基于马尔科夫概率跃迁矩阵的消费者偏好分析

Consumer Preference Analysis Based on Markov Transition Probability Matrix

采用马尔科夫概率跃迁矩阵工具对汽车消费者偏好进行了分析。首先通过抽样调查获得消费者偏好转移的初始矩阵,再通过迭代求解的方法,提高原矩阵内部隐性数值的精确性,并构建动态概率跃迁矩阵,最后使用PPMCC法评价矩阵的稳定性。实例表明,2013-2014年消费者对汽车产品的偏好比例最大为经济优先,比例最小为技术优先。预测2015-2018年,消费者对汽车产品奢侈优先的偏好比例逐年下降,而其他三项的偏好比例逐年上升。

Analyze the consumer preference of a product （car） by Markov matrix probability transition ma‐trix .Get the consumer preference initial matrix by the sample survey first ,then improve the accuracy tacit numerical of the original matrix by iterative method and construct transition probability matrix ,and finally use PPMCC method to evaluate the stability of matrix .The example shows that the economic priority is the maximum consumer preference ratio in 2013-2014 automotive products ;the technical priority is the mini‐mum consumer preference ratio .Predict that the luxury priority of the consume preference ratio will fall ,but other preference ratio will rise among 2015-2018 .