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The Effect of Perceived Similarity on Sequential Risk-Taking

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The Effect of Perceived Similarity on Sequential Risk-Taking THE EFFECT OF PERCEIVED SIMILARITY ON SEQUENTIAL RISK-TAKING ELIZABETH C. WEBB* SUZANNE B. SHU * (corresponding author) Elizabeth C. Webb ([email protected]) is Assistant Professor of Marketing at Columbia Business School, Columbia University, 511 Uris Hall, New York, NY 10027, (212) 854-7864. Suzanne B. Shu ([email protected]) is Associate Professor of Marketing at The Anderson School of Management, University of California, 110 Westwood Plaza, Los Angeles, CA 90095, (310) 825-4818. Author Note This work is part of the first author’s dissertation. Acknowledgement The authors would like to thank Stephen Spiller, Marissa Sharif, Scott Shriver, Eric Johnson, Robert Zeithammer, Mariam Hambarchyan, Katelyn Wirtz, Ashley Culver, Melanie Argoff, Carly Lenniger, The BDM Lab group at UCLA Anderson, and seminar participants at Columbia University and Stanford University for their encouraging comments and support throughout the research process. 1 THE EFFECT OF PERCEIVED SIMILARITY ON SEQUENTIAL RISK-TAKING Abstract We examine how perceived similarity between sequential risks affects individuals’ risk-taking behavior. Specifically, in six studies we find that in sequential choice settings individuals exhibit significant positive state dependence in risk-taking: they are more likely to take a risk when it is similar to a previously taken risk than when it is dissimilar. For example, if an individual has previously taken a health/safety risk, that individual is more likely to take a second health/safety risk than a second risk that is in the financial domain. Since similarity between risks is malleable and can be determined by situational and contextual variables, we show that we can change subsequent risk-taking behavior in a predictable manner by manipulating similarity through framing. Finally, we establish that state dependent risk-taking behavior is driven by increased feelings of self-efficacy and self-signaling through the prior risk-taking experience. We further show that the effect of similarity on preferences is not moderated by the outcome received in the prior risk and holds controlling for individual-level and domain-specific heterogeneity. Taken together, our results demonstrate that the similarity structures that exist between risks have a significant effect on risk-taking preferences in dynamic choice settings. Keywords: risk, domain-specificity, sequential choice, similarity 2 INTRODUCTION Every day individuals encounter risks of different types and must decide whether or not to engage in those risks. What factors affect these decisions? Economic theory proposes that an individual’s risk attitude is generally stable. As a result, risk-taking should not be affected by how a risky prospect is framed or by how it fits among other past or future risks. An alternative approach is a psychological model in which risk-taking is driven by an affect-based assessment of the level of risk associated with a given choice. In this model, both risk perception and preference vary by domain such that the same individual can be risk-seeking in one domain but risk averse in another, ceteris paribus. In other words, the individual who likes to gamble at casinos (a financial risk) is not necessarily the same person who enjoys skydiving (a recreational risk). But can an individual’s risk preferences be further affected by the relationships between sequential risky prospects? For example, is an individual more or less likely to take a given risk dependent on how similar it is to a risk she has taken before? Broadly, the research at hand is about how current risk-taking intentions relate to prior risky choices. Research on sequential risk-taking has found that risk-taking increases when a choice is part of a combined set of sequential or simultaneous risks, rather than an isolated decision (Benartzi and Thaler 1999; Gneezy and Potters 1997; Haisley, Mostafa, and Loewenstein 2008; Moher and Koehler 2010; Read, Loewenstein, and Rabin 1999; Redelmeier and Tversky 1992; Thaler et al. 1997; Webb and Shu 2017; Wedell and Böckenholt 1994). However, most of this research has held similarity between the risks constant by focusing on identical risks. What happens if the risks in a decision sequence are not identical but rather represent varying degrees of similarity? The research presented here brings together several of these features of risk-taking—similarity, domain-specificity, sequential choice—to explore how individuals’ attitudes towards risk are affected by the similarity structures that exist between risks considered in a sequence. For example, imagine the risk of riding a bicycle without a helmet. An individual who remembers taking a similar risk before (such as riding in a car without a seatbelt) will be more likely to ride a bicycle without a helmet than if that same individual instead remembers taking a dissimilar risk (such as investing in a speculative stock). 