On the relationship between organizational complexity and organizational structuration (original) (raw)
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A Journal of Complexity Issues in Organizations and Management
Emergence A Journal of Complexity Issues in Organizations and Management EDITORIAL BOARD Michael Lissack, New England Complex Systems Institute < http://www. emergence. org/>;< lissack@ lissack. com> Max Boisot, Judge Management Institute, Cambridge,< max. boisot@ bcn. servicom. es> David Boje, New Mexico State University,< dboje@ NMSU. Edu> Jerry Chandler, George Mason University,< jlrchand@ erols. com> Robert Chia, University of Essex,< rchia@ essex. ac.
Method to Address Complexity in Organizations Based on a Comprehensive Overview
Information, 2021
Digitalization increasingly enforces organizations to accommodate changes and gain resilience. Emerging technologies, changing organizational structures and dynamic work environments bring opportunities and pose new challenges to organizations. Such developments, together with the growing volume and variety of the exchanged data, mainly yield complexity. This complexity often represents a solid barrier to efficiency and impedes understanding, controlling, and improving processes in organizations. Hence, organizations are prevailingly seeking to identify and avoid unnecessary complexity, which is an odd mixture of different factors. Similarly, in research, much effort has been put into measuring, reviewing, and studying complexity. However, these efforts are highly fragmented and lack a joint perspective. Further, this negatively affects the complexity research acceptance by practitioners. In this study, we extend the body of knowledge on complexity research and practice addressing i...
Applying the science of complexity to the question of organization
Applying the science of complexity to the question of organization, 2014
In this master thesis, the question is explored of how complexity theory can inform and challenge the study of organizations. Complexity theory researches complex social and natural systems and the phenomena to which they give rise, such as emergence, adaptiveness, self-organization and complexity. It has been suggested that (human) organizations are complex systems, being composed of many actors which, through local interactions, generate emergent behavior on the level of the organization as a whole. If this is true, it challenges many of the – implicit - assumptions we hold when thinking and writing about organizations. Drawing on complexity scholars and organization theorists such as Ralph Stacey, Paul Cilliers, and Edgar Morin, I analyze and critically evaluate (1) How complexity theory has been used in organizations studies so far (2) What theoretical and ethical consequences the insights from complexity theory hold for the way we think about organizations (3) What a theory of organization rooted in complexity studies could look like (4) How professionals working with organizations can develop an attitude that allows them to better deal with complexity in their practice. I conclude that complexity theory has important consequences for the way we think and work in organizations, proposing an approach which is not aimed at reducing complexity for those involved, but at engaging it from an attitude which is both modest and reflective. My thesis was awarded with the Leo Polak Thesis Prize 2014 (second prize).
Internal versus external complexity: how organizations react
Weber, T., McPhee, M.J. and Anderssen, R.S. (eds) MODSIM2015, 21st International Congress on Modelling and Simulation, 2015
This paper investigates the effects of environmental complexity on organizational performance by means of computational modeling. There are few works that prepare a bottom-up, mechanism-based account of organization-environment interactions. Rather, a lot of top-down, statistical models have been developed which fall short of explaining how an organization can handle uncertainties. The theoretical foundation of this paper is based on the concept of learning, which is a running thread linking organization science with the agent-based modeling paradigm. The definition of environmental complexity is based on Shannon's famous information entropy which represents a good conceptualization of complexity. The definition contains appropriately all facets of environmental uncertainty including degree of uncertainty, number of decision elements, and interdependence or interrelatedness among decision elements. In this paper, the process conception of learning is considered, because it is consistent with behavioral theory of organizational learning and can be modeled as a learning algorithm. Organizational learning is modeled as a Reinforcement Learning (RL) algorithm that operates as a trial-and-error search with delayed reward. The appropriateness of RL comes from the fact that the overall objective of managers is to align organizations towards environmental requirements and thus the environment feedback plays a key role in the decision making process within any organization. Among various conceptualizations of organizations, they are viewed problem-solving entities in this paper. The question considered is how environmental complexity affects organizational performance. To examine the effects of environmental complexity, an organization is exposed to different levels of environmental complexity, represented as decision rules. The requirements to accommodate environmental complexity have some counterintuitive effects on productivity. The results of the model show that the complexity of environment requirements has positive effects on organizational performance. In other words, if the organization can learn from the complexity of the environment, it can improve its performance. The computational model developed can be used to investigate other questions like the effects of internal complexity or organizational memory on performance.
… , University of California …
Stephen J. DeCanio* William E. Watkins** Glenn Mitchell* Keyvan Amir-Atefi* Catherine Dibble*** ... Stephen J. DeCanio Department of Economics University of California Santa Barbara, CA 93106 805-893-3130 fax: 805-893-8830 E-mail: decanio@econ.ucsb.edu
On the Study of Complexity in Information Systems
International Journal of Information Technologies and Systems Approach, 2000
This article addresses complexity in information systems. It defines how complexity can be used to inform information systems research, and how some individuals and organizations are using notions of complexity. Some organizations are dealing with technical and physical infrastructure complexity, as well as the application of complexity in specific areas such as supply chain management and network management. Their approaches can be used to address more general organizational issues. The concepts and ideas in this article are relevant to the integration of complexity into information systems research. However, the ideas and concepts in this article are not a litmus test for complexity. We hope only to provide a starting point for information systems researchers to push the boundaries of our understanding of complexity. The article also contains a number of suggested research questions that could be pursued in this area.
An Enterprise Complexity Model
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In this chapter, the author proposes an enterprise complexity model (ECM), which is visualized as a methodology to achieve the distributed governance of an ecology of evolving enterprises. Governance is understood as guiding the enterprises selforganization towards policies creating, regulating, and producing products and services for society. Self-organization is grounded in the communications and interactions of stakeholders. The purpose of an ECM model is not institutional development but guiding, enabling and facilitating interactions of all kinds with the support of current and disruptive technologies to increase society's requisite variety to deal with social, ecological, and economic challenges. An enabling context helps the branching of the enterprises' creativity into all kinds of innovations, forms of coordination, and operational alignment of their interests. Quality of life, fairness, and social justice are the values driving this ecology of enterprises towards a deeper and wider appreciation of issues of social concern.
Complexity theories and organizational change
International Journal of Management Reviews, 2005
Complexity theory or, more appropriately, theories, serves as an umbrella term for a number of theories, ideas and research programmes that are derived from scientific disciplines such as meteorology, biology, physics, chemistry and mathematics. Complexity theories are increasingly being seen by academics and practitioners as a way of understanding and changing organizations. The aim of this paper is to review the nature of complexity theories and their importance and implications for organizations and organizational change. It begins by showing how perspectives on organizational change have altered over the last 20 years. This is followed by an examination of complexity theories and their implications for organizational change. The paper concludes by arguing that, even in the natural sciences, the complexity approach is not fully developed or unchallenged, and that, as yet, organization theorists do not appear to have moved beyond the stage of using it as metaphor rather than as a mathematical way of analysing and managing organizations.
The evolution of complexity within firms
Connectivity and complexity of markets influence the internal organization of firms. As markets move through their lifecycle, so do the firms competing in the market. There is a small spectrum of appropriate fit between the stage of market evolution and the corresponding internal structure of the firm and its ability to exchange information with the market. Furthermore, as markets develop and simplify their dynamics, there is a migration of information and complexity to within the firm dictated by the permeability; or lack thereof, of the firms' boundaries and their strategic stance. This article examines the development of internal firm complexity as a mirror image of what is happening in the market and explores the mechanisms of information transfer between the market and the firm and the attendant problems of controllability and observability.