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.
關聯:
Electronic Commerce Research and Applications 6(4) , pp490-498