3 Controlling for existing preferences, sequential dynamics, and individual-level and domain-specific heterogeneity, we manipulate similarity to show positive state dependence in risk-taking intentions. We incorporate the findings related to domain-specific risk-taking by examining risks of several different types (financial, recreational, social, health/safety, and ethical) and show that, while sequential aggregation can increase risk-taking likelihood generally, similarity between risks is an important moderator of the effect. While similarity determines which risks individuals are more inclined to take, it is also a variable that can be directly manipulated. Since similarity is malleable and can be affected by contextual factors, this ultimately means that the decision to take a given risk can be manipulated by changing similarity between that risk and a prior risk. For example, the risk of riding a motorcycle without a helmet can be framed as a recreational risk or as a health/safety risk by highlighting different facets of the activity (e.g., the possible adrenaline rush versus the freedom of not wearing a helmet). If framed as a recreational risk, then our theory predicts that individuals will feel more open to another recreational risk; however, if framed as a health/safety risk, our theory predicts that individuals will feel more open to another health/safety risk instead. Thus, holding the prior risk in a sequence constant, we can change subsequent risk-taking intentions for a current risk by manipulating its similarity with that prior risk. While we show positive state dependence in risk-taking and how to manipulate it, we are also interested in the process behind this effect. We propose that similarity between a current risk and a prior risk (1) increases feelings of self-efficacy through experience and familiarity for risks of the same type; and (2) signals to the individual that they prefer risks of a given type more than risks of other types. We show that this shift is occurring through risk attitude since risk perception (subjective beliefs about the level of risk inherent in the activity) does not change with differences in similarity. In other words, individuals do not believe that risks that are more similar to a prior risk are less risky than risks that are dissimilar to that prior risk. Taken together, our empirical results suggest that perceived similarity is an important determinant of risk-taking intentions and that these intentions can be affected by factors that change perceived similarity. 4 What value is this deeper understanding of risk to marketers? While psychological models of risk-taking account for risk type and have shown that risk attitude is highly dependent on the type of risk being considered, none have accounted for the potential malleability of risk type in affecting future behavior. If risk type can be manipulated through framing, this suggests that an individual’s likelihood of taking a risk (e.g., trying a new product, switching brands, not purchasing a warranty) can be increased or decreased by changing its perceived similarity to a prior risk. THEORETICAL BACKGROUND How does an individual decide to take a risk? First, the choice must be assessed to determine how risky it is. This assessment, risk perception, is a subjective judgment that represents the beliefs or feelings individuals have about the level of risk inherent in the prospect under consideration (Blais and E. Weber 2006; Holtgrave and E. Weber 1993; Mellers, Schwartz, and E. Weber 1997; Slovic, Fischoff, and Lichtenstein 1978; E. Weber and Hsee 1998; E. Weber, Blais, and Betz 2002). Risk perception has been shown to account for much of the variance in risk preferences across individuals (E. Weber and Hsee 1998; E. U. Weber and Milliman 1997; E. Weber, Blais, and Betz 2002). Risk perception by itself is not enough to determine whether a risk will be taken, however, since two individuals who perceive the same level of risk may still make different choices about that risk. Individual differences in preferences for risk- taking beyond risk perception can come from differences in risk attitude. Within the economics literature, risk attitude is a stable facet of behavior determined by an expected-utility function. In this model, individuals are consistently risk-seeking or risk averse across different types of risk. In accordance with this model, risk-taking behavior is not affected by context, framing, or shifting relationships between risks. Importantly, this means that the likelihood of taking a given risk is the same regardless of whether that risk is being considered in isolation or as part of a sequence, or if that risk is from the same domain or a different domain as another risk. Much research to date has suggested that models of consistent risk attitude are not descriptive of actual choice (Fox and Tversky 1998; Fox and See 2003; Kahneman and Tversky 1979; March and Shapira 1987; Payne 2005; Rabin and Thaler 2001; Tversky and Kahneman 1992). Within the psychology 5 literature, risk attitude can be affected by psychological factors wherein individual-level risk-taking is not stable across domains or contexts.
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