A Systematic Literature Review of the Relationship Between Performance Management and Job Satisfaction in the Sharing Economy

The research paper explores the connection between the performance management and job satisfaction in the sharing economy using systematic literature review (SLR). The accelerated growth of workplaces in platform format has altered the past trend of work, now performance measurement algorithms that act under the algorithm basis have a tremendous influence on the experiences of working population. With the PRISMA framework, 200 studies were in total first identified using major academic databases. After the comprehensive screening and elimination procedure, 15 relevant studies published within the years 2016-2025 were selected as the ones to be included in the qualitative synthesis. The results show that algorithmic systems, such as ratings, rankings, and efficiency-based measures, are predominant in performance measurement of the sharing economy. Although these systems improve operational efficiency and quality of service, they increase performance pressure and decreased perceived autonomy. The most significant aspects that determine job satisfaction include flexibility, income stability, autonomy and platform fairness. The findings also suggest that there is a complex and situation-specific relationship between performance and satisfaction with positive and negative impacts based on the conditions of the platforms. The research adds value to the literature in terms of offering a comprehensive insight into the performance- satisfaction nexus and of the dual role of algorithmic management. It also provides practical and policy implications to the designing of balanced and sustainable platform-based work systems.