:
  • Amy David

    (Mitchell E. Daniels School of Business, Purdue University, West Lafayette, Indiana 47907)

Abstract

This case focuses on forecasting a number of grocery items from the perspective of a demand planner who notices that the items have irregular patterns in the seasonality of their historical sales. It introduces students to the need for diverse cultural knowledge in forecasting certain consumer products and provides instructors with a starting point for discussing the business case for diversity and the value of diverse teams in a supply chain management context. This case is recommended for use in an undergraduate-level course in supply chain management, operations management, or business analytics. Learning goals are for students to identify irregular patterns in historical sales data and determine their root causes, evaluate a statistical forecast created without human intervention, and explain how culturally diverse teams can be valuable in a forecasting process.

Suggested Citation

  • Amy David, 2025. "Case Article–Forecasting at FoodMart: A Case on Cultural Diversity in Supply Chain Management," INFORMS Transactions on Education, INFORMS, vol. 25(3), pages 203-206, May.
    • Handle: RePEc:inm:orited:v:25:y:2025:i:3:p:203-206
    DOI: 10.1287/ited.2023.0037ca
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/ited.2023.0037ca
    Download Restriction: no
    File URL: https://libkey.io/10.1287/ited.2023.0037ca?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. David G. Loomis & James E. Cox, Jr., 2003. "Principles for Teaching Economic Forecasting," International Review of Economic Education, Economics Network, University of Bristol, vol. 2(1), pages 69-79.
    2. Michael Brusco, 2022. "Logistic Regression via Excel Spreadsheets: Mechanics, Model Selection, and Relative Predictor Importance," INFORMS Transactions on Education, INFORMS, vol. 23(1), pages 1-11, September.
    3. Dessislava Pachamanova & Vera Tilson & Keely Dwyer-Matzky, 2022. "Case Article—Machine Learning, Ethics, and Change Management: A Data-Driven Approach to Improving Hospital Observation Unit Operations," INFORMS Transactions on Education, INFORMS, vol. 22(3), pages 178-187, May.
    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. Vahid Roshanaei & Bahman Naderi & Opher Baron & Dmitry Krass, 2024. "An Interactive Spreadsheet Model for Teaching Classification Using Logistic Regression," INFORMS Transactions on Education, INFORMS, vol. 25(1), pages 55-80, September.
    2. Dean Garratt & Rebecca Taylor, 2004. "Issue-based teaching in economics," Working Papers 2004/2, Nottingham Trent University, Nottingham Business School, Economics Division.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:inm:orited:v:25:y:2025:i:3:p:203-206. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.