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Economic Demand Functions in Simulation: Agent-Based Vs. Monte Carlo Approach

  • Roman ŠperkaEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 38)

Abstract

The aim of this paper is to compare an agent-based and Monte Carlo simulation of microeconomic demand functions. Marshallian demand function and Cobb-Douglas utility function are used in simulation experiments. The overall idea is to use these function as a core element in a seller-to-customer price negotiation in a trading company. Furthermore, formal model of negotiation is proposed and implemented to support the trading processes. The paper firstly presents some of the principles of agent-based and Monte Carlo simulation techniques, and demand function theory. Secondly, we present a formal model of demand functions negotiations. Lastly, we depict some of the simulation results in trading processes throughout one year of selling commodities to the consumers. The results obtained show that agent-based method is more suitable than Monte Carlo, and the demand functions could be used to predict the trading results of a company in some metrics.

Keywords

Simulation Agent-based Monte carlo Demand functions Business process Trading negotiation 

Notes

Acknowledgment

This paper was supported by the Ministry of Education, Youth and Sports Czech Republic within the Institutional Support for Long-term Development of a Research Organization in 2015.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Business Administration in Karviná, Department of Informatics and MathematicsSilesian University in OpavaKarvináCzech Republic

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