It has been well-documented in the consumer behavior literature that risk relievers play an important role in reducing perceived risk. However, the research on the efficacy of risk relievers in segmenting online customers is scant. Thus, this study aims to investigate the usefulness of risk relievers in online shopping by presenting a cluster analysis of consumer risk reduction behavior based on risk-reliever utility scores and to understand whether these risk-reliever segments differ on the basis of perceived risk dimensions and purchase intention.
The data were collected from a survey of 677 customers using a nonprobability sampling technique. A two-step cluster analysis, using hierarchical and nonhierarchical clustering, was conducted on risk-reliever utility scores to segment the customers based on their risk reduction behavior. Furthermore, multivariate discriminant analysis was used to validate the results of cluster analysis. The segments were profiled based on their sociodemographic and behavioral characteristics. Later, one-way analysis of variance was applied to identify differences in the dimensions of perceived risk and purchase intention across clusters.
The cluster analysis on the risk-reliever utility scores yielded a classification of customers into four groups − maximum security seekers, minimum security seekers, information seekers and guarantee seekers. Discriminant analysis confirmed the validity of the four-cluster solution.
This study contributes to the existing literature on risk relievers by augmenting a new perspective of customer segmentation based on their risk reduction behavior. The findings are limited to the cultural context of the study. The researchers are, therefore, encouraged to extend the clustering approach to other developing countries to enhance the generalizability of the results.
The classification of customers provides better knowledge to the service providers about the preferences of risk relievers by different user segments. It offers valuable insights into the understanding of customers’ risk reduction behavior that will influence marketers to adopt different strategies for each segment to the alleviation of risk perception.
The originality of the research is its novelty in examining risk reduction as a segmentation variable to guide marketers toward adopting effective risk reduction strategies based on the personality and behavioral characteristics of each user segment.
