Understanding the Forced Adoption of an AI-Based Health Code System in China

Jingbo Yuan, Sayed Kifayat Shah (), Jozsef Popp () and Angel Acevedo-Duque
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Jingbo Yuan: Shenzhen University, Shenzhen, China
Sayed Kifayat Shah: Shenzhen University, Shenzhen, China
Jozsef Popp: WSB University, Poland
Angel Acevedo-Duque: Public Policy Observatory, Universidad Autonoma de Chile, Santiago, Chile

The AMFITEATRU ECONOMIC journal, 2024, vol. 26, issue 66, 550

Abstract: With the growth of technology and the exigency to continuously improve their socioeconomic position, users must gradually adopt new AI-based solutions. However, users may experience dissatisfaction and frustration when faced with the replacement of previous systems. To bridge this gap, this study proposes a theoretical model that relies on the forced acceptance and usage of AI-based services during COVID-19 in China. This research examined the implementation of a novel health code system in which users were forced to exclusively adopt this system to restrict face-to-face interactions. The study hypotheses were evaluated by employing structural equation modelling (SEM) on the data obtained from a survey of 262 Chinese users. The results show that the forced acceptability of use is impacted by technological and personal factors. This study demonstrates the forced implementation and daily utilisation of the health code system to meet the social needs of the vulnerable population and offers a comprehensive analysis of the process by which policies are formulated. This framework will incentivise socioeconomic progress in institutions and society, as well as assist other academicians in organising their thoughts and promoting the development of theory.

Keywords: forced acceptance; PLS-SEM model; COVID-19; health-code system; China (search for similar items in EconPapers)
JEL-codes: I1 M3 O1 O3 (search for similar items in EconPapers)
Date: 2024
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