About this book
This book proposes an approach to analyzing, designing and implementing Group Decision Support Systems (GDSS). The experience gained in developing a concrete system, Co-oP, suggests that GDSS should be distributed, loosely-coupled and process-driven. A distributed and loosely-coupled GDSS architecture provides autonomy and flexibility for individual decision-making, and homogeneity and simplicity for group problem solving. Also, process-driven GDSS are able to deal with the unpredictable nature of group problems since collective decision processes have been shown to be the only elements in a GDSS that are (i) stable enough to fit into most collective problems, (ii) reasonably structurable to be implementable, and (iii) sufficiently controllable to guarantee appropriate use. From a Multiple Criteria Decision-Making (MCDM) viewpoint, this book supports the integrated use of various MCDM methods to help a GDSS (i) support a wide range of decision situations, (ii) attenuate the difficulty of information search, (iii) allow division of decision-making tasks, and (iv) permit consensus seeking analysis. Co-oP runs on a network of individual workstations. It contains a set of MCDM methods, techniques of aggregation of preferences, and a consensus seeking algorithm to support negotiation. Electronic communication among group members is monitored by a group norm filter which is adaptable to a large number of collective decision situations. This book also reports some empirical evaluations of Co-oP and expands the proposed approach to non-cooperation and organizational decision-making.
algorithms control decision support system linear optimization organization problem solving