Individual Decision Model for Using Technology of Health Crowdsensing in the Digital Era

Author:

Li Li1ORCID,Cai Xuliang2,He Xin3,Yu Xi1,Li Haoran4,Liu Yanhong4

Affiliation:

1. School of Computer and Information Engineering, Henan University, China

2. YiHe (Shenzhou) Center of Life and Health Sciences, China

3. International Joint Laboratory of Intelligent Network Theory and Key Technology, School of Software, Henan University, China

4. School of Software, Henan University, China

Abstract

Digital transformation has brought about great social changes, and individuals are constantly facing the challenge of using emerging technologies. This article, for the first time, combines the Diffusion of Innovation Theory and Contract Theory to build a decision model to solve the above challenge. The decision model is constructed according to the key factors that influence the individual decision process, including technological relative advantages, intrinsic motivation, risk-taking, use-cost, technological complexity and compatibility. Through the analysis of the cost utility of each party in Health CrowdSensing technology, the question of whether individuals use the technology is transformed into the question of cost utility. In the experiments, the validity of the decision model is verified by numerical analysis. The decision model proposed in this article provides theoretical basis and experimental verification for further research on how an individual decides whether to use technology or not.

Publisher

IGI Global

Subject

Strategy and Management,Computer Science Applications,Human-Computer Interaction

Reference46 articles.

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4. Chen, X., Xu, H., & Zhu, Z. (2015, August). Ladder theory of individual behavioral decision making. In 2015 11th International Conference on Natural Computation (ICNC) (pp. 1176-1182). IEEE.

5. Chen, X., & Yang, J. (2021). Analysis on Farmers' Entrepreneurship Decision-making Based on digital technologies. 2nd International Conference on E-Commerce and Internet Technology (ECIT), 360-363

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