Streams

Stream organizers:

Liping Fang, Ryerson University, Toronto, Canada

Keith W. Hipel, University of Waterloo, Waterloo, Canada

D. Marc Kilgour, Wilfrid Laurier University, Waterloo, Canada

Stream description:

Strategic conflict arises whenever humans interact, individually or in groups. New, recently-developed methodologies and techniques that can help analysts understand strategic conflicts and provide strategic support to negotiators have been of great benefit to many decision makers. New theoretical issues are being explored, and at the same time new software systems are making modeling easier and analytical results clearer. Theoretical and practical advances have been utilized to study strategic conflicts arising in diverse areas including environmental management, global warming, energy projects, the food crisis, economic disparities, international trade and aging infrastructure. The main objective of the Stream on Conflict Resolution is to provide a forum for discussion of research advances on the development of formal approaches to conflict resolution with insightful applications in a range of domains. Prospective authors are cordially invited to submit original research developments and applications.

Stream organizers:

Stream description:

Electronic negotiations (or digital negotiations) are nowadays common business practice. The most important digital support is provided by dedicated Negotiation Support Systems (NSSs). These systems enable complex, asynchronous, and dislocated negotiations.

NSSs have always had the goal to support human intelligence. That goal has become broader in recent years incorporating Artificial Intelligence (AI) into system development and system design to enable the support of human intelligence by means of Artificial Intelligence.

Researchers, developers and practitioners who design and develop NSSs with or without AI, who study the use of NSSs in simulations and in the field, or who incorporate NSS components into negotiation, mediation and facilitation are invited to participate in the NS3 stream. We also encourage research addressing digital transformation of negotiations, i.e. how negotiation support systems transform organisations, processes, and practices.

We solicit papers looking at theory or practice or both. In particular, we seek papers that help bridging the gap between the vast amount of work on face-to-face negotiations and electronic negotiations as well as decision and negotiation aids embedded in negotiation processes. We also seek papers that focus on the design and use of tools for decision support, communication support, document management, or conflict management for the negotiators and mediators in electronic negotiation processes. Furthermore, we specifically look for papers on AI and NSSs, be it using Machine Learning, Generative AI, or some other type of AI.

One goal of the NS3 stream is to show the latest technological advances in NSS research and the current research in NSSs as well as in negotiation agents and their use in e-negotiation processes.

Topics of interest include but are not limited to:

• Digital transformation of business negotiations
• Artificial Intelligence in e-negotiations
• Machine learning as a research method in negotiation research
• Design of negotiation support systems
• Empirical research on negotiation support systems
• Bilateral, multi-bilateral and multi-lateral e-negotiations
• Cross-cultural online negotiations
• Electronic mediation and facilitation
• New applications for e-negotiations

Stream organizers:

Tomasz Wachowicz, Katowice School of Economics, Poland

Danielle Morais, Federal University of Pernambuco, Brazil

Stream description:

A variety of methods, techniques and normative models may be used for supporting group of negotiators and decision makers (DM) in defining their goals, eliciting preferences and building the negotiation offers’ scoring systems, often integrated with multicriteria decision making (MCDM) and game theory. Cognitive issues, formal knowledge and skills of DMs influence the redesigning of existing and designing the new methods for preference modeling and elicitation for group decision and negotiation (GDN) process. In order to make these models and methods more appropriate for real-world decision problems, preference modeling approaches need to be continuously improved, considering behavioural issues and DMs’ limitations regarding information and perception for evaluating preferences.

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 to exchange their experience and knowledge, and discussing the recent developments and results of their research. Thus we invite contributors to submit to this stream the papers and sessions. Although not limited to, the stream includes 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 onexperts’ knowledge

Stream organizers:

Pascale Zaraté, Toulouse Capitole University, France

Guy Camilleri, Université Paul Sabatier, France

Stream description:

Making a decision for a group engaged in a common task is a difficult challenge. There are several kinds of group decision making processes. This stream addresses Collaborative Decision Making processes. By Collaborative Decision Making processes, we intend that involved participants must pool their efforts in order to define and work on the achievement of a common goal. They have to integrate multiple points of view which reveal to be difficult. They have to work together, although not necessarily in the same place or at the same time. Decisional processes are then complex and involve a non-closed set of actors. The difficult point for decision-makers is to make a balance between their own preferences and the building of common preferences within the group. One direct application in the daily life of such Collaborative Decision-Making processes can be implemented through the e_democraty which is defined as a form of government in which all adult citizens are presumed to be eligible to participate equally in the proposal, development, and creation of laws.

