Strategic enrollment management in higher education: A multivariate and nonlinear optimization methodology to enroll the first-year class.
详细信息
文摘
Similar to the complexities of defining strategic purchasing or supply chain management, strategic enrollment management (SEM) has numerous perspectives. The literature review indicates that essential elements of SEM include environmental forces, factors of the SEM construct, and performance measures. These concepts extend the literature base and identify avenues for future research.;An in-depth case study was performed to develop a SEM decision support model. One critical aspect of SEM is to enroll an academically qualified, demographically diverse first year class at a reasonable cost and within budget. Once admitted, factors (i.e. gender, academic potential, ability to pay, location, etc.) must be considered in evaluating probability of enrollment. This research uses institutional admission data to build a two-phase decision support system: (1) A multivariate research model that predicts the probability of enrollment based on academic qualifications and student diversity predictors. (2) A non-linear mathematical model to help the institution determine the amount of financial aid to be awarded to help "shape" the first year class based on desired academic qualifications and study body characteristics.;These objectives were successfully achieved. The logistic regression model can be improved by studying the effect of additional predictor variables, which were identified in the literature but not available. Optimizing on student clusters of pre-determined dimensions (i.e. early application, location, need level and projected GPA level) has proved to be an awarding structure that closely meets the enrollment objectives of the college. The flexibility of the decision support model allows organizations to identify a variety of cluster demographics and objective functions.