Modified Even-Swaps: A Novel, Clear, Rational And An Easy-To-Use Mechanism For Multi-Issue Negotiation

"Even-Swaps" is a well-known and easy-to-use trade-off methodology which provides several useful features to decision makers. It allows them to find the difference among alternatives in terms of any issue under consideration. In a typical negotiation environment, allocating these differences in terms of a bargainable issue can help the negotiators to clarify the agreement area for each alternative. This allocation can contribute to make bargaining decisions more rationally. However, this feature could not be used in the original version of the Even-Swaps method because of its rigid structure that tries to reveal only the best alternative. The original Even-Swaps method also provides several hypothetical questions to decision makers while performing issue trade-offs. It is believed that the original Even-Swaps method can be improved upon (adapted) by forwarding the hypothetical questions to sellers and by developing a modified/flexible structure which considers all bargainable alternatives. With these modifications are successfully realized, an agent can generate counter offers and interact with sellers for bargaining by means of an appropriate automated-negotiation mechanism. The development of an automated & multi-issue negotiation-mechanism for bargaining also presents unique opportunities for the re-evolution of consumers into customers while contributing to the buyer-seller interactions. In this study, we present a novel multi-issue negotiation mechanism which adapts a modified Even-Swaps method that finds the differences among alternatives and makes use of those differences to assess the value of multi-issue offers. It uses a fuzzy inference system for bargaining on several issues simultaneously. In order to accomplish the steps of the proposed mechanism, a supplementary semi-automated decision-aid tool, so called: "Modified Even-Swaps Agent (MESA)" is developed. A real case-study is presented step by step in order to demonstrate how the proposed mechanism works. (C) 2012 Elsevier Ltd. All rights reserved.