Value Sinks: A Process Theory of Corruption Risk during Complex Organizing.

Theories and studies of corruption typically focus on individual ethics and agency problems in organizations. In this paper, we use concepts from complexity science to propose a process theory that describes how corruption risk emerges from conditions of uncertainty that are intrinsic in social systems and social interactions. We posit that our theory is valid across multiple levels of scale in social systems. We theorize that corruption involves dynamics that emerge when agents in a system take actions that exploit disequilibrium conditions of uncertainty and ethical ambiguity. Further, systemic corruption emerges when agent interactions are amplified locally in ways that create a hidden value sink which we define as a structure that extracts, or 'drains,' resources from the system for the exclusive use of certain agents. For those participating in corruption, the presence of a value sink reduces local uncertainties about access to resources. This dynamic can attract others to join the value sink, allowing it to persist and grow as a dynamical system attractor, eventually challenging broader norms. We close by identifying four distinct types of corruption risk and suggest policy interventions to manage them. Finally, we discuss ways in which our theoretical approach could motivate future research.

Emotional contagion and proto-organizing in human interaction dynamics.

This paper combines the complexity notions of phase transitions and tipping points with recent advances in cognitive neuroscience to propose a general theory of human proto-organizing. It takes as a premise that a necessary prerequisite for organizing, or "proto-organizing," occurs through emotional contagion in subpopulations of human interaction dynamics in complex ecosystems. Emotional contagion is posited to engender emotional understanding and identification with others, a social process that acts as a mechanism that enables (or precludes) cooperative responses to opportunities and risks. Propositions are offered and further research is suggested.

Toward a theory of leadership in complex systems: computational modeling explorations.

I propose a new theory of leadership in complex systems based upon computational modeling approaches that have appeared to date. It is new in that it promises an approach that is well specified, coherent across levels of analysis, is transparent to the outside observer and can be modeled computationally. Although many of its independent components have been modeled, the underlying theory connecting these models is articulated here for the first time. Leadership is defined as those aspects of agent interactions which catalyze changes to the local rules defining other agents' interactions. There are five distinct aspects of leadership to be observed. Leadership involves actions among agents that: (a) identify or espouse a cooperation strategy or program, (b) catalyze conditions where other agents choose to participate in the program, (c) organize choices and actions in other agents to navigate complexity and avoid interaction catastrophe (sometimes called 'complexity catastrophe'), (d) form a distinct output layer that expresses the system as a unity in its environment, and (e) translate feedback into structural changes in the influence network among agents. The contribution of this approach is discussed.