Debunking the Myth of Network Effects

What a merger between two pet-sitting platforms can tell us about network effects

Platform Papers is a monthly blog about platform competition and Big Tech. Blogposts are written by prominent scholars based on their research. The blog is linked to, an online repository that collects and organizes academic research on platform competition.

This blog is written by Chiara Farronato

How many times have you heard managers, regulators, and academics talk about network effects in digital platforms? Network effects arise when the value a participant derives from joining a platform is an increasing function of the number of other participants on the same platform. Network effects are as old as your grandparents’ home telephone. Back then, there was no use in a phone if none of the people you wanted to talk to also had it. And the more friends and family had a phone, the more you benefited from buying one to communicate with them.

Network effects

Fast forward almost 150 years, and many of the most valuable companies today benefit from network effects. Meta, Facebook’s parent company, is currently valued at USD 780 billion thanks to its ability to attract almost 3 billion active monthly users, which in turn make the platform attractive to millions of advertisers. The same is true for Amazon Marketplace, where millions of sellers and hundreds of millions of buyers exchange products globally.

When network effects are strong, having market participants join a single dominant platform rather than spreading across many competing platforms maximizes value creation. This implication was not lost on Theodore Vail, the fourth president of the Bell Telephone Company, who in the early 1900’s, used network effects to argue that Bell Telephone should have a monopoly on telephone networks. Since then however, network effects have been used to justify launch strategies and acquisition decisions across a variety of industries, not all of which in reality exhibit strong network effects.

How can we quantify the strength of network effects? The truth is: it’s hard. In theory, one would want to measure participants’ utility and how it varies as the number of platform participants changes. However, changes in the number of platform participants are often correlated with other events that may affect participants’ value from a platform. Think about Amazon Prime Day, when many deals are available to Prime members. On those days, you’re likely going to see a sizable increase both in the number of sellers listing products and people shopping on Amazon. But the increase in transaction volume—a clear sign that buyers and sellers benefit from Amazon—is due to the presence of deals and discounts rather than network effects.

Dog eat dog: The merger of Rover and DogVacay

In a Management Science paper that I wrote in collaboration with Jessica Fong and Andrey Fradkin, we found an ideal setting where a platform experienced a sudden increase in the number of its participants. Rover, the largest pet sitting platform in the US, acquired DogVacay, its largest competitor, in the Spring of 2017. By the summer of the same year, Rover had shut down DogVacay, and asked pet owners and sitters to migrate to

Because pet owners typically look for pet sitters close to their home, the geographic variation in the size of the two competing platforms implies that Rover experienced larger increases in the number of platform participants in some cities—those where DogVacay was large—compared to others. Thus, if network effects were real, we would expect greater benefits in cities where Rover experienced a larger influx of participants from DogVacay. This is indeed true in our context, where we find clear evidence of network effects. But our results do not end there.

As much as pet owners and sitters benefit from being able to find a trading partner with whom to transact, and the likelihood of that match increases when there are more pets and sitters to choose from, there’s a reason why not all pet owners and sitters hadn’t already converged to a single dominant platform. Academics call that reason “horizontal preferences.” The fact that some consumers may prefer red shoes while others may opt for blue shoes is an example of horizontal preferences. If people have horizontal preferences over Rover and DogVacay (perhaps because of their web design, or brand reputation), eliminating DogVacay may hurt pet owners and sitters for whom DogVacay was their favorite alternative. And if this effect were too large, it could end up offsetting the network benefits of the merger.

If horizontal preferences were strong, we would expect that pets and sitters from DogVacay  would have a harder time finding matches on Rover, and would leave as a result. Our analyses strongly support this hypothesis. But, why would DogVacay users prefer DogVacay? After all, both platforms were designed to match pets with sitters, with similar pricing, search algorithms, payment systems, and review mechanisms.

We find evidence for repeat exchanges and switching costs to play an important role in explaining why DogVacay users left after the merger with Rover. Owners often prefer their pets to stay with the same sitter over time. The migration to a new platform likely made finding the same sitter harder, especially if the sitter left altogether rather than migrating to Rover. Owners may also find their previous sitters offline, making disintermediation an additional driver of attrition. Surprisingly, new users had similar experiences, suggesting that horizontal preferences do not simply originate from experience gained while using a particular platform.            

Managerial and policy implications

Overall, we show that platform differentiation is in practice an important factor in offsetting network effects. Our results imply that a single dominant platform may not be as effective as multiple platforms, both from a strategic and antitrust perspective. The antitrust perspective is more obvious. Regulators are interested in ensuring that consumers have multiple options to choose from, because that creates healthy price competition and incentives for companies to keep innovating. Even though antitrust authorities have historically been hesitant to get involved in regulating digital platforms, the tide has already changed in Europe with the passing of the Digital Markets Act, and may soon be changing in other countries. After all, even the Bell telephone monopoly system was eventually dismantled.

The strategic perspective is more subtle. Network effects are often assumed to be large enough to warrant mergers and acquisitions strategies that progressively concentrate activity on a single dominant digital platform. However, the simple presence of network effects is not sufficient to justify these strategies. Instead, it may be beneficial for a company to operate multiple platforms rather than combining them. In fact, there are many instances of acquisitions where the acquired platforms remained operative—e.g., Zillow and Trulia, or the many online travel sites within the Booking Holdings group.

Beyond mergers, our study calls into question the importance of a first-mover advantage and the likelihood of a winner-take-all equilibrium, which have historically pushed platforms to invest heavily to achieve scale fast and deter competitive entry. In fact, despite network effects, entry and competition are likely in equilibrium, where multiple platforms can coexist and new platforms can successfully enter by identifying niche consumer preferences. This may be why in the ride-sharing market, Uber and Lyft are still competing, and why Alto may end up becoming a thriving alternative for the luxury segment.

In this evolving narrative of network effects, the true strength lies not solely in the number of participants, but in the variety of choices. The finale of this story is yet unwritten, but it’s clear that a balance of platform size and platform variety will guide the next act in the ever-changing digital landscape.

This blog is based on Chiara’s research forthcoming in Management Science, which is included in the Platform Papers references dashboard:

Farronato, C., Fong, J., & Fradkin, A. (2023). Dog eat dog: Balancing network effects and differentiation in a digital platform merger. Management Science.

Platform Papers is edited and published by Joost Rietveld.