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May 18, 2026Higher Education Quarterly0 citations

An Integrated Statistical Methodology Approach to Enrollment Management

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DNDavid NickellBSBeheruz N. Sethna

Key Points

  • This research aims to develop an evidence-based framework for higher education enrollment management by understanding decision-making processes.
  • Surveyed 948 students and 990 parents to gather data.
  • Employed conjoint analysis, factor analysis, and cluster segmentation to analyze responses.
  • Identified key institutional choice drivers and student segments.
  • Found that academic reputation is the most influential factor in enrollment decisions.
  • Revealed three main constructs influencing decisions: Reputation, Recommendation, and Fit.
  • Developed a data-driven model for improving recruitment strategies.

Abstract

ABSTRACT This study examines the decision‐making processes of prospective students and parents to establish an evidence‐based framework for higher education enrollment management. Utilizing a survey of 948 students and 990 parents, the research employs conjoint analysis, factor analysis, and cluster segmentation to identify key institutional choice drivers. Findings reveal that while academic reputation is the most influential attribute, decisions are primarily shaped by three latent constructs: Reputation, Recommendation, and Fit. This paper makes a substantive contribution by operationalizing market orientation through advanced analytics, revealing heterogeneous student segments with distinct motivational profiles. These insights provide university administrators with actionable diagnostics for resource allocation and targeted messaging. Ultimately, the study bridges theoretical understanding and practical application, offering a robust, data‐driven model for improving competitive positioning and recruitment outcomes within the increasingly complex higher education landscape.

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Cite This Study

Nickell et al. (2026) studied this question.

synapsesocial.com/papers/6a0aad5c5ba8ef6d83b70ccdhttps://doi.org/10.1111/hequ.70138
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