Dynamic Cross Impact Analysis with Markov Chain

Abstract

Early warning and intelligent decisions have proved to be important tools to handle the unprecedented events (wildcards) that might emerge in the future. Relying on forecasting techniques only are not enough to shape the future, since they depend only on the historical shape and they generate one image of the future. The Futures Methodologies are capable of overcoming the constraints imposed on the Forecasting techniques. This is so since they explore, create, and test both possible and desirable futures to improve the decision making process and combine quantitative and qualitative techniques. Cross Impact Analysis generates occurrence probabilities of wildcards taking into account the interdependencies between their occurrences at a specific point in the future. Cross Impact Analysis is a hybrid quantitative and qualitative futures methodology and is very prominent in the Futures Studies literature. This paper introduces a novel contribution to the Futures Studies literature. The Dynamic Cross Impact Analysis is an enhancement to the traditional Cross Impact Analysis by adding the dynamic behavior, time dimension, through the use of Markov Chains. It generates dependent wildcards occurrence probabilities for a number of future years. As a result of this hybridization, a more realistic and rational anticipation of the future is obtained and hence allows for better decision making. The proposed hybrid methodology is applied to the tourism sector to study different wildcards.