Understanding the Nature of Predatory Pricing in Large-Scale Market Economy with Genetic Algorithms

Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/23289

Title:	Understanding the Nature of Predatory Pricing in Large-Scale Market Economy with Genetic Algorithms
Authors:	陳樹衡;C.-C. Ni;S. Feng Chen,Shu-Heng
Keywords:	Chain-store game;Predatory pricing;Evolutionary game;Genetic algorithms;Co-evolutionary stability
Date:	1996-09
Issue Date:	2009-01-09 12:18:30 (UTC+8)
Abstract:	This paper applies co-evolutionary genetic algorithms to an economic modelling problem. The chain-store game is a game-theoretic model for predatory pricing (price wars); the modelling goal is to study when predatory pricing can arise. It is found that, even under the same payoff structure, the results of the co-evolution of weak monopolists and entrants are sensitive to the representation of the decision-making process. Two representations are studied: 1) the action-based representation, and 2) the strategy-based representation. The former is to represent a naive mind and the latter is to capture a sophisticated mind. For the action-based representation, the convergence results are easily obtained and predatory pricing is only temporary in all simulations. However, for the strategy-based representation, predatory pricing is not a rare phenomenon and its appearance is cyclical but not regular
Relation:	Journal of Systems Engineering and Electronics,8(2),33-44
Data Type:	article
DOI link:	http://dx.doi.org/10.1109/ISIC.1996.556227
Appears in Collections:	[Department of Economics] Periodical Articles

Files in This Item:

File	Description	Size	Format
0102.pdf		423Kb	Adobe PDF	560	View/Open