Empirical Comparative Study of Wearable Service Trust Based on User Clustering

2.1 Clustering Variables

The traditional user clustering or market segmentation variables are mainly based on demographic characteristics, but this method has great limitations, and cannot accurately classify user groups, let alone effectively predict customer behavior. Since the 1970s, many scholars and experts began to use psychological characteristics to study consumer behavior and user segmentation, among which the more important method is based on consumer “lifestyle”. Lifestyle is measured mainly by using the mental map method. The research on the application of mental maps mainly includes the VALS (Values and Life Style Survey) method, which is currently popular, and the modified VALS^TM (Dale et al., 2011) methods.

According to the previous research results of experts on individual psychological characteristics (Wang et al., 2013; Wayne et al., 2010; Luo et al., 2007) and VALS^TM, the variables of the clustering model of wearable service consumers in this paper come from two dimensions: the horizontal dimension is the resource dimension and the vertical dimension is the motivation dimension, which are as follows:

Resource Dimension

Demographic variables: gender, age, education, occupation, income

Personality characteristics: (a) Ability: Energy, intelligence, leadership; (b) Personality: curiosity, self-confidence, impulse

Motivation Dimension

It can be divided into three motivations: ideal motivation, achievement motivation and self-expression motivation.