Market competitive situation: Cellular automata simulations

AuthorSuela Bylykbashi - Khalil Assala - Gilles Roehrich
PositionBrest Business School, France
Vol. 1 No. 1
January 2017
European Journal of Economics, Law and Social Sciences
IIPCCL Publishing, Graz-Austria
ISSN 2519-1284
Acces online at
Market competitive situation: Cellular automata simulations
Suela Bylykbashi
Brest Business School, France
Khalil Assala
Brest Business School, France
Gilles Roehrich
Univ. Grenoble Alpes, France
Cellular automata are mathematical models that were initially used in hard sciences, but which
were then adopted by social sciences and management for the modelling of behaviour. This
paper deals with the usefulness of cellular automata for the study of a competitive situation
on a given market. We present the possibility of using cellular automata to carry out market
studies, and for simulating the launch of new products and the withdrawal of a product.
Cellular automata can allow us to understand the behaviour of agents and the implications, in
terms of market share variations, of competing brands on a given market.
Keywords: Market, Cellular automata simulations, product.
Cellular automata are mathematical models that were initially used in hard sciences,
but which were then adopted by social sciences for the modelling of behaviour.
They were introduced by John von Neumann and Stanislas Ulam in 1940 (under
the name of "cellular spaces") for the purposes of developing simple mathematical
systems that could replicate, in a manner similar to that of living organisms. In 1970,
John Conway created the most well-known cellular automaton, the "Game of Life",
as a representation of the survival of the species. His idea was that reproduction
and the survival of the species are o en governed by simple and locally e ective
rules, depending on each species and on the neighbouring species. Today, cellular
automata are used in many disciplines, including hard sciences such as physics,
chemistry and metallurgy. However, they have also found their way into social
sciences. For the la er, there is a dual interest: they make it possible on the one hand
to mimic the decision-making behaviour and actions of a social agent, and on the
other hand to take into account the interactions between agents (cells). They are for
example used in sociology to model the transmission of culture between individuals,
to explain the formation of groups and conformity, or to analyse the manner in
which individuals interact with each other, by exchanging their values in an e ort
to improve themselves, etc. (Gaylord & Nishidate, 1996). The study published by
Schelling (1969) concerning spatial segregation (the advent of ghe os in the USA) for
example, has been one of the most frequently commented examples (Varenne, 2011).
Cellular automata (CA) are also used in management to study the global dynamics
of organizational populations (Lomi and Larsen, 1996) or the interdependence of the

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