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A mathematical model for exploring the evolution of organizational structure

A mathematical model for exploring the evolution of organizational structure Purpose – This paper aims to explore organizational structure, efficiency and evolution, and its relationship to bureaucracy. A new mathematical model is utilized to generate theoretically consistent relationships between economic performance and organizational scale and structure, and to develop a taxonomy of organizational structure. Design/methodology/approach – A systems approach is used to model structural evolution and generate consistent, testable hypotheses concerning organizational sustainability and financial performance. This theoretical treatment seeks to reconcile contradictory views of bureaucracy, modeling both positive and negative impacts on performance and behavior. A variant of agency theory is used as an organizing paradigm, based on three competing organizational needs: control, autonomy and ownership of consequences. Findings – Simulations reveal that organizations evolve through five stages of development: from an entry (flat/parallel) stage, through a hybrid or mixed stage, to the massively serial (hierarchical) stage. As firms evolve, the risk/return ratio first falls as employment expands, but later rises as higher levels of hierarchy appear. Eventually, organizational complexity rises sufficiently to produce lower levels of managerial ownership of consequences and professional autonomy, as well as higher levels of control, leading to a collapse of organizational efficiency. A subtle variation of agency theory is revealed: upper-management may maximize organizational depth, increasing salary differences between levels. Originality/value – This paper uses an internally consistent, deductive framework to elucidate relationships between task complexity, skill level, industry life-cycle and firm age – providing the first known attribute-based metric for organizational complexity. This approach is reminiscent of Perrow’s (1999) non-mathematical treatment of organizational systems complexity. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Organizational Analysis Emerald Publishing

A mathematical model for exploring the evolution of organizational structure

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1934-8835
DOI
10.1108/IJOA-10-2011-0519
Publisher site
See Article on Publisher Site

Abstract

Purpose – This paper aims to explore organizational structure, efficiency and evolution, and its relationship to bureaucracy. A new mathematical model is utilized to generate theoretically consistent relationships between economic performance and organizational scale and structure, and to develop a taxonomy of organizational structure. Design/methodology/approach – A systems approach is used to model structural evolution and generate consistent, testable hypotheses concerning organizational sustainability and financial performance. This theoretical treatment seeks to reconcile contradictory views of bureaucracy, modeling both positive and negative impacts on performance and behavior. A variant of agency theory is used as an organizing paradigm, based on three competing organizational needs: control, autonomy and ownership of consequences. Findings – Simulations reveal that organizations evolve through five stages of development: from an entry (flat/parallel) stage, through a hybrid or mixed stage, to the massively serial (hierarchical) stage. As firms evolve, the risk/return ratio first falls as employment expands, but later rises as higher levels of hierarchy appear. Eventually, organizational complexity rises sufficiently to produce lower levels of managerial ownership of consequences and professional autonomy, as well as higher levels of control, leading to a collapse of organizational efficiency. A subtle variation of agency theory is revealed: upper-management may maximize organizational depth, increasing salary differences between levels. Originality/value – This paper uses an internally consistent, deductive framework to elucidate relationships between task complexity, skill level, industry life-cycle and firm age – providing the first known attribute-based metric for organizational complexity. This approach is reminiscent of Perrow’s (1999) non-mathematical treatment of organizational systems complexity.

Journal

International Journal of Organizational AnalysisEmerald Publishing

Published: Mar 9, 2015

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