What is it about?
In this paper we use the Generalised Population Based Incremental Learning (GPBIL) in order to found profit-maximizing strategies for the Artificial Payment Card Market (APCM). The artificial market has modeled explicitly a multidimensional consumers' and merchants' demand for payment instruments. Given the complex shape of the demand, we have found that the GPBIL effectively explores the areas of intersection between the price and the demand on both sides of the payment card market, in order to reach a price structure and a price level that maximize the profit of the payment card providers.
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Why is it important?
This paper use a Generalized Population Based Incremental Learning approach to gain insights on possible business strategies of card payment providers given specific market competition rules.
Perspectives
In this paper we combine two powerfull tools: an agent-based model (ABM) and a learning algorithm. We used the ABM to simulate interactions at the point of sale among consumers and merchants; the learning algorithm is applied by card payment providers to design their business strategies based on the market indicators obtained from the simulation.
Dr Biliana Alexandrova-Kabadjova
Banco de Mexico
Read the Original
This page is a summary of: Profit-Maximizing Strategies for an Artificial Payment Card Market. Is Learning Possible?, Journal of Intelligent Learning Systems and Applications, January 2011, Scientific Research Publishing, Inc,,
DOI: 10.4236/jilsa.2011.32009.
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