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

Published Online:https://doi.org/10.1287/ited.2023.0037ca

References

  • AACSB (2020) Accreditation standards for business accreditation. AACSB. Accessed May 23, 2023, https://www.aacsb.edu/educators/accreditation/business-accreditation/aacsb-business-accreditation-standards.Google Scholar
  • Anand R, Winters MF (2008) A retrospective view of corporate diversity training from 1964 to the present. Acad. Management Learn. Ed. 7(3):356–372.CrossrefGoogle Scholar
  • Beal M, Wilson JH (2015) Forecasting in the marketing curriculum. Internat. J. Bus. Marketing Decision Sci. 8(1):109–115.Google Scholar
  • Bell MP, Connerley ML, Cocchiara FK (2009) The case for mandatory diversity education. Acad. Management Learn. Ed. 8(4):597–609.CrossrefGoogle Scholar
  • Brusco M (2022) Logistic regression via Excel spreadsheets: Mechanics, model selection, and relative predictor importance. INFORMS Trans. Ed. 23(1):1–11.LinkGoogle Scholar
  • Campbell K, Mínguez-Vera A (2008) Gender diversity in the boardroom and firm financial performance. J. Bus. Ethics 83(3):435–451.CrossrefGoogle Scholar
  • Carter D, D’Souza FP, Simkins BJ, Simpson WG (2007) The diversity of corporate board committees and firm financial performance. Preprint, submitted March 15, http://dx.doi.org/10.2139/ssrn.972763.Google Scholar
  • Chen Y, Albert LJ, Jensen S (2022) Innovation farm: Teaching artificial intelligence through gamified social entrepreneurship in an introductory MIS course. Decision Sci. J. Innovative Ed. 20(1):43–56.CrossrefGoogle Scholar
  • Chu S (2007) Some initiatives in a business forecasting course. J. Statist. Ed. 15(2):1–11.Google Scholar
  • David A, Coates V (2021) Representations of people of color and Hispanic people in business school teaching cases. Susan Bulkeley Butler Center for Leadership Excellence and ADVANCE Purdue Center for Faculty Success Working Paper Series No. 4(2):44–64, Purdue University, West Lafayette, IN.Google Scholar
  • Devine PG, Forscher PS, Austin AJ, Cox WT (2012) Long-term reduction in implicit race bias: A prejudice habit-breaking intervention. J. Experiment. Soc. Psych. 48(6):1267–1278.CrossrefGoogle Scholar
  • Diamant A (2024) Introducing prescriptive and predictive analytics to MBA students with Microsoft Excel. INFORMS Trans. Ed. 24(2):152–174.LinkGoogle Scholar
  • Emerson J (2017) Don’t give up on unconscious bias training-make it better. Harvard Bus. Rev. (April 28), https://hbr.org/2017/04/dont-give-up-on-unconscious-bias-training-make-it-better.Google Scholar
  • Gavirneni S (2008) Teaching the subjective aspect of forecasting through the use of basketball scores. Decision Sci. J. Innovative Ed. 6(1):187–195.CrossrefGoogle Scholar
  • Gel YR, O’Hara Hines RJ, Chen H, Noguchi K, Schoner V (2014) Developing and assessing e-learning techniques for teaching forecasting. J. Ed. Bus. 89(5):215–221.CrossrefGoogle Scholar
  • Hanke J, Weigand P (1994) What are business schools doing to educate forecasters? J. Bus. Forecasting 13(3):10.Google Scholar
  • Kros JF, Nadler SS (2008) Longitudinal regression forecasting using Excel. Marketing Ed. Rev. 18(3):67–81.CrossrefGoogle Scholar
  • Kros JF, Rowe WJ (2016) Business school forecasting for the real world. Lawrence KD, ed. Advances in Business and Management Forecasting, vol. 11 (Emerald Group Publishing Limited, Leeds, UK), 149–161.Google Scholar
  • Kulik CT, Roberson L (2008a) Common goals and golden opportunities: Evaluations of diversity education in academic and organizational settings. Acad. Management Learn. Ed. 7(3):309–331.CrossrefGoogle Scholar
  • Kulik CT, Roberson L (2008b) Diversity Initiative Effectiveness: What Organizations Can (and Cannot) Expect from Diversity Recruitment, Diversity Training, and Formal Mentoring Programs (Cambridge University Press, Cambridge, UK).Google Scholar
  • Layton RA, Loughry ML, Ohland MW, Ricco GD (2010) Design and validation of a web-based system for assigning members to teams using instructor-specified criteria. Adv. Engrg. Ed. 2(1):1–28.Google Scholar
  • Legaki NZ, Assimakopoulos V (2018) F-LauReLxp: A gameful learning experience in forecasting. GamiFIN Conf. 2018 (Pori, Finland), 1–10.Google Scholar
  • Leiter D (2023) Teaching forecasting without teaching methods. J. Political Sci. Ed. 19(2):185–194.CrossrefGoogle Scholar
  • Loomis DG, Cox JE Jr (2003) Principles for teaching economic forecasting. Internat. Rev. Econom. Ed. 2(1):69–79.CrossrefGoogle Scholar
  • Madva A (2017) Biased against debiasing: On the role of (institutionally sponsored) self-transformation in the struggle against prejudice. Ergo 4(6):145–179.Google Scholar
  • Noon M (2018) Pointless diversity training: Unconscious bias, new racism and agency. Work Employment Soc. 32(1):198–209.CrossrefGoogle Scholar
  • Pachamanova D, Tilson V, Dwyer-Matzky K (2022) Case article-machine learning, ethics, and change management: A data-driven approach to improving hospital observation unit operations. INFORMS Trans. Ed. 22(3):178–187.LinkGoogle Scholar
  • Robinson G, Dechant K (1997) Building a business case for diversity. Acad. Management Perspect. 11(3):21–31.CrossrefGoogle Scholar
  • Snider BR, Eliasson JB (2013) Beat the instructor: An introductory forecasting game. Decision Sci. J. Innovative Ed. 11(2):147–157.CrossrefGoogle Scholar
  • Torres C, Babo L, Mendonça J (2018) Engaging students to learn forecasting methods. Gómez Chova L, López Martínez A, Candel Torres I, eds. Proc. 10th Internat. Conf. Edu. New Learn. Tech. (ITED, Palma, Spain), 10337–10343.Google Scholar
  • Tropp L, Godsil R (2015) Overcoming implicit bias and racial anxiety. Psych. Today (January 23), https://www.psychologytoday.com/intl/blog/sound-science-sound-policy/201501/overcoming-implicit-bias-and-racial-anxiety.Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.