Mustafa Sohaib, Zhang Wen, Shehzad Muhammad Usman, Anwar Aliya, Rubakula Gelas
College of Economics and Management, Beijing University of Technology, Beijing, China.
School of Management Engineering, Zhengzhou University, Zhengzhou, China.
Front Psychol. 2022 Feb 10;13:836194. doi: 10.3389/fpsyg.2022.836194. eCollection 2022.
Every emerging technology has its pros and cons; health-conscious users pay more importance to healthy and environment-friendly technologies. Based on the UTAUT2 model, we proposed a comprehensive novel model to study the factors influencing consumers' decision-making to adopt the technology. Compared to prior studies that focused on linear models to investigate consumers' technology adoption intentions and use behavior. This study used a Structural Equation Modeling-fuzzy set qualitative comparative analysis (SEM-QCA) approach to account for the complexity of customers' decision-making processes in adopting new technology. We collected valid responses from 830 consumers, analyzed them, and evaluated them using a deep learning SEM-QCA technique to capture symmetric and asymmetric relations between variables. We have extensively incorporated a health-consciousness attitude as a predictor and mediator to understand better the decision-making toward technology adoption, specifically 5G technology. All the factors tested in our model are statistically significant except the economic factors. Health-consciousness attitude (HCA) and behavioral intention (BI) found significant predictors and valid mediators in the process of 5G technology adoption. sQCA provided six configurations to achieve high 5G adoption. The findings have significant practical ramifications for telecom corporations, advertisers, government officials, and key policymakers. Additionally, the study added substantial theoretical literature to technology adoption, particularly the adoption of 5G technology.
每项新兴技术都有其优缺点；注重健康的用户更看重健康环保的技术。基于UTAUT2模型，我们提出了一个全面的新颖模型来研究影响消费者采用该技术决策的因素。与之前专注于线性模型来调查消费者技术采用意图和使用行为的研究相比，本研究采用了结构方程模型-模糊集定性比较分析（SEM-QCA）方法来解释客户采用新技术决策过程的复杂性。我们收集了830名消费者的有效回复，对其进行分析，并使用深度学习SEM-QCA技术进行评估，以捕捉变量之间的对称和不对称关系。我们广泛纳入了注重健康的态度作为预测因素和中介因素，以更好地理解对技术采用的决策，特别是对5G技术的决策。我们模型中测试的所有因素除经济因素外均具有统计学意义。注重健康的态度（HCA）和行为意图（BI）在5G技术采用过程中是显著的预测因素和有效的中介因素。sQCA提供了六种配置以实现高5G采用率。这些发现对电信公司、广告商、政府官员和关键政策制定者具有重大的实际影响。此外，该研究为技术采用，特别是5G技术的采用增加了大量的理论文献。
