Intra-Team Strategies for Teams Negotiating Against Competitor, Matchers, and Conceders

Victor Sánchez-Anguix, Reyhan Aydogan, Vicente Julian, Catholijn Jonker

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Under some circumstances, a group of individuals may need to negotiate together as a negotiation team against another party. Unlike bilateral negotiation between two individuals, this type of negotiations entails to adopt an intra-team strategy for negotiation teams in order to make team decisions and accordingly negotiate with the opponent. It is crucial to be able to negotiate successfully with heterogeneous opponents since opponents’ negotiation strategy and behavior may vary in an open environment. While one opponent might collaborate and concede over time, another may not be inclined to concede. This paper analyzes the performance of recently proposed intra-team strategies for negotiation teams against different categories of opponents: competitors, matchers, and conceders. Furthermore, it provides an extension of the negotiation tool Genius for negotiation teams in bilateral settings. Consequently, this work facilitates research in negotiation teams.
Original languageEnglish
Title of host publicationNovel Insights in Agent-based Complex Automated Negotiation
EditorsIvan Marsa-Maestre, Miguel A. Lopez-Carmona, Takayuki Ito, Minjie Zhang, Quan Bai, Katsuhide Fujita
Place of PublicationTokyo
PublisherSpringer
Pages3-22
Number of pages20
ISBN (Electronic)978-4-431-54758-7
ISBN (Print)978-4-431-54757-0
DOIs
Publication statusPublished - 24 Jan 2014

Publication series

NameStudies in Computational Intelligence
Volume535

Keywords

  • Agreement technologies
  • Collective decision making
  • Negotiation teams

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    Sánchez-Anguix, V., Aydogan, R., Julian, V., & Jonker, C. (2014). Intra-Team Strategies for Teams Negotiating Against Competitor, Matchers, and Conceders. In I. Marsa-Maestre, M. A. Lopez-Carmona, T. Ito, M. Zhang, Q. Bai, & K. Fujita (Eds.), Novel Insights in Agent-based Complex Automated Negotiation (pp. 3-22). (Studies in Computational Intelligence; Vol. 535). Tokyo: Springer. https://doi.org/10.1007/978-4-431-54758-7_1