This research analyzes how digital technologies contribute to improving the successive stages of the recruitment process: identifying, selecting, and retaining talented people. E-recruitment is an emerging and polymorphous phenomenon that starts with identification of candidates on social networks, continues through gamification of recruitment and job interviews with chatbots, and ends by matching a candidate and a job using artificial intelligence. These technologies are particularly useful for social businesses looking to recruit not only skilled people, but above all employees who have behaviors and values that match their mission. The methodology is based on grounded theory, participant observation, and qualitative data collection. A multiple case study is designed to analyze, compare, and combine several technologies dedicated to recruitment: (1) a social network with LinkedIn, (2) a MOOC with Udacity, (3) a serious game called Reveal from L'Oréal, (4) a chatbot called Ari from TextRecruit, and (5) a massive data analysis matching system with Randstad.tech. The discussion examines the respective performance and limits of these tools and their convergence via a progressive integration that leads to an uberization of recruitment. Managerial recommendations are formulated to support recruiters in their adoption of e-recruitment.

这项研究分析了数字技术如何为改善招聘流程的后续阶段做出贡献：识别，选择和留住人才。电子招聘是一种新兴的多态现象，其始于在社交网络上识别候选人，然后通过聊天机器人的招聘和求职面试游戏化，一直持续到通过使用人工智能将候选人与工作相匹配而结束。这些技术对于希望不仅招募技术人员，而且最重要的是具有符合其使命的行为和价值观的员工的社会企业，特别有用。该方法基于扎根的理论，参与者的观察和定性的数据收集。旨在研究，比较和组合几种专门用于招聘的技术的多案例研究：揭示了从欧莱雅，（4）被称为聊天机器人阿里从TextRecruit，和（5）一个海量数据分析匹配系统Randstad.tech。讨论将探讨这些工具各自的性能和局限性，以及通过逐步整合（导致招募工作繁琐）而实现的融合。制定了管理建议，以支持招聘人员采用电子招聘。