Abstract

Systems theory has been challenged in the recent literature due to its perceived disconnection from today’s research and practice demands. Moving away from the reductionist frameworks and the complicated domain predominated by known unknowns and order, a call is being made to the social sciences to begin adopting complexity theory and newer connectionist methods that better address complexity and open social systems. Scholars and scholar-practitioners will continue to find the need to apply complexity theory as wicked problems become more prevalent in the social sciences. This paper differentiates between general systems theory (GST) and complexity theory, as well as identifies advantages for the social sciences in incorporating complexity theory as a formal theory. Complexity theory is expanded upon and identified as providing a new perspective and a new method of theorizing that can be practiced by disciplines within the social sciences. These additions could better position the social sciences to address the complexity associated with advancing technology, globalization, intricate markets, cultural change, and the myriad of challenges and opportunities to come.

Highlights

  • The implementation of new technological innovations in the workplace and globalization are just two indicators of future, higher skilled workforce requirements [1] and herald the intensification of complexity in the workplace due to an increasing rate of unpredictable change [2], information overload, globalization, and geopolitical unrest

  • Complexity theory, synonymous with complexity science in the literature, is best described in the following quote: Complexity science targets a sub-set of all systems; a sub-set which is abundant and is the basis of all novelty; a sub-set which is evidenced in biology, chemistry, physics, social, technical and economic domains; a sub-set which coevolves with its environment; a sub-set from which structure emerges

  • Having the potential of being able to provide insight into organizational change dynamics, which have been insufficiently modeled in the social sciences [32], complexity theory is more frequently found in the literature today and is showing new promise for disciplines studying complex systems

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Summary

Introduction

The implementation of new technological innovations in the workplace and globalization are just two indicators of future, higher skilled workforce requirements [1] and herald the intensification of complexity in the workplace due to an increasing rate of unpredictable change [2], information overload, globalization, and geopolitical unrest. By understanding the workings of the smaller parts, the whole can be understood more comprehensively [4] This reductionistic framework has served science well in the past, such as during the Industrial Revolution [4], it is inadequate to serve science well today due to the complexities of the modern world (e.g., increasing wicked problems, global warming, information overload, globalization, and geopolitical unrest). The article provides some current examples of the use of complexity theory and concludes with new directions for disciplines in the social sciences, recommending the inclusion of complexity theory in future research efforts. The current article expands upon the work presented by Haslberger [8] in describing complexity theory as a new potential method for explanation and theorizing. We propose the same in the current article—that complexity theory be adopted as a new method of explanation and theorizing for the social sciences

System versus Systems
General Systems Theory
Distinguishing Boundaries of GST
Open versus Closed Systems
Complexity Theory
Evaluation practice
Differentiating GST from Complexity Theory
The Principle of System Holism
Open and Closed Systems
Linear and Non-Linear Systems
Irreducibility
Complexity Theory for the Social Sciences
Addressing Complex Issues and Wicked Problems
Wicked Problems
Decision Making and the Cynefin Framework
New Directions for Social Systems Research
Incorporating More Non-Reductionistic Methods
Network Analysis to Look for Relevant Nodes in a Network
New Complexity-Related Theories
Conclusions
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