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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/14538
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| Title: | KNOWLEDGE SHARING AND NEGOTIATION SUPPORT IN MULTIPERSON DECISION
SUPPORT SYSTEMS |
| Authors: | Jarke, Matthias |
| Issue Date: | May-1985 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | IS-85-37 |
| Abstract: | A number of DSS for supporting decisions by more than one person have
been proposed. These can be categorized by spatial distance (local vs.
remote), temporal distance (meeting vs. mailing), commonality of goals
(cooperation vs. bargaining), and control (democratic vs. hierarchical).
Existing frameworks for model management in single-user DSS seem
insufficient for such systems. This paper views multiperson DSS as a
loosely coupled system of model and data bases which may be human (the
DSS builders and users) or computerized. The systems components have
different knowledge bases and may have different interests. Their
interaction is characterized by knowledge sharing for uncertainty
reduction and cooperative problem-solving, and negotiation for view
integration, consensus-seeking, and compromise. Requirements for the
different types of multiperson DSS can be formalized as
application-level communications protocols. Based on a literature review
and recent experience with a number of multiperson DSS prototypes,
artificial intelligence-based message-passing protocols are compared
with database-centered approaches and model-based techniques, such as
multicriteria decision making. |
| URI: | http://hdl.handle.net/2451/14538 |
| Appears in Collections: | IOMS: Information Systems Working Papers
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