By Heather Barry Kappes – London School of Economics and Political Science
Reisch and Zhao give an accessible and comprehensive review of the ways that major findings from behavioural economics have been and can be applied to consumer policy. As they note, such policy is intended to help people make “better, smarter, healthier, and more sustainable choices.” Their review reflects what consumer researchers know right now. What’s next on the agenda?
I’d suggest that as consumer researchers, we have 3 priorities for the coming years.
First, we need a better understanding of how robust and powerful findings like those that Reisch and Zhao cite are. Recent discussions and studies have made it clear that we cannot simply assume that every published finding is a reliable guide for the decisions of individuals, companies, or governments. It’s undoubtedly true that—as they note—seemingly irrelevant physical cues influence consumer decisions. However, we should not assume that all effects identified in controlled research with relatively small sample sizes will replicate consistently in diverse contexts. Even effects that are consistently reproducible may or may not yield effect sizes big enough to be consequential in the messy real world.
A recent Registered Replication Report included 17 independent direct tests of the “facial feedback hypothesis,” the idea that people’s feelings and judgments are influenced by their facial expressions (i.e., people find cartoons funnier when they hold a pen with their teeth than when they hold it with their lips). Although some of the experiments found a sizeable effect consistent with the hypothesis, as a group they found on average no effect. Lingering questions about the size and generalizability of published findings makes both teaching and policy design challenging. We have to continue to probe the reliability of the effects that we study, so that we can make clear recommendations to consumer and policy-makers.
Second, we must keep thinking carefully about which “biases” actually need to be eradicated in order for people to flourish. Research by Gigerenzer and colleagues (see Arkes, Gigerenzer, & Hertwig 2016) points out that many decision heuristics are “fast and frugal” –that is, some heuristics not only save effort, they are as good as or better than more complex inference procedures. Not all decisions that could be labeled irrational are problematic; indeed, many are, on balance, beneficial. When we make suggestions about improving decision-making, we have to first make sure that there’s a need for intervention—that what people are doing needs improvement—and that the benefits of our interventions outweigh the costs of the change. It would be useful to work toward consensus about the criteria for defining “better” decisions.
A third direction for coming years is to explore how existing beliefs about the process of decision-making shape reactions to policy. Reisch and Sunstein find that most people are in favor of most of the commonly used sorts of nudges. What happens, however, when policy suggestions conflict with what people believe about their own behaviour?
Some years ago I was involved in a program of research findings that imagining achievements could actually decrease effort and success (Kappes & Oettingen 2011; see Kappes & Morewedge 2016). Inevitably, when I presented this research someone would say “that’s very interesting, but for me, it’s not true.”
Many people may not be swayed by empirical evidence that conflicts with their personal experience—and experience isn’t always an accurate teacher. This is good news in some ways for consumer researchers, since our research adds value beyond the power of introspection, but it means that it can be tough to “sell” counterintuitive effects. For instance, Goldsmith and Dhar found that loss frames are more motivating than gain frames for participants who are paid to unscramble anagrams—no surprise here in light of the research on prospect theory summarized by Reisch and Zhao.
However, about 75% of a separate sample that Goldsmith and Dhar surveyed made the opposite prediction, believing that they would be more motivated by the gain frame. The mis-predictions apparently stemmed from beliefs about enjoyment; those surveyed also expected to enjoy working under the gain frame more.
Beliefs about what’s motivating and what’s enjoyable are consequential in understanding how people react to policy; if they don’t think it will work, or that they’ll like it, we shouldn’t expect them to embrace it. (See the outcry among educators in response to discussion of a field experiment that presented teacher bonuses in a loss frame; Fryer et al. 2012). Thus, in addition to identifying powerful effects and carefully considering whether intervention is needed, consumer research needs to think about how these interventions are likely to be perceived.
What makes a successful intervention, as opposed to what makes a good policy, remains a matter for debate in 2017. As Reisch and Zhao’s review makes clear, these are exciting times in the behavioural sciences.
Read the full article by Lucia A Reisch and Min Zhao “Behavioural economics, consumer behaviour and consumer policy: State of the art” in the second issue of Behavioural Public Policy, for free here