Platforms and Limits to Network Effects

Posted by D. Daniel Sokol

Hanna Halaburda (Harvard Business School, Strategy Unit) and Mikolaj Jan Piskorski (Harvard Business School, Strategy Unit) explore Platforms and Limits to Network Effects.

ABSTRACT: We model conditions under which agents in two-sided matching markets would rationally prefer a platform limiting choice. We show that platforms that offer a limited set of matching candidates are attractive by reducing the competition among agents on the same side of the market. An agent who sees fewer candidates knows that these candidates also see fewer potential matches, and so are more likely to accept the match. As agents on both sides have access to more candidates, initially positive indirect network effects decrease in strength, reach their limit and eventually turn negative. The limit to network effects is different for different types of agents. For agents with low outside option the limit to network effects is reached relatively quickly, and those agents choose the platform with restricted number of candidates. This is because those agents value the higher rate of acceptance more than access to more candidates! . Agents with higher outside option choose the market with larger number of candidates. The model helps explain why platforms offering restricted number of candidates coexist alongside those offering larger number of candidates, even though the existing literature on network effects suggests that the latter should always dominate the former.