In daily negotiation, decision maker often affected to change the evalution of negotiation results by the offers which the opponent brought up in either positive or negative description. This is what the negotiation researcher callled ¡§framing effect¡¨. Framing theory first poposed by Kahneman & Tversky (1982) and researchers found there are many framing types and the framing effects proofed in many negotiation areas. On the other hand, the development of electronic bargainging is ofthen based on the assumption that human decision making is rational behavior, and there is no research applying framing theory on internet. Therefore this research would like to discuss whether framing could change electronic bargaining results. This research adopts attribute framing and goal framing proposed by Levin et al. (1998) and apply it with negotiation model to develop a virtual bargin store, then we play a role as seller to do field experiment. After collecting the experiment data and analyze them, we found framing do affect electronic bargining. Framing match concession will influence the seller¡¦s gain. General speaking, attribute framing effect is better than goal framing, and the difference between positive and negative attribute framing effect looms larger when it corporates with concession. However the difference between positive and negative goal framing looms less when it ties up with concession.

Abstract¡G With the rapid development of electronic marketplace, buyers and sellers can trade more easily without the limitations of time and distance. Internet trading is benefited to both sides in many ways. However, the matching mechanism between buyers and sellers in the electronic marketplace is not explored deeply. Consequently, the purpose of this research is to study the screening and negotiation in the process of matching. In this research, four screening models and related flow charts have been proposed. A negotiation model is also proposed to deal with the bargaining process. Finally, a prototype based on development method is built to demonstrate how the screening models and negotiation models work.

Multi-agent systems are a new computational approach for solving real world, dynamic and open system problems. Problems are conceptualized as a collection of decentralised autonomous agents that collaborate to reach the overall solution. Because of the agents autonomy, their limited rationality, and the distributed nature of most real world problems, the key issue in multi-agent system research is how to model interactions between agents. Negotiation models have emerged as suitable candidates to solve this interaction problem due to their decentralised nature, emphasis on mutual selection of an action, and the prevalence of negotiation in real social systems. The central problem addressed in this thesis is the design and engineering of a negotiation model for autonomous agents for sharing tasks and/or resources. To solve this problem a negotiation protocol and a set of deliberation mechanisms are presented which together coordinate the actions of a multiple agent system. In more detail, the negotiation protocol constrains the action selection problem solving of the agents through the use of normative rules of interaction. These rules temporally order, according to the agents' roles, communication utterances by specifying both who can say what, as well as when. Specifically, the presented protocol is a repeated, sequential model where offers are iteratively exchanged. Under this protocol, agents are assumed to be fully committed to their utterances and utterances are private between the two agents. The protocol is distributed, symmetric, supports bi and/or multi-agent negotiation as well as distributive and integrative negotiation. In addition to coordinating the agent interactions through normative rules, a set of mechanisms are presented that coordinate the deliberation process of the agents during the ongoing negotiation. Whereas the protocol normatively describes the orderings of actions, the mechanisms describe the possible set of agent strategies in using the protocol. These strategies are captured by a negotiation architecture that is composed of responsive and deliberative decision mechanisms. Decision making with the former mechanism is based on a linear combination of simple functions called tactics, which manipulate the utility of deals. The latter mechanisms are subdivided into trade-off and issue manipulation mechanisms. The trade-off mechanism generates offers that manipulate the value, rather than the overall utility, of the offer. The issue manipulation mechanism aims to increase the likelihood of an agreement by adding and removing issues into the negotiation set. When taken together, these mechanisms represent a continuum of possible decision making capabilities: ranging from behaviours that exhibit greater awareness of environmental resources and less to solution quality, to behaviours that attempt to acquire a given solution quality independently of the resource consumption. The protocol and mechanisms are empirically evaluated and have been applied to real world task distribution problems in the domains of business process management and telecommunication management. The main contribution and novelty of this research are: i) a domain independent computational model of negotiation that agents can use to support a wide variety of decision making strategies, ii) an empirical evaluation of the negotiation model for a given agent architecture in a number of different negotiation environments, and iii) the application of the developed model to a number of target domains. An increased strategy set is needed because the developed protocol is less restrictive and less constrained than the traditional ones, thus supporting development of strategic interaction models that belong more to open systems. Furthermore, because of the combination of the large number of environmental possibilities and the size of the set of possible strategies, the model has been empirically investigated to evaluate the success of strategies in different environments. These experiments have facilitated the development of general guidelines that can be used by designers interested in developing strategic negotiating agents. The developed model is grounded from the requirement considerations from both the business process management and telecommunication application domains. It has also been successfully applied to five other real world scenarios.

Made available in DSpace on 2016-08-17T14:53:18Z (GMT). No. of bitstreams: 1 Sergio Martins.pdf: 700705 bytes, checksum: 71c0b694334049a0c5cb00444741f529 (MD5) Previous issue date: 2007-09-14 / This work is part of the ICS Project (Intelligent Commerce System), currently in development in the Intelligent Systems Laboratory (LSI), at Universidade Federal do Maranhão (UFMA), under the coordination of the Prof. Dr. Sofiane Labidi. The project aims at developing an Intelligent environment of negotiation for electronic commerce among companies (business-to-business) and in a approaching in cycle of life composed of five stages. This work aims at main feature of the ICS that is the automation of the negotiation process to provide companies with favorable conditions for commercialization at a low operational cost, with rapidity and efficiency. The negotiation is the stage where the intelligent agents who represent the users (companies), initiate its searches for the satisfaction of its necessities through exchanges of purchase or seller proposals of goods and services. We present the proposed Negotiation Model and a prototype of the mediator agent which is responsible for the management of the negotiation process as a whole. / Este trabalho é parte do Projeto ICS (Intelligent Commerce System), atualmente em desenvolvimento no Laboratório de Sistemas Inteligentes (LSI), da Universidade Federal do Maranhão (UFMA), sob a coordenação do Prof. Dr. Sofiane Labidi. O projeto tem como objetivo desenvolver um ambiente inteligente de negociação de comércio eletrônico entre empresas (business-to-business). O ICS é baseado na tecnologia de agentes inteligentes móveis e numa abordagem em ciclo de vida composto de cinco fases. Este trabalho foca a característica principal do ICS que é a automação do processo de negociação para proporcionar às empresas condições favoráveis de comercialização a um baixo custo operacional, com rapidez e eficiência. A negociação é a fase em que os agentes inteligentes que representam os usuários (empresas) iniciam suas buscas pela satisfação de suas necessidades através de trocas de propostas de compra ou venda de bens e serviços. Apresentamos o modelo de negociação proposto e o protótipo do agente mediador, responsável pelo gerenciamento do processo de negociação como um todo.