Tag Archives: consumer behaviour

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The swaying effects of online product reviews

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Based on the ‘wisdom of the crowd’ effect (Surowiecki, 2005), consumers make use of reviews to make accurate product evaluations. However, due to the large amount of information and conflicting opinions in reviews, it becomes difficult for them to identify and consider the attributes that are relevant to their consumer situation.

Imagine you are browsing a webstore, looking for a new camera to take on your backpacking trip. For this situation, you prefer a camera that is lightweight, easy to use, shock-resistant and cheap. You don’t have a lot of experience with camera’s, so you decide to look at the reviews of other consumers that bought Camera X. As you browse through several reviews, you start to notice that a lot of reviews mention things like FPS, image stabilization, Wi-Fi connection and GPS tracking. However, the reviews are in conflict about the quality of the image stabilization and many mention the lack of a Wi-Fi connection. After reading most of the reviews, you decide that you want to look for a camera that has better image stabilization and a Wi-Fi connection, attributes which you originally didn’t pick as relevant for your situation …

The scenario above, is what Liu & Karahanna (2017) describe as the ‘swaying’ effect. After reading reviews, people might over-weigh irrelevant attributes and under-weigh relevant attributes. They suggest that attribute preferences are more heavily influenced by characteristics of the online reviews rather than by the relevance of the attributes to the consumers decision context.

Theory development & methodology

Liu & Karahanna (2017) developed their theory from the constructive preference perspective theory (Bettman, Luce, & Payne, 1998; Payne, Bettman, Coupey, & Johnson, 1992). This theory suggests that preferences are shaped by the interaction between the properties of the information environment of the choice problem and the properties of the human information-processing system. Liu & Karahanna (2017) propose that three characteristics of online reviews affect the assessment of attribute preference and theorize that these characteristics together may ‘sway’ attribute preferences.

  1. the amount of information about attribute level performance,
  2. the degree of information conflict about attribute level performance
  3. the overall numeric rating and the attribute-level performance information

They conducted three studies, in which they provided the participants with a consumer scenario, asked them to weigh different attributes in terms of relevance and made them evaluate a digital camera based on reviews.

In study 1 they manipulated the three hypothesized factors and examined their effects on the attribute preferences. In study 2, they reproduced this study but added a monetary incentive to induce high motivation to process review information. The third study was a free simulation experiment to provide more realism and to allow for higher generalizability, in which verbal protocol analysis was used to capture and measure the factors.

Main findings

When the participants were asked to weigh the attributed based on the provided scenario, they placed more weight on the relevant attributed than the irrelevant attributes (in the scenario above, the attributes cost, ease-of-use and weight are relevant attributes, whereas image stabilization is not). But when they had to evaluate the camera based on reviews (that contained an uneven amount of information across different attributes, varying degrees of information conflict, and a numeric overall rating), the relevance of the attributes did not have a significant impact on attribute preferences.

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Figure 1. Participants’ Constructed Attribute Preferences  (Liu & Karahanna, 2017)

The amount of attribute information in the reviews had the greatest impact on attribute preferences. Study 2 showed that the degree of attribute information conflict only affects attribute preferences when people have high motivation to process information. Study 3 showed consistent results. The studies provided evidence that attribute preferences that result from reading the reviews are primarily driven by the review characteristics and not by attribute relevance, thus supporting the hypothesized ‘swaying’ effect of online product reviews.

Practical implication.

What implications can be derived from these results? To support informed consumer decision making, it should be investigated how reviews should be organized and presented and how making sense of information conflicts can become less cognitively demanding. The effectiveness of some practical suggestions, such as providing a short description of the reviewer’s background (newegg.com), displaying the amount of positive and negative comments on an attribute (Q. (Ben) Liu, Karahanna, & Watson, 2011) and allowing people to see the overall rating from reviewers who have similar decision context, need to be investigated. Implementation of these suggestions allows consumer to filter reviews from people in a similar consumer scenario, makes making sense of conflicts become less demanding and causes the numeric overall rating to make more sense.

Strengths, weaknesses, suggested improvements

By conducting multiple studies with consistent results, the article provides strong evidence for generalizability & robust hypotheses, which enhances the external validity of the results. Nevertheless, there are some limitations. The study only examines a single product category (camera) and a single scenario. Additionally, the samples only consisted of students with a similar expertise of cameras. It would be interesting to examine whether the effects differ based on the consumer’s level of expertise with the product category (camera) or the product category itself. Additionally, to increase the generalizability of this study, it would be interesting to see if these results also apply on a sample that is more representative of the population (not only students).

I would love to hear your opinions on this. Do you recognize yourself in the ‘swaying’ effect? Are reviews influencing your preferences? 

