Interaction effects of consumers' product class knowledge and agent search strategy on consumer decision making in electronic commerce

摘要

This paper investigates the interaction effects between the search strategy of software agents and consumers' product class knowledge in the context of consumers seeking to purchase cars on the Internet. The research design used was a 2/spl times/4, between-groups, completely randomized, two-factor, factorial design. The independent variables that were manipulated were product class knowledge (HIGH KNOWLEDGE, LOW KNOWLEDGE) and agent search strategy [elimination by aspects (EBA STRATEGY), weighted average method (WAD STRATEGY), profile building (PROFILE STRATEGY), simple hypertext (HYPERTEXT STRATEGY)]. The dependent variables that were measured were satisfaction with the decision process (SATISFACTION), confidence in the decision (CONFIDENCE), trust in the agent's recommendations (TRUST), propensity to purchase (PURCHASE), perceived cost savings (SAVINGS), and cognitive decision effort (EFFORT). Significant differences were found in the affective reactions of the subjects toward the agent/application depending on the level of product class knowledge possessed by the subjects. Subjects with high product class knowledge had more positive affective reactions toward agents/applications that used the WAD and EBA strategies as compared to the PROFILE strategy. Subjects with low product class knowledge had more positive affective reactions to agents/applications that used the PROFILE strategy as compared to the EBA and WAD strategies.