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Be Fit and Be Strong: Mastering Self-Regulation through Regulatory Fit

Authors: Hong, Jiewen; Lee, Angela Y.;

Be Fit and Be Strong: Mastering Self-Regulation through Regulatory Fit

Abstract

This research examines the effect of regulatory fit on self-regulation. People experience regulatory fit when their strategy of goal pursuit fits (vs. conflicts) with their regulatory focus. Four experiments provide support for the hypothesis that regulatory fit improves whereas regulatory nonfit impairs self-regulatory performance. These results were obtained across multiple self-regulatory tasks that included a handgrip exercise to test physical endurance (experiment 1), a choice between a healthy and a decadent snack to test willpower in the face of temptation (experiments 2 and 3), and a health-related compliance decision to demonstrate self-regulation (experiment 4). Intensified motivation seems to be the mechanism underlying the regulatory fit effect. I magine Susan and Jim searching online for a new cellular phone. Susan wants to find a phone that ensures her calls get through even when the signals are patchy, whereas Jim’s goal is to get a phone that makes him stand out and look good. Both Susan and Jim make their selection based on an analysis of the features of the phones and place their orders. An interesting question that this research addresses is whether Susan and Jim are more or less likely to head out to the gym for a workout when they log off—would their online shopping experience affect a subsequent behavior that requires self-regulation? Consumer self-regulation or the lack thereof has captured the interest and attention of researchers in the last decades. Research has examined how consumers engage in impulse buying (e.g., O’Guinn and Faber 1989; Rook 1987; Vohs and Faber 2007), make decisions based on affective versus cognitive response (e.g., Drolet and Luce 2004; Shiv and Fedorikhin 1999), and indulge in hedonic rather than utilitarian consumptions (Kivetz and Simonson 2002). More recently, researchers have begun to examine factors that influence self-regulation. In particular, consumer self-regu

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China (People's Republic of)
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
159
Top 1%
Top 10%
Top 10%
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