Hong Jin, Jiayue Yan, Vol. 4, No. 2, pp. 8-11, Jun. 2020
10.22662/IJEMR.2020.4.2.008, Full Text:
Keywords: Distributed network, Machine Learning, Block-chain, Load-Balancing, Performance Improvement

Abstract

Background/Objectives: Based on the existing user acceptance model, this paper proposes a quantitative self-acceptance model for wearable device users, and puts forward relevant assumptions and provide advice on the development of wearable technology. Methods/Statistical analysis: In this paper, we set the hypothesis based on the results of previous studies. This was structured and a questionnaire survey was conducted on users on a Packard 5-point scale through a questionnaire. Analytical tools are SPSS and AMOS. Findings: In terms of theoretical research, the model proposed in this study is limited by the degree of development of the research object, and the variables and interrelationships of the model are relatively simple. According to the previous research experience, the model still has a lot of room for improvement, and it has yet to be optimized in terms of complexity and effectiveness. Improvements/Applications: All in all, this research has achieved the initial research purpose, completed the research task of the factors affecting the willingness of wearable device users to accept, has some innovation in the academic theory level, and has certain reference significance for practical activities.

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