Green vs. Non-Green Customer Behavior: A Self-Organizing Time Map over Greenness

Abstract

Companies have traditionally used segmentation approaches to study and learn more about their customer base. One area that has attracted considerable amounts of research in recent years is that of green customer behavior. However, the approaches used have often been static clustering approaches and have focused on identifying green vs. non-green customers. In fact, results have been non-unanimous and not seldom contradictory. An alternative approach is to study customers according to degrees of green purchases. Recently, a Self-Organizing Time Map (SOTM) over any variable of cardinal, ordinal or higher level of measurement has been proposed. The key idea is to enable the exploration of changes in cluster structures over not only the time dimension, but also any other variable. This paper presents an application of the SOTM to demographic and behavioral customer data, in which the key focus is on assessing how customer behavior varies over customers' degree of greenness.