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This paper aims to draw on data from a study of professionals’ experiences of work and learning framed by a complex adaptive systems approach to examine the nexus of work and learning in complex adaptive organisations.

The study used an adapted phenomenographic approach and the complex adaptive systems conceptual framework (CAOCF) to analyse data from semi-structured interviews with fourteen professionals from a variety of organisations and industry sectors within Sydney, Australia.

The findings highlight that work in complex adaptive organisations is best described as fluid work. Further, the findings suggest that fluid work influences professionals towards flexible learning approaches that take place in the flow of work.

This paper empirically demonstrates the nexus of work and learning as experienced by professionals in their day-to-day work, as well as the ways in which fluid work influences flexible and adaptable learning through participation in work.

This article explores how complexity theory can help marketers to understand a market and to operate within it. Essentially, it argues that complexity theory has the potential to provide both global and some local explanations of markets and is complementary to local theories like relationship marketing that may be more familiar to marketing managers. It establishes four types of complex systems that might be used to model social systems. Of these four types, complex adaptive systems seem most appropriate to describe markets. This is illustrated in an investigation of Honda in the global automobile industry. Implications for marketing managers centre on the need to understand feedback loops at many levels of a path‐dependent system that are inherently difficult to predict and control.

The purpose of this paper is to outline an empirical study of how professionals experience work and learning in complex adaptive organisations. The study uses a complex adaptive systems approach, which forms the basis of a specifically developed conceptual framework for explaining professionals’ experiences of work and learning.

Semi-structured interviews were conducted with 14 professionals from a variety of organisations, industry sectors and occupations in Sydney, Australia. The transcripts were subjected to an adapted phenomenographic analysis, and an analysis using the complex adaptive organisations conceptual framework (CAOCF).

The findings indicated that professionals experienced learning mainly through work, where work was experienced as fluid and influenced by varying degrees of emergence, agency, complex social networks and adaptation. Further, the greater the degree of work fluidity, the greater the impetus towards learning through work, empirically indicating that the experience of learning in contemporary organisations is entwined with work.

This study used the concept of complex adaptive organisations as a conceptual framework, coupled with an adapted phenomenographic methodology, to investigate individual professionals’ experiences of work and learning. The adoption of the concept of complex adaptive organisations provided a rigorous way to adopt a complexity approach. In particular, the concept of emergence provides insights into how organisational complexity influences work and, subsequently, learning and adaptation.

This article proposes an adaptive strategy for managing knowledge in complex organizations. Specifically, this article aims to extend understanding in the field of knowledge management (KM) by examining how an adaptive strategy for managing knowledge can help organizations become innovative and build dynamic capabilities.

Literature on complexity theory and KM is reviewed to propose the development of an adaptive strategy that will assist organization in managing knowledge and becoming innovative. The paper is structured around the following constructs: complexity theory, complex adaptive systems, and KM.

A link between an adaptive strategy for managing knowledge, innovation and dynamic capability is established. The central proposition of the article is the organizations that follow adaptive complex processes for managing knowledge are better able to compete in the market today.

This article extends prior research on KM by proposing complexity theory as a framework for establishing adaptive strategies for managing knowledge and fostering innovation.

With the dramatic environmental changes and fierce competition that organizations are faced with today, managing knowledge becomes critical for driving creativity and adapting to changing markets. Organizations lack direction on how best to develop an adaptive strategy for managing knowledge. The revelation of adaptive processes for managing knowledge in complex systems can lead to more effective KM practices and a higher rate of creativity and flexibility.

The study answers recent calls for defining processes for the second generation of KM that shift focus from the codification and transfer of knowledge to the creation of new knowledge. Although previous studies have established a link between complex adaptive systems and KM, this study takes it one step further in defining an integrative strategy for the creation of knowledge based on the processes of complex adaptive systems. The paper provides a foundation for future studies to test the causal relationship between adaptive processes for knowledge creation and innovation.

Complex systems adapt to survive, but little comparative literature exists on various approaches. Adaptive complex systems are generic, this referring to propositions concerning their bounded instability, adaptability and viability. Two classes of adaptive complex system theories exist: hard and soft. Hard complexity theories include Complex Adaptive Systems (CAS) and Viability Theory, and softer theories, which we refer to as Viable Systems Theories (VSTs), that include Management Cybernetics at one extreme and Humanism at the other. This paper has a dual purpose distributed across two parts. In Part 1, the purpose of this paper is to identify the conditions for the complementarity of the two classes of theory. In Part 2, the purpose is to explore (in part using Agency Theory) the two classes of theory and their proposed complexity continuum.

A detailed analysis of the literature permits a distinction between hard and softer approaches towards modelling complex social systems. Hard theories are human-incommensurable, while soft ones are human-commensurable, therefore more closely related to the human condition. The characteristics that differentiate between hard and soft approaches are identified.

Hard theories are more restrictive than the softer theories. The latter can embrace degrees of “softness” and it is explained how hard and soft approaches can be mixed, sometimes creating Harmony.

There are very few explorations of the relationship between hard and soft approaches to complexity theory, and even fewer that draw in the notion of harmony.

Smallholder value chains are dynamic, changing over time in sudden, unpredictable ways as they adapt to shocks. Understanding these dynamics and adaptation is essential for these chains to remain competitive in turbulent markets. Many guides to value chain development, though they focus welcome attention on snapshots of current structure and performance, pay limited attention to the dynamic forces affecting these chains or to adaptation. The paper aims to discuss these issues.

This paper develops an expanded conceptual framework to understand value chain performance based on the theory of complex adaptive systems. The framework combines seven common properties of complex systems: time, uncertainty, sensitivity to initial conditions, endogenous shocks, sudden change, interacting agents and adaptation.

The authors outline how the framework can be used to ask new research questions and analyze case studies in order to improve our understanding of the development of smallholder value chains and their capacity for adaptation.

The framework highlights the need for greater attention to value chain dynamics.

The framework offers a new perspective on the dynamics of smallholder value chains.

Organizations are faced with solving increasingly complex problems. Addressing these issues requires effective leadership that can facