These two papers are pretty similar and are written by the same author, W. Brian Arthur: Positive Feedbacks in the Economy,

Competing Technologies, Increasing Returns, and Lock-In Historical Events. Both papers are from the late ’80s, and show that the idea of Network Effects dates back, although in these paperes it is discussed in terms of positive feedback. The paper mentions the example that Professor Easley gave of the classic Betamax versus VHS adoption, where it is argued that it is not superior technology that won out, and that the outcome was influenced by luck. In a sense, this also is symmetry breaking, as “Both systems were introduced about the same time and thus started with roughly equal market shares, but those shares fluctuated early on due to external circumstance, “luck” and other actions by companies manouvering for position.” The paper talks about two positive feedback loops which we have discussed as network effects,”the more people adopt a particular technology, the more it improves, and the more incentive there is for further adoption,” and, “increasing adoption makes it advantageous for newcomers to a field–who must exchange information or products with those already working in the field–to fall in with the standard.”

These papers also combine some of the earlier topics, such as graph theory and the importance of building ties, “…hi-tech products, unlike bulk goods, require specialized marketing and good relationships with customers. Increasing market share requires building a network of such ties; the more extensive this network the easier further increases become.”

Also interesting in the papers is seeing the nascence of this analysis and the quasi-prediction that it would become more common as technology develops, “If increasing-returns mechanisms are important, why have they been largely ignored until recently? Some would say that complicated products–high technology–for which increasing returns are so prevalent, are themselves a recent phenomen. This goes back to what was said in class that the very low marginal cost involved is also important to creating network effects, where distributing more units of already programmed software can be simplified to having no marginal cost.