Glossary · Behavioral Economics
Affect Regulation
also: mood repair · retail therapy · emotion regulation
Definition
Affect regulation in consumer behavior is the use of purchase decisions to repair, sustain, or adjust mood states. Atalay and Meloy (2011) demonstrated that unplanned purchases reliably improve self-reported affect for hours after the transaction, with the effect concentrated in indulgence categories like cosmetics, apparel, and accessories.
Affect-regulatory shopping is one of the most robust findings in consumer psychology. Atalay and Meloy's 2011 paper in Psychology and Marketing established the empirical baseline; Rick, Pereira, and Burson (2014) replicated and extended it in the Journal of Consumer Psychology. The behavioral signature in e-commerce data includes basket creation in the 22:00 to 02:00 window, single-item baskets, premium-tier outliers in otherwise mid-tier histories, and return-then-repurchase loops. The pattern is healthy in moderation and pathological at the high-frequency tail, where it overlaps with compulsive buying disorder. Mick and DeMoss's 1990 phenomenological study of self-gifts mapped four contexts (reward, therapy, holiday, incentive), with therapy gifts dominated by personal-care and cosmetic items in female samples.
Essays on this concept
- Behavioral Economics
The Mood Index: Reading Affect, Compulsivity, and Identity Signals in Cosmetics E-commerce Baskets
Cosmetics is the only consumer e-commerce category where four clinical psychology mechanisms operate at unusually high intensity at the same time. Each one leaves a distinct fingerprint in checkout data. Standard segmentation models miss most of it.
- Behavioral Economics
Loss Aversion Asymmetry in Digital Marketplaces: Evidence from A/B Tests Across 14 Million Users
Prospect theory predicts that losses hurt 2.25x more than gains. Our data across 14 million marketplace users shows the real ratio depends on something economists have overlooked.
- Behavioral Economics
Hyperbolic Discounting and Subscription Fatigue: A Quantitative Framework for Churn Prediction
How time-inconsistent preferences explain why subscribers cancel, and a mathematical framework that predicts churn windows before they open.
Related concepts
Authoritative references