Earticle

초록

영어

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.

목차

ABSTRACT
Ⅰ. Introduction
1.1. Ethics of Biometric Data
Ⅱ. Research Model Development
Ⅲ. Research Methodology
3.1. Neural Network Analysis vs Inferential Statistics
3.2. Sampling and Data Collection
3.3. Variables and Measures
3.4. Reliability and Validity Measures
Ⅳ. Data Analysis and Results
Ⅴ. Discussion and Implications
5.1. Key Theoretical Contributions and Implications
5.2. Key Practical Contributions and Implications
5.3. Future Studies

저자

• Tahereh Saheb [ Assistant professor, Management Studies Center, Tarbiat Modares University, Iran ] Corresponding Author
• Tayebeh Saheb [ Assistant professor, Law School, Tarbiat Modares University, Iran ]

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