![](bg7.png)
2
*
2
ii
iiii
i
A
L
(10)
Then, we consider two situations for ω*: First
where the platform charges all the e-retailers a
standard rate, the service charges are:
22
22
2
11
2
2
1
1
*
1
...
11
...
2
1
KK
K
K
AAA
(11)
On the other hands, the platform can charge the
e-retailers based on the category of product they sell,
ω* will be calculated as follows:
2
*
iii
i
A
(12)
7 CONCLUSIONS
This work proposed a game model E-CGM to find
out the optimal charging rate within an e-commerce
platform. Based on the game theory, a dynamic
game between two players, which are platform host
and union of e-retailers, was applied to model
behaviours in e-commerce. The Nash equilibrium of
this game was calculated utilizing backward
induction. And by applying this model in a case
study evaluating a real data set of Alibaba’s
transaction records, Alibaba’s profit was increased
5.87 times compared with the current profit value,
and the profit of e-retailers increased 1.41 times. To
increases the applicability of E-CGM, an expanded
form is also proposed to include the variability
caused by the existence of different categories of
products, thus taking into consideration additional
aspects of an actual business environment.
However, although the E-CGM model can
improve the profitability of both the platform and e-
retailers, it has its limitations. For example, the
platform must dominate its market so the e-retailers
have no other options and cannot negotiate service
charges. Another problem is that this model greatly
reduces the position of e-retailers, which could result
in a more social problem. To lessen the impact of
these problems, the Nash equilibrium can be
analyzed and calculated based on a percentage of
closing fee, which would lead to an improved
service charge calculation method and minimize
these limitations.
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