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Motivating employee referrals: The interactive effects of the referral bonus, perceived risk in referring, and affective commitment.
- Source :
- Human Resource Management; Sep2018, Vol. 57 Issue 5, p1159-1174, 16p
- Publication Year :
- 2018
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- 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
Subjects
Details
- Language :
- English
- ISSN :
- 00904848
- Volume :
- 57
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Human Resource Management
- Publication Type :
- Academic Journal
- Accession number :
- 131862330
- Full Text :
- https://doi.org/10.1002/hrm.21895