The relationships between customer requirements and technical measures are typically resolved by a cross-functional team with the assumption that the relationships are able to be identified objectively. However, due to the limited knowledge and experiences, determining the appropriate relationship could be difficult since the decision makers might not have enough information to evaluate the actual relationship. Moreover, the importance of technical measures is typically expressed in the current time period. It would be of interest to trace the future trends of technical measures since customer needs are fulfilled by technical measures. Under such circumstances, a Markov chain model could be an approach to model the relationship and monitor the trends of technical measures from probabilities viewpoints. With the needed probabilities, the dynamic relationships as well as the trends of technical measures can be performed by different time periods. Finally, the relationships and future trends of technical measures can be updated when the new information is available.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Social Sciences(all)