Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
An Analysis of Artificial Intelligence (AI) Capability in Libraries and Archives
0
Zitationen
2
Autoren
2025
Jahr
Abstract
This paper seeks to evaluate the AI capability of libraries and archives using a qualitative content analysis of 54 case studies of AI uses published between 2018 and 2024. It is framed by the model of AI capability proposed by Mikalef and Gupta (Patrick Mikalef and Manjul Gupta, ‘Artificial Intelligence Capability: Conceptualization, Measurement Calibration, and Empirical Study on Its Impact on Organizational Creativity and Firm Performance’, Information & Management 58, no. 3 (2021): 103434.). The findings of the analysis largely confirm the model, but suggest that there are many gaps in library and archive AI capability, especially in areas such as infrastructure and technical resources, data issues arising from metadata inconsistencies, and financial resources.
Ähnliche Arbeiten
The Coding Manual for Qualitative Researchers
2025 · 17.907 Zit.
Research methods for business: A skill building approach
1993 · 17.079 Zit.
The NIST definition of cloud computing
2011 · 11.605 Zit.
The DeLone and McLean Model of Information Systems Success: A Ten-Year Update
2003 · 11.267 Zit.
Introduction to Information Retrieval
2008 · 10.793 Zit.