Authors:
Zheng Jianya
1
;
Daniel L. Li
2
;
Li Weigang
1
;
Zi-Ke Zhang
3
and
Hongbo Xu
4
Affiliations:
1
University of Brasilia, Brazil
;
2
Coleman Research Group, United States
;
3
Hangzhou Normal University, China
;
4
AliResearch Center, China
Keyword(s):
e-Commerce, Service Charges, Game Theory, Nash Equilibrium.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Computational Intelligence
;
Electronic Commerce
;
Enterprise Information Systems
;
Evolutionary Computing
;
Game Theory Applications
;
Soft Computing
;
Software Agents and Internet Computing
Abstract:
One of the biggest challenges in e-commerce is to utilize data mining methods for the improvement of profitability for both platform hosts and e-commerce vendors. Taking Alibaba as an example, the more efficient method of operation is to collect hosting service fees from the vendors that use the platform. The platform defines a service fee value and the vendors can decide whether to accept or not. In this sense, it is necessary to create an analytical tool to improve and maximize the profitability of this partnership. This work proposes a dynamic in-cooperative E-Commerce Game Model (E-CGM). In E-CGM, the platform hosting company and the e-commerce vendors have their payoff functions calculated using backwards induction and their activities are simulated in a game where the goal is to achieve the biggest payoff. Taking into consideration various market conditions, E-CGM obtains the Nash equilibrium and calculates the value for which the service fee would yield the most profitable res
ult. By comparing the data mining results obtained from a set of real data provided by Alibaba, E-CGM simulated the expected transaction volume based on a selected service fee. The results demonstrate that the proposed model using game theory is suitable for e-commerce studies and can help improve profitability for the partners of an online business model.
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