The rapid development in global e-business has made the Internet an important and inevitable channel of trade and business communication, including e-negotiations, across countries. To have knowledge of how national culture may affect behavior, decision-making and negotiations is getting more important not only in conducting business but also in daily communications in the Internet age. The purpose of this study is to explore what will be different if people negotiate with counterparts who have different culture background. Will the negotiators behave differently when they negotiate with people who have different cultural background? In order to have more comprehensive understanding of the impact of culture on the actual negotiation behavior of negotiators in a negotiation process, we decided to apply content analysis methodology has been applied to the draft of negotiation interactions collected through the Inspire system which has collected countless records of negotiation activities since 1996.

Electronic negotiation (e-negotiation) is a relatively new technology that has spawned as a result of the growth of electronic commerce (e-commerce). While researchers have dealt with a variety of topics in the area of e-negotiation the acceptance of e-negotiation technology is a subject that needs further exploration. This study contributes to the research in e-negotiation, by putting forward a conceptual model that explains the factors that affect technology acceptance of e-negotiation. We survey past works in the technology acceptance literature, and review three seminal theories ? the technology acceptance model (TAM), the theory of planned behaviour (TPB) and the diffusion of innovation theory (DOI). We develop a conceptual model by identifying various factors and interrelationships amongst them that are valid for the context of our study. To test our model, we develop a web interface for participants to experience e-negotiation, and incorporate a survey instrument, adapted from previous studies, to assess participants' attitudes and perceptions towards using e-negotiation. We also test whether the presence of learning agents has an effect on perceptions of negotiation outcomes. Regression and MANOVA tests indicate that attitude and associated attitudinal beliefs have a significant influence on acceptance of e-negotiation technology. We also find that perceptions of negotiation outcomes affect e-negotiation acceptance; however, learning agents were not found to have an influence on perceptions of negotiation outcomes.

Electronic negotiation (e-negotiation) is a relatively new technology that has spawned as a result of the growth of electronic commerce (e-commerce). While researchers have dealt with a variety of topics in the area of e-negotiation the acceptance of e-negotiation technology is a subject that needs further exploration. This study contributes to the research in e-negotiation, by putting forward a conceptual model that explains the factors that affect technology acceptance of e-negotiation. We survey past works in the technology acceptance literature, and review three seminal theories ? the technology acceptance model (TAM), the theory of planned behaviour (TPB) and the diffusion of innovation theory (DOI). We develop a conceptual model by identifying various factors and interrelationships amongst them that are valid for the context of our study. To test our model, we develop a web interface for participants to experience e-negotiation, and incorporate a survey instrument, adapted from previous studies, to assess participants' attitudes and perceptions towards using e-negotiation. We also test whether the presence of learning agents has an effect on perceptions of negotiation outcomes. Regression and MANOVA tests indicate that attitude and associated attitudinal beliefs have a significant influence on acceptance of e-negotiation technology. We also find that perceptions of negotiation outcomes affect e-negotiation acceptance; however, learning agents were not found to have an influence on perceptions of negotiation outcomes.

Because of global economic influence and the prevalence of internet technology, the new e-commerce market gradually takes form. The more e-commerce grows the more e-negotiation activities increase. In the meanwhile, growing access to the worldwide has increased the amount of international, cross-cultural e-commerce negotiations conducted online. Due to increasing probability of inter-cultural factors in e-negotiation, understanding strategies over e-negotiations and discovering the impact of culture on strategies of e-negotiations become increasingly important. The purpose of this study is to explore the impact of different cultures on strategies of dyadic e-negotiations and to investigate the difference of strategy both in intra- and inter-cultural e-negotiation. Going to more detailed, this study further examines how Eastern and Western negotiators differ from each other in terms of their strategic adjustments. In order to have more comprehensive understanding of the impact of culture on the actual negotiation strategic behaviors in negotiation processes, we apply content analysis, which is more thorough than the questionnaire in terms of qualitative criteria. According to the result of this study, there are four major propositions: firstly, there are differences between intra- and inter-culture e-negotiation; secondly, the negotiation behavior of Easterners in inter-cultural negotiations will be different from that in intra-cultural negotiations; thirdly, the negotiation behavior of Westerners in inter-cultural negotiations will be different from that in intra-cultural negotiations; and finally, inter-cultural negotiation consistently has more ¡§distributive information¡¨ behavior in e-negotiations. These propositions can be analyzed from further viewpoints or conscientious experimentations in the future.

