Title
An Agent-Based Simulation Model for Analysis on Marketing Strategy Considering Promotion Activities
Abstract
This paper proposes a new agent-based model for simulation analysis on firms' marketing strategy in competitive markets environments. In the previous model proposed by Tay and Lasch, firm agents determine their marketing strategies such as price and product attribute at every period so as to maximize their profit. This paper shows that the firm agents constructed based on the Tay-Lasch model do not learn the preferences of consumer agents under a very simple situation. This article proposes a novel agent-based model based on a learning classifier system so that the firm agents have abilities to learn the preferences of consumer agents. Moreover, in order to construct a more realistic simulation model, promotion activity of firm agents is incorporated in the strategy of firm agents. Some relationship between the strategy the firm and profitable firm are clarified through simulation analysis.
Year
DOI
Venue
2009
10.1007/978-3-642-01665-3_62
KES-AMSTA
Keywords
Field
DocType
agent-based simulation model,previous model,marketing strategy,promotion activities,firm agent,realistic simulation model,tay-lasch model,consumer agent,new agent-based model,profitable firm,simulation analysis,novel agent-based model,profitability,learning classifier system,simulation model
Marketing strategy,Simulation,Computer science,Knowledge management,Artificial intelligence,Machine learning,Learning classifier system
Conference
Volume
ISSN
Citations 
5559
0302-9743
0
PageRank 
References 
Authors
0.34
5
4
Name
Order
Citations
PageRank
Hideki Katagiri143646.48
Ichiro Nishizaki244342.37
Tomohiro Hayashida32911.56
Takahiro Daimaru400.34