Decision Analysis using Markov Chain to Predict Marketing Trends

Astutik, Yayuk Setyaning and Shahrullah, Rina Shahriyani (2011) Decision Analysis using Markov Chain to Predict Marketing Trends. In: Proceedings of the ProMAC Symposium 2011, 29 November - 2 December, Batam.

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Abstract

The Markov chain is one of the tools that can be used to gain information regarding the past and present actions with opportunity movements from one to another condition in a certain time range. The Markov chain in its efforts to predict the future actions only depends on the on-going actions. The past actions are regarded as to independent to the future actions. The Markov chain contains a changing process with a fixed pattern, so it eventually leads to a balanced and steady state. The balanced and steady state will provide information to decision makers. The steady state is used to predict the long term actions. Market will continue changing in line with the increase of competitors. Costumers wish to obtain the best facilities with a minimum cost. The decrease of customers may occur due to the movement of customers in choosing similar products with a different brand. The Markov chain may be adopted to analyze the movement of customers in choosing a different brand of a similar product. Hence, the Markov chain may be beneficial for corporations to determine their efficient and effective marketing strategies to encounter their competitors.

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