Digital platforms: how do supply and demand interact to create value?

The takeoff point for our analysis is the assumption that users are generally more attracted to platforms with big ecosystems that offer additional services and good value for the money. With our theoretical model, we try to unpack how the strategies of a platform provider shape the choices of developers, which in turn are what underpin the structure of a digital ecosystem and its evolution over time. 

Striking the right balance between the ecosystem size and the incentives to innovate at every level of the technological environment: this is the prerequisite for creating competitive digital platforms. When users decide to join a platform, this naturally serves as a valid metric to gauge how attractive it actually is. They’ll prioritize its technological characteristics, or the products and services that complementors provide to differing degrees.

The central focus of our model is platform pricing: what end users are charged and how much developers are paid in royalties. When users prioritize a platform’s technology, the provider will up the price they pay and cut royalties for partners to push them to come up with more innovative complements. On the other hand, if the ecosystem’s compliments count most for users, the provider will opt to lower their price and boost developers’ royalties. Either way, end users are subsidized because they are charged below cost.

Prior literature shows that pricing plays a key role, especially during the early development of an ecosystem. Our study goes further by demonstrating that this aspect is fundamental in later life stages as well, to incentivize supply and demand of innovative complements within the context of a technological environment.  Factor

Our theoretical model reveals that user preferences impact the strategic choices of a platform, which in turn influence developers’ decisions and ultimately affect the capacity of the ecosystem to create value for all stakeholders. But what factors prompt users to modify their behavior? For example, in the initial platform development stages, users tend to focus more on the quality of the products and services that developers offer, whereas later they look at the size of the ecosystem. Our analysis also takes into account the dynamics of change in user preferences throughout the life cycle of a digital ecosystem.

Another factor that makes a difference is the platform’s competitive scenario.  It’s one thing if the platform is a market leader, and quite another if a number of platforms are vying for the top spot. In the first case, the leading digital platform looks more interesting to complementors, who will compete for its end users. In the second case, on the other hand, with competition between platforms being more heated, we find a trade-off between size and innovation that’s even more tenuous.

The main takeaway of our model is that it shows how user preferences actually shape the very structure of a digital ecosystem and the strategies that drive its development. In our analysis, we demonstrate the key role of demand-side economies of scale in determining the intensity of the indirect network effects.

A fruitful path for future research would be to empirically evaluate the role that internal network effects play in the trade-off between ecosystem size and incentives to innovate, distinguishing between contexts in which one or the other is more important for users. Such preferences may also differ depending on the type of platform.

Finally, in light of the recent debate on the role of technology giants, to further our understanding of the value created by platforms and value distribution among its participants, we could dig deeper into the competitive strategies within an ecosystem and among multiple ecosystems.