Four Categories of Academic Libraries: A Cluster Analysis Based on Collections, Expenditures, and Circulation per Student Data. Issue 3 (1st October 2017)

• Record Type: Journal Article
• Authors: Lund, Brady D.
• Is Part Of: Library collections, acquisitions & technical services. Volume 40:Issue 3/4(2017)
• Page Start: 96
• Page End: 105
• Publication Date: 2017-10-01
• Subjects: library collections -- library expenditures -- circulation -- academic libraries -- cluster analysis -- machine learning -- data mining -- university libraries -- collections data -- user data -- spending -- finances -- faculty; Acquisitions (Libraries) -- Periodicals; Collection management (Libraries) -- Periodicals; Technical services (Libraries) -- Periodicals; Library Collection Development; Library technical services; Acquisitions (Bibliothèques) -- Publications en série; Gestion des collections (Bibliothèques) -- Périodiques; Traitement (Bibliothèques) -- Périodiques; Electronic journals; Periodicals; 025.2
• DOI: 10.1080/14649055.2020.1794748
• Languages: English
• ISSNs: 1464-9055

Abstract

Abstract: The purpose of this study is to determine whether hidden categories of academic libraries exist based on collections, circulations, and expenditures per student. This study utilizes k-means clustering analysis to identify categories of academic libraries based on three variables: number of library resources per enrolled students, library circulation per enrolled student, and library expenditures per enrolled student. Four distinct clusters are identified: high circulation per student, high expenditures per student, large collections per student, and standard circulation, expenditures, and collections. Attributes of these clusters of libraries (institution type, university endowment, year established) are explored. These findings indicate new means of classifying libraries based on funding and use statistics as opposed to characteristics of the institution of higher education which the library serves.