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- Title
Motivating employee referrals: The interactive effects of the referral bonus, perceived risk in referring, and affective commitment.
- Authors
Pieper, Jenna R.; Schlachter, Steven D.; Greenwald, Jessica M.
- Abstract
Research has provided compelling evidence that employee referrals result in positive outcomes for organizations and job seekers, but it has been limited on how organizations can increase the likelihood of obtaining employee referrals. Using the theoretical lens of social exchange theory and tenets from expectancy theory, we tested two common assumptions of most employers: A referral bonus motivates employees to refer, and higher bonus amounts incite greater likelihood of referring. We theoretically developed and tested a model integrating the effects of perceived risk in referring and affective commitment and their interactions with the referral bonus to better explain the likelihood of referring. Results largely supported our predictions. Referral bonus presence, referral bonus amount, and affective commitment positively related to likelihood of referring, while perceived risk in referring negatively related to likelihood of referring. The findings also suggest that larger referral bonuses can help offset perceived risk in referring and low affective commitment levels. We contribute to the literature by developing theory, expanding the scope of the current referral literature, and offering a quantitative examination of previously theorized variables in the referring process. We conclude with suggestions to practicing managers on ways to improve the motivating potential of their employee referral programs.
- Subjects
UNITED States; HYPOTHESIS; COMMITMENT (Psychology); CONFIDENCE intervals; STATISTICAL correlation; EMPLOYEE recruitment; MOTIVATION (Psychology); PROBABILITY theory; PSYCHOLOGY; SCALE analysis (Psychology); SELF-evaluation; STATISTICAL hypothesis testing; SURVEYS; MATHEMATICAL variables; WAGES; THEORY; MULTIPLE regression analysis; CROSS-sectional method; DATA analysis software; DESCRIPTIVE statistics
- Publication
Human Resource Management, 2018, Vol 57, Issue 5, p1159
- ISSN
0090-4848
- Publication type
Article
- DOI
10.1002/hrm.21895