Performance based assessment of LIS professionals toward digital data sets management in university libraries: A TAM model approach

Abstract

In recent times, computer systems have acquired the capacity to gather, process and analyze massive quantities of data, as well as techniques for distributing, transmitting, and computing estimates. Therefore, the study is conducted with an objective to ascertain the performance-based assessment of LIS professionals toward digital data sets management DDSM in university libraries. A six-factor measurement model was tested based on the 28-valid items obtained from the literature. The hypothesized research model was validated through the application of confirmatory factor analysis (CFA), and structural equation modeling (SEM) technique. LIS professionals in research-oriented organizations possess the necessary data analytical skills and technical expertise to extract insights from the data. The findings indicated that analytical skills have a significant positive impact on PEOU (β =246, SE = 0.54, p < 0.000). Perceived usefulness (PU) of digital data management practices is significantly influenced by analytical skills (AS) (β =0.443, SE = 0.077, p ⩽ 0.000), PEOU significantly influence the attitude of LIS professionals toward digital data management practices (β =0.215, SE = 0.214, p ⩽ 0.000), and attitude of LIS professionals has a positive impact on their performance in managing digital data sets in university libraries (β =0.584, SE = 0.178, p ⩽ 0.005). The study reports primary data gathered through survey on constructs given in technology acceptance (TAM) model. The study provides a valuable insight for organizational leaders, stakeholders, and planners to enhance and refine DDSM practices and methodologies in academic libraries. This will enable them to effectively utilize library resources and services through the implementation of DDSM techniques.