On estimating the impact of information spreading in a consumer market modeled by probabilistic cellular automata and ordinary differential equations. (December 2017)

• Record Type: Journal Article
• Authors: Schimit, PHT; Barros Junior, DF; Araújo, SA
• Is Part Of: Simulation. Volume 93:Number 12(2017)
• Page Start: 1063
• Page End: 1072
• Publication Date: 2017-12
• Subjects: Consumer market -- business game -- probabilistic cellular automata -- Susceptible/Infected/Recovered model -- rumor-spreading model; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549717722625
• Languages: English
• ISSNs: 0037-5497

Abstract

Individuals spread information about their lives, their career, and their recently purchased items. In addition, considering that the customer's opinions may influence their friendship circle, neighbors, and work colleagues, they constitute a very important factor to consider in future actions of companies. In this paper, we present an approach based on probabilistic cellular automata and ordinary differential equations for modeling the consumer market, inspired by a biological system of an infectious disease-spreading model. However, instead of spreading a disease, consumers spread their opinion to other individuals, thereby having consequences on sales levels. Using marketing, the economic situation, and individual opinion as input variables of the consumer market model, simulation output (generated demand) is then used in the business game, helping the mediator (teacher) to create different scenarios and giving feedback to the student at simulation runtime, even if many players are involved in the game. Analytical and numerical simulations show that the proposed approach allows the teacher to create virtual markets for the players just by setting the parameters that describe a scenario, increasing the dynamism of the game, saving time, and allowing the mediator to focus on other important subjects, such as the teaching concepts of business strategies and decision support. Moreover, simulations are conducted to demonstrate the applicability of the proposed model in real life problems, such as the electro-domestic market.