In the past decade, electronic negotiation has become an important research topic in the field of information systems. A desirable goal of negotiation agents is to understand their owners' requirements, and to learn their opponents' behavior, thereby lessening the involvement of human beings. Studies on human negotiation bring out that several issues can affect a human's negotiation behavior, including learning an opponent's behavior, exerting power on an opponent, and setting an individual goal to improve the level of accomplishment. Research on incorporating these issues into negotiation agents is, however, still at an infancy state. We therefore take up this topic in this thesis. Researchers have proposed many different negotiation agents that follow a preset behavior based on human models of negotiation. In this thesis, we consider one such model, known as the time-dependent-tactical model, which is used by human negotiators and in which the values of the negotiating issues are determined based on the time elapsed in the negotiation. A learning mechanism for this model might be beneficial, because this model is frequently used in electronic negotiation. Thus, we propose heuristic algorithms that estimate the parameters of an agent's time-dependent-tactical model, and that then react to the estimated parameters for achieving higher negotiation performance. Besides learning, we incorporate two other factors that have been found to affect a human negotiation outcome. These are situational power, which represents differences in negotiators' status based on market conditions, and goal constraints, which stand for the levels of accomplishment negotiators try to strive for. To validate the impacts of learning, situational power and goal constraints in electronic negotiation, we first present how to integrate these features into negotiation agents, and then conduct simulations. With 187,500 simulation runs, we observe that our learning algorithms are effective in improving both individual and dyadic negotiation performances. For the effects of situational power and goal constraints, we obtain congruent results between human and electronic negotiations. By incorporating learning into situational power and goal constraints, we achieve significant joint effect between learning and situational power as well as that between learning and goal constraints. In summary, this thesis provides three primary contributions to the fields of information systems and electronic-commerce research. First, we have designed algorithms for learning an opponent's negotiation behavior. Second, our learning algorithms are found to be effective in improving negotiation performance. Third, we have shown how learning can be integrated with situational power and goal constraints, although this is not a major focus in this study. Finally, the agreement on the joint effects of learning, situational power and goal constraints between human and electronic negotiations suggests that our integrated design of the agent appears to be effective.

In the past decade, electronic negotiation has become an important research topic in the field of information systems. A desirable goal of negotiation agents is to understand their owners' requirements, and to learn their opponents' behavior, thereby lessening the involvement of human beings. Studies on human negotiation bring out that several issues can affect a human's negotiation behavior, including learning an opponent's behavior, exerting power on an opponent, and setting an individual goal to improve the level of accomplishment. Research on incorporating these issues into negotiation agents is, however, still at an infancy state. We therefore take up this topic in this thesis. Researchers have proposed many different negotiation agents that follow a preset behavior based on human models of negotiation. In this thesis, we consider one such model, known as the time-dependent-tactical model, which is used by human negotiators and in which the values of the negotiating issues are determined based on the time elapsed in the negotiation. A learning mechanism for this model might be beneficial, because this model is frequently used in electronic negotiation. Thus, we propose heuristic algorithms that estimate the parameters of an agent's time-dependent-tactical model, and that then react to the estimated parameters for achieving higher negotiation performance. Besides learning, we incorporate two other factors that have been found to affect a human negotiation outcome. These are situational power, which represents differences in negotiators' status based on market conditions, and goal constraints, which stand for the levels of accomplishment negotiators try to strive for. To validate the impacts of learning, situational power and goal constraints in electronic negotiation, we first present how to integrate these features into negotiation agents, and then conduct simulations. With 187,500 simulation runs, we observe that our learning algorithms are effective in improving both individual and dyadic negotiation performances. For the effects of situational power and goal constraints, we obtain congruent results between human and electronic negotiations. By incorporating learning into situational power and goal constraints, we achieve significant joint effect between learning and situational power as well as that between learning and goal constraints. In summary, this thesis provides three primary contributions to the fields of information systems and electronic-commerce research. First, we have designed algorithms for learning an opponent's negotiation behavior. Second, our learning algorithms are found to be effective in improving negotiation performance. Third, we have shown how learning can be integrated with situational power and goal constraints, although this is not a major focus in this study. Finally, the agreement on the joint effects of learning, situational power and goal constraints between human and electronic negotiations suggests that our integrated design of the agent appears to be effective.

