Examining the Influence of Emotional Expressions in Online Consumer Reviews on Perceived Helpfulness

Drawing on the cognitive appraisal theory of emotions and the attribution theory, this study extends existing research by examining how the emotional expressions influence perceived helpfulness of online consumer reviews (OCRs). We include two negative emotions (anger, fear) and two positive emotions (pride, surprise). Each of these four emotions can be described with respect to six emotional appraisal dimensions which containing certainty, pleasantness, attentional activity, anticipated effort, control and others’ responsibility. Hypotheses thus developed were empirically validated using the laboratory experiment in the context of restaurant services. Research results indicated that emotion expressions in OCRs have an indirect effect on perceived helpfulness through attribution about the reviewer's cognitive effort. We find that reviews with negative emotions are perceived to be more reviewer's cognitive efforts than positive emotions. More specifically, OCRs with negative emotions tend to comprise more diagnostic features related the product or service, and are more informative. We further examined whether the gender of reader moderates the relationship between different emotional expressions and perceived reviewer's cognitive effort. The results find that reviews conveying positive emotions tended to have a greater impact on male readers’ perception of reviewer's cognitive effort than those of female readers. Reviews conveying negative emotions were found to have a greater impact on female readers’ perception of reviewer's cognitive effort than that of male readers. The study results add to existing knowledge of the influence of emotional expression on perceived helpfulness, which will advance our understanding of information processing in the psychological mechanisms influencing the attitude. Applying the results from this study, restaurant service providers can make different coping strategy for discrete emotions and platform administrators can assistant reviewer express their emotions more precisely.