Modeling college faculty users’ potential acceptance of library data services for research and teaching
Abstract
Purpose
The increasingly active data practice in academic environments makes investigating college faculty users’ potential needs for library data services (LDS) essential. Guided by a conceptual framework rooted in the data lifecycle and the extended technology acceptance model, this study aims to investigate the relationship between faculty’s data engagement (DE) and their attitudes toward multiaspect LDS.
Design/methodology/approach
An online survey at a master’s college was conducted to collect data regarding faculty data practice, potential needs for data services (DS) and attitudes toward multiaspect LDS. Based on 139 complete and valid responses, the study built three conceptual models to demonstrate faculty users’ potential acceptance of LDS for research and teaching.
Findings
Participants’ research and teaching-related DE and background factors directly or indirectly affect their attitudes toward general DS, an institutional data repository if available and repository-based data curation.
Originality/value
The study contributes to DS and librarianship research by offering three conceptual models to explore LDS’ holistic support for faculty research and teaching. Moreover, the study provides insights into faculty’s job-related DE factors and calls for future research on effective DS in more college communities.
Keywords
Acknowledgements
The author would like to sincerely thank Dr Dwayne M. Baker, Dr Hongwei Xu, Alexandra de Luise, librarian, retired, and other anonymous experts who helped with of the research the questionnaire examination of the research. She must also thank the survey respondents for their time and participation in this study. The author wishes to thank all anonymous reviewers for their insightful comments and suggestions for improving this article. The author would also like to express her special thanks to Brett Spencer, Research Librarian, Penn State Berks and other anonymous experts for their invaluable reviews and edits to enhance the quality of this article.
Declaration of competing interest: the author declares that no known competing financial interest could have appeared to influence the work reported in this article.
Data availability: according to the Institutional Review Board (IRB) approval, the anonymized data supporting the research are available upon reasonable request from the corresponding author.
Conflict of interest: Author have no known conflict of interest to disclose.
Citation
Xu, Q. (2024), "Modeling college faculty users’ potential acceptance of library data services for research and teaching", Information Discovery and Delivery, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IDD-10-2023-0115
Publisher
:Emerald Publishing Limited
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