Using Social Network Classifiers for Predicting E-Commerce Adoption

摘要

This paper indicates that knowledge about a person's social network is valuable to predict the intent to purchase books and computers online. Data was gathered about a network of 681 persons and their intent to buy products online. Results of a range of networked classification techniques are compared with the predictive power of logistic regression. This comparison indicates that information about a person's social network is more valuable to predict a person's intent to buy online than the person's characteristics such as age, gender, his intensity of computer use and his enjoyment when working with the computer.