Psychometric analysis of Integrated Digital Library User Success (IDLUS) Scale in academic digital library environment

Purpose The purpose of this study is to execute the application of confirmatory factor analysis in structural equation modeling, to investigate the reliability and validity of the proposed integrated digital library user success (IDLUS) scale in academic digital library computing information system in the area of information management and systems. Design/methodology/approach The study analyzed 355 valid responses (MPhil and PhD) from the largest and oldest public sector university in Pakistan. Sample selection was calculated through a stratified random sampling technique from the four faculties of the University of the Punjab. The instrument was constructed based on the available two digital library and information system success models. The first model is Jung’s (1997) digital library user success model that is further composed of flow model (1977), end user computing satisfaction model (1987) and Joshi’s overall user satisfaction model (1990). Similarly, the second model is DeLone and McLean’s reformulated information system success (2003) theory. The question items used a five-point Likert scale and executed regression weights, standardized regression weights, convergent validity, variance extracted, construct reliability and discriminant validity to infer results. Findings Findings show that the IDLUS scale has excellent validity and reliability estimates. Research limitations/implications The study has theoretical implications for researchers and practical implications for information system developers. Originality/value To the best of the authors’ knowledge, this scale is the first-ever effort to measure the digital library user success in the context of Higher Education Commission-National Digital Library of Pakistan. Therefore, there was a dire need to conduct the psychometric analysis of the scale to examine the model fit statistics on the current sample in the particular cultural norms. Scale is based upon human factors taken from various Web success and information system success models from the fields of human–computer interaction information systems and computer-mediated communication.