With the rapid growth of the Internet, more and more business conducted commercial activities electronically. It brought more and more electronic negotiations. Electronic negotiations solve the time and space problems between negotiators, and they could raise efficiency and effectiveness of negotiation. Furthermore, world-wide Internet access and globalization have increased the amount of international negotiations conducted online. To communicate with others coming from different countries, people maybe force to use non-native language as communication tool. Language usage is an important factor in electronic negotiation. Some studies on language usage on communication and traditional negotiation, and the findings can¡¦t apply to the e-negotiation because of the degree of media richness has been shown to affect negotiations. E-negotiation provides the function of recording negotiation history, and the negotiation history could be used to analyze the negotiation process. This study used content analysis methodology to analyze the strategic behavior of negotiators. This study is an exploration study, and provides four propositions: first, the language usage (native vs. non-native language) will impact e-negotiation behavior. Second, negotiators using native language employ more claiming value strategic behaviors than negotiators using non-native language. Third, compared with non-native language, negotiators will have higher communication effectiveness and efficiency when using native language in negotiation. Forth, compared with non-native language, negotiators will be easier to reach agreement when using native language in negotiation.

With the rapid development of global e-business and the popularity of Web technologies, e-negotiation has become an integral part of daily life for many managers in business. Moreover, female job achievements rose abruptly during these years. As greater numbers of females achieve upper level positions in business, the need to have an understanding of how gender affects negotiation behaviors becomes even more important. An awareness of the clear gender differences can help in managing conflicts in e-negotiations. This study aims to discover some interesting findings about the interdependence of gender and negotiation behaviors by using the research methodologies of explorative research and content analysis. We expect to infer propositions which will be verified in future research and have some contributions. This study also tries to understand if gender has influence on negotiators¡¦ behaviors and to determine whether negotiators¡¦ behaviors have departures in different dyadic composition of gender. This study reveals that females and males have different negotiation behaviors in e-negotiations, and negotiation behaviors are influenced by gender composition. Moreover, there are some differences in detailed negotiation behaviors between females and males in e-negotiations. Negotiators who meet the same gender counterparts have more ¡§reference to relationship¡¨ behavior. When males negotiate with females, they have more ¡§suggest package trade-off¡¨ behaviors. Females have more ¡§show negative emotions¡¨ behaviors in negotiating with males.

Today people already accustom to do businesses on the Internet. The electronic negotiation also becomes popular because of its advantages. Furthermore more and more females get high positions in their company and often engage important activities such as electronic negotiation for their company. If negotiators could understand the differences of males and females on their behavioral sequence and response strategy, they could have a better interaction during negotiation no matter what their counterpart s gender is. This study explores the relation of different gender compositions and response strategy in E-Negotiation. We design an algorithm to find significant sequential patterns and then group them into three kinds of response strategies. Lastly we use Chi-Square Independence Test to see the correlation and Column Comparison to see which gender composition has significant higher proportion on three types of response strategies. The result suggests gender compositions and response strategies are interrelated. Negotiators in inter-gender dyad are more likely to response with reciprocal strategy and negotiators in intra-gender dyad are more likely to response with structural strategy. Moreover female-only dyad is more likely to response with all kinds of strategies compared to male-only dyad. Finally female would response to male with more reciprocal strategies and to female with more complementary and structural strategies. On the other hand, male would response to female counterpart with more reciprocal strategies and to male counterpart with more structural strategies.