The Benefit Of Network Effects For Lyft And Uber
Jet Hardie
Blog Post 3
The article, “The power Of Network Effects: why they make such valuable companies, and how to harness them” begins by outlining exactly what network effects are and what different types of network effects exist. According to the article, the definition of a network effect is something (usually a product) that illustrates a positive network effect when more usage of the product by any user increases the product’s value for other users. For clarity sake, the umbrella term “network effects” encompasses four distinct versions of how the effects can take place and their dynamics change according to their application. The four specific types of network effects are: direct, indirect, two-sided and local. I will focus on the two-sided network effect for this post by below are the definitions of all four types.
- Direct Network effects
- This is the simplest form of network effects, what this means is an increase in usage leads to an increase in value. An example of this could be a telephone service, as the number of people who use the telephone service increase so does its value as people can easily communicate with one another.
- Indirect Network Effects
- This refers to the increased usage of a product brining about the creation of increasingly valuable complementary goods which in turn increases the value of the original product. An example could be the more people buy Apple products the company will be able to create new and improved apps or software updates that users would be able to utilize to improve their experience and functioning ability.
- Two-sided Network Effects
- This refers to the increase in usage of a product by one set of users which leads to the increase in value of a complementary products to a different set of users. Examples of this are detailed below the definition section.
- Local Network Effects
- This refers to the microstructure of an underlying network of connections which often influences how much the actual network effects matter. An example of this would be a new homeowner in Ithaca would influence the Ithaca network effect but does not influence the Boston network effect. This highlights how a local product illustrates its local network effects when each user in the network is directly influenced by the decisions of a small group of people, in this case the new homeowner.
The two-sided network effect is most interesting to me because it applies to a marketplace populated with companies like Uber, Lyft and Airbnb. The two-sided network effect is illustrated in the company models of Uber and Lyft in the following way. Both companies will provide a sufficient number of drivers as to lower the potential waiting times for their respective clients – the riders. With the ample supply of drivers and minimal waiting times the drivers will be able to complete more trips which in turn leads to increased revenues. Due to the high ride rate and potential to increase ones earning this model will encourage more people to become drivers for Uber and Lyft. With the further increase in drivers the waiting times are further reduced as are the fares of the rides. As one can see if model remains as such, it is favorable for the riders in terms of short waiting times and low costs and there will be a higher demand for drivers – these drivers would be incentivized to join Uber or Lyft as a result of the possibility of a higher earning potential created by the increased demand for rides. One could almost think of the two-sided network effect as a positive feedback loop, should the demand and supply be sufficient as to render positive incentives and outcomes to both parties.
The two-sided network effect is powerful because the feedback loop allows the company (in this case Uber or Lyft) to amass revenue quickly. With this additional revenue the company is able to create new products or add software updates to their apps which will improve the usability or experience of the product for their users. This illustrates the idea of the creation of positive complementary services. A specific example of a complementary service that could arise from Uber of Lyft benefitting from a two-sided network effect is the creation of UberEats. The more people want to use Uber the more drivers will want to join the company which will allow the company to fully “staff” their UberEats division which in turn allows for better service and higher satisfaction for the users – and so the cycle of mutual benefit will continue.
In conclusion it is easy to see how powerful network (especially two-sided) effects can be for companies. Should the conditions be right – both parties benefit from the product and thus there will be continued incentive to use the product which ultimately leads to further benefits for both parties in the form of complementary services. This “win-win” type of situation is ideal for companies to further their hold or domination of a specific marketplace.