Sharing economy platforms bring individual buyers and sellers together to promote transactions between the two parties. Since most of the platforms include decentralized network of individual sellers who provide their own products or services, these lack standardized or established quality which may lead to quality uncertainty. Although sharing economy platforms rely on user-generated reviews and seller-provided information to provide trust between buyers and sellers, these would not completely reduce the quality uncertainty. In my dissertation, I examine the impact of platform-managed quality certification and simultaneous review system to find out how these mechanisms address quality uncertainty in the context of Airbnb. Leveraging a quasi-experimental design in combination with a machine learning algorithm, I find that the quality certification launched by Airbnb has differential impacts on consumers, property owners, and the platform. Also, I show how the reciprocity under the bilateral review system affects volume, valence, and semantic diversity of reviews. My findings have significant implications for researchers and practitioners who deal with quality management and review system designs especially within an online platform area.