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.

The butterfly effect of the "butterfly effect".

The "Butterfly Effect" metaphor states with variance that the flap of a butterfly's wings in Brazil can cause a tornado in Texas. This metaphor has become part of the common vernacular of Western culture. In this paper I discuss the origins of the metaphor, examine its current usage within popular culture, and present an argument as to why it is popular. I propose that the metaphor is a type of semantic attractor, a narrative device with invariant meaning but audience-specific contextualization. Finally I address whether the Butterfly Effect metaphor is a good example of itself.

Modeling high-resolution broadband discourse in complex adaptive systems.

Numerous researchers and practitioners have turned to complexity science to better understand human systems. Simulation can be used to observe how the microlevel actions of many human agents create emergent structures and novel behavior in complex adaptive systems. In such simulations, communication between human agents is often modeled simply as message passing, where a message or text may transfer data, trigger action, or inform context. Human communication involves more than the transmission of texts and messages, however. Such a perspective is likely to limit the effectiveness and insight that we can gain from simulations, and complexity science itself. In this paper, we propose a model of how close analysis of discursive processes between individuals (high-resolution), which occur simultaneously across a human system (broadband), dynamically evolve. We propose six different processes that describe how evolutionary variation can occur in texts-recontextualization, pruning, chunking, merging, appropriation, and mutation. These process models can facilitate the simulation of high-resolution, broadband discourse processes, and can aid in the analysis of data from such processes. Examples are used to illustrate each process. We make the tentative suggestion that discourse may evolve to the "edge of chaos." We conclude with a discussion concerning how high-resolution, broadband discourse data could actually be collected.

Merger as marriage: communication issues in postmerger integration.

Many health care organizations have found themselves involved in mergers, acquisitions, alliances, networks, and other forms of structural change in order to reduce costs, improve utilization and service breadth, increase market leverage, and reduce variation in demand. This article examines three levels of communication issues that interact with one another and impact the likelihood of successful postmerger integration: affect, discursive frame, and negotiating position.