Full Citation
Title: Proposal of a New Method to Classify Higher Education Institutions Instead of Rankings
Citation Type: Miscellaneous
Publication Year: 2016
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Abstract: Purpose The objective of this paper is to propose a new method for classifying higher education institutions that differs from traditional rankings. The proposed model segments colleges and universities based on like attributes and describes the groups according to their differentiating features. Research Method Data from several rankings publications was collected and simplified for analysis. Several observations (i.e. schools) were eliminated because they did not fit the sampling frame and/or did not include a sufficient amount of information. Duplicate variables (i.e. attributes) were also eliminated. First, exploratory factor analysis was applied to reduce the number of variables being examined. Second, cluster analysis was employed to segment the observations. Findings Exploratory factor analysis and cluster analysis revealed five clusters of schools based on seven main underlying factors. Several post-hoc analyses determined that the EFA and cluster models were stable. These analyses confirmed that the constructs measured are in fact distinct, as are the five generated clusters. Practical Implications The five-cluster model generated from this study has practical and beneficial applications for both higher education managers and prospective college students and their parents. The insights gained from the model can help colleges and universities more effectively target students in their marketing efforts, and prospective students and their parents can make better-informed decisions about college plans. Originality/Value This paper is the first to propose the use of EFA and cluster analysis to segment higher education institutions. The validity of traditional college rankings has been questioned in recent years, and the model proposed in this paper solves many of the inherent problems with conventional rankings.
Url: http://digitalcommons.otterbein.edu/cgi/viewcontent.cgi?article=1031&context=stu_dist
User Submitted?: No
Authors: Elam, Kate D
Publisher: Otterbein University
Data Collections: IPUMS USA
Topics: Education, Methodology and Data Collection
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