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. 2023 Feb 6:1-22.
doi: 10.1007/s10639-023-11621-y. Online ahead of print.

An information system success model for e-learning postadoption using the fuzzy analytic network process

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An information system success model for e-learning postadoption using the fuzzy analytic network process

Puong Koh Hii et al. Educ Inf Technol (Dordr). .

Abstract

The underutilization of e-learning among university lecturers is an important issue that needs to be resolved. This study aimed to formulate an e-learning postadoption model for Malaysian universities. Data were collected using self-administered questionnaires involving 36 e-learning experts who from lecturers in public and private universities in Malaysia. The data collected was then analyzed using the extent analysis method proposed by Chang (European Journal of Operational Research, 95(3), 649-655, 1996) to examine the weights and rankings of the factors and subfactors. This study showed that for e-learning postadoption, the most important factor is institution service quality, followed by system quality, content quality, instructors' characteristics, and learners' characteristics. This study extends the information systems success model into the e-learning postadoption context. In particular, this study offered insights concerning the dependencies among the factors in the model within the Malaysian university context. The findings are useful for the long-range strategic management of university administrators, and the model can be adopted as a reference to form a rating system to analyze e-learning postadoption. University administrators can analyze critical factors that increase e-learning's post adoption and lead to more efficient resource allocation and management of e-learning.

Keywords: Analytic Network Process; E-learning; Extent analysis method; Fuzzy Set Theory; Information System Success Model.

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Figures

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Fig. 1
Research framework of this study
Fig. 2
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Boolean logic and fuzzy logic
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Fig. 3
Membership functions of the classical set and fuzzy set
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Fig. 4
Systematic procedure of Fuzzy Analytic Network Process

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