Employee Referral Dynamics in Social Hiring: Evidence from LinkedIn

Abstract

Social hiring describes a job hiring process wherein employers and job seekers rely on social network sites to engage and inform each other. According to LinkedIn, its network comprises over 700 million professionals, and many recruiters utilize LinkedIn to identify qualified job candidates. Despite the growth of social hiring, we do not clearly understand referral dynamics in social hiring. This study empirically investigates how employees make referrals based on their LinkedIn networks. In particular, given that a common tactic of job seekers is to network with those in similar industries and functions, we aim to offer insight into how job similarity between an employee and a job seeker affects an employee’s referral decision. While employees in similar fields are valuable information sources to job seekers, it is unclear whether they are a promising source of referrals. Because qualified job candidates in similar fields may become future competitors, employees may be reluctant to refer qualified job candidates to avoid future competition. Our analysis using data from a global consulting company shows that the likelihood of referral decreases as job similarity between an employee and a job candidate increases. We further find that the adverse effect of job similarity on referrals weakens as an employee’s hierarchical position becomes higher than that of a candidate. This result supports the proposed competition mechanism because the adverse job similarity effect diminishes as an employee is less likely to compete directly with a job candidate. Although one might expect that gender homophily dilutes this competitive force, we found that gender homophily is effective only when a candidate is the same gender as an employee of a minority gender.

Keywords: Social hiring, professional online network, employee referral, job similarity, gender homophily