The purpose of this stream is to allow researchers to present methodologies, mathematical models, and software supporting Collaborative Decision-Making processes. Submitted papers/abstracts can describe both theoretical and empirical studies like for example survey, field study, case study, experimentation…

Stream organizers:

Tung Bui, University of Hawaii Shidler College of Business

Stream description:

The rapid rise of generative AI has led to intelligent applications across many domains, including group decision and negotiation systems (GDNSS). While these technologies hold great promise for enhancing efficiency, effectiveness, and adaptability, they also raise global concerns around transparency, bias, ethical issues, and potential misuse.

This research stream explores the opportunities, limitations, and risks of generative AI in GDNSS and related fields such as conflict resolution, multi-agent systems, and collaborative environments. We invite position papers, empirical studies, and case analyses on the design, implementation, and ethical implications of AI in decision-making and negotiation systems. Key areas of interest include developing innovative applications of AI in GDNSS and ensuring transparency, fairness, accountability, and addressing broader societal impacts.

We welcome submissions from disciplines such as business, public policy, social sciences, and computer science that examine responsible AI design, development, and use in GDNSS to promote transparent, fair, and accountable systems while mitigating risks.

Stream organizers:

Zhen Zhang, Dalian University of Technology, China.

Yucheng Dong, Sichuan University, China.

Francisco Chiclana, De Montfort University, UK.

Enrique Herrera-Viedma, University of Granada, Granada, Spain.

Stream description:

In the contemporary era, group decision making has emerged as a pivotal approach for addressing complex and multifaceted problems. This process involves the collaboration of at least two experts who work together to devise solutions for predefined decision problems. With the rapid advancement of information and communication technology and the emergence of new decision paradigms such as Web 2.0, social networks, and e-democracy, decision environments have become increasingly intricate. The integration of intelligent technologies, particularly machine learning and artificial intelligence (AI), into group decision making has garnered significant attention from academics, researchers, and practitioners across various domains. AI-driven methodologies have shown promise in enhancing decision making processes by leveraging sophisticated algorithms and data analytics to improve the accuracy, efficiency, and effectiveness of group decisions.

Moreover, achieving satisfactory solutions in group decision making often requires a consensus process, wherein decision-makers engage in discussions, negotiations, and revisions of their opinions to reach a mutually agreed-upon level of agreement. This consensus process is crucial for ensuring that diverse perspectives are considered, thereby increasing the likelihood of successful implementation.

The aim of this stream is to create a platform where researchers and practitioners can converge to discuss cutting-edge advancements in intelligent group decision making and consensus process. We invite contributions that explore the theoretical, methodological, and practical aspects of these topics, as well as their applications in real-world decision making scenarios. Topics of interest include, but are not limited to:

• Information fusion in intelligent group decision making
• Computational intelligence-based group decision making
• Data-driven group decision making
• Generative AI-based group decision making
• Preference learning in group decision making
• Consensus modeling in group decision making
• Opinion dynamics and social network-based consensus modeling
• Behavior management in consensus modeling
• Decision support systems and software for intelligent group decision making and consensus modeling
• Real-world applications of intelligent group decision making and consensus modeling in various fields, such as healthcare, finance, transportation, and digital transformation

Stream organizers:

Stream description:

Risk evaluation over business, programs, and conflicts are commonly observed and extensively analyzed in the real world. Risks in complex systems have been paid increasing attentions by researchers. Formal methodologies have been developed to help understand risks in negotiation and discover courses of action to reach desired agreements. The main purpose of this stream is to provide a forum to present novel risk evaluation models and their applications to negotiation. The topics of interest includes but are not limited to:

• Risk evaluation models and tools
• Conflict intervention
• Negotiation models and tools
• Negotiation strategies with third-party intervention
• Attitude and behavior of intervention