Using Visual Basic for Applications to Implement Markov Analysis in Market Share Forecasting

Abstract

Objective: This paper is an examination of the use of Markov analysis in market share prediction, and the use of Visual Basic for Applications (VBA) to increase the speed and precision of the computation and model. Theoretical Framework: The Markov analysis, used to predict future states from current transitions, sheds light on the consumer behavior and brand loyalty dynamics With VBA, the data processing can be automated, and transition matrices built that are dynamic, so that forecasts can be updated in real time. Method: Markov analysis is based on transition matrices, which define the probabilities of transitioning from one state to another. These matrices are then used to predict long term probabilities by raising the transition matrix to some power that is equal to the number of future steps being studied. Results and Discussion: By utilizing Visual Basic for Applications (VBA), the study facilitates the swift creation of transition matrices and enables real-time modifications in response to new data. This implies that with the use of VBA and Markov analysis, not only is the forecasting process made easier, but also more accurate predictions are made, and for that reason VBA should be one of the tools that any firm looking to maximize its market share strategies should employ. Research Implications: This capability results in a more flexible and responsive forecasting instrument, enhancing the overall adaptability of market share predictions. Originality/Value: The originality of this research is found in its innovative methodological framework that builds upon conventional Markov analysis.