History Dependence, Cohort Attachment, and Job Referrals in Networks of Close Relationships

Ayal Chen-Zion, James E. Rauch
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Abstract

We model network formation in a firm. Agents learn about the quality of their working relationships with each other. Their good relationships become their networks. Accumulating relationships becomes increasingly costly, however. Over time agents become less open to forming relationships with others unknown to them, leading their networks to be front-loaded with agents they met near the beginning of their careers. The interaction of this dynamic with turnover yields predictions about the time pattern of history dependence in an agent’s network as a function of his tenure. Mutual openness of newly arrived agents in a firm also leads to the cross-section prediction of “cohort attachment,” a tendency for members of an agent’s hiring cohort to be disproportionately represented in his network. When members of a network formed within a firm are subsequently split across many firms, the desire to renew their successful working relationships can lead to job referrals. Former co-workers who provide referrals will be drawn disproportionately from the referred workers’ hiring cohorts at their previous employers.
亲密关系网络中的历史依赖、群体依附与工作推荐
我们建立了公司网络形成的模型。代理人了解他们彼此之间的工作关系的质量。他们的良好关系成为他们的网络。然而,积累人际关系的成本越来越高。随着时间的推移,经纪人变得不太愿意与不认识的人建立关系,这导致他们的网络中充斥着他们在职业生涯开始时认识的经纪人。这种动态与离职的相互作用产生了关于代理网络中历史依赖的时间模式的预测,作为其任期的函数。公司中新来的代理人的相互开放也会导致“群体依附”的横断面预测,这是一种代理人雇佣群体的成员在其网络中不成比例地代表的趋势。当公司内部形成的网络成员随后分散到许多公司时,更新他们成功的工作关系的愿望可能会导致工作推荐。提供推荐的前同事将不成比例地从被推荐的员工在前雇主的招聘团队中挑选。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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