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In 1964, Xerox released the Long Distance Xerography (LDX) system — essentially the first commercial fax machine. It cost $46,000, weighed hundreds of pounds, and had exactly zero other machines to talk to. For over a decade, fax adoption crawled. By 1970, fewer than 50,000 fax machines existed worldwide. Each one could only connect to the handful of others already installed, making the value proposition weak. Why spend thousands on a machine when you could only reach a few dozen offices? Then something shifted. Japanese manufacturers like Sharp and Matsushita slashed prices below $1,000 in the early 1980s. By 1983, roughly 300,000 fax machines were operating in the US. The math was changing: 300,000 machines meant 90 billion possible connections (n² / 2). A new buyer wasn't just gettin...
Popular framing: Fax machines took off when they finally got cheap enough.
Structural analysis: Network value scales as n² while machine count scales linearly, so adoption stays flat until installed base crosses a tipping point — then nonlinear value-per-buyer drives a hockey-stick. Past that threshold the network itself becomes the moat: a competitor would need not a better machine but 10 million installed endpoints, an option no entrant has.
Conflating 'price caused adoption' with 'price enabled crossing the tipping point' leads to systematically wrong predictions: it implies that making a product cheap enough will always drive adoption, when the actual requirement is achieving critical network density. This gap causes investors and policymakers to underfund network-building subsidies for nascent two-sided markets and overfund product-cost reductions in markets that are actually stuck in coordination traps.
