Data Scientist Texas A&M University, United States
Session Abstract: This study investigates drivers of noninstructional staffing at American Association of Universities (AAU) institutions amid growing concerns about administrative expenditures and efficiency (Briody et al., 2021; McClure & Titus, 2018). Guided by Bowen’s Revenue Theory of Costs (Bowen, 1980), Neo-Institutional Theory (DiMaggio & Powell, 1983), and Organizational Contingency Theory (Donaldson, 2001), elastic net regression explained 97% of staffing variation and revealed distinct public–private patterns. Findings identified institutions over- or understaffed relative to predicted benchmarks. For institutional research professionals, this study offers a replicable, theory-driven framework for benchmarking staffing efficiency and supporting evidence-based resource allocation. Participants will gain insight into predictors of staffing, learn how penalized regression strengthens benchmarking, and engage in interactive exercises to connect results to their local practice.
Keywords: higher education, administrative staffing, elastic net regression, staffing efficiency