Leadership and Decision-Making in Team-Based Organizations: A Model of Bounded Chaotic Cycling in Emerging System States

Abstract

This article discusses the results of both intrinsic and instrumental case study investigations of team-based leadership and decision-making in an Association of Research Libraries (ARL) institution undergoing dramatic change and restructuring activities. Since team-based models were used extensively within the organization, systems theory is introduced. Chaos theory is next explained as a more robust theoretical framework for analyzing and describing the turbulence and rapid changes encountered by individuals attempting to make sense of these organizational shifts at both the micro and macro levels. Findings of this research suggest that a paradox occurs during periods of restructuring activities in organizations going through significant change: 1) models which are alternatives to traditional hierarchical bureaucracies are necessary for organizations to break from the status quo when confronted with the need for rapid and inclusive decision-making, and 2) organizational structures heavily influenced by self-organizing teams go through recursive phases of expansion, leading to unbounded chaos in leadership and decision-making processes. Employees identified a lack of individual accountability in team-based decisionmaking, the challenges of leadership at the individual level, and the need for defined supervisory roles were all issues to be addressed for the continued, successful evolution of the organization. As a result of these findings, the author then introduces an iterative, phase state model of chaotic cycling in emerging system states. This model focuses on bounded chaotic systems that blend selforganization with structural feedback mechanisms in leadership and decisionmaking processes.

Description
Keywords
Chaos theory
Citation
Gilstrap, Donald L. (2013): Leadership and Decision-Making in Team-Based Organizations: A Model of Bounded Chaotic Cycling in Emerging System States. Emergence: Complexity and Organization, 15 (3).