In economics, a network effect (also called network externality or demand-side economies of scale) is the phenomenon by which the value or utility a user derives from a good or service depends on the number of users of compatible products. Network effects are typically positive feedback systems, resulting in users deriving more and more value from a product as more users join the same network. The adoption of a product by an additional user can be broken into two effects: an increase in the value to all other users (total effect) and also the enhancement of other non-users' motivation for using the product (marginal effect).
Network effects can be direct or indirect. Direct network effects arise when a given user's utility increases with the number of other users of the same product or technology, meaning that adoption of a product by different users is complementary. This effect is separate from effects related to price, such as a benefit to existing users resulting from price decreases as more users join. Direct network effects can be seen with social networking services, including Twitter, Facebook, Airbnb, Uber, and LinkedIn; telecommunications devices like the telephone; instant messaging services such as MSN, AIM or QQ; or even Wikipedia itself. Indirect (or cross-group) network effects arise when there are "at least two different customer groups that are interdependent, and the utility of at least one group grows as the other group(s) grow". For example, hardware may become more valuable to consumers with the growth of compatible software.
Network effects are commonly mistaken for economies of scale, which describe decreasing average production costs in relation to the total volume of units produced. Economies of scale are a common phenomenon in traditional industries such as manufacturing, whereas network effects are most prevalent in new economy industries, particularly information and communication technologies. Network effects are the demand side counterpart of economies of scale, as they function by increasing a customer's willingness to pay due rather than decreasing the supplier's average cost.
Upon reaching critical mass, a bandwagon effect can result. As the network continues to become more valuable with each new adopter, more people are incentivised to adopt, resulting in a positive feedback loop. Multiple equilibria and a market monopoly are two key potential outcomes in markets that exhibit network effects. Consumer expectations are key in determining which outcomes will result.
Origins Network effects were a central theme in the arguments of Theodore Vail, the first post-patent president of Bell Telephone, in gaining a monopoly on US telephone services. In 1908, when he presented the concept in Bell's annual report, there were over 4,000 local and regional telephone exchanges, most of which were eventually merged into the Bell System.
Network effects were popularized by Robert Metcalfe, stated as Metcalfe's law. Metcalfe was one of the co-inventors of Ethernet and a co-founder of the company 3Com. In selling the product, Metcalfe argued that customers needed Ethernet cards to grow above a certain critical mass if they were to reap the benefits of their network. According to Metcalfe, the rationale behind the sale of networking cards was that the cost of the network was directly proportional to the number of cards installed, but the value of the network was proportional to the square of the number of users. This was expressed algebraically as having a cost of N, and a value of N2. While the actual numbers behind this proposition were never firm, the concept allowed customers to share access to expensive resources like disk drives and printers, send e-mail, and eventually access the Internet.
The economic theory of the network effect was advanced significantly between 1985 and 1995 by researchers Michael L. Katz, Carl Shapiro, Joseph Farrell, and Garth Saloner. Author, high-tech entrepreneur Rod Beckstrom presented a mathematical model for describing networks that are in a state of positive network effect at BlackHat and Defcon in 2009 and also presented the inverse network effect with an economic model for defining it as well. Because of the positive feedback often associated with the network effect, system dynamics can be used as a modelling method to describe the phenomena. Word of mouth and the Bass diffusion model are also potentially applicable. The next major advance occurred between 2000 and 2003 when researchers Geoffrey G Parker, Marshall Van Alstyne, Jean-Charles Rochet and Jean Tirole independently developed the two-sided market literature showing how network externalities that cross distinct groups can lead to free pricing for one of those groups.
Evidence and consequences
While the diversity of sources is in decline, there is a countervailing force of continually increasing functionality with new services, products and applications — such as music streaming services (Spotify), file sharing programs (Dropbox) and messaging platforms (Messenger, WhatsApp and Snapchat). Another major finding was the dramatic increase in the infant mortality rate of websites, with the dominant players in each functional niche, once established, guarding their turf more staunchly than ever.
On the other hand, a growing network effect does not always bring a proportional increase in returns. Whether additional users bring more value depends on the commoditization of supply, the type of incremental user and the nature of substitutes. For example, social networks can hit an inflection point, after which additional users do not bring more value. This could be attributed to the fact that as more people join the network, its users are less willing to share personal content and the site becomes more focused on news and public content.
