A large amount of literature is devoted to researching the conditions and motives for customers to leave an online review and the effect of these positive and negative online reviews on the product sales. It is argued that the willingness of customers to post a review is amongst others influenced by the magnitude of disconfirmation – the discrepancy between the expected and experienced assessment of the same product – (Ho, Wu, Tan, 2017) and that negative online reviews impact the product sales more significantly than positive online reviews (Chavalier & Mayzlin, 2006). Nevertheless, the helpfulness of the positive and negative online reviews as perceived by the customers is present day not covered extensively in the online word-of-mouth literature. The limited current empirical literature has concluded mixed contradicting results. The paper “When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth” by Yin, Mitra and Zhang (2016) examines the helpfulness of online reviews on the basis of confirmation bias, confidence in initial beliefs and positive-negative asymmetry.
Confirmation bias – a tendency of humans to overweigh information that confirms (versus disconfirms) their initial beliefs and position (Klayman & Ha, 1987)
Customers initial beliefs – the extent of perceived certainty that their beliefs are accurate (Smith & Swinyard, 1988)
Positive-negative asymmetry – whether positive or negative reviews are perceived to be more helpful by customers (Baumeister et al., 2001)
The authors developed thee hypotheses based on existing literature. Confirmation bias is argued to have an effect in the perceived helpfulness of the review. The information provided in reviews confirming the customers’ initial beliefs stimulates less psychological discomfort than information that contradicts their initial beliefs. This idea composes the first hypothesis. Furthermore, the extent of confirmation bias is likely to depend on the confidence of the customers in their initial beliefs. It is argued that a high dispersion of ratings indicates low agreement among reviewers. A high dispersion of ratings lowers the validity of the average ratings, consequently decreasing the certainness of the initial beliefs. This stream of thought composes hypothesis two. Additionally, the paper reviews the effect of the confirmation bias on the positive-negative asymmetry. It is suggested that confirmation bias can influence the degree of perceived helpfulness for positive reviews when the average product rating is high and for negative reviews when the average product rating is low, creating hypothesis 3. A panel data set from Apple’s App Store comprising of 106.045 reviews from 505 different applications was extracted to conduct three types of analysis including cross-sectional analysis and vote-level analysis. All hypotheses were supported.
Main findings of the article
- The perceived helpfulness of individual online reviews is affected by the confirmation bias.
- The confidence of customer of their initial belief about a product as formed on the basis of summary rating statistics moderates the tendency of confirmation bias.
- The confirmation bias influences the positive-negative asymmetry, for positive reviews when the average product rating is high and for negative reviews when the average product rating is low.
Strengths & weaknesses and relevance
One of the main strong points of the paper by Yin, Mitra and Zhang (2016) is the academic contributions. Within the discourse of online word-of-mouth, the study is the first to include confirmation bias and initial belief to explain possible positive-negative asymmetry. The inclusion of these elements enhances the understanding of the helpfulness of online reviews, providing clarity in the current literature. One of the main weakness is that the initial belief of the product is accounted for by the product’s summary rating, however other aspects might influence the initial belief of the product as well possibly influencing the proposed moderation on confirmation bias. In terms of managerial implications, the deeper understanding of the helpfulness of reviews allows for review website to adjust the design of review placement based on the findings. It is helpful to account for the confirmation bias to increase the objectivity of the review site, hence including both negative and positive comments on the main page.
Firstly, in the paper the statistics of Apple’s App Store are used to conduct the study, therefore the products reviewed are applications. Would the results have differed if the statistics of other products were used i.e. Coolblue washing machines? Secondly, keeping the results of the study in mind. What results are expected if the perceived helpfulness was not generically conducted (useful/not useful), but rated? Would the confirmation bias effect the degree of usefulness?
Baumeister RF, Bratslavsky E, Finkenauer C, Vohs KD (2001), Bad is stronger than good. Review of General Psychology, 5(4), pp. 323–370.
Chevalier JA, Mayzlin D (2006), The effect of word of mouth on sales: Online book reviews, Journal of Marketing Research 43(3), pp. 345–354.
Ho, Yi-Chun (Chad) and Wu, Junjie and Tan Yong (2017), Disconfirmation Effect on Online Rating Behavior: A Structural Model, Information Systems Research, 28(3), pp. 626-642.
Klayman J, Ha YW (1987) Confirmation, disconfirmation, and information in hypothesis testing, Psychological Review, 94(2) pp. 211–228.
Smith RE, Swinyard WR (1988), Cognitive response to advertising and trial: Belief strength, belief confidence and product curiosity, Journal of Advertising, 17(3) pp, 3–14.
Yin D, Mitra S, Zhang H (2016), Research Note—When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth, Information Systems Review, 27(1), pp. 131-144.