The recent COVID-19 pandemic has cast into sharper relief media, governmental, and public concerns about fairness in allocation. For example, firms are often accused of price gouging when demand for certain things increases dramatically and prices follow suit. However, a new Journal of Marketing article suggests some potential nuance: Consumers might tolerate rising prices in response to demand shocks if they appreciate that doing so can sometimes help direct scarce goods and services to those who will make the best use of them—that is, help sort preferences.
Broadly, our research team asked: When do markets, lines, and lotteries seem most appropriate and why? This is a critical topic for marketing theory and practice because beliefs about fairness not only pose a fundamentally psychological question for researchers, but also place significant constraints on firms.
When allocating scarce goods and services, firms often either prioritize those willing to spend the most resources (e.g., money, in the case of markets; time, in the case of lines) or they simply ignore such differences and allocate randomly (e.g., through lotteries). When is each approach deemed most fair, and why? Our team found that people are more likely endorse markets and lines when these systems increase the likelihood that scarce goods and services go to those who have the strongest preferences. And this is most feasible when preferences are dissimilar (i.e., some consumers want something much more than others). Consequently, people are naturally attuned to preference variance: When preferences for something are similar, markets and lines seem less appropriate because it is unlikely that the highest bidders or those who have waited the longest actually have the strongest preferences. However, when preferences are dissimilar, markets and lines seem more appropriate because they can more easily sort preferences.
Thus, while there are many potential reasons why people might favor markets (e.g., they are common, they help supply meet demand) or lines (e.g., they seem egalitarian), it turns out people also care a great deal about whether these resource-based allocation rules improve distributive efficiency—allocating scarce goods and services to those who want them the most. This characterizes a novel source of market aversion that can be traced to views about the basic purpose of markets: preference sorting. And it also demonstrates how the same conditions that give rise to market aversion dampen support for lines.
When allocating scarce goods and services, then, a one-size-fits-all policy is a risky proposition. Beliefs about the appropriate allocation rules depend not only on what is being allocated, but also to whom (e.g., people with similar or dissimilar preferences). Consequently, when firms choose the option regarded as less appropriate or fair, the resulting perceptions of unfairness yield negative downstream consequences, resulting, for example, in reduced purchase intentions.
Moreover, this basic insight could apply to other allocation rules in non-consumer contexts. For example, a primary function of admissions committees at elite universities can be viewed as “merit sorting”—allocating limited seats in each freshman class to the most qualified applicants. But merit sorting should be similarly infeasible when qualifications are too similar. This has led some experts to call for lottery admissions for applicants that meet certain academic thresholds.
People often disagree about how to allocate things fairly. And it can sometimes seem like these disagreements stem from intractable differences in moral convictions or political philosophies (e.g., socialism versus capitalism). However, this new theory offers a more flexible view. People seem to earnestly try to discern the nature of preferences and choose an allocation rule that fits.
From: Franklin Shaddy and Anuj K. Shah, “When to Use Markets, Lines, and Lotteries: How Beliefs About Preferences Shape Beliefs About Allocation,” Journal of Marketing.
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Franklin Shaddy is Assistant Professor of Marketing and Behavioral Decision Making, Anderson School of Management, University of California, Los Angeles
Anuj Shah is Associate Professor of Behavioral Science, Booth School of Business, University of Chicago.