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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

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.

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
Date: 2015-10-22
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