Higher Education Pricing: Effects of Tuition Pricing on Nontraditional Student Persistence Moderated by Demographics

Higher education pricing models have focused heavily on traditional student population analysis, net earnings, financial aid, and enrollment projections or unduplicated headcount. As the population of students shifts to a nontraditional majority, research of the effect of tuition price on nontraditional population segments is needed with a focus on persistence (the likelihood of re-enrollment in the next semester for a given student) rather than overall enrollment levels. It becomes prudent to re-evaluate pricing models and the associated coefficients from tuition pricing changes on persistence to more effectively serve the nontraditional population as nontraditional students rely less on financial aid and progress through their curriculum at an individualized pace consistent with their needs. The nontraditional population is, on average, older, with more professional experience, often with military affiliations (active duty, veteran, reservist, or family member), and education in progress. Using a quantitative longitudinal empirical case study, the researcher utilized student-level data from a private, nonprofit university in the Commission on Colleges of the Southern Association of Colleges and Schools regional accreditation territory to determine the effect of a tuition increase on nontraditional student (age 25 ) persistence. The data was analyzed using a linear regression interaction model in STATA. The researcher found statistical significance, with the counterintuitive finding that the effect of a 1 percent tuition increase for all students was an increase in persistence by 2.01 percent with a clear explanation for this finding of the overall tuition effect on persistence. Consistent with theory, this research finds that nontraditional students only increased their persistence by 0.62 percent, persisting less than traditional students. For every 1 percent increase in tuition, nontraditional online students are decreasing their persistence by 0.9 percent, persisting less than face-to-face students. These findings are important, as they provide contributions to Elasticity Theory, Tuition Elasticity Theory, and practice including application for higher education institutions, administrators and advisors in higher education, and customer relationship management software as service companies targeting students utilizing variations of predictive analytics to estimate persistence of different populations, estimate and understand tuition price increase effects on different populations, set recruiting and enrollment goals based upon expected attrition, and design customized communication plans to facilitate more in-depth relationships with those less likely to persist in an effort to overcome this statistic. These findings are also the first portion of exploring elasticities as they apply toward developing a pricing model for nontraditional student populations using the framework established by the TENEP model (Bryan & Whipple, 1995).