Performance-based evaluation of academic libraries in the big data era

Author:

Islam A Y M Atiquil1ORCID,Ahmad Khurshid2ORCID,Rafi Muhammad3ORCID,JianMing Zheng3

Affiliation:

1. Faculty of Education, Department of Education Information Technology, East China Normal University, Shanghai, China

2. Department of Library and Information Science, The Islamia University of Bahawalpur, Pakistan; Nanjing University, China

3. School of Information Management, Nanjing University, China

Abstract

The concept of big data has been extensively considered as a technological modernisation in organisations and educational institutes. Thus, the purpose of this study is to determine whether the modified technology acceptance model (MTAM) is viable for evaluating the performance of librarians in the use of big data analytics in academic libraries. This study used an empirical research method for collecting data from 211 librarians working in Pakistan’s universities. On the basis of the findings of the MTAM analysis by structural equation modelling, the performances of the academic libraries were comprehended through the process of big data. The main influential components of the performance analysis in this study were the big data analytics capabilities, perceived ease of access and the usefulness of big data practices in academic libraries. Subsequently, the utilisation of big data was significantly affected by skills, perceived ease of access and the usefulness of academic libraries. The results also suggested that the various components of the academic libraries lead to effective organisational performance when linked to big data analytics.

Funder

Peak Discipline Construction Project of Education at East China Normal University

Publisher

SAGE Publications

Subject

Library and Information Sciences,Information Systems

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