Track: Decision Technologies and Service Sciences
Minitrack: Multi-Agent and Intelligent Systems for Decision Support

To react quickly and successfully is a matter of knowledge and the task to provide relevant, updated and useful knowledge for management is the arena for developing, building and implementing intelligent support systems. With the advent of the World Wide Web and in an increasingly interconnected and networked world, Agents are semi-autonomous continuously running software entities that can support decision making. Multi-Agents use Web Services to provide new functionality or improved services to their users.

Web Intelligence has been recognized as a new direction for scientific research and development. It explores the fundamental roles as well as practical impacts of Artificial Intelligence and advanced Information Technology on the next generation of Web-empowered products, systems, services, and activities. It is one of the most promising IS research fields.

The Multi-Agent and Web Intelligence for Decision Support mini‑track is focused on the theory and applications of multi-agent, intelligent and knowledge-based systems, Web intelligence in management and for management support.

Topics and research areas include, but are not limited to:

• Concepts, methodologies, models, architectures and applications

• Technologies, frameworks, benchmarking and performances

• Problem solving and decision making

• Applications and experiences connected to relevant areas of decision making

• Knowledge engineering and management

• Foresight and scenario planning

• Digital economy

• Negotiation and contracting

• Supply chain management and cross-enterprise interoperability

• Business process management and re-engineering

• Marketing and customer relations management

• Social network technologies and management

• Financial decision making

• Organizational learning and e-learning

The methodologies used may be analysis or systems oriented, they may be actions research or case based, or they may be experimentally or empirically focused. Studies are favoured, which combine good theoretical results with careful empirical verifications, or good empirical problem solving with innovative theory building. A common denominator for all studies should be the design and use of multi-agent and/or intelligent or knowledge-based system and the implementation of this technology for effective and innovative management support.

Minitrack Co-chairs:

Dongming Xu
UQ Business School
The University of Queensland
Brisbane, Australia
Email: d.xu@business.uq.edu.au

Timothy J. Norman
Dept. of Computing Science
University of Aberdeen
Aberdeen, UK
Email: t.j.norman@abdn.ac.uk