A Data-Driven Approach to High-Volume Recruitment: Application to Student Admission

Published Online:https://doi.org/10.1287/msom.2019.0779

References

  • Afifi A, May S, Clark VA (2011) Practical Multivariate Analysis (CRC Press, Boca Raton, FL).Google Scholar
  • Amemiya T (1973) Regression analysis when the dependent variable is truncated normal. Econometrica 41(6):997–1016.CrossrefGoogle Scholar
  • Arnold J, Silvester J, Patterson F, Robertson I, Cooper C, Burnes B (2004) Work Psychology: Understanding Human Behaviour in the Workplace, 4th ed. (Financial Times Prentice Hall, Harlow, UK).Google Scholar
  • Bessire & Associates, Inc. (2016) Four secrets to hiring hard-to-fill at volume. Accessed April 4, 2019, http://www.bessire.com/four-secrets-tfill-at-volume/.Google Scholar
  • Boudreau J, Hopp W, McClain J, Thomas L (2003) On the interface between operations and human resources management. Manufacturing Service Oper. Management 5(3):179–202.LinkGoogle Scholar
  • Cronbach LJ, Gleser GC (1965) Psychological Tests and Personnel Decisions (University of Illinois Press, Urbana).Google Scholar
  • De Corte W (1998) Estimating and maximizing the utility of sequential selection decisions with a probationary period. British J. Math. Statist. Psych. 51(1):101–121.CrossrefGoogle Scholar
  • De Corte W, Lievens F, Sackett PR (2006) Predicting adverse impact and mean criterion performance in multistage selection. J. Appl. Psych. 91(3):523–537.CrossrefGoogle Scholar
  • Feller W (1968) An Introduction to Probability Theory and Its Applications, vol. 1 (John Wiley & Sons, New York).Google Scholar
  • Feller W (1971) An Introduction to Probability Theory and Its Applications, vol. 2 (John Wiley & Sons, New York).Google Scholar
  • Hogan JW, Roy J, Korkontzelou C (2004) Handling drop-out in longitudinal studies. Statist. Medicine 23(9):1455–1497.CrossrefGoogle Scholar
  • Hosmer DW, Lemeshow S (1980) Goodness of fit tests for the multiple logistic regression model. Comm. Statist. Theory Methods 9(10):1043–1069.CrossrefGoogle Scholar
  • Johnson RA, Wichern DW (2014) Applied Multivariate Statistical Analysis (Prentice-Hall, Upper Saddle River, NJ).Google Scholar
  • Lim W (2001) Producer-supplier contracts with incomplete information. Management Sci. 47(5):709–715.LinkGoogle Scholar
  • Little R (1993) Pattern-mixture models for multivariate incomplete data. J. Amer. Statist. Assoc. 88(421):125–134.Google Scholar
  • Little R (1994) A class of pattern-mixture models for normal incomplete data. Biometrika 81(3):471–483.CrossrefGoogle Scholar
  • Little R (1995) Modeling the drop-out mechanism in repeated-measures studies. J. Amer. Statist. Assoc. 90(431):1112–1121.CrossrefGoogle Scholar
  • Little R, Rubin D (2002) Statistical Analysis with Missing Data (John Wiley & Sons, Hoboken, NJ).CrossrefGoogle Scholar
  • Mayer KJ, Nickerson JA, Owan H (2004) Are supply and plant inspections complements or substitutes? A strategic and operational assessment of inspection practices in biotechnology. Management Sci. 50(8):1064–1081.LinkGoogle Scholar
  • Patterson F, Barron H, Carr V, Plint S, Lane P (2009) Evaluation of three short-listing methodologies for selection into postgraduate training in general practice. Medical Ed. 43(1):50–57.CrossrefGoogle Scholar
  • Reyniers DJ, Tapiero CS (1995) The delivery and control of quality in supplier-producer contracts. Management Sci. 41(10):1581–1589.LinkGoogle Scholar
  • Robins JM, Rotnitzky A, Zhao L (1995) Analysis of semiparametric regression models for repeated outcomes in the presence of missing data. J. Amer. Statist. Assoc. 90(429):106–121.CrossrefGoogle Scholar
  • Tomlinson P, Krumwiede J (2009) Five “do”s for handling high-volume recruitment in a down economy. Report, Aon Consulting, Morristown, NJ.Google Scholar
  • White H (2014) Asymptotic Theory for Econometricians (Academic Press, Cambridge, MA).Google Scholar
  • Yano C, Lee H (1995) Lot-sizing with random yields: A review. Oper. Res. 43(2):311–334.LinkGoogle Scholar
  • Yao DD, Zheng S (2002) Dynamic Control of Quality in Production-Inventory Systems, Springer Series in Operations Research (Springer, Berlin).Google Scholar
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