Lock-In Effects in Online Labor Markets

Online platforms that implement reputation mechanisms typically prevent the transfer of ratings to other platforms, leading to lock-in effects and high switching costs for users. Platforms are able to capitalize on this arrangement, for example, by charging their users higher fees. In this paper, we theoretically and experimentally investigate the effects of platform pricing on workers' switching behavior in online labor markets and analyze whether a policy regime with reputation portability could mitigate lock-in effects and reduce the likelihood of worker capitalization by the platform. We examine switching motives in depth, differentiating between monetary motives and fairness preferences. We provide theoretical evidence for the existence of switching costs if reputation mechanisms are platform-specific. Our model predicts that reputation portability lowers switching costs, eliminating the possibility for platforms to capitalize on lock-in effects. We test our predictions using an online lab-in-the-field experiment. The results are in line with our theoretical model and show that platforms can capitalize on lock-in effects more effectively in a policy regime without reputation portability. We also find that reputation portability has a positive impact on worker mobility and the wages of highly rated workers. The data further show that the switching of workers is primarily driven by monetary motives, but perceiving the platform fee as unfair also plays a significant role for workers.

Ciotti, Fabrizio, Lars Hornuf und Eliza Stenzhorn (2024), Lock-In Effects in Online Labor Markets, Journal of Economics & Management Strategy