"I’ll Have One of Each": How Separating Rewards into (Meaningless) Categories Increases Motivation

DSpace/Manakin Repository

"I’ll Have One of Each": How Separating Rewards into (Meaningless) Categories Increases Motivation

Citable link to this page

. . . . . .

Title: "I’ll Have One of Each": How Separating Rewards into (Meaningless) Categories Increases Motivation
Author: Wiltermuth, Scott S.; Gino, Francesca

Note: Order does not necessarily reflect citation order of authors.

Citation: Wiltermuth, S., and F. Gino. "'I'll Have One of Each': How Separating Rewards into (Meaningless) Categories Increases Motivation." Journal of Personality and Social Psychology (forthcoming).
Full Text & Related Files:
Abstract: We propose that separating rewards into categories can increase motivation, even when those categories are meaningless. Across six experiments, people were more motivated to obtain one reward from one category and another reward from another category than they were to obtain two rewards from a pool that included all items from either reward category. As a result, they worked longer when potential rewards for their work were separated into meaningless categories. This categorization effect persisted regardless of whether the rewards were presented using a gain or loss frame. Using both moderation and mediation analyses, we found that categorizing rewards had these positive effects on motivation by increasing the degree to which people felt they would "miss out" if they did not obtain the second reward. We discuss implications for research on motivation and incentives.
Other Sources: http://www.apa.org/pubs/journals/psp/index.aspx
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10018933

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters