Convincing DSS users that complex models are worth the effort
Decision Support Systems
Pluralistic multi-agent decision support system: a framework and an empirical test
Information and Management
Human versus automated facilitation in the GSS context
ACM SIGMIS Database
Could the use of a knowledge-based system lead to implicit learning?
Decision Support Systems
Impact of GDSS: opening the black box
Decision Support Systems
Information and Software Technology
Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs
Journal of Management Information Systems
Supporting group decisions by mediating deliberation to improve information pooling
Proceedings of the ACM 2009 international conference on Supporting group work
A Distributed Facilitation Framework
Proceedings of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges
How Incorporating Feedback Mechanisms in a DSS Affects DSS Evaluations
Information Systems Research
Using the fuzzy majority approach for GIS-based multicriteria group decision-making
Computers & Geosciences
Let's Shop Online Together: An Empirical Investigation of Collaborative Online Shopping Support
Information Systems Research
How are distributed groups affected by an imposed structuring of their decision-making process?
Proceedings of the 3rd International Conference on Human Computer Interaction
Gandhigiri in cyberspace: a novel approach to information ethics
ACM SIGCAS Computers and Society
The Level Paradox of E-Collaboration: Dangers and Solutions
International Journal of e-Collaboration
Facilitating Team Processes with Recommender Systems: A Behavioral Science Perspective
Proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies
Explaining data-driven document classifications
MIS Quarterly
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Intelligent user interfaces, particularly in interactive group settings, can be based on system explanations that guide model building, application, and interpretation. Here we extend Silver's (1990, 1991) conceptualization of decisional guidance and the theory of breakpoints in group interaction to operationalize feedback and feedforward for a complex multicriteria modeling system operating within a group decision support system context. We outline a design approach for providing decisional guidance in GDSS and then test the feasibility of the design in a preliminary laboratory experiment. Findings show how decisional guidance that provides system explanations at breakpoints in group interaction can improve MCDM GDSS usability. Our findings support Dhaliwal and Benbasat's (1996) conjecture that system explanations can improve decisional outcomes due to improvement in user understanding of decision models. Further research on intelligent agents, particularly in interactive group settings, can build on the concepts of decisional guidance outlined in this paper.