The Bias Assimilation Effect and Attitude Polarization in AIoT Smart Healthcare Word-of-Mouth Communication

Abstract

Consumers’ pre-existing attitudes toward Artificial Intelligence of Things (AIoT) smart healthcare technologies significantly shape the effectiveness of electronic word-of-mouth (eWOM) and contribute to attitude polarization. This study aims to examine how attitude consistency influences recipients’ attitude polarization through credibility. Additionally, it explores the moderating effect of medical brands’ attitude consistency and investigates potential age differences. Based on the biased assimilation theory, this research conducts a quasi-experiment involving a 2 (Valence of eWOM on AIoT smart medical technolog: Positive vs negative) × 2 (Valence of eWOM on medical brands: Positive vs negative) ×2 (2 versions of messages). The results of 1,010 valid data demonstrates that greater consistency leads to higher credibility; attitude consistency exerts a negative impact on attitude polarization by enhancing credibility. In contrast, attitude consistency does not play a significant moderating role. Additionally, the influence of biased assimilation regarding AIoT smart medical technology varies between older and younger groups.