마코프 프로세스를 활용한 다세대 제품군 전략을 위한 제품생명주기 예측 모델

It is essential to establish a planned strategy in order for multi-generation product lines to be launched in the market sequentially at a planned timeand to maximize profits by efficiently utilizing technology assets and resources. To do this, it is necessary to be able to predict the state of each generation's product line at a specific point in the future. In this paper, we developed a model that can predict the future state of each of the multi-generation product lines from a product life cycle perspective by using Markov process. In order to explain the model and verify its validity, the historical sales data of the iPhone's generational products were used, and in particular, the transition probabilities matrix, an essential element of the Markov chain model, was obtained from these data by using a percentage prediction method. The experiment that performed 20 tests showed that the expected value presented by the model and the actual value matched 90%. To make the predictions accurate, it is found that data from more recent generations of products should be utilized to obtain transition probability matrices, and that the unit period for data collection and management should also be finer from quarter to month.