Understanding Agent-Based On-Line Persuasion and Bargaining Strategies: An Empirical Study

The application of software agents to facilitate on-line trading was an important initiative at the dawn of e-commerce, but researchers have not studied the effects of agent-to-human persuasion under different customer characteristics. This paper investigates the application of several persuasion and bargaining strategies to customers with different elaboration levels. Two experiments based on the Elaboration Likelihood Model (ELM) were conducted in an on-line used-car-selling scenario. A software agent interacting with customers as a virtual salesperson adopted a persuasion strategy that was either relevant or irrelevant to product attributes and a bargaining strategy that was either tough or moderate. The results show that if the sales agent's strategies accord with the customer's characteristics, the customer's purchasing attitude can be changed and the seller's profit increased. This finding can be used as a guideline in designing sales agents for on-line sales activities.