This was my immediate thought as well -- but by mentioning Scale you must also link the excellent review of it by Freeman Dyson(!):
http://www.nybooks.com/articles/2018/05/10/the-key-to-everyt...
Another point is that it's easy to mistake a power law for a sigmoid and vice versa.
There's remarkably little study of technology, in the general sense, as its own thing. There are a few good book,s, W. Brian Arthur's especially, and numerous ones that strike me as oversold (Kevin Kelley's strikes me this way).
Arthur, like West, is affiliated with the Santa Fe Institute, and it strikes me that much of the most interesting work I've seem in recent decades comes from there, see alse Farmer, Holland, van der Leeuw, Krakauer, and others.
There's a philosophy of technology (good overview at http://plato.stanford.edu) but it focuses almost exclusively on socialy and ethical interactions, and not what technology is or its mechanisms. Much of the literature is quite woolley (Heidigger, Elul), though not without merits. Others (Schumpeter) seem to me so far to miss a critical essence. Often its the study of failure which seems most instructive (Perrow, etc.).
I'm not quite sure what to make of your comment on companies: yes, large-scale networks do somewhat tend to resemble one a nother, and no, a given network maw not be exclusive to a domail (think: water, electricity, gas, comms, data, sewage, transport, social, financial, all or most of which likely connect your residence). At scale, the interesting questions tend to relate to interplay between various networks.
What's your glass metaphor indicating? Brittleness? Transparency? Amorphous state? Other?
Siqmoid and power laws strongly resemble one another, until they don't. They're also not the universe of growth and decay functions.
Aa realisation I'd had a few years back was that networks -- and here I'm talking about any organisation of components with flows, not just data networks, but people, organisations, cities, companies, markets, transport, conversations or discussion boards, etc., -- have several characteristics which govern behaviour. These define a large class of hence related dynamics.
There's topology: (peer, star, chain, ring, mesh, tree, , web, complex...). There's scale: null, unary, pair, triple (largest size where links equal nodes), 4 (first where links exceed nodes), etc. And the scale effects discussed here resemble those I've noted.
At large scale, scale tends to domininate topology in large part as there's only one viable topology, the dendritic tree (this is West's bugbear).
There's also network depth -- the number of nodes between pairs, particularly on average. Even relatively shaallow depths can have huge significance, think Six Degrees of Separation (or Kevin Bacon): this gives you everyone within a substantial industry (cinema) or even the world (Facebook, national security agency threat matrices).
Related is the characteristic of specific individuals -- superstars and regression toward the mean. A Gresham's Law type effect means that the effective functional level of a group is set by its least capable rather than most capable members (absent some means of effective management or moderation), another tendency which favours smaller groups initially.
It's also worth noting that certain transition points, such as HR being required as headcount climbs above 50, are determined by regulatory requiremment -- beware outside influences in anacdotal observation.
A particularly pervasive similarity comes to mind between agriculture and media, and how scale, topology, node characteristics, and complexity result in conceptually similar activity models. This is, of course, broadcasting. Named for the farmer casting seed on fields, the analogy continues when the harvest is considered: the mass-gathering of commodity high-utility carbohydrates through a uniform and undifferentiated processing. In media, this is advertising. And the results are similar: focus is on nondifferentiation, uniform processing, and maximising harvest yield, not the field's (or audience's) quality experience.
It's also interexting to note that even before the term was adopted there was a trend to more targeted cultivation in ag, including Jethro Tull's seed drills (and those of China long preceeding him), pressaging moves to media segmentation and targeting.
It's also possible that there are other ag analogies which might prove useful or insightful: herd-tending (prevalent in religious contexts), orchards, forestry, foraging, hunting, fishing, vegetable vs. staple crops, reserving methods such as fermentation, etc. Food for thought, as it were....
https://www.nytimes.com/2017/05/26/business/dealbook/geoffre...