Understanding the product information inference process in electronic word-of-mouth: An objectivity–subjectivity dichotomy perspective

We examined the actions of a customer when inferring product information from electronic word-of-mouth (eWOM) material at a website. We developed a customer purchase intention model and simulated various eWOM levels within this, adopting an objectivity–subjectivity dichotomy, and considering quality and preference as the major antecedents of customer purchase intention. We inferred the information that the customers had obtained from the eWOM by categorizing the customers’ responses. The eWOM was parameterized using mean and variance; products that were categorized into quality and preference goods. We considered four cases in which customers infer different product information and exhibit different reactions. Items for quality and preference goods were developed by using a card-sorting method. An experimental survey was conducted on 121 Korean Internet shopping mall users. The hypotheses were partially supported using a Partial Least Squares path comparison method. Overall, our study should provide guidance to firms in their managing eWOM systems by identifying how customers react to them at various levels.