• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.161-169
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• 2010

The requirement elicitation is the task of eliciting requirements from needs of stakeholders, and preparing for information for negotiation. However, there are methods for gathering needs, but there is no specific method for classifying them, generating information for negotiation. Therefore, To solve the problems, this paper proposes a method to classify requirement and to generate information for negotiation. The proposed methods use Kano model, statistical technique, and identifying relationship between requirements and problems within scope. Finally, we validate the proposed method on simulations, Rough Set Theory, and case study of model.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.155-175
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• 2003

In context of e-commerce, negotiation is a procedure to help negotiate between buyer and seller by adjusting their negotiation issues such as price and in terms of payment. We used intelligent agent and mobile device to promote new framework of e-commerce. Moreover, this framework can help buyers and sellers to carry their commercial transactions effectively. In regard to that issue, we need to carry out the research of negotiation agent that can be used in e-commerce fields. In this paper, we modeled the negotiation using CSP for the performance of agent in m-commerce environment. Furthermore we implemented interface for mobile device to extract buyer's requirement and preference easily Besides that we used utility function to make a decision for various evaluation functions and suggestions that are used for evaluation of negotiation issues. A difficulty of generating offer is dependent on the number of negotiation issues and the range of the values. Therefore, if any offer has a number of negotiation issues and the range of values are wide, the search space will be exponentially expanded. There have been many studies fur solving this problem, we applied those techniques to improve the agent's ability of negotiation. For example, a contract can be accomplished by exchanging seller and buyer's offer that is generated by agent to adjust the requisite profit for each party. Finally, we show the improvement of satisfaction as the negotiation is processed.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.35-51
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• 2005

The wide spread of Internet and rapid development of e-commerce-related technology have brought sweeping changes on the traditional commercial transactions. Accordingly, many efforts to transform these transactions electronically under e-commerce environment have been carried out. As most transactions are usually made through negotiations, the function of automated negotiation is also required in the e-commerce environment. This paper aims to develop the method to generate and evaluate the multi-attribute negotiation proposals for automated negotiation systems. To this end the related articles are reviewed and the method dealing with e-negotiation strategy is suggested. In this method, the seller generates his or her own negotiation proposal and then evaluates the buyer's proposal based on SAW (Simple Additive Weighting Method), one of the MADM (Multi Attribute Decision Making) methods. To verify the suggested method, a case study is conducted in the order-based manufacturing environment.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.731-740
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• 2004

In this paper we propose a fast negotiation agent system that guarantees the reciprocity of the attendants in a bilateral negotiation on the e-commerce. The proposednegotiation agent system exploits the incremental learning method based on an artificial neural network in generating a counter-offer and is trained by the previous offer that has been rejected by the other party. During a negotiation, the software agents on behalf of a buyer and a seller negotiate each other by considering the multi-attributes of a product. The experimental results show that the proposed negotiation system achieves better agreements than other negotiation agent systems that are operated under the realistic and practical environment. Furthermore, the proposed system carries out negotiations about twenty times faster than the previous negotiation systems on the average.