4: Network effects Flashcards

1
Q

network effect:

  • 2 alternative economic names
  • Def
  • Law
  • Law name, in what context
A
  • network externality or
    demand-side economies of scale
  • def: effect that 1 user of a good/service has on other users
  • Value(network) ~= #edges ~= N^2
    where N is the Nr of nodes
  • Metcalfe law invented it in the context of old ethernets
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2
Q

positive VS negative network effects: examples

A
  • positive: each new facebook user adds a tiny bit value (=potentially interacting) for all other users
  • negative: each situation of network congestion
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3
Q

supply side economies of scale

VS

demand side economies of scale

A

w volume increasing, the production costs go down due to:

  • better tools
  • more negotiating power w suppliers
  • running process

VS

(positive) network effect = each user adds value for other users

==> producers must consider this and try to profit from this, too

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4
Q
  • resource-based economy: returns & costs

VS

  • network effect: returns & costs
    • conseq.
A
  • marginal returns of resources are decreasing, while costs are increasing, therefore you can calculate the optimum production quantity

VS

  • w positive network effects, returns increase w increasing Nr of users, even though costs increase, too; if returns increase faster than costs, than the optimal Nr of users is infinite!
    • ==> winner-takes-it-all markets, eg 2-sided markets: it is optimal for both buyers & sellers to have just 1 market in every region
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5
Q

goods / service & markets:

1 consideration for both

1 differential consideration

A
  • the type of good / service determines whether the optimal market is global or local
  • services tend to have local markets
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6
Q

complementary goods game

  • =def
  • where attractive
    • 3 IT examples
A
  • availability of complementary goods makes good more attractive
  • large installed base attracts producers of complementary goods
  • eg.
    • iTune songs & iPods,
    • android phones & apps,
    • Windows & compatible SW applications
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7
Q

interoperability & standard games:

3 types of actors

+ what economic effect is being used

A

should you make your standards compatible or non-compatible with competitors?

  • Apple –> non-compatible strategy: use only Apple products & SW together
  • MS –> compatible with all else
  • regulators also play!

+ these are games with network effects!

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8
Q

customer facing analytics based on customer data:

example

goal

how is it made

A

e.g. recommender systems

–> create network effects for users

–> simple algos, but new data that adds value

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9
Q

bandwagon effect:

def

usage

A

def: the more ppl do something, the more want to… trend/hype!
usage: marketing

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10
Q

2 particular features of network economics
w examples

A
  • push towards mono- or oligopoly
  • path dependence ==> early choices limit your future options due to building up switching costs, e.g. in setting standards: many small decisions add up over time to a standard,
    • driving on left or right, or
    • VHS winning thanks to allowing porn
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11
Q

why are standards sometimes suboptimal?

–> 2 conseqs., 1 example

A

If tech A has lower initial value than tech B, even though its value increases much faster w Nr of users; but the lockin happens at a Nr of users lower than the crossover value, then tech B becomes the standard

–> big barrier for new entrants

–> Cos must build up their user base & complementary goods very fast

eg Google launched Android by pre-sending out phones to developers and also w million$ prizes for best apps

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12
Q

Network economics: 2 managerial conseqs.

(1 branching into 7 = 2-3 + 2 + 2)

A
  • engineer network effects in your products
  • 2-3 social:*
    • connect w your customers via user forums –> powerful organization form
    • recommender systems –> user data
    • (bandwagon effect <– not sustainable except in fashion)
  • 2 market-based:*
    • market place / platform
    • complementary goods
  • 2 openness-based:*
    • API
    • interoperability
  • watch for the critical mass –> there are tipping points, very difficult to identify, where value to users becomes greater than cost
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