The dark side of AI transparency: investigating AI-induced anxiety, technostress, and consumer satisfaction through a hybrid SEM-ANN approach

人工智能透明度的阴暗面:通过混合结构方程模型-人工神经网络方法研究人工智能引发的焦虑、技术压力和消费者满意度

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Abstract

As AI-driven technologies transform customer interactions, understanding their impact on consumer satisfaction is crucial. This study investigates the relationship between artificial intelligence (AI) transparency and consumer satisfaction, incorporating AI-induced anxiety and technostress as mediators and consumer digital literacy as a moderator. A hybrid methodology combining structural equation modelling and artificial neural network (SEM-ANN) was employed to analyse data from 341 e-commerce consumers from China. The SEM results reveal that AI transparency positively influences consumer satisfaction, while AI-induced anxiety and technostress mediate this relationship negatively. However, the moderating role of consumer digital literacy is not significant. The ANN findings identify consumer digital literacy as the most influential factor, highlighting its critical role in shaping consumer responses to AI-powered interactions. These results provide novel insights into the psychological impact of AI transparency on consumers and offer theoretical and practical implications for enhancing AI-driven customer service strategies.

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