Economics
Network economics refers to business economics that benefit from the network effect. This is when the value of a good or service increases when others buy the same good or service. Examples are websites such as eBay, or iVillage, where the community comes together and shares thoughts to help the website become a better business organization.
In sustainability, network economics refers to multiple professionals (architects, designers, or related businesses) all working together to develop sustainable products and technologies. The more companies are involved in environmentally friendly production, the easier and cheaper it becomes to produce new sustainable products. For instance, if no one produces sustainable products, it is difficult and expensive to design a sustainable house with custom materials and technology. But due to network economics, the more industries are involved in creating such products, the easier it is to design an environmentally sustainable building.
Another benefit of network economics in a certain field is the improvement that results from competition and networking within an industry.
Adoption and competition
Critical mass In the early phases of a network technology, incentives to adopt the new technology are low. After a certain number of people have adopted the technology, network effects become significant enough that adoption becomes a dominant strategy. This point is called critical mass. At the critical mass point, the value obtained from the good or service is greater than or equal to the price paid for the good or service.
When a product reaches critical mass, network effects will drive subsequent growth until a stable balance is reached. Therefore, a key business concern must then be how to attract users prior to reaching critical mass. Critical quality is closely related to consumer expectations, which will be affected by price and quality of products or services, the company's reputation and the growth path of the network. Thus, one way is to rely on extrinsic motivation, such as a payment, a fee waiver, or a request for friends to sign up. A more natural strategy is to build a system that has enough value without network effects, at least to early adopters. Then, as the number of users increases, the system becomes even more valuable and is able to attract a wider user base.
Limits to growth
Network growth is generally not infinite, and tends to plateau when it reaches market saturation (all customers have already joined) or diminishing returns render the cost of acquiring the remaining customers prohibitive.
Networks can also stop growing or collapse if they do not have enough capacity to handle growth. For example, an overloaded phone network that has so many customers that it becomes congested, leading to busy signals, the inability to get a dial tone, and poor customer support. This creates a risk that customers will defect to a rival network because of the inadequate capacity of the existing system. After this point, each additional user decreases the value obtained by every other user.
Peer-to-peer (P2P) systems are networks designed to distribute load among their user pool. This theoretically allows P2P networks to scale indefinitely. The P2P based telephony service Skype benefited from this effect and its growth was limited primarily by market saturation.
Market tipping Network effects give rise to the potential outcome of market tipping, defined as "the tendency of one system to pull away from its rivals in popularity once it has gained an initial edge". Tipping results in a market in which only one good or service dominates and competition is stifled, and can result in a monopoly. This is because network effects tend to incentivise users to coordinate their adoption of a single product. Therefore, tipping can result in a natural form of market concentration in markets that display network effects. However, the presence of network effects does not necessarily imply that a market will tip; the following additional conditions must be met:
The utility derived by users from network effects must exceed the utility they derive from differentiation Users must have high costs of multihoming (i.e. adopting more than one competing networks) Users must have high switching costs
If any of these three conditions are not satisfied, the market may fail to tip and multiple products with significant market shares may coexist. One such example is the U.S. instant messaging market, which remained an oligopoly despite significant network effects. This can be attributed to the low multi-homing and switching costs faced by users.
Market tipping does not imply permanent success in a given market. Competition can be reintroduced into the market due to shocks such as the development of new technologies. Additionally, if the price is raised above customers' willingness to pay, this may reverse market tipping.
Multiple equilibria and expectations Network effects often result in multiple potential market equilibrium outcomes. The key determinant in which equilibrium will manifest is the expectations of the market participants, which are self-fulfilling. Because users are incentivised to coordinate their adoption, users will tend to adopt the product that they expect to draw the largest number of users. These expectations may be shaped by path dependence, such as a perceived first-mover advantage, which can result in lock-in. The most commonly cited example of path dependence is the QWERTY keyboard, which owes its ubiquity to its establishment of an early lead in the keyboard layout industry and high switching costs, rather than any inherent advantage over competitors. Other key influences of adoption expectations can be reputational (e.g. a firm that has previously produced high-quality products may be favoured over a new firm).