Investigating the Acceptance of Mobile Library Applications with an Extended Technology Acceptance Model (TAM)
By Hamaad Rafique, Alaa Omran Almagrabi, Azra Shamim, Fozia Anwar, Ali Kashif Bashir. Comput. Educ., 2020
451 citations recorded by the source corpus.
Abstract Mobile applications are getting a great deal of interest among researchers due to their proliferation and pervasiveness, especially in the context of digital libraries of educational institutes. However, their low acceptance and usage are observed, hence, in-depth investigations are required in order to understand the factors behind low acceptance and intention to use mobile library application (MLA). Therefore, the aim of this work is to empirically explore the acceptance of MLA with a proposed model that is evolved from the technology acceptance model (TAM). The study objects to deliver empirical provision on acceptance of MLA. A self-administrated cross-sectional survey-based study was conducted to gather data from 340 users of MLA. Structural equation model (SEM) with an analysis of moment structure (AMOS) software was conducted to examine quantitative data. Results revealed that perceived usefulness and perceived ease of use are direct significant predictors with the intention to use MLA whereas system quality and habit are the influencing factors toward the usage intention of MLA. The findings help as a guide for effective decision in the design and development of MLA. Further, the outcomes can be utilized in the resource allocation process for ensuring the success of the library's vision and mission.
Subfields: Information Systems and Management, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/77724c3ccf3f49ba5a098165a3b1c078653a935d
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In Information Systems and Management
In Sociology and Political Science
Citations in the corpus
- Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model (2021, result): “In connection with QS, previous studies also reported that it significantly affected user’s intention (Fathema & Sutton, 2013; Fathema et al., 2015; Park et al., 2012; Rafique et al., 2020).”