Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach
Due to the low adoption rate of mHealth apps, the apps designers need to understand the factors behind adoption. But understanding the determinants of mHealth apps adoption remains unclear. Comparatively less attention has been given to the factors affecting the adoption of mHealth apps among the yo...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier Ltd.
2020
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/27188/1/TS%206%201%202020%201%2048.pdf |
| _version_ | 1825805606507773952 |
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| author | Alam, Mohammad Zahedul Hu, Wang Kaium, Md Abdul Hoque, Md Rakibul Alam, Mirza Mohammad Didarul |
| author_facet | Alam, Mohammad Zahedul Hu, Wang Kaium, Md Abdul Hoque, Md Rakibul Alam, Mirza Mohammad Didarul |
| author_sort | Alam, Mohammad Zahedul |
| collection | UUM |
| description | Due to the low adoption rate of mHealth apps, the apps designers need to understand the factors behind adoption. But understanding the determinants of mHealth apps adoption remains unclear. Comparatively less attention has been given to the factors affecting the adoption of mHealth apps among the young generation. This study aims to examine the factors influencing behavioral intention and actual usage behavior of mHealth apps among technology prone young generation. The research model has extracted variables from the widely accepted Unified Theory of Acceptance and Use of Technology (UTAUT2) alongside privacy, lifestyles, self-efficacy and trust. Required data were collected from mHealth apps users in Bangladesh. Firstly, this study confirmed that performance expectancy, social influence, hedonic motivation and privacy exerted a positive influence on behavioral intention whereas facilitating conditions, self-efficacy, trust and lifestyle had an influence on both behavioral intention and actual usage behavior. Secondly, the Neural Network Model was employed to rank relatively significant predictors obtained from structural equation modeling (SEM). This study contributes to the growing literature on the use of mHealth apps in trying to elevate the quality of patients' lives. The new methodology and findings from this study will significantly contribute to the extant literature of technology adoption and mHealth apps adoption intention especially. Therefore, for practitioners concerned with fostering mHealth apps adoption, the findings stress the importance of adopting an integrated approach centered on key findings of this study. |
| first_indexed | 2024-07-04T06:35:02Z |
| format | Article |
| id | uum-27188 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:35:02Z |
| publishDate | 2020 |
| publisher | Elsevier Ltd. |
| record_format | eprints |
| spelling | uum-271882020-07-09T06:16:43Z https://repo.uum.edu.my/id/eprint/27188/ Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach Alam, Mohammad Zahedul Hu, Wang Kaium, Md Abdul Hoque, Md Rakibul Alam, Mirza Mohammad Didarul QA76 Computer software Due to the low adoption rate of mHealth apps, the apps designers need to understand the factors behind adoption. But understanding the determinants of mHealth apps adoption remains unclear. Comparatively less attention has been given to the factors affecting the adoption of mHealth apps among the young generation. This study aims to examine the factors influencing behavioral intention and actual usage behavior of mHealth apps among technology prone young generation. The research model has extracted variables from the widely accepted Unified Theory of Acceptance and Use of Technology (UTAUT2) alongside privacy, lifestyles, self-efficacy and trust. Required data were collected from mHealth apps users in Bangladesh. Firstly, this study confirmed that performance expectancy, social influence, hedonic motivation and privacy exerted a positive influence on behavioral intention whereas facilitating conditions, self-efficacy, trust and lifestyle had an influence on both behavioral intention and actual usage behavior. Secondly, the Neural Network Model was employed to rank relatively significant predictors obtained from structural equation modeling (SEM). This study contributes to the growing literature on the use of mHealth apps in trying to elevate the quality of patients' lives. The new methodology and findings from this study will significantly contribute to the extant literature of technology adoption and mHealth apps adoption intention especially. Therefore, for practitioners concerned with fostering mHealth apps adoption, the findings stress the importance of adopting an integrated approach centered on key findings of this study. Elsevier Ltd. 2020 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/27188/1/TS%206%201%202020%201%2048.pdf Alam, Mohammad Zahedul and Hu, Wang and Kaium, Md Abdul and Hoque, Md Rakibul and Alam, Mirza Mohammad Didarul (2020) Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach. Technology in Society, 61. pp. 1-48. ISSN 0160791X http://doi.org/10.1016/j.techsoc.2020.101255 doi:10.1016/j.techsoc.2020.101255 doi:10.1016/j.techsoc.2020.101255 |
| spellingShingle | QA76 Computer software Alam, Mohammad Zahedul Hu, Wang Kaium, Md Abdul Hoque, Md Rakibul Alam, Mirza Mohammad Didarul Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach |
| title | Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach |
| title_full | Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach |
| title_fullStr | Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach |
| title_full_unstemmed | Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach |
| title_short | Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach |
| title_sort | understanding the determinants of mhealth apps adoption in bangladesh a sem neural network approach |
| topic | QA76 Computer software |
| url | https://repo.uum.edu.my/id/eprint/27188/1/TS%206%201%202020%201%2048.pdf |
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