Asia Pacific Journal of Information Systems (APJIS)

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Past Issue

Date	March 2021
Vol. No.	Vol. 31 No. 1
DOI	https://doi.org/10.14329/apjis.2021.31.1.121
Page	121~140
Title	Predicting the Adoption of Health Wearables with an Emphasis on the Perceived Ethics of Biometric Data
Author	Tahereh Saheb, Tayebeh Saheb
Keyword	Health Wearables, Adoption, Neural Network Analysis, Bibliometric Analysis, Data Ethics
Abstract	The main purpose of this research is to understand the strongest predictors of wearable adoption among athletes with an emphasis on the perceived ethics of biometric data. We performed a word co-occurrence study of biometrics research to determine the ethical constructs of biometric data. A questionnaire incorporating the Unified Theory of Acceptance and Use of Technology (UTAUT), Health Belief Model and Biometric Data Ethics was then designed to develop a neural network model to predict the adoption of wearable sensors among athletes. Our model shows that wearable adoption’s strongest predictors are perceived ethics, perceived profit, and perceived threat; which can be categorized as professional stressors. The key theoretical contribution of this paper is to extend the literature on UTAUT by developing a predictive modeling of factors affecting acceptance of wearables by athletes, and highlighting the ethical implications of athlete’s adoption of wearables.