Flexible decision support in dynamic interorganizational networks

wolfketterKolloquium von Wolf Ketter auf unbestimmte Zeit verschoben.

Abstract: An effective Decision Support System (DSS) should help its users improve decision-making in complex, information-rich, dynamic environments. We present a feature gap analysis of current decision support technologies, and we identify a set of DSS Desiderata, properties that can contribute both effectiveness and flexibility to users in such environments. We show that there is a gap between the features provided by current DSS technologies and the DSS Desiderata we aim for. We present a design-science approach that extends the boundaries of human decision-makers by creating a new and innovative artifact called „evaluator service networks“ at the confluence of people, organizations, and technology. Our artifact enables users to compose decision behaviors from separate, configurable components, and allows dynamic construction of analysis and modeling tools from small, single-purpose evaluator services. The result is a network that can easily be configured to test hypotheses and analyze the impact of various choices for elements of decision processes. We have implemented and tested this design in an interactive version of the MinneTAC trading agent, an agent designed for the Trading Agent Competition for Supply Chain Management. We present an example of an evaluator service network that determines sales prices in a rich, dynamic trading environment. Additionally we describe visual interface elements that allow users to see and manipulate the configuration of the network, and to construct economic dashboards that can display the current and historical state of any node in the network.

CV: Wolf Ketter is an assistant professor for business networks and markets at the Department of Decision and Information Sciences at the Rotterdam School of Management of the Erasmus University. Furthermore, he is a research member of the Computer Science and Engineering Department of the University of Minnesota. He founded and directs the Learning Agents Research Group at Erasmus (LARGE) where we research, develop, and use multi-agent systems in combination with machine learning methods to work on interesting problems in business and economic environments. He has published his work on major international conferences like AAAI or AAMAS and in reputed international journals like Decision Support Systems or the International Journal of Electronic Commerce.

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