Judith,
Thanks for taking the time to address the network stuff. When I posted the initial message that got you thinking, I wasn't counting on having to wade through such deep-thinking stuff as you proposed :), so bear with me if I appear to gloss over your stuff too much.
1. Can we get a handle on intangible assets--categorize them--and correlate them to knowledge earnings, intellectual earnings.
In essence, I think that is the ideal outcome of the exercise. "Getting a handle" on them comes in various degrees of shallow or deep understandings. Maybe we should aim for waist-deep as a compromise. :)
2. With a better handle on i.a. and how they behave--relationship to profitability, growth, time cycles--we might be able to plot specific technology adoption cycles. We could then see where critical mass is achieved and at what level.
If you and others can do that, more power to you! It's certainly beyond my realm of expertise.
3. If networks are complex systems, then what event might cause as steep a crash as the ascent? Is it only a discontinuous innovation or are there other externalities to consider? What externalities are just general phenomena and which are specific to the network.
I think that depends on the nature of the network. If the business model thrives on being built around a core of discontinuity (such as Gemstar) it's more likely that a displacing discontinuous innovation is needed to "bring it down." However, if it "only" thrives on the magnitdue of its size and a certain amount of "stickiness" (such as AOL), I imagine a change in cultural life styles of the end users is the sort of thing that can effect a change in the network, especially if management is slow to percieve and react to the changed demands of its users.
4. There is clearly an intricate relationship between i.a. and the networks. Does it vary from network to network? In what ways? Can one spot the differences and what do those differences mean for the magnitude of growth and its likely duration?
I forgot already. What does "i. a." mean?
What, in effect, do network effects say about CAP and GAP?
A lot or a little, depending on the network in question, or so I think. That question is exactly why our exercise has potential merit.
Perhaps we could start with three networks from the G&K and Godzilla realms--maybe a Gorilla, a King, and a Godzilla--and analyze them individually.
I like that idea a lot, especially if each can be exemplary of a particular kind of network for which conclusions we draw about the example might be applicable to a group of similar networks as much as is reasonably possible.
Keep the grey matter goin'! Comments from others?
--Mike Buckley |
