To test H2a and H2b (i.e., valence disparity will have an inverse relationship with trust and perceived information quality), both negative and positive reviews text reviews (i.e., with positive, neutral, and negative images) were presented in each study. Neutral text reviews were not reported. As the image differed further from the text, the disparity increased (i.e., so the positive image resulted in no disparity, the neutral in moderate disparity and the negative in high disparity). It was for this reason that we excluded reporting the neutral text, as the study could only offer moderate disparity (i.e., placing a positive or negative image with the neutral text), but could not offer a high disparity (i.e., as there we no ‘very positive’ or ‘very negative’ images). Like the testing for H1, a series of ANOVAs was run to evaluate the data.
This study examined the effects that images have on consumer outcomes associated with eWOM. We began by testing H1 and H1a, that stated that reviews which contain images will be trusted more, and perceived as having higher information quality than text-only reviews. We ensured that the text and the images had similar themes (e.g., the positive text had positive images). This held across all three product categories. In all cases, H1 and H1a were confirmed.
Our results suggest that when considering the type of valence of a review (i.e., positive, neutral, or negative), the addition of images was more beneficial when the review was positive or negative, rather than neutral specifically, with the exception of perceived information quality for positive reviews of a cruise ship (i.e., which can be found in Table 1
), the addition of neutral images to neutral reviews did not have as large a significant impact on consumer perception. On the other hand, the addition of images did influence consumer outcomes when positive images were added to positive reviews and when negative images were added to negative reviews. This is logical, since presenting a strong positive or negative image has been shown to have more of an impact on such outcomes as trust and purchase intention (as opposed to neutral reviews) in previous studies [73
]. Given our finding that positive and negative reviews have a stronger impact on consumer perception than neutral reviews, it stands to reason that more information (i.e., in the form of images) would likely have a stronger positive effect on those outcomes.
Our findings support H2a and H2b (i.e., valence disparity will have an inverse relationship with trust and perceived information quality). Across all product categories (cruise ships, fast food and hotels), our data indicate that when the valence disparity was high (i.e., positive text was presented with negative images, or vice versa), the results indicated a large decrease in trust and perceived information quality. This is not surprising as schema congruity theory dictates that when presented with a disparity between information (i.e., images and text not matching), negative outcomes (e.g., reduced trust) will occur [74
]. This is of particular significance in industries such as travel and food, as the customer does not get the benefit of trying the product before buying (i.e., such as one might when test driving a car). As such, consistency of reviews is vital for such products [10
Interestingly, the outcome related to the pairing of negative text and positive images for fast food resulted in the largest gap between high and low valence disparity. This may be because tastes are quite subjective, likely more so than the other product categories that we studied. Indeed, there is an entire area of research in the medical field that explores the idiosyncratic nature of taste [75
Although the high valence disparity gaps supported H2a and H2b, when moderate valence disparity was presented (i.e., neutral image with either positive or negative text), the pair-wise comparisons resulted in nonsignificant outcomes. The only exception being, again, fast food trust (i.e., see Table 2
). This suggests that, generally speaking, there does not need to be perfect congruence between text and images, and that only when large valence disparity exists, do issues regarding trust and perceived information quality arise.
There does not seem to be a large difference between trust and perceived information quality based upon the review being negative or positive. In both cases, the disparity was similar. That is to say, that having negative text, combined with positive images is just as diminutive as having positive text paired with negative images. Although interesting, this finding is not surprising, as both situations result in cognitive dissonance, since the consumer is presented with both a positive message and a negative message in the same review.
4.3. Contributions to Theory
Our findings augment emerging eWOM literature in a variety of ways. First, by exploring the subject with multiple different products and services, this study has a broader generalizability than single product studies, because the effects of product specific factors are mitigated. Next, the study provides fundamental, foundational evidence that images do increase consumer outcomes when added to text reviews. While anecdotal evidence has suggested this relationship for some time, empirical evidence was lacking. Having outlined the influence of images on consumer outcomes in online reviews, researchers may now design and conduct more advanced eWOM studies that include images (see below future research section for an expansion of this topic).
Hypotheses 2a & b (i.e., where non-congruent images were added to the same text) provide insight into the range of variance that is acceptable by consumers with regard to the text/image relationship. They indicate that consumers are able to accept a certain level of disparity between text and images. This finding suggests that eWOM researchers might consider the influence of other types of disparity within the review on consumer outcomes. For example, when a review covers multiple facets of a product, and the reviews of some facets are positive and others are negative, how do consumers process this disparity? Do they tend to trust the reviewer more, viewing them as more objective? If so, this finding would suggest that review platform operators who are interested in increasing purchase intention should develop algorithms which are capable of identifying the valence of several product characteristics, and prioritize those reviews which have at least some level of disparity, with the goal of winning consumer trust. Other potential practical implications are discussed in the following subsection.