No abstract

The impact of pandemics is magnified by the coexistence of two contradicting reactions to rare dire risks: panic and the 'it won't happen to me' effect that hastens spread of the disease. We review research that clarifies the conditions that trigger the two biases, and we highlight the potential of gentle rule enforcement policies that can address these problematic conditions.

Given the rapid proliferation of smartphone applications and data aggregation websites, in many situations people can use decision aids to guide their choices. For example, they may consider whether to use a navigation device to check the fastest route or whether to use a price comparison website to find the cheapest deal. In what circumstances will subjects use a costly comparison decision aid (which I refer to as "checking") to choose for them? In six studies, I investigate the impact of the number of available alternatives and checking's attractiveness on the decision to check. While at first increasing the attractiveness of checking led to higher checking rates, a further increase in the number of available alternatives (and thus checking's attractiveness) did not increase the checking rate. Surprisingly, even when checking had a 40% higher expected value compared with not checking, the observed checking rate was below 45%, contrary to risk and ambiguity aversion predictions. Furthermore, labeling the checking alternative as the default had no impact on its choice rate. I find large individual differences in decisions to check. Surprisingly, subjects' initial decisions had high predictive power over their subsequent checking rates, even after 100 trials with full feedback. I propose two simple learning models that capture well the aggregated results. K E Y W O R D S checking decisions, decisions from experience, inertia, information search, two-sample 1 | INTRODUCTION "Comparison is the death of joy." Mark Twain Imagine that you want to book accommodation in a foreign city. Even a small city may have scores of different hotels, not to mention hundreds of other alternatives, such as apartments for rent through Airbnb. These alternatives may differ in many dimensions-price, location, cleanliness, etc. Today's consumers constantly face choice decisions between a varying number of alternatives: which road to drive to work, where to book a room for their next vacation, or which breakfast cereal to choose. To help them resolve these decisions, consumers also have access to an exploding number of decision aids, such as price and quality comparison websites and apps. The present paper asks how consumers make decisions in this environment, and in particular, under what circumstances they use available decision aids. An abundant literature examines how consumers choose between products in multidimensional (multiattribute) settings, going back to the famous MouseLab studies (e.g., Payne, 1976; Payne, Bettman, & Johnson, 1988). The general findings of these studies show that people often make suboptimal decisions, whether because of confusion, required cognitive effort or task complexity (Stark & Choplin, 2009). More recent studies propose additional factors behind consumers' suboptimal decisions, such as time constraints (Dhar & Nowlis, 1999),

Research on small decisions from experience suggests people often behave as if they underweight rare events and choose the options that are frequently better. In a pandemic, this tendency implies complacency and reckless behavior. Furthermore, behavioral contagion exacerbates this problem. We analyze two versions of a repeated social game (N = 116). In the first, people clearly preferred the dangerous reckless behavior that was better most of the time over the safer responsible behavior. In the second, we added a stochastically dominated alternative abstracting the use of an application that frequently saves time but sometimes has high costs. Most people chose this “irrelevant alternative”, making this the first clear demonstration of underweighting of rare events in fully described social games. These results were replicated fully in a conceptual replication (N = 196). We discuss public policies that can make the use of such applications better most of the time, thus helping them get traction and facilitate compliance with physical distancing guidelines.

No abstract