US academic libraries' staffing and expenditure trends (1996–2016). Issue 4 (3rd June 2020)

• Record Type: Journal Article
• Authors: Hoffman, Starr; Godbey, Samantha
• Is Part Of: Library management. Volume 41:Issue 4/5(2020)
• Page Start: 247
• Page End: 268
• Publication Date: 2020-06-03
• Subjects: Academic libraries -- Quantitative -- Expenditures -- Academic libraries survey -- IPEDS -- Library staffing; Library administration -- Periodicals; 025.005
• DOI: 10.1108/LM-12-2019-0093
• Languages: English
• ISSNs: 0143-5124

Abstract

Abstract : Purpose: This paper explores trends over time in library staffing and staffing expenditures among two- and four-year colleges and universities in the United States. Design/methodology/approach: Researchers merged and analyzed data from 1996 to 2016 from the National Center for Education Statistics for over 3, 500 libraries at postsecondary institutions. This study is primarily descriptive in nature and addresses the research questions: How do staffing trends in academic libraries over this period of time relate to Carnegie classification and institution size? How do trends in library staffing expenditures over this period of time correspond to these same variables? Findings: Across all institutions, on average, total library staff decreased from 1998 to 2012. Numbers of librarians declined at master's and doctoral institutions between 1998 and 2016. Numbers of students per librarian increased over time in each Carnegie and size category. Average inflation-adjusted staffing expenditures have remained steady for master's, baccalaureate and associate's institutions. Salaries as a percent of library budget decreased only among doctoral institutions and institutions with 20, 000 or more students. Originality/value: This is a valuable study of trends over time, which has been difficult without downloading and merging separate data sets from multiple government sources. As a result, few studies have taken such an approach to this data. Consequently, institutions and libraries are making decisions about resource allocation based on only a fraction of the available data. Academic libraries can use this study and the resulting data set to benchmark key staffing characteristics.