Lock-in effects in online labor markets


Online platforms that implement reputation mechanisms usually prevent the transfer of ratings to other platforms, leading to lock-in effects and high switching costs for users. This situation can be capitalized by platforms, 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 further examine switching motives more thoroughly and differentiate between monetary motives and fairness preferences. Theoretically, we provide evidence for the existence of switching costs if reputation mechanisms are platform-specific. The model predicts that reputation portability lowers switching costs, eliminating the possibility for platforms to capitalize 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 the absence of reputation portability leads to worker lock-in, which can be capitalized by platforms. Moreover, reputation portability has a positive impact on 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.

R&R Journal of Economics & Management Strategy