A Novel Approach for Predicting the Adoption of Smartwatches Using Machine Learning Algorithms

Author:

Arpaci Ibrahim,Al-Emran Mostafa,Al-Sharafi Mohammed A.,Shaalan Khaled

Publisher

Springer International Publishing

Reference28 articles.

1. Çiçek, M.: Wearable technologies and its future applications. Int. J. Electr. Electron. Data Commun. 3(4), 45–50 (2015)

2. Alvarez, V., Bower, M., De Freitas, S., Gregory, S., de Wit, B.: The use of wearable technologies in Australian universities: examples from environmental science, cognitive and brain sciences and teacher training. In: Mobile Learning Futures—Sustaining Quality Research and Practice in Mobile Learning (2016)

3. Chuah, S.H.W., Rauschnabel, P.A., Krey, N., Nguyen, B., Ramayah, T., Lade, S.: Wearable technologies: the role of usefulness and visibility in smartwatch adoption. Comput. Human Behav. (2016)

4. Kim, K.J., Shin, D.H.: An acceptance model for smart watches: implications for the adoption of future wearable technology. Internet Res. (2015)

5. Al-Emran, M., Malik, S.I., Al-Kabi, M.N.: A survey of internet of things (IoT) in education: opportunities and challenges. In: Toward Social Internet of Things (SIoT): Enabling Technologies, Architectures and Applications, pp. 197–209. Springer (2020)

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