Using structural technology acceptance models to segment intended users of a new technology: Propositions and an empirical illustration
提出一种基于结构性技术接受模型的用户细分方法，并利用欧洲销售自动化技术实施数据，通过有限混合偏最小二乘估计揭示人们接受新技术的不同方式，为技术推广提供更精准的用户分类依据。
Abstract This article aims to offer an alternative method to analyse technology acceptance models, namely a segment‐wise analysis. The empirical illustration of this method involves data that were collected during a company‐wide implementation of a Sales Force Automation technology in Europe. The data comprise a variety of commonly used technology‐related, context‐related, and person‐related variables. The segmentation procedure, which involved a finite mixture partial least squares estimation, provides more insight into the different ways in which people come to accept new technologies. Unlike other segmentation studies published in IS journals, the resulting segments are based on similarities and differences in the structure of the underlying theoretical models rather than (a collection of) individual variables. Further research or a re‐analysis of existing data should help establish robust “technology acceptance model”‐based segments as well as comprehensive profiles of the individuals in each segment.