Academic journal article The Innovation Journal

Micro-Dynamic Disturbances in the Government Workforce as a Cause of Poor Organizational Performance

Academic journal article The Innovation Journal

Micro-Dynamic Disturbances in the Government Workforce as a Cause of Poor Organizational Performance

Article excerpt


Complex systems research has shown that localized interactions by select individuals can yield proliferated impact and hidden consequences for the total organization. This could be a poorly understood reason for why some government workforce transformation initiatives to improve motivation, management, goal identification, and know-how have not yielded consistently ideal results. This paper presents a set of complex systems analyses based on behavioral constructs for individual government workers who might use perception manipulation to falsely enhance their utility, authority, and criticality. These constructs can be used to build agents to simulate specific dynamic disturbances within a government organization. To support the analysis of such simulations, a range of potential impacts upon the organization are further formulated and presented.

Keywords: Government Workforce, Employee Behaviors, Organizational Dynamics, Complex Systems


Current public administration research is heavily reliant upon the application of quantitative-statistical analysis techniques on organization and government-wide performance data (Raadschelders, 2011). Other avenues of research through deductive, legal, historical, and heuristic techniques have also been pursued, and many theoretical perspectives have been formulated to drive continuing research (Harmon, 1986). The results of decades of study into the organization-wide (macro-dynamic) behaviors of the government workforce have promoted major transformational initiatives in the United States and elsewhere. Yet, contending schools of thought still endure and consistent results in advancing workforce performance remain elusive.

To investigate the disconnects between transformational objectives and results, the behaviors of the government workforce can be studied as a complex system where each individual in a large human-centric organization can push and pull against policies, processes, management structures, standards, and one another. The importance of complexity research to public sector innovation has recently been explained (Goldstein, 2008). In this paper, specific complex systems analysis techniques will be used to reveal the performance of the government workforce as a challenging unbounded problem with hidden patterns, latent forces, and unforeseen consequences. Past results in complex systems research have shown that even very simple behavioral constructs at the individual actor (agent) level can lead to incredibly complex system results at the organizational level as many agents interact with one another over time (Bossomaeir, 2007). Therefore, the isolated behaviors of individuals, such as a government employees misinterpreting, self adapting to, and/or self organizing against government reform efforts, may hinder sound public administration theories from achieving anticipated results at points of application.

Unbounded complex problems typically will not have enough initial data to enable statistical analysis or enough structure to enable traditional systems modeling through nodes and links. This is because the scope and dimensionality of each problem can only be determined through a process of discovery. Computer driven agent-based models can support this discovery process by following threads of interactions between many agents that lead to complexity. Through this process, patterns of poor behavior, forces causing employees to give up on responsibilities, and proliferated impact in the organization can be projected. These projections can then be used to search for validating data as well as areas where solutions can be applied. The heart of agent-based modeling is behavioral constructs for types of individuals in the complex system. This paper seeks to define a group of behavioral constructs for those individuals who could disrupt the transformational initiatives of a government organization. When agents with these constructs are placed in a specific simulation of an organizational environment, the proposal is that researchers will be able to see how difficult it is to detect localized (micro-dynamic) behaviors that can impact the greater macro-dynamic behaviors of the total organization. …

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