Affiliations: School of Business Administration in Karviná, Silesian University in Opava, Univerzitní Nám. 1934/3, 733 40, Karviná, Czech Republic. E-mail: sperka@opf.slu.cz
Abstract: The main goal of this paper is to compare the results of an
agent-based and Monte Carlo simulation experiments in business process
negotiation between sellers and customers of a simple trading commodity. The
motivation of the presented research is to find suitable method for
predicting key performance indicators of a business company. The intention
is to develop a software module in the future which might help the
management of business companies to support their decisions. Microeconomic
demand functions were used as a core element in the negotiation.
Specifically, Marshallian demand function and Cobb-Douglas utility functions
is introduced. The paper firstly presents some of the principles of
agent-based and Monte Carlo simulation techniques, and demand function
theory. Secondly, we present a conceptual model of a business company in
terms of a simulation framework. Thirdly, a formalization of demand
functions and their implementation in a seller-to-customer negotiation is
introduced. Lastly, we discuss some of the simulation results in one year of
selling commodities. The results obtained show that agent-based method is
more suitable than Monte Carlo in the presented domain, and the demand
functions could be used to predict the trading results of a company in some
metrics.