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Crowdworking (CW) or paid digital work on intermediary internet platforms is usually associated in public and academic discourses as a highly flexible work organization without long-term working relationships. This view misses the point that although CW platforms are working environments without an employment contract, platforms and their registered crowdworkers establish long-term working relationships often stretching over years. In addition, some platforms that deal with challenging tasks offer long-term compensation based on the individual rating levels of the crowdworkers and, therefore, show some extent of self-commitment. Nevertheless, research on commitment and rating-based compensation systems (RBCS) on CW platforms is rather rare. This paper examines how RBCSs on CW platforms motivate and commit crowdworkers on the platform; whether crowdworkers report higher affective and calculative commitment to a platform and perform better when the platform operates a RBCS; and whether the affective and calculative commitment of crowdworkers and their performance increase with their rating level on a CW platform. It is argued that a RBCS uses elements of internal labor markets and deferred compensation, both concepts developed for regular employment. In addition, goal-setting theory can explain how a platform hierarchy and its associated rewards set desirable goals for crowdworkers, and why these motivate and commit in the long run. It is therefore assumed that a CW platform with a RBCS motivates and commits crowdworkers much like a regular organization its employees. The hypotheses are tested with cross-sectional questionnaire data that includes 378 crowdworkers involved in text creation tasks from four CW platforms, two of which have implemented a RBCS, and the other two non-reputational fixed task prizes. The analyses show significant positive effects of a RBCS ...