Employment relationships in algorithmic management: A psychological contract perspective. (January 2022) - Tomprou, Maria; Lee, Min Kyung
Abstract: Algorithms increasingly automate or support managerial functions in organizations, with implications for the employee-employer relationship. We explored how algorithmic management affects this relationship with a focus on psychological contracts, or employees' perceptions of their own and their employers' obligations. Through five online experiments, we investigated how organizational agent type—algorithmic versus human—influenced one's psychological contract depending on the organizational inducement type—transactional versus relational. We explored psychological contracts in two stages of employment: during early phases, such as recruiting (Studies 1 and 2) and onboarding (Studies 4 and 5), when the agent explains the inducements to the employee; and during employment, when the agent under-delivers the inducements to varying degrees (Studies 3–5). Our results suggest that agent type did not affect psychological contracts around transactional inducements but did so for relational inducements in the cases of recruiting and low inducement delivery (Studies 1–5). Algorithmic agents signaled reduced employer commitments to relational inducements during recruiting (Study 1). Using human agents resulted in greater perceived breach when delivery of relational inducements was low (Study 5). Regardless of inducement type, turnover intentions were higher when the human agent under-delivered compared to the algorithmic agent (Study 5). Our studies show how algorithmic management may influence one's psychological contract. Highlights: Human agents increase perceived employer commitments in relational inducements in recruiting. No difference between the agents in perceived breach in moderate inducement delivery. Algorithmic agents reduce perceived breach in low relational inducement delivery. Algorithmic agents reduce turnover intention in low inducement delivery.