Attitude Predictability and Helpfulness in Online Reviews: The Role of Explained Actions and Reactions


Introduction

Online word of mouth (WOM) reviews are becoming increasingly important for both consumers and firms. Different types of reviews for different kinds of products can have an impact on the ultimate purchase decisions of the review readers. This paper focusses on the linguistic content, also called explanation type, of the online WOM reviews by focusing in what way review writers explain their ‘actions’ or ‘reactions’ to certain product types.

Background

The article makes a distinction between utilitarian products and hedonic products and the distinction between explained actions (‘I chose this book because..’) and explained reactions (I love this book because..’). Utilitarian products are bought out of necessity and exhibit more cognitive and functional attributes, whereas hedonic products are primarily more luxury products exhibiting more emotional and sensory aspects. Therefore, a compatibility between explanation types (explained actions vs. explained reactions) and products types (utilitarian vs. hedonic) is suggested.

It is hypothesized that review readers find explained actions more helpful for utilitarian products and explained reactions more helpful for hedonic products, because of an increase in the ability to make their attitudes towards the product more predictable. Thereby, increased attitude predictability and review helpfulness will increase the ultimate product choice of the review reader (see figure 1). Increased attitude predictability makes individuals more certain of how they will like the reviewed product. Whereas review helpfulness increases the level of understanding of the product and being able to better assess to products due to having read the review. As mentioned before, an increase in the two above mentioned variables will most likely also increase sales, which is interesting from a managerial point of view.

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Results

The main hypothesis is tested along five different studies, each having a different set up and focusing on different aspects.

Study 1
The first study provides insights in whether review readers favor – and review writers provide – different explanations across products types. Reviews from different books, both nonfiction (utilitarian) and fiction (hedonic), were gathered from Amazon and studied. It was found that nonfiction reviews included more explained actions sentences and fiction reviews contained more explained reactions sentences, they were also found to be more helpful, in line with the hypothesis (see figure 2).

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Study 2
The second study was done through AmazonTurk and 132 participants were assigned the role of review writer or reader and had to fill out the blanks in reviews for certain product types. They found that product type significantly influenced the sentence choice, as predicted. Nonfiction reviews contained more explained actions, whereas fiction reviews contained more explained actions.

Study 3
159 Participants from a panel had to imagine writing a review about a photo camera for professional use (utilitarian) or fun (hedonic). It was found that participants chose more explained actions for the professional camera and more explained reactions for a camera used for holidays. Review readers perceived these explanations also as more helpful.  This study also proved that the hypothesis holds in a different product category.

Study 4
Study four finds that explained actions allow review readers to better predict their attitude towards utilitarian products, whereas explained reactions increase the attitude predictability for hedonic products. Thereby, increase in attitude predictability increases the likelihood of buying the product by the review reader.

Study 5
The last study finds that review readers prefer explained actions for utilitarian products and explained reactions for hedonic products, as this increases attitude predictability. In turn, increased attitude predictability increases review helpfulness and the intention the purchase the products.

Strengths & Weaknesses

As the article dives into the aspect of the linguistic features of WOM, it contributes valuable information to the existing literature. One of the strengths of the article is that it tests its assumptions in different set ups and through different channels. This enhances the reliability of the study and its findings. Thereby, the implications provide helpful managerial insights for consumers and marketers. By knowing what kind of specific language is used and perceived as most helpful in WOM, online retailers can encourage review writers to write with the most desired linguistic features in order to boost sales.

Although the research focusses on explanation type, the explanation content can also be very valuable, especially when consumers are deciding on particular product specifics or choosing between similar products. Thereby, the article assumes that ‘attitude prediction’ and ‘review helpfulness’ both influence the product choice and purchase intention. However, other variables such as price, perceived brand perception and many others variables can influence whether people buy the product or not, this is however not considered in the article. Thereby, purchase intentions can yield significantly different results in real life, as real purchasing decisions can differ from the intention of purchase. This could have been tackled by monitoring real life purchasing decisions, instead of asking for purchase intentions.

Conclusion

In conclusion, the linguistic features in WOM reviews are very important when it comes to utilitarian and hedonic products, as each category requires different explanations types, as to be viewed as most helpful and increase likeliness of product choice. This research clearly states that explained actions are most valuable for utilitarian products and explained reactions are most valuable for hedonic products. Further research in this field of WOM can increase the implications for both consumers and marketers, as to increase satisfaction and sales.

 

 

Reference

Moore, S. (2015). Attitude Predictability and Helpfulness in Online Reviews: The Role of Explained Actions and Reactions. Journal of Consumer Research, 42(1), pp.30-44.

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