How to achieve cooperation in employer referral networks
How to achieve cooperation in employer referral networks
When hiring, it is difficult for employers to assess the abilities and work ethics of candidates, because potential workers have little incentive to reveal their true characteristics (Autor, 2008; Rees, 1966; Stigler, 1962). One way of learning about candidates despite these information asymmetries is through common acquaintances referring candidates and providing trustworthy information. Referred candidates already passed a screen, tend to be better suited for the job and also may have more realistic job expectations (Bills, Stasio, & Gërxhani, 2017; Fernandez, Castilla, & Moore, 2000; Marsden & Gorman, 2001).
An important source providing information on potential employees are other employers (Saloner, 1985). It is for instance common to rely on reference letters when hiring (Abel, Burger, & Piraino, 2017). However, forming such a referral network also poses a cooperation problem to employers. After all, employers are potential competitors. Building a referral network is a classical cooperation dilemma: All employers would be better off if referrals would convey trustworthy information to make sure non-performing employers are excluded from the labor market. However, every individual employer has an incentive not to provide such information to its competitors. This paper analyzes the referral network of employers in two sectors, childcare and fiduciary in Switzerland, based on exponential random graph models. It examines which organizational characteristics (i.e. resources, prestige) and which endogenous dynamics (i.e. reciprocity) play a role in such referral networks. Preliminary results show that triadic closure ensures cooperation, and that more prestigious organizations are better connected.
Analyzing whom employers trust and how they form referral networks closes an important research gap. Previous studies have focused on the role of a firm’s current employees recommending candidates rather than on the role of other employers (see for instance the studies by Fernandez et al., 2000; Schram, Brandts, & Gërxhani, 2010). Referral networks among employers have hence received only scant attention (Bills et al., 2017; Marsden & Gorman, 2001). One exception is the seminal study by Gërxhani et al. based on experimental data. They show how the cost of ties affects how employer network forms (Gërxhani, Brandts, & Schram, 2013).
Based on the literature, resource complementarity (Mizruchi, 1993; Oliver & Ebers, 1998; Pfeffer, 1987), homophily (Marsden, 1988; McPherson, Smith-Lovin, & Cook, 2001), and reputation may facilitate cooperation networks among firms (Raub & Weesie, 1990). My own research has shown that gaining prestige may also be an important motive for firms to cooperate (Aerne, 2020). In addition to these individual-level factors, I am interested in the role of network dynamics. Actors connect to others based on the ties already formed. An example of such a network dynamic is actors’ tendency to connect unconnected others (brokerage across structural holes) (Burt, 1976, 2000; Buskens & Rijt, 2008). This dynamic is particularly beneficial when access to new information is important. In contrast, linking two actors previously indirectly connected through a third party (closure) is central in order to mitigate uncertainty (Coleman, 1988).
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When hiring, it is difficult for employers to assess the abilities and work ethics of candidates, because potential workers have little incentive to reveal their true characteristics (Autor, 2008; Rees, 1966; Stigler, 1962). One way of learning about candidates despite these information asymmetries is through common acquaintances referring candidates and providing trustworthy information. Referred candidates already passed a screen, tend to be better suited for the job and also may have more realistic job expectations (Bills, Stasio, & Gërxhani, 2017; Fernandez, Castilla, & Moore, 2000; Marsden & Gorman, 2001).
An important source providing information on potential employees are other employers (Saloner, 1985). It is for instance common to rely on reference letters when hiring (Abel, Burger, & Piraino, 2017). However, forming such a referral network also poses a cooperation problem to employers. After all, employers are potential competitors. Building a referral network is a classical cooperation dilemma: All employers would be better off if referrals would convey trustworthy information to make sure non-performing employers are excluded from the labor market. However, every individual employer has an incentive not to provide such information to its competitors. This paper analyzes the referral network of employers in two sectors, childcare and fiduciary in Switzerland, based on exponential random graph models. It examines which organizational characteristics (i.e. resources, prestige) and which endogenous dynamics (i.e. reciprocity) play a role in such referral networks. Preliminary results show that triadic closure ensures cooperation, and that more prestigious organizations are better connected.
Analyzing whom employers trust and how they form referral networks closes an important research gap. Previous studies have focused on the role of a firm’s current employees recommending candidates rather than on the role of other employers (see for instance the studies by Fernandez et al., 2000; Schram, Brandts, & Gërxhani, 2010). Referral networks among employers have hence received only scant attention (Bills et al., 2017; Marsden & Gorman, 2001). One exception is the seminal study by Gërxhani et al. based on experimental data. They show how the cost of ties affects how employer network forms (Gërxhani, Brandts, & Schram, 2013).
Based on the literature, resource complementarity (Mizruchi, 1993; Oliver & Ebers, 1998; Pfeffer, 1987), homophily (Marsden, 1988; McPherson, Smith-Lovin, & Cook, 2001), and reputation may facilitate cooperation networks among firms (Raub & Weesie, 1990). My own research has shown that gaining prestige may also be an important motive for firms to cooperate (Aerne, 2020). In addition to these individual-level factors, I am interested in the role of network dynamics. Actors connect to others based on the ties already formed. An example of such a network dynamic is actors’ tendency to connect unconnected others (brokerage across structural holes) (Burt, 1976, 2000; Buskens & Rijt, 2008). This dynamic is particularly beneficial when access to new information is important. In contrast, linking two actors previously indirectly connected through a third party (closure) is central in order to mitigate uncertainty (Coleman, 1988).
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