The Impact of Algorithm Management on Employee Job Satisfaction: Exploring the Mediating Role of Job Autonomy and the Moderating Effect of Employee Attitude: A Case Study on Two Premier Universitas Muhammadiyah (UMS and UMY)

Abstract

This study delves into the intricate relationships among algorithm management, job autonomy, employee attitudes, and job satisfaction in the higher education landscape of Universitas Muhammadiyyah in Indonesia (UMS and UMY). Employing a quantitative methodology with a sizable sample of 550 individuals, comprising 250 respondents, and data collection encompassed surveys and interviews, yielding 215 responses. Ensuring the reliability of survey tools through test-retest and Cronbach's alpha analysis utilized Microsoft Excel, SPSS, and Smart PLS. Key hypotheses were tested, highlighting the positive impact of algorithm management on job autonomy. Additionally, the study explored job autonomy's positive effect on employee job satisfaction and its mediating role in the relationship between algorithm management and Job satisfaction. Employee attitudes were scrutinized as moderators of these relationships, and their positive influence on job satisfaction was established. The findings reveal the significant implications of algorithm management on both job autonomy and job satisfaction. Job autonomy was found to empower employees, leading to increased satisfaction and reduced stress, and employee attitude has no connection between algorithms management and job satisfaction. Therefore, these findings illuminate the intricate interplay between algorithm management, job autonomy, employee attitudes, and job satisfaction in the context of higher education.