Hussin, Siti Farah and Abdollah, Mohd Faizal and Ahmad, Ibrahim (2023) Acceptance of IoT technology for smart homes a systematic literature review. In: International Conference on Information Systems and Intelligent Applications, ICISIA 2022, 1 July 2022 through 2 July 2022, Virtual, Online.
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Abstract
The Internet of things for smart home (IoT SH) technology is the latest technology for homes that integrates sensors, functional software, and network connections. However, the acceptance of IoT SH technology remain low. Hence, Information System (IS) researchers have shown interest in determining the theories and models that influence the acceptance of this technology. This study can assist IoT SH practitioners in enhancing the functionality and shortcomings of IoT products or services for smart homes in order to attract more users. Apart from identifying theo- ries and models, this study will suggest a direction for future research. A systematic literature review was conducted to explore IoT SH by re- viewing previous studies from 2018 to February 2022 with a total of 22 selected research papers. The results show that previous studies covered different technology acceptance theories related to IoT SH namely Technology Acceptance Model (TAM), Unified Theory of Accep- tance and Use of Technology (UTAUT), Unified Theory of Acceptance and Use of Technology (UTAUT 2) and alternative theory to measure the factors. The findings of this review will aid academics, especially novice researchers in understanding the current trends and gaps, as well as future work for IoT SH research.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Internet of things (IoT), Systematic literature review, Technology acceptance theories |
| Divisions: | Faculty of Information and Communication Technology |
| Depositing User: | WIZANA ABD JALIL |
| Date Deposited: | 10 Sep 2024 09:05 |
| Last Modified: | 10 Sep 2024 09:05 |
| URI: | http://eprints.utem.edu.my/id/eprint/27846 |
| Statistic Details: | View Download Statistic |
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