References

Bettman, J. R., Luce, M. F., & Payne, J. W. (1998). Constructive Consumer Choice Processes. Journal of Consumer Research, 25(3), 187–217. https://doi.org/10.1086/209535

Liu, Q. (Ben), Karahanna, E., & Watson, R. T. (2011). Unveiling user-generated content: Designing websites to best present customer reviews. Business Horizons, 54(3), 231–240. https://doi.org/10.1016/j.bushor.2011.01.004

Liu, Q. Ben, & Karahanna, E. (2017). The dark side of reviews: The swaying effects of online product reviews on attribute preference construction. MIS Quarterly, 41(2), 427–448. https://doi.org/10.25300/misq/2017/41.2.05

Payne, J. W., Bettman, J. R., Coupey, E., & Johnson, E. J. (1992). A constructive process view of decision making: Multiple strategies in judgment and choice. Acta Psychologica, 80(1–3), 107–141. https://doi.org/10.1016/0001-6918(92)90043-D

Surowiecki, J. (2005). The Wisdom of Crowds. American Journal of Physics, 75(908), 336. https://doi.org/10.1038/climate.2009.73

 

Articles

“THIS POST IS SPONSORED”

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Effects of Sponsorship Disclosure on Persuasion Knowledge and Electronic Word of Mouth in the Context of Facebook

facebook-logo-100035675-mediumThey are everywhere. We all have seen one: a post on Facebook, Instagram or any other social media platform with a little sign saying that the post is sponsored. We see a celebrity enjoying a certain product and recommending it to the audience. We think to ourselves if the person in question is genuine in his or her motives of sharing it, whether they are actually using the product or whether we should follow their recommendation to purchase it ourselves and possibly share our newly found trophy with our family and friends. This simple everyday ritual we have with ourselves, sometimes multiple times a day, has prominent psychological mechanisms coming into play, guiding us through the journey starting from the recognition of the post as sponsored to eventually activating us to share it with our loved ones.

These psychological mechanisms lay the foundation of the research conducted by Boerman, Willemsen and Van der Aa (2017). The researchers identify the source of the sponsored post(brand or celebrity) as the initial step to recognizing it as carrying persuasive, or in other words, advertising value by consumers. This is defined as the activation of the conceptual persuasion knowledge, which in turn, activates the attitudinal persuasion knowledge. Attitudinal PK gets activated when consumers start developing critical and distrusting feelings towards the advertisement (Boerman, Van Reijmersdal and Neijens 2012).  All these are used as determinants to find out whether the consumers eventually engage in electronic word of mouth (eWOM; cf., Berger 2014).

Designing the experiment

Building on the theoretical foundations mentioned above, researchers conduct an online experiment with 409 participants. A post with David Beckham drinking an Illy branded cup of coffee with the text ‘Starting the day with a nice cup of coffee!’ (posted by David Beckham) and ‘David Beckham starts his day with a nice cup of coffee!’ (posted by the brand) is shown to participants to test the following hypotheses by having participants answer a series of questions:

H1. A Facebook ad that is accompanied by a sponsorship disclosure (‘Sponsored’) will be more likely to activate consumers’ conceptual persuasion knowledge, than a Facebook ad without a sponsorship disclosure.

H2. A Facebook ad that is posted by a celebrity will be less likely to activate conceptual persuasion knowledge, than a Facebook ad that is posted by a brand.

H3. The effects of a sponsorship disclosure on the use of conceptual persuasion knowledge are stronger when a Facebook ad is posted by a celebrity compared to when a Facebook ad is posted by a brand.

H4. Source moderates the effect of the sponsorship disclosure on attitudinal persuasion knowledge through the activation of conceptual persuasion knowledge: The mediated relationship of the disclosure on attitudinal persuasion knowledge will be stronger when the Facebook ad is posted by a celebrity (vs. a brand).

H5. When a Facebook ad is posted by a celebrity, a sponsorship disclosure activates conceptual persuasion knowledge, which results in the use of attitudinal persuasion knowledge and ultimately lowers eWOM. When a Facebook ad is posted by a brand, such serial mediation is less likely to occur.

The figure below clearly outlines the experiment design and the source of the Facebook post as the initial stimulus.

Screen Shot 2018-02-14 at 18.06.39

Anticipated results

In line with the expectations, researchers found evidence to support all five hypotheses. They found that the conceptual and attitudinal PK activation was significantly different when the source of the post was a celebrity in the presence of a sponsorship disclosure. This was not the case when the ad was posted on Facebook by the brand. Activation of the attitudinal PK after recognizing the post as an ad resulted in consumers engaging less in eWOM as a result of the distrusting feelings they developed by recognizing the post as advertising. An interesting finding of the study, however, indicates that little attention is paid to the sponsorship disclosures. The study shows that 59% of the participants did not recognize the sponsorship disclosure which is also in line with previous studies conducted (e.g., Boerman, Van Reijmersdal, and Neijens 2012; Campbell, Mohr, and Verlegh 2013; Wojdynski and Evans 2016). Intuitively, this has an impact on the interpretation of the results. Even though the activation of the conceptual and attitudinal persuasion knowledge of the consumers will result in less engagement, lowering the perceived success of the ad, this does not directly condemn sponsored celebrity Facebook posts to failure since the majority of the people won’t recognize the post as an ad.

 

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 Leveling the playing field

Although the study comes with its limitations due to its single product, brand (Illy coffee), celebrity (David Beckham) and geographical (conducted in the Netherlands) focus, it provides invaluable insights into the effect of sponsorship disclosures on Facebook posts. It seems the regulators’, such as FTC’s, disclosure requirements are not sufficient enough to level the playing field for consumers when it comes to social media advertising. Further research might reveal, however, how this could be overcome as well as consumers moving along the learning curve might become more aware themselves. Until then, better to think twice before you share that post by your favorite celebrity you saw on your newsfeed.

References

Berger, Jonah (2014), “Word of Mouth and Interpersonal Communication: A Review and Directions for Future Research,” Journal of Consumer Psychology, 24, 4, 586–607.

Boerman, Sophie C., Eva A. Van Reijmersdal, and Peter C. Neijens (2012),“Sponsorship Disclosure: Effects of Duration on Persuasion Knowledge and Brand Responses,” Journal of Communication, 62, 6, 1047–64.

Boerman, S., Willemsen, L. and Van Der Aa, E. (2017). “This Post Is Sponsored” Effects of Sponsorship Disclosure on Persuasion Knowledge and Electronic Word of Mouth in the Context of Facebook. Journal of Interactive Marketing, 38, 82-92.

Campbell, M., Mohr, G. and Verlegh, P. (2013). Can disclosures lead consumers to resist covert persuasion? The important roles of disclosure timing and type of response. Journal of Consumer Psychology, 23(4), pp.483-495.

Wojdynski, Bartosz W. and Nathaniel J. Evans (2016), “Going Native: Effects of Disclosure Position and Language on the Recognition and Evaluation of Online Native Advertising,” Journal of Advertising, 45, 2, 157–68.

Articles

Know Yourself And Know Your Enemy

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‘If you know yourself and know your enemy, you need not fear the result of a hundred battles’ (Sun Tzu, Art of War)

Online retailers currently implement and leverage a variety of sales support tools. This article provides insight in consumer (users) behaviour on those e-commerce websites (Adomavicius and Tuzhilin 2005). It looks at different factors that might affect consumer behaviour (specifically consumers’ decisions whether or not to buy a product) (Hennig-Thurau et al. 2012). In this research the effect of two things on sales of a product is examined. One is recommendation systems (generated by the firm) and the other is online review systems (generated by customers). Previous literature has primarily focused on both loose effects; this study particularly looks at how these two factors might combine together to affect consumers’ behaviour.

Recommendation systems are where each product will give you recommendations to other (similar) products (Oestreicher-Singer and Sundararajan 2012). This study argues that we should see recommendations systems as networks with a number of different products linked to each other. This study seeks to analyse the whole network of related product referrals. The author predicts that the position of all the different products within a network might affect the sales of a product. Any product near to the centre of the recommendation network will get more attention. So, if the Product A is near to the centre of the network it will get more sales. If the competing product (or normally products) is near to the centre these will get more attention, taking attention away from the Product A, and so Product A will get less sales.
Online review systems (eWOM: electronic word-of-mouth) are where users of this site write a review of a product. This study observes when the consumers is shopping on the site, they can see both reviews of the product they are considering and also all reviews of other recommended products. The author predicts that the fact that they can see these other reviews creates competition, which makes the customer less likely to buy the particularly product.

The empirical analysis are performed with collected data from Amazon.com on 1.740 randomly selected books within four categories (programming, business, health and guide books) over a period from two years. This empirical analysis yields three major findings. The research has shown that recommendation systems intensify the competition between products. The authors state that the products which are linked to recommendation systems generate more sales if they have a central place in the referral recommendation network. There have been extensive findings that these sales gains are impeded by improvements in the reviews (eWOM) of competing products. This indicates that a positive eWOM received by a competing book worsen the rank of the focal book.

The main limitation of this study is that they used data at aggregate level, and not at individual consumer level. Therefore, the collected data does not track the actual activity of reviews/recommendations. This is a missing link for virtually all eWOM studies. The solution to this limitation could may be collecting click-stream data to better connect behavior and action.

 

 

References
Adomavicius, G., and Tuzhilin, A. 2005. “Towards the Next Generation of Recommender Systems: A Survey of the State-of- the-Art and Possible Extensions,” IEEE Transactions on Knowl- edge and Data Engineering (17:6), pp. 734-749.

Hennig-Thurau, T., Marchand, A., and Marx, P. 2012. “Can Auto- mated Group Recommender Systems Help Consumers Make Better Choices?,” Journal of Marketing (76:5), pp. 89-109.

Oestreicher-Singer, G., and Sundararajan, A. 2012. “Recommen- dation Networks and the Long Tail of Electronic Commerce,” MIS Quarterly (36:1), pp. 65-83