GDNICDSST2024
Congresso24th International Conference on Group Decision and Negotiation & 10th International Conference on Decision Support System Technology
In a time when technology is rapidly evolving, decision-makers face two major challenges: (1) using technology to improve the decision process, and (2) ensure that decisions really support the best interest of the actors involved. On the one hand, the evolution of machine learning and AI offers incredible benefits, on the other hand, we, as technology creators, must ensure that humans remain the main beneficiaries of new services, software, and policies.
The transition period society is going through brought even more complexity to the decision processes by increasing uncertainty regarding the future. Whatever is our research focus (climate, energy, AI, automation, information and communication technology, etc.), change, transition, and challenges are recurrent. Add uncertainty to the mix and we have highly complex decisions processes, with several interested actors and multiple levels of goals. This recurring uncertainty has impacts on economics, employment, demographics, politics, and other societal concerns.
At this joint conference, we will promote discussions on the human and technological aspects of decision-making processes to build bridges between the two domains:
1- From the human perspective, research should ensure that humans remain at the centre of the decisions, with participatory and negotiation processes that promote co-creation and co-design of technology, services, and regulations. Such reliable decision processes increase trust and fairness of the decisions.
2- From the technological perspective, research must demonstrate that technology can be trusted and that proposed solutions are safe, inclusive, and fair.
These two perspectives are brought to the conference from the experience that each group has in the decision-making domain.
Group Decision and Negotiation
The field of Group Decision and Negotiation focuses on decision processes with at least two participants and a common goal. Such processes are complex and self-organising, and constitute multi-participant, multi-criteria, ill-structured, dynamic, creative, and often evolutionary problems. Major approaches include:
- Information systems, in particular negotiation support systems (NSSs) and group decision support systems (GDSs);
- Cognitive and behavioural sciences as applied to group decision and negotiation;
- Conflict analysis and resolution;
- Applied game theory, experiment, and social choice;
- Artificial intelligence;
- Management science as it relates to group decision making and negotiation.
Many research initiatives combine two or more of these approaches.
Group Decision and Negotiation can be performed in an intra-organisational as well as an inter-organisational context. Both consist of complex processes, including preference elicitation, proposals and counter-proposals, preference adjustment, and choice. Communication and decision making are the two key process steps in Group Decision and Negotiation, and thus require sophisticated support in many ways.
Application areas of Group Decision and Negotiation include intra-organisational and inter-organisational coordination (as in operations management and integrated design, production, finance, marketing, and distribution functions, such as coordination of all phases of the life cycle of a product), computer-supported collaborative work and meetings, electronic negotiations, including negotiating agents and negotiation support systems, labour-management negotiations, inter-organisational, intercultural negotiations, environmental negotiations, and many others.
Decision Support Systems Technology
Decision support systems assume an important role in ensuring that the decision-makers really get the best information, knowledge, and support in designing the correct solutions. Decision Support Systems (DSS) are designed to assist policymakers (and not only) to tackle issues that are increasingly complex, allowing to consider multiple objectives, multiple actors, offering robust solutions based on mathematical theoretical models, such as multicriteria decision analysis, optimization algorithms, heuristics, or simple data visualization based on data mining analysis. Moreover, DDS require great amount of data to offer information, knowledge, and real support to decision-makers.
In the modern digital age, theoretical and technological advances allow DSSs to better model human decision-making capabilities. Societal dependence on digital platforms, and the “real time information” offerings, accentuate the demand for a customized and intelligent decision support able of meeting the needs of modern industry, business, and society.