In the war for talents, the need for appropriate tools to fill open positions with the right talents is becoming increasingly important for employers. AI-based technologies simplify recruiters' daily work and increase the efficiency of the recruitment process by replacing time-consuming approaches. However, little is known about the reactions of stakeholders to AI-based recruiting. Thus, this paper aims to identify personal and contextual factors that influence the acceptance of AI-based technologies in the recruitment process. Based on the interviews with recruiters, managers, and applicants involved in the recruitment process, we present that transparency, complementary features of the AI tools, and a sense of control play key roles in the acceptance of AI-based technology when used for recruiting. The findings contribute to research on the adoption of AI in the recruitment process and provide recommendations on the use of AI technologies when hiring talents.

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Agile software development projects still show a high failure rate. Despite a growing amount of research, underlying reasons for project performance currently remain rare. Drawing on the job demandsresources theory, we propose a theoretical model of work engagement in agile software development teams. Using structural equation modeling, we found that agile practices diminish job demands (perceived workload and role ambiguity) and support job resources (perceived meaningfulness and job autonomy). Job resources have been found to be positively related to work engagement in agile software development teams. Our research contributes to the limited empirical understanding on work engagement in agile software development. For practitioners, our model provides tools to effectively manage team members' work engagement.

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