Abstract: Online platforms like AirBnB and Upwork generate revenue by matching prospective buyers and sellers and extracting commissions from completed transactions. Disintermediation, where sellers transact offline with buyers to bypass commission fees, can lead to significant revenue losses for these platforms. For example:
a) the talent outsourcing platform ZBJ estimates that up to 90% of their service providers’ transactions may occur off-platform
b) a recent study estimates that online labour markets (e.g., cleaning platforms) lose out on 25% of potential transactions due to disintermediation
c) in the extreme case, disintermediation can threaten the viability of the platform itself as in the case of the home-cleaning platform Homejoy, which was shut down in 2015.
In this talk, we will use a modelling and analytical framework to examine how disintermediation impacts the platform’s incentives, commission rate, and revenue. First, we argue that in the presence of disintermediation, platforms have strong incentives to keep its review systems noisy as providing more information about risky buyers can amplify disintermediation and hurt platform revenue. This goes against conventional wisdom that lowering information asymmetry can benefit platforms by enabling more efficient matches. Second, and somewhat surprisingly, we show that the risk of disintermediation may actually force platforms to increase the commission rate, i.e., the platform may not lower the commission rate to encourage users to stay online. Instead, they may look to make up for lost revenue by overcharging the remaining users. Finally, motivated by platforms like Thumbtack which have migrated from commissions to charging sellers for “leads”, we examine whether platform-access fees or seller-side subscriptions can hedge against losses from disintermediation. While access fees do indeed reduce the incentives for disintermediating, they may drive away sellers who face too much uncertainty, and as a result, fall short of recovering the full revenue lost due to disintermediation.
About the Speaker: Shreyas Sekar is an Assistant Professor of Operations and Analytics at the Rotman School of Management, University of Toronto. Prior to this, he was a Postdoctoral Fellow at the Harvard Business School. His research tackles questions pertaining to revenue management that arise in the context of online platforms, specifically in relation to understanding novel pricing models, and making sure that platforms are robust to strategic and fraudulent behaviour. Shreyas received his doctoral degree in Computer Science from Rensselaer Polytechnic Institute in 2017, where he was awarded the Robert McNaughton Prize for the best graduate dissertation. He is also the recipient of funding grants from the TD-Management Lab and NSERC and best paper (finalist) awards from ACM and INFORMS. Shreyas has also worked closely with platforms such as Wayfair and Freelancer in the past to help design data-driven policies.