Analyzing the Relationship between Citation-Based Impact Metrics and Electronic Journal Usage: A Case Study

Abstract

This study examines the relationship between Journal Impact Factors (JIF) and e-journal usage in collection management. We focus on the impact of major JIFs on local e-journal usage and propose an alternative approach to conventional methods for collection selectors. By treating journal usage patterns as panel data and employing fixed-effects regression models, we find that journal popularity has the greatest influence on local e-journal usage and the effects of impact factors on academic article usage can vary across different disciplines. The methodology and findings of our study offer valuable insights and practical implications for academic librarians overseeing collection development.

Keywords:

• Journal impact factor
• JCR
• SNIP
• SJR
• collection assessment
• statistical analysis
• e-journal usage

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The descriptive statistics, correlation analysis, and fixed effect analysis were conducted using Stata SE 17.0.

2 Scopus Subject Areas and All Science Journal Classification Codes (ASJC): https://service.elsevier.com/app/answers/detail/a_id/14882/supporthub/scopus/∼/what-are-the-most-frequent-subject-area-categories-and-classifications-used-in/, accessed on January 4, 2022.

3 Journal Citation Reports: Average Journal Impact Factor Percentile, https://support.clarivate.com/ScientificandAcademicResearch/s/article/Journal-Citation-Reports-Average-Journal-Impact-Factor-Percentile?language=en_US, accessed on January 4, 2022.