An Experimental Approach to Find a Suitable Simulation Method in Business Economics

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19520%2F16%3A00010368" target="_blank" >RIV/47813059:19520/16:00010368 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3233/KES-150327" target="_blank" >http://dx.doi.org/10.3233/KES-150327</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/KES-150327" target="_blank" >10.3233/KES-150327</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An Experimental Approach to Find a Suitable Simulation Method in Business Economics

Popis výsledku v původním jazyce

The main goal of this paper is to compare the results of agent-based and Monte Carlo simulation experiments in a business process negotiation between sellers and customers of a simple trading commodity. The motivation of this research is to find a suitable method for predicting key performance indicators of a business. The intention is to develop a software module in the future that may help company management to support their decisions. Microeconomic demand functions were used as a core element in the negotiation. Specifically, the Marshallian demand function and the Cobb-Douglas utility functions are introduced. This paper first presents certain principles of the agent-based and Monte Carlo simulation techniques and of the demand function theory. Second, a conceptual model of a company is presented in terms of a simulation framework. Third, a formalization of demand functions and their implementation in a seller-to-customer negotiation is introduced. Last, we discuss the simulation results in one year of selling commodities. The results obtained show that the agent-based method is more suitable than the Monte Carlo in this domain; in addition, the demand functions could be used to predict the trading results of a company using certain metrics.

Název v anglickém jazyce

An Experimental Approach to Find a Suitable Simulation Method in Business Economics

Popis výsledku anglicky

The main goal of this paper is to compare the results of agent-based and Monte Carlo simulation experiments in a business process negotiation between sellers and customers of a simple trading commodity. The motivation of this research is to find a suitable method for predicting key performance indicators of a business. The intention is to develop a software module in the future that may help company management to support their decisions. Microeconomic demand functions were used as a core element in the negotiation. Specifically, the Marshallian demand function and the Cobb-Douglas utility functions are introduced. This paper first presents certain principles of the agent-based and Monte Carlo simulation techniques and of the demand function theory. Second, a conceptual model of a company is presented in terms of a simulation framework. Third, a formalization of demand functions and their implementation in a seller-to-customer negotiation is introduced. Last, we discuss the simulation results in one year of selling commodities. The results obtained show that the agent-based method is more suitable than the Monte Carlo in this domain; in addition, the demand functions could be used to predict the trading results of a company using certain metrics.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Knowledge-Based and Intelligent Engineering Systems

ISSN

1327-2314

e-ISSN

—

Svazek periodika

19

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

8

Strana od-do

269-276

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-84956984270