Referent Networks Predict Just Rewards

David Melamed, Yue Liu, Hyomin Park, Jingwen Zhong

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


This study introduces the referent network, the set of relations defined by knowing others reward levels, and makes initial predictions about how the structure of that network shapes perceptions of income fairness. Previous research recognizes that justice assessments are driven by social comparisons; yet there is a paucity of research on how the structure of interpersonal contacts shapes justice assessments. Using a social networks perspective, the arguments here suggest that the referent network affects social comparisons, which in turn affect justice assessments of rewards. This reasoning is also integrated with the notion that people make both local and referential comparisons when determining their just rewards. An experiment evaluates these arguments. Results show support for the argument linking network structures to justice assessments and partial support for the extension to local and referential comparisons. Supplemental analyses show how reward levels qualify the arguments. Implications and directions for future research are discussed.

Original languageEnglish
Pages (from-to)304-317
Number of pages14
JournalSociological Focus
Issue number4
StatePublished - 2 Oct 2018


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