The Combination Signaling Effect of Text and Image on Mobile Phone Review Helpfulness - The Moderating Effect of Signaling Environment

Consumers are increasingly using both texts and images to express their opinions about products rather than using texts alone. Generally, texts usually contain more detailed description of product attributes, contributing to the diagnosticity of reviews, whereas images are visually more attention-grabbing on the screen, contributing to the accessibility of reviews. These two types of information complement each other in influencing potential consumers' evaluation on review helpfulness. However, extant studies mainly investigate the impact of texts and images on review helpfulness independently. Based on signaling theory and level of processing theory, this study attempts to investigate the potential interaction effect of textual signal and imagery signal instead of only examining them in isolation. Particularly, textual signal is operated as review length, while imagery signal is operated as number of pictures in a review. Furthermore, this study also examines whether these effects vary in different signaling environment that is conceptualized as the number of reviews associated with a product. By developing a Tobit regression model for 4,063 online reviews of 39 Huawei mobile phones crawled from ZOL.com, this study empirically demonstrates that review helpfulness is positively influenced by both types of signals. Interestingly, the interaction between two types of signals has a negative impact on the perception of review helpfulness. The results also reveal that the signaling environment augments the impact of textual signal but does not significantly influence the impact of imagery signal. Additionally, it is also found that the signaling environment mitigates the negative impact of the interaction between two types of signals on review helpfulness. These findings are anomalous to the established knowledge on consumer behaviors and possible explanations are presented. Based on these findings, both theoretical and practical implications for the improvement of online review mechanism are discussed.