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Provides an overview of major developments pertaining to generalized information theory during the lifetime of Kybernetes. Generalized information theory is viewed as a collection of concepts, theorems, principles, and methods for dealing with problems involving uncertainty‐based information that are beyond the narrow scope of classical information theory. Introduces well‐justified measures of uncertainty in fuzzy set theory, possibility theory, and Dempster‐Shafer theory. Shows how these measures are connected with the classical Hartley measure and Shannon entropy. Discusses basic issues regarding some principles of generalized uncertainty‐based information.

Presents an overview of currently recognized theories of imprecise probabilities and their possible extensions. It is shown how the theories are ordered by their levels of generality. A summary of current results regarding measures of uncertainty and uncertainty‐based information is also presented.

Decision making is inherently stressful since the decision maker must choose between potentially conflicting alternatives with unique hazards and uncertain outcomes. Whereas decision aids such as decision support systems (DSS) can be beneficial in stressful scenarios, decision makers sometimes misuse them during decision making, leading to suboptimal outcomes. The purpose of this paper is to investigate the relationship between stress, decision making and decision aid use.

The authors conduct an extensive multi-disciplinary review of decision making and DSS use through the lens of stress and examine how stress, as perceived by decision makers, impacts their use or misuse of DSS even when such aids can improve decision quality. Research questions examine underlying sources of stress in managerial decision making that influence decision quality, relationships between a decision maker’s perception of stress, DSS use/misuse, and decision quality, and implications for research and practice on DSS design and capabilities.

The study presents a conceptual model that provides an integrative behavioral view of the impact of a decision maker’s perceived stress on their use of a DSS and the quality of their decisions. The authors identify critical knowledge gaps and propose a research agenda to improve decision quality and use of DSS by considering a decision maker’s perceived stress.

This study provides a previously unexplored view of DSS use and misuse as shaped by the decision and job stress experienced by decision makers. Through the application of four theories, the review and its findings highlight key design principles that can mitigate the negative effects of stressors on DSS use.