生活型態在實體與虛擬通路之市場區隔研究

Abstract

在動態的環境下，因為可以接觸到的商品種類與傳播媒體的發達，造成消費者的偏好分歧，也使得以往傳統的市場區隔愈加難以解釋消費者選擇行為。本研究希望改善以往的市場區隔模式，首先利用生活型態變數來增加解釋的豐富性，並提出一個結合一般生活型態變數與適當的方法論的新市場區隔模型來解決之前模式的複雜性。在實證分析中，為了簡化過去生活型態問卷的長度與繁雜度，本研究分別針對實體與網路購物行為，利用分類與決策樹與約略集合理論來找出與傳統研究不同的市場區隔變數。本研究發現，利用生活型態變數所找出的市場區隔之預測購買行為之能力，除了可以找出不同於以往的市場區隔之內涵外，分類與預測之效果可比傳統人口統計變數佳；此外，分類與決策樹加上約略集合理論兩種研究方法的結合，將可以有效加強此模式分類與預測之結果。

Under the dynamic environment, consumers have much more chance to access products and media; this may create more difference in their preferences. This study aims to improve the elder method of market segmentation; first, lifestyle variables are used to predict consumer choices to increase the richness of the explanation. Second, the novel model which integrates general lifestyle variables and appropriate methodologies is proposed to solve the complexity of the previous research problems. To simplify and reduce the length of the questionnaire in lifestyle research, classification and regression tree (CART) is applied to discover the general lifestyle variables to segment the market. The empirical results show that, under different purchasing situation, the explanatory power of general lifestyle variables is not less than those traditional demographic variables; in fact, some models with different combinations of general lifestyle variables have higher explanatory power than demographic ones. Also, in this paper, a novel method, integrated by CART and rough sets, is propose to improve the shortcoming of CART. From the comparison of CART, rough sets and the proposed method, we can conclude that the proposed method appropriately integrates the advantages of CART and rough sets.