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Cognition

When Positivity Prevails

Favorable information can be sticky when you research a purchase online.

One of the accepted wisdoms in psychology and marketing is that of negativity dominance. Ten years ago, Roy Baumeister and his colleagues published a paper titled ‘Bad is Stronger Than Good’. According to the authors, the power of bad events over good ones can be seen everywhere, including when bad feedback has more impact than good feedback, when bad information is processed more thoroughly than good information, and when bad impressions are more resistant to disconfirmation than good ones. In his book Thinking, Fast and Slow, Daniel Kahneman illustrates this concept by citing the psychologist Paul Rozin: “a single cockroach will completely wreck the appeal of a bowl of cherries but a cherry will do nothing at all for a bowl of cockroaches”.

We can learn a great deal from instances that help theorists find so-called boundary conditions on general rules like the power of bad over good. An article by Brent Coker, recently published in the Journal of Economic Psychology, achieves this by providing an example of the opposite: good is sometimes stronger than bad. In a couple of experiments, the researchers set out to understand what happens when consumers evaluate a mix of positive and negative information about products and services.

In the first study, participants were told that they had to evaluate two new coffee brands entering the market and were given fact sheets about a coffee brand with positive facts (e.g. “Spruce Co. factories have mad moves to cut carbon emissions…”) and another one with negative facts (e.g. “Juniper Co. has been found trying to cover up the exploitation of foreign workers…”). In the control condition of the experiment, participants read the fact sheet and then provided their evaluations of the brands. Participants in the experimental condition, on the other hand, first read the statements and were then told that the brand names attributed to the positive and negatives statements were switched by mistake. They then had to pretend the mistake didn’t happen when they rated the brands. When evaluations across conditions were compared, results indicated that participants in the experimental group were able to use positive information to invalidate previously formed negative attitudes towards the Juniper brand, but less able to use negative information to invalidate previously formed positive attitudes towards the Spruce brand.

The second experiment used a setting that we’re all familiar with, namely reading online product reviews. Participants were asked to imagine they were planning a trip to LA and looking for a suitable hotel. Five reviews were shown to each participant, including a few sentences about the hotel guests’ experience and an overall rating from one to five stars, presented one review at a time. Participants were told that the reviews were taken from last weekend. For one group of participants, reviews were presented from worst (one star) to best (five stars); another group was given the opposite order. Results showed higher attitudes and intentions to book the hotel when the reviews were ordered from positive to negative than when they went from negative to positive. This demonstrated the same “positive contamination” observed in the first experiment.

But what would happen if participants were told that the reviews represented some kind of trend, indicating a gradual worsening of a hotel's quality over time? The researchers tested this hypothesis as well, but to their surprise found no evidence that a positive to negative order of reviews leads to more negative attitudes when reviews are presented as a trend over time.

The author of this research uses the term “asymmetric affective perseverance” to describe what was observed in the laboratory. A key explanation he offers as to why the positive dominates the negative in this instance has to do with the consumption context. When people evaluate information to find a product they would like to purchase, they pursue a positive goal, potentially leading to a positive bias prior to choice. This explanation implies that future researchers could complement the current scenario by also testing what happens when a consumer pursues a negative goal (say, when evaluating information about unhealthy food products that should be avoided). Another approach might look at people with different dispositions by comparing consumers with a promotion (approach) orientation to those with a prevention (avoidance) orientation in pursuing the same goal (see my recent blog on the subject of regulatory focus). Consumers with a prevention focus are more vigilant and sensitive to negative information when they prepare for a purchase, which may dampen or even reverse the effect found in Coke's study.

Available from July 2014: The Behavioral Economics Guide 2014 on BehavioralEconomics.com (free download)

References

Baumeister, R. F., Bratslavsky, E., Finkenauer, C., & Vohs, K. D. (2001). Bad is stronger than good. Review of General Psychology, 5, 323-370.

Coker, B. L. S. (2012). Seeking the opinions of others online: Evidence of evaluation overshoot. Journal of Economic Psychology, 33, 1033-1042.

Kahneman, D. (2011). Thinking, fast and slow. London: Allen Lane.

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