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An information system success model for e-learning postadoption using the fuzzy analytic network process
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 fro...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900560/ https://www.ncbi.nlm.nih.gov/pubmed/36779193 http://dx.doi.org/10.1007/s10639-023-11621-y |
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author | Hii, Puong Koh Goh, Chin Fei Tan, Owee Kowang Amran, Rasli Ong, Choon Hee |
author_facet | Hii, Puong Koh Goh, Chin Fei Tan, Owee Kowang Amran, Rasli Ong, Choon Hee |
author_sort | Hii, Puong Koh |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9900560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-99005602023-02-06 An information system success model for e-learning postadoption using the fuzzy analytic network process Hii, Puong Koh Goh, Chin Fei Tan, Owee Kowang Amran, Rasli Ong, Choon Hee Educ Inf Technol (Dordr) Article 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. Springer US 2023-02-06 /pmc/articles/PMC9900560/ /pubmed/36779193 http://dx.doi.org/10.1007/s10639-023-11621-y Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Hii, Puong Koh Goh, Chin Fei Tan, Owee Kowang Amran, Rasli Ong, Choon Hee An information system success model for e-learning postadoption using the fuzzy analytic network process |
title | An information system success model for e-learning postadoption using the fuzzy analytic network process |
title_full | An information system success model for e-learning postadoption using the fuzzy analytic network process |
title_fullStr | An information system success model for e-learning postadoption using the fuzzy analytic network process |
title_full_unstemmed | An information system success model for e-learning postadoption using the fuzzy analytic network process |
title_short | An information system success model for e-learning postadoption using the fuzzy analytic network process |
title_sort | information system success model for e-learning postadoption using the fuzzy analytic network process |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900560/ https://www.ncbi.nlm.nih.gov/pubmed/36779193 http://dx.doi.org/10.1007/s10639-023-11621-y |
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