Dynamics of Negative Evaluations in the Information Exchange of Interactive Decision-Making Teams: Advancing the Design of Technology-Augmented GDSS

Abstract

Applications of technology that contribute to managing decision-making teams for their objectives benefit from an explicit account of microprocessing in the information exchange of team members. While negative evaluations are well recognized as a key information type in this exchange, the micro-processing that underlies its exchange has not been well defined. Negative evaluations will be proposed to differ from other information types because of their dual properties as information and affect. We propose dynamics that are implied by the duality in negative evaluations we cite and report empirical studies that test abstract generalizations on the proposed dynamics. We then give an explicit form to exchange of negative evaluations in a numerical model of information exchange and use the model in exercises that directly demonstrate the proposed properties of negative evaluations in information exchange. Finally, we review contributions that the discourse offers to the design of AI-supported GDSSs for managerial objectives in the exchange of information in ill-structured decision making and introduce architecture of a prototype GDSS that implements quality-maximizing information exchange. Directions for subsequent study are discussed.