A variety of methods, techniques, and normative models, mainly derived from multiple criteria decision making (MCDM) and game theory, may be used to support groups of negotiators and decision makers (DM) in defining their goals, eliciting preferences, and building the negotiation offers’ scoring systems. The latter is fundamental for providing the groups with reliable decision support throughout the entire negotiation or group decision making process. However, many factors, such as cognitive issues, formal knowledge, and DM skills, may influence the actual use of scoring systems. Therefore, there is a constant need for redesigning the existing methods and designing new ones that allow for accurate preference modeling and elicitation for group decision and negotiation (GDN) process in a particular decision-making context, given the DMs’ limitations regarding information processing and all formal and behavioral issues involved.
The main goal of this stream is to create a forum for scientists, researchers, and practitioners working on the topic of preference modeling for GDN that will allow them to exchange their experience and knowledge and discuss the recent developments and results of their research. Thus, we invite contributors to submit the papers and sessions to this stream. Although not limited to, the stream includes the following topics:
- Preference modeling in GDN problems
- Methodological issues of preference analysis
- Preference issues for choosing voting procedures
- Preference modeling for mediation and arbitration
- Preference learning
- Behavioral studies on preference for GDN
- Neuroscience experiments on preference for GDN
- Experimental studies on preference for group decision and negotiation
- Experimental studies on decision makers’ cognitive capabilities and needs for formal support in group decision and negotiation
- Interfaces between GDN and MCDM
- Use of MCDM methods for preference modeling in group decision and negotiation
- Preferences in group decisions for MCDM
- Group decision support based on partial information on preferences
- Handling the imprecise and vague preference information
- Preference aggregation of decision-makers versus knowledge aggregation of experts
- Group decision support based on partial information on experts’ knowledge
Stream organizers
Danielle Morais, Federal University of Pernambuco, Brazil
Tomasz Wachowicz, University of Economics in Katowice, Poland