In economics and business, a network effect (also called network externality or demand-side economies of scale) is the effect that one user of a good or service has on the value of that product to other people. When a network effect is present, the value of a product or service is dependent on the number of others using it.
The classic example is the telephone. The more people who own telephones, the more valuable the telephone is to each owner. This creates a positive externality because a user may purchase a telephone without intending to create value for other users, but does so in any case. Online social networks work in the same way, with sites like Twitter and Facebook becoming more attractive as more users join.
The expression "network effect" is applied most commonly to positive network externalities as in the case of the telephone. Negative network externalities can also occur, where more users make a product less valuable, but are more commonly referred to as "congestion" (as in traffic congestion or network congestion).
Over time, positive network effects can create a bandwagon effect as the network becomes more valuable and more people join, in a positive feedback loop.
Diagram showing the network effect in a few
Network effects were a central theme in the arguments of Theodore Vail, simple phone networks. The lines represent
the first post patent president of Bell Telephone, in gaining a monopoly on potential calls between phones.
US telephone services. In 1908, when he presented the concept in Bell's annual report, there were over 4000 local and regional telephone exchanges, most of which were eventually merged into the Bell System.
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. 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 (1) the cost of the network was directly proportional to the number of cards installed, but (2) 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 definition were never firm, the concept allowed customers to share access to expensive resources like disk drives and printers, send e-mail, and access the Internet. 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.
Network effects become significant after a certain subscription percentage has been achieved, 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. As the value of the good is determined by the user base, this implies that after a certain number of people have subscribed to the service or purchased the good, additional people will subscribe to the service or purchase the good due to the value exceeding the price.
A key business concern must then be how to attract users prior to reaching critical mass. 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...
References:  https:/ / www. facebook. com/ TheVault. TX
 Wunsch, Steve (1999)
• Madureira, António; den Hartog, Frank; Bouwman, Harry; Baken, Nico (2013), "Empirical validation of
Metcalfe’s law: How Internet usage patterns have changed over time", Information Economics and Policy, http://
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