Simulation Methods Comparison in Business Process Domain
Roman Šperka ()
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Roman Šperka: Department of Business Economics and Management, School of Business Administration, Silesian University
No 19, Working Papers from Silesian University, School of Business Administration
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.
Keywords: simulation; agent-based; Monte Carlo; trading; price negotiation; commodity; key performance indicators. (search for similar items in EconPapers)
JEL-codes: C63 C99 L21 M21 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp and nep-upt
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Persistent link: https://EconPapers.repec.org/RePEc:opa:wpaper:0019
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