针对多项LOGIT选择模型存在解释变量难以度量的问题,本文构建了网络消费者品牌选择的模糊LOGIT模型。采用三角模糊数来描述定性变量,并利用其均值、方差及模糊隶属度将模糊LOGIT模型转化为确定性模型进行求解。本文以手机品牌为例,通过问卷获取数据并对数据进行处理,以挖掘影响网络消费者品牌选择行为的关键因素并对模型参数进行估计。研究结果表明:消费者人口统计特征、品牌属性和网络环境变量一定程度上对网络消费者品牌选择有显著影响,并利用模糊LOGIT模型预测消费者选择各品牌的概率,为制定有效的网络营销策略提供理论依据和决策支持。
A fuzzy LOGIT model of the web consumer brand choice was put forward to solve the problem that explanatory variables in the rnultinomial LOGIT model were hard to accurately measure. The triangular fuzzy number was used in this model to describe to the qualitative variables. The fuzzy model was changed into a deterministic model by using the mean, variance and fuzzy membership of triangular fuzzy number. Taken mobile phone brands for an example, applied the constructing model to analyze the dates which were got from the questionnaires to explore the key factors affecting network consumer brand choice behavior and estimate the parameters in model. The results reveal that demographic characteristics, brand attributes and network environment variables have significant influence on the web consumer brand choice. And using the probabilities of selecting each brand provides the theoretical support to make an effective marketing strategy.