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The purpose of this paper is to: give a brief history of the development of complexity science for people unfamiliar with the details of complexity science; describe the different types of complexity; discuss examples of the types of complexity, and introduce some ideas about how complexity could be introduced into education.

This paper summarizes other work in the field of complexity science, and organizes the results in a new way with the intent of making a difficult subject easier for the reader to understand.

Two different types of complexity are described – organized and unorganized. The focus of the paper is on organized complexity of which three categories are described – complicated, chaotic and critical. Examples, descriptions and characteristics of each category are given.

Suggestions are given as to how this transformational science could be integrated into education.

The paper summarizes other work in the field of complexity science, and organizes the results in a new way with the intent of making a difficult subject easier for the reader to understand.

We discuss the impact of complexity science on the design and management of health care organizations over the past decade. We provide an overview of complexity science issues and their impact on thinking about health care systems, particularly with the rising importance of information systems. We also present a complexity science perspective on current issues in today’s health care organizations and suggest ways that this perspective might help in approaching these issues.

We review selected research, focusing on work in which we participated, to identify specific examples of applications of complexity science. We then take a look at information systems in health care organizations from a complexity viewpoint.

Complexity science is a fundamentally different way of understanding nature and has influenced the thinking of scholars and practitioners as they have attempted to understand health care organizations. Many scholars study health care organizations as complex adaptive systems and through this perspective develop new management strategies. Most important, perhaps, is the understanding that attention to relationships and interdependencies is critical for developing effective management strategies.

Increased understanding of complexity science can enhance the ability of researchers and practitioners to develop new ways of understanding and improving health care organizations.

This analysis opens new vistas for scholars and practitioners attempting to understand health care organizations as complex adaptive systems. The analysis holds value for those already familiar with this approach as well as those who may not be as familiar.

Certain elements of Hayek’s work are prominent precursors to the modern field of complex adaptive systems, including his ideas on spontaneous order, his focus on market processes, his contrast between designing and gardening, and his own framing of complex systems. Conceptually, he was well ahead of his time, prescient in his formulation of novel ways to think about economies and societies. Technically, the fact that he did not mathematically formalize most of the notions he developed makes his insights hard to incorporate unambiguously into models. However, because so much of his work is divorced from the simplistic models proffered by early mathematical economics, it stands as fertile ground for complex systems researchers today. I suggest that Austrian economists can create a progressive research program by building models of these Hayekian ideas, and thereby gain traction within the economics profession. Instead of mathematical models the suite of techniques and tools known as agent-based computing seems particularly well-suited to addressing traditional Austrian topics like money, business cycles, coordination, market processes, and so on, while staying faithful to the methodological individualism and bottom-up perspective that underpin the entire school of thought.

The purpose of this study is to propose a methodological approach for modeling catastrophic consequences caused by black swan events, based on complexity science, and framed on Feyerabend’s anarchistic theory of knowledge. An empirical application is presented to illustrate the proposed approach.

Thom’s nonlinear differential equations of morphogenesis are used to develop a theoretical model of the impact of catastrophes on international business (IB). The model is then estimated using real-world data on the performance of multinational airlines during the SARS-CoV-2 (COVID-19) pandemic.

The catastrophe model exhibits a remarkable capability to simultaneously capture complex linear and nonlinear relationships. Through empirical estimations and simulations, this approach enables the analysis of IB phenomena under normal conditions, as well as during black swan events.

To the best of the author’s knowledge, this study is the first attempt to estimate the impact of black swan events in IB using a catastrophe model grounded in complexity theory. The proposed model successfully integrates the abrupt and profound effects of catastrophes on multinational corporations, offering a critical perspective on the theoretical and practical use of complexity science in IB.

The purpose of this paper is to describe and apply teleological approaches from complexity sciences in services.

The performance of service encounters and the outcome of service quality are dependent upon complex and dynamic interactions between service providers and service receivers. A set of teleological approaches from complexity sciences is incorporated and applied in the context of service settings.

A teleological application from complexity sciences in relation to the interactive nature of the performance of service encounters and the outcome of service quality offers opportunities to apply innovative research designs and alternative methodological approaches to future research problems in services.

Future research could focus on where and how the insights from other research disciplines can be used that have encapsulated teleological approaches from complexity sciences more sophisticated, and how this knowledge could be incorporated and applied in services.

The inclusion and consideration of teleological approaches from complexity sciences in the performance of service encounters and the outcome of service quality generates a series of managerial and research implications regarding the dynamics and complexity of the interactive nature in services.

The research opportunities into service quality and service encounters by applying teleological approaches from complexity sciences are extensive. They might also stimulate innovative analytical techniques that may generate important empirical findings, in extension, with relevant and valuable implications for practice in services. A maintained focus on multi‐disciplinary aspects of research may enhance contemporary research and practice of services.

Preparing for a potential bioterroism is a difficult task for health care leaders because of the fundamental unpredictability of bioterroist acts. Complexity science thinking is presented as an approach that can help in this task. Basic concepts from complexity science, especially the role of relationships, are presented. Specific recommendations for action including sensemaking, learning, and improvisation are made. A case study is used to illustrate the power of complexity science thinking in assisting health care leaders addressing potential bioterroism. Questions for further research are presented.

Complexity received increasing attention from researchers in integration and evaluation studies. Complex adaptive systems are the most prominent formulation of complexity used in programme evaluations. However, there remain significant theoretical and conceptual barriers to using complexity as an explanatory model in social sciences, and thus in applying it successfully in integration and evaluation studies. The paper aims to discuss these issues.

Discussion paper outlining the potential uses and risks of complexity theory for studying integration programmes in health and social care and programme evaluations in general. The paper proceeds by synthesising the work of various critics and proponents of complexity theory in the social sciences and evaluation theory.

Complexity offers opportunities and risks to social scientists working in programme evaluations and integration studies. The opportunities are defined by additional modelling and verification/falsification of possible cause and effect links in programme settings. The risks, on the other hand, are twofold. Social scientists may use complexity as a shorthand for as yet insufficient understanding of the contexts under examination, or they mistake it for an explanatory device without testing its potential to explain. The second risk emerges as a result of the nature of complexity and its role in natural sciences. Assigning complexity an explanatory role may prevent further investigation of a given setting that may reveal that complexity is insufficient to understand what is going on.

Researchers should make clear how they have operationalised and measured the various features of the complexity model to allow robust verification of the evidence. Scholars should also assume that complexity as defined by the natural sciences is philosophically and epistemologically problematic when transferred into the realm of social sciences that largely operate with concepts informed by the paradigm of understanding social behaviour.

The purpose of this paper is to contribute to refine the conceptual framework of complexity. For such a purpose, a number of epistemologically oriented remarks are provided, arguing about the relevance of second-order considerations for complexity and the importance of pluralism in scientific research.

At first, the paper focuses on one of the topical areas of complexity research, i.e. network theory, but uses this for drawing the attention to more general issues. The underlying assumption is that scientific and philosophical research might complement each other, and that this is especially crucial for the advancement of complexity.

The paper suggests three ways for refining the scheme of complexity: analyzing it at the right level, i.e. not focusing on single principles or theories (e.g. network theory), but rather on the overall frame; including both ontological and epistemological considerations; and recognizing how the epistemological implications of complexity foster the adoption of a pluralist stance in scientific research (and beyond).

The way in which science (complexity) is portrayed, i.e. as “perspectival” and inclined to pluralism, could impact on how it is thought, designed and socially perceived.

Complexity is one of most promising fields of contemporary science, but still lacks of a coherent frame of analysis. This requires an investigation from different point of views, as an object of interdisciplinary cooperation. The main paper’s value consists of providing second-order considerations which puts scientific findings in perspective and can contribute to a better understanding of their meaning from a philosophical standpoint too.

Cybernetics started when Wiener stated that not only observations but also the way the observer feeds them back into reality are part of science. Dynamic system analysis supported the art and science of steering with feedback by computer modelling techniques. Cybernetics introduced the question of how self‐reference functioned in the feedback between observer and models. This led to the idea of cybernetics of the second order. Analyses the logic of feedback and how it relates to the question of how logical, mathematical and linguistic instruments can articulate scientific observations and connected theories. Uses the concept of complexity to relate cybernetics to the interdisciplinary practice of modern science. Presents the notion of “strangification” as a concept by which the transfer of knowledge from one discipline to another can be better understood and facilitated.

The implicit and indirect influence of classical science on strategic management has been of utmost importance in the development of the discipline. Classical science has underpinned the main and even contrasting strategic management cultures. Classical science has undoubtedly allowed strategic management to thrive. Nevertheless, important limitations, roadblocks and challenges have also been produced. This paper aims to explore the influence of classical science on the main positivist and interpretive strategic management cultures.

A conceptual review is done on the influence of classical science on positivist and interpretivist traditions in strategic management.

The benefits and shortcomings of classical science in strategic management are explored and presented. Furthermore, the convoluted implicit relationship between strategic management and science is shown to be changing but persisting, as to face some of the challenges of the classical science culture of strategic management, a complexity culture, also inspired partially on science, seems to be developing in strategic management. Complexity seems to be emerging as an alternative, which might allow strategic management to solve some of its current dilemmas and, thus, change its implicit relationship with science.

The paper presents a novel way to conceptualize historical cultures of strategic management via their connection with academic cultures that have historically emerged from science. Through the analysis here done, a possible candidate for a Kuhninan normal strategic management and its potential revolution will be suggested, based on the recognition of the inheritance of classical science and currently complexity theory in strategic management.