Knowledge Discovery on Consumer Trust in B2C Electronic Commerce

The purpose of this research is to discover knowledge (association rules) in consumer behavioral data with regard to their trusting intension. The main research question is: “what are there consumer perception profiles that tend to be associated with a consumer's perception of trust?” To answer the question, real-world data obtained from a customer trust survey have been collected and analyzed using a data mining association rule discovery algorithm (APRIORI). From a managerial point of view, the analyzed results will provide some insights into specific target groups and their relevant drivers for trustworthiness. For example, one of the association rules is, customers who have high perception of trustworthiness and high perception of convenience make a transaction with 95% confidence. This shows the importance of trustworthiness and convenience for completion of transactions.