The Michigan Internet AuctionBot: a configurable auction server for human and software agents
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Fuzzy logic: intelligence, control, and information
Fuzzy logic: intelligence, control, and information
Knowledge management and data mining for marketing
Decision Support Systems - Knowledge management support of decision making
E-Business and E-Commerce for Managers
E-Business and E-Commerce for Managers
Electronic commerce 2006: a managerial perspective
Electronic commerce 2006: a managerial perspective
Effect of bargaining in electronic commerce
International Journal of Electronic Commerce - Special issue: Intelligent agents for electronic commerce
Computers and Industrial Engineering
International Journal of Intelligent Engineering Informatics
Expert Systems with Applications: An International Journal
Multi-Agent Negotiation in B2C E-Commerce Based on Data Mining Methods
International Journal of Intelligent Information Technologies
Customer Orientation Based Multi-Agent Negotiation for B2C e-Commerce
International Journal of Agent Technologies and Systems
Multi-Agent Negotiation Paradigm for Agent Selection in B2C E-Commerce
International Journal of Agent Technologies and Systems
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The growth of electronic commerce has created the need of automated bargaining agents for improving the efficiency of online transactions. From the perspective of customer relationship marketing (CRM), establishing and maintaining the best possible relationship with valuable customers is a good way to survive in the competitive global market. In order to retain valuable customers, high share customers ought to be treated differently from the low share customers in the bargaining process. In our research, we formulate strategies for a bargaining agent based on the CRM principle. Bargaining tactics are expressed as fuzzy rules that mimic a human bargainer's knowledge and judgment in making decisions. Actions of the bargaining agent are determined by using approximate reasoning from the set of fuzzy rules. Our bargaining agent and three other bargaining agents found in the literature are employed in an experimental online store. Experimental results indicate that our bargaining agent is more efficient and creates greater customer satisfaction and customer loyalty than do the bargaining agents from the literature.