Demand function and its role in a business simulator

Dominik Vymetal and Filip Ježek

MPRA Paper from University Library of Munich, Germany

Abstract: Business simulations are useful tools due to the fact that it eases management decision making. No doubt there are many processes which must be considered and simulated. Therefore, such business simulator is often composed of many processes and contains many agents and interrelations as well. Since the business simulator based on multi-agent system is characterized by many interrelations within, this article deals with a specific part of the business simulator only – a demand function and its modeling. The aim of this partial research is to suggest demand function which would be most suitable for the business simulation. In this paper a new approach for customer decision function in business process simulation was presented. The decision of the customer is based on Marshallian demand function and customer utility function using Cobb-Douglas preferences. The results obtained by means of the MAREA simulation environment proved that this approach yields correct simulation results.

Keywords: business simulator; multi-agent system; demand function; MAREA (search for similar items in EconPapers)
JEL-codes: C63 C88 D4 (search for similar items in EconPapers)
Date: 2014-03-22
New Economics Papers: this item is included in nep-cmp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/54716/1/MPRA_paper_54716.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:54716

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().