Classroom Companion: Business

Fig. 10.2 Two-sided platform with cross-side network effects. (Authors’ own 
figure)
Potential users
Users
Potential advertisers
Advertisers
Flow: p(N − A)
Flow: qA(M − B)
B
qA
A
p
N − A
M − B
10.3 · Network Effects and MSPs

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10
an S-curve and lagging the growth curve 
for type- A customers. In the example, it 
takes about 6 months until 10% of the 
market of type-A customers has been 
captured. At that time, only about 0.5% 
of the potential market of type-B cus-
tomers has been captured. It takes 
2 years to capture 10% of the market of 
type-B customers. If the revenues 
depend only on the number of type-B 
customers, the cross-side network effect 
may result in too small revenues to sus-
tain the service initially. The service may 
then be prematurely terminated.
Fig. 10.3 Temporal market evolution for a two-sided platform. The parameters 
used are p = 0.17 and qN = 0.21. (Authors’ own figure). The abscissa is the time in 
years
0,0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1,0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Percentage of market share
Users
Advertisers
 
Chapter 10 · Multisided Platforms

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10
The simple model in 
7
Box 
10.1
shows that the network effects may lead to slow 
service adoption by one (or even both) user groups in two-sided markets. 
Strategically, this may deceive the platform provider to believe that this user group 
will not adopt the service and, therefore, prematurely abandon it. This is a general 
problem associated with positive network effects as explained in 
7
Chap. 
8
 and 
shown mathematically in 
7
Chap. 
18
. This problem is particularly vital if the rev-
enues of the platform provider depend mainly on the service of the customer group 
subject to the positive network effects. The revenues of Facebook depend almost