Dynamics of Negative Evaluations in the Information Exchange of Interactive Decision-Making Teams: Advancing the Design
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Dynamics of Negative Evaluations in the Information Exchange of Interactive Decision-Making Teams: Advancing the Design of Technology-Augmented GDSS Steven D. Silver 1 Accepted: 8 September 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
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. Keywords Team decision-making . Information exchange in teams . AI-augmented GDSSs . Ill-structured decisions . Negative evaluations in information typologies
1 Introduction The increasing use of teams as decision-making and problemsolving units in organizations (e.g. Park and DeShon 2010; Wong et al. 2011; Uitdewilligen and Waller (2018) increases the challenge to managing the well-recognized complexity in the interaction of their members. The decisions that these teams are commonly charged with most often do not have algorithmic or well-defined heuristic procedures for the evaluation of decision alternatives. Such decisions have consequently been classified as ill-structured (e.g. Mintzberg et al. 1976; Wu et al. 2013). The complexity of the managing teams
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10796-020-10063-y) contains supplementary material, which is available to authorized users. * Steven D. Silver [email protected] 1
Lucas Graduate School of Business, California State University, One Washington Square, San Jose, CA 95192, USA
toward optimizing decisions is clearly increased when decisions are ill-structured. Although there are now an increasing number of algorithmic and heuristic applications for the computer management of interactive task-directed teams (e.g., Hosack et al. 2012), managing interactive teams as aggregations of individuals with multiple objectives in decision-making continues to be a work-in-progress. See, for example, Kudaravalli e
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