I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice

Kate  Barasz; Tami  Kim; Ioannis  Evangelidis

Article | Cognition

I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice

by Kate Barasz, Tami Kim and Ioannis Evangelidis

Abstract

People often speculate about why others make the choices they do. This paper investigates how such inferences are formed as a function of what is chosen. Specifically, when observers encounter someone else's choice (e.g., of political candidate), they use the chosen option's attribute values (e.g., a candidate's specific stance on a policy issue) to infer the importance of that attribute (e.g., the policy issue) to the decision-maker. Consequently, when a chosen option has an attribute whose value is extreme (e.g., an extreme policy stance), observers infer-sometimes incorrectly-that this attribute disproportionately motivated the decision-maker's choice. Seven studies demonstrate how observers use an attribute's value to infer its weight-the value-weight heuristic-and identify the role of perceived diagnosticity: more extreme attribute values give observers the subjective sense that they know more about a decision-maker's preferences, and in turn, increase the attribute's perceived importance. The paper explores how this heuristic can produce erroneous inferences and influence broader beliefs about decision-makers.

Keywords: self-other difference; social perception; inference-making; preferences; consumer behavior; prediction; prediction error; Decision Choices and Conditions; Perception; Behavior; Forecasting and Prediction;

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Citation:

Barasz, Kate, Tami Kim, and Ioannis Evangelidis. "I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice." Cognition (in press).

Over the last decade, healthcare in many parts of the world has shifted toward a more patient-centric, consumeristic model, marked by an emphasis on choice and a proliferation of typical consumer-facing information (e.g., price and quality data). However, while the "patients as consumers" perspective is an apt one, there are crucial differences between healthcare and typical consumer domains that warrant special consideration by policymakers and researchers alike. This article discusses some of these differences and explores the challenges that consumers (a.k.a. patients) face when making tradeoffs between price and quality.

Article | Harvard Business Review | January–February 2018

Ads That Don't Overstep: How to Make Sure You Don't Take Personalization Too Far

Leslie John, Tami Kim and Kate Barasz

Data gathered on the web has vastly enhanced the capabilities of marketers. With people regularly sharing personal details online and internet cookies tracking every click, companies can now gain unprecedented insight into individual consumers and target them with tailored ads. But when this practice feels invasive to people, it can prompt a strong backlash. Marketers today need to understand where to the draw the line. The good news is that psychologists already know a lot about what triggers privacy concerns off-line. These norms—and the authors’ research—strongly suggest that firms steer clear of two ad-targeting techniques generally disliked by consumers: using information obtained on a third-party site rather than on the site on which an ad appears, which is akin to talking behind someone’s back; and deducing information about people (such as a pregnancy) from analytics when they haven’t declared it themselves. If marketers avoid those tactics, use data judiciously, focus on increasing trust and transparency, and offer people control over their personal data, their ads are much more likely to be accepted by consumers and help raise interest in engaging with a company and its products.

Keywords: Online Advertising; Customization and Personalization; Information; Customers; Attitudes;

Citation:

John, Leslie, Tami Kim, and Kate Barasz. "Ads That Don't Overstep: How to Make Sure You Don't Take Personalization Too Far." Harvard Business Review 96, no. 1 (January–February 2018): 62–69. View Details

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Pseudo-set framing—arbitrarily grouping items or tasks together as part of an apparent “set”—motivates people to reach perceived completion points. Pseudo-set framing changes gambling choices (Study 1), effort (Studies 2 and 3), giving behavior (Field Data and Study 4), and purchase decisions (Study 5). These effects persist in the absence of any reward, when a cost must be incurred, and after participants are explicitly informed of the arbitrariness of the set. Drawing on Gestalt psychology, we develop a conceptual account that predicts what will—and will not—act as a pseudo-set and defines the psychological process through which these pseudo-sets affect behavior, concluding that over and above typical reference points, pseudo-set framing alters perceptions of (in)completeness, making intermediate progress seem less complete. In turn, these feelings of incompleteness motivate people to persist until the pseudo-set has been fulfilled.

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I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice

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