| In recent years,with the widespread application of algorithms in human resource management,many studies have begun to focus on people’s psychological reactions to this application,but have overlooked algorithmic dismissal as a new organizational behavior.Algorithmic dismissal has become a reality and a trend,accompanied by significant risks and ethical implications.Therefore,it is urgent to explore people’s psychological reactions to this phenomenon.Five studies were conducted with enterprise employees as participants.Based on mind perception theory,selfdetermination theory,and organizational justice theory,this study reveals the psychological effects and after-effects of algorithmic dismissal on individuals and the underlying mechanisms.At the same time,it also examines the psychological strategies for coping with this negative event from the perspective of dismissed employees,in order to better meet the opportunities and challenges of the algorithmic era.The pilot study verified the psychological impact of algorithmic dismissal on individuals by comparing their psychological acceptance and threat emotions towards algorithmic and human decision makers regarding dismissal decisions through withinsubject design.The results showed that individuals were less accepting of algorithmic dismissal and perceived stronger threat emotions than when they were dismissed by humans.Study 1,using between-subject design and adding resistance as an indicator,confirmed the findings of the pilot study.Study 2 explored the after-effects of algorithmic dismissal on individuals,namely,the impact of dismissal decisions made by the two types of decision makers on individual self-perceived employability and their willingness to conceal their job termination during job searching.The results showed that compared with being dismissed by humans,individuals expected lower possibilities of being re-employed after being dismissed by algorithms and were less willing to let potential employers know that they had been dismissed by algorithms.Study 3 focused on exploring the underlying mechanisms of the psychological impact of algorithmic dismissal based on mind perception theory,self-determination theory and organizational justice theory.A parallel chain mediation model was constructed,in which the effect of decision-maker type on acceptance/self-perceived employability could be mediated by the autonomy frustration and interactional justice which are both triggered by experience perception.When the decision maker was an algorithm,individuals perceived lower experience towards this decision maker,leading to an increase in the autonomy frustration and decrease in the interactional justice,ultimately reducing their acceptance of the dismissal decision and confidence in their future employability.Study 4 attempted to find a buffer for the negative effects of algorithmic dismissal from the perspective of dismissed employees,including two sub-studies.Study 4a found that compared with being dismissed by humans,individuals tended to view algorithmic dismissal as a hindrance rather than a challenge,according to their stress appraisal.Challenge stress appraisal played a moderating role between the type of decision makers and acceptance,such that individuals with low challenge stress appraisal were significantly less accepting of algorithmic dismissal than human dismissal.This effect did not exist for individuals with high challenge stress appraisal.Study 4b selected gig workers such as food delivery drivers and ride-hailing drivers,and initiated intervention group to promote challenge stress appraisal towards algorithmic dismissal.The results showed that compared with the neutral group,the intervention group exhibited higher acceptance and self-perceived employability towards algorithmic dismissal,indicating that viewing algorithmic dismissal as a beneficial challenge could help reduce its negative effects.In summary,this study reveals the psychological effects of algorithmic dismissal on individuals.It was found that individuals are less likely to accept algorithmic dismissal compared to human dismissal,and experience more threat emotions after being dismissed by an algorithm.Self-perceived employability also decreases,and individuals are less likely to disclose their previous algorithmic dismissal to potential new employers(hiding intentions in resumes).Furthermore,the mediating effects of experience perception to autonomy frustration and experience perception to interactional justice was found in the relationship between the type of decision maker and acceptance/self-perceived employability,and the challenge stress appraisal can act as a buffer.The psychological effects of algorithmic dismissal on individuals,mechanisms,and countermeasures discovered in this study can provide reference for further research in this field and provide inspiration for algorithm management practices in companies. |
