Emotions within Online Reviews and their Influence on Product Attitudes in Austria, USA and Thailand

Abstract

Online reviews are of considerable interest to both practitioners and academics. Prior research has focused mostly on the valence and volume of online reviews. Questions on how the emotional content of online reviews influence consumers remain open. Given that non-verbal cues of communication are limited in the online environment, content can be a strong driver of attitudes and, in turn, online purchases. Importantly also, a wide stream of research indicates that different self-construal levels (i.e. independent or interdependent self-construal) perceive emotions in different ways. Therefore it is necessary to examine whether the effect of emotional content within online reviews on product attitudes varies across consumers with different self-construals. Hence, we conduct three studies to analyze the relationship between the emotional content within online reviews (positive, negative, mixed) and product attitudes. Results from Study 1, conducted in Austria ( n = 280), show that emotional content within online reviews has an effect on product attitudes, which goes above and beyond that of a review's overall valence. Further building on this finding, Study 2, also conducted in Austria ( n = 420), offers specific insights on how reviews containing different emotional cues (i.e. positive, negative and mixed emotions) influence consumers’ hedonic and utilitarian attitudes. Finally, Study 3 investigates the moderating role of self-construal by comparing consumers from two countries which differ considerably in terms of self-construal, namely USA ( n = 480) and Thailand ( n = 480). The findings of these three studies are discussed. Theoretical and managerial implications of these findings are considered as well as implications for future research.

Emotional Contagion: A Brief Overview and Future Directions

“…Previous studies on consumer behavior have aimed to explain the role of emotions during the decision-making process (Hennig-Thurau et al, 2006;Felbermayr and Nanopoulos, 2016;Zablocki et al, 2019). Using traditional behavioral measures, researchers have concluded that emotions, whether positive or negative, can be contagious by observing other people's experiences (Cowley, 2014;Kramer et al, 2014).…”

The impact of online reviews on e-commerce sales in India: a case study

“…Actions are more from a logical perspective, whereas reactions are more from an emotional viewpoint. Positive and negative valence has been observed in online reviews, where valence indicates the evaluative direction of review (Zablocki et al, 2019) and can be positive, negative or neutral (Purnawirawan et al, 2012). Earlier research on electronic word of mouth suggests that negative valence provides data that show products negatively and positive valence provides data that show products positively.…”

“…Emotions play a major role in customers' decisions (Zablocki et al, 2019). Emotions are more in persuasive advertisements (Lau-Gesk & Meyers-Levy, 2009), and the feeling developed towards the advertisement is the feeling towards the brand (Orth & Holancova, 2003;Ullal et al, 2020).…”

“…Joy positively affects customer attitudes towards e-commerce portals (Richard & Chebat, 2016). Feelings and beliefs affect ecommerce market and the decisions of online customers (Zablocki et al, 2019). The product types negating the effects of bad reviews on luxury and daily-use products have been documented in the extant literature (Sen & Lerman, 2007).…”

Using XGBoost and Skip-Gram Model to Predict Online Review Popularity

“…Another stream of research has explored the moderating role of product and consumer-related characteristics in the effect of online reviews, including product involvement and reviewer self-disclosure (Zhu & Zhang, 2010). In the advertising field, most studies have focused on exploring the effect of online reviews and their influence on product attitudes (Zablocki et al, 2019) and brand awareness (Zhao et al, 2015). Other research has investigated factors that influence online review readers' evaluation of review helpfulness, for instance, the rating of a product based on the sentiment score of a review (F. Wang & Karimi, 2019) or on the linguistic category features of the text (Krishnamoorthy, 2015).…”