Algorithmic performance appraisal intensity in hospitals: implications for professional autonomy and innovative work...

Area of Science:

• Healthcare Management
• Organizational Psychology
• Human-Computer Interaction

Background:

• Hospitals increasingly utilize algorithmic systems for employee appraisal.
• These systems aim to enhance consistency and efficiency in performance evaluation.
• Concerns exist regarding potential negative impacts on professional autonomy and innovation.

Purpose of the Study:

• To examine the relationship between algorithmic performance appraisal intensity and medical professionals' autonomy and innovative work behavior.
• To test the moderating role of algorithmic transparency in these relationships.

Main Methods:

• Three studies were conducted: a vignette experiment (N=240), a two-wave survey (N=287), and a three-wave multisource design (N=273).
• Methods included between-subjects comparisons, mediation analysis, and moderated mediation analysis.
• Data were collected through experiments and surveys, with supervisor ratings for innovative work behavior in Study 3.

Main Results:

• High appraisal intensity negatively impacted perceived professional autonomy in Study 1 and Study 3.
• Professional autonomy consistently predicted innovative work behavior across studies.
• Algorithmic transparency was positively associated with autonomy but did not moderate the effects of appraisal intensity.

Conclusions:

• Intensive algorithmic appraisal generally constrains professional autonomy, while autonomy supports innovation.
• Algorithmic transparency can support autonomy but does not fully mitigate the negative effects of intense algorithmic control.
• Hospitals should integrate human judgment and view transparency as a supportive feature, not a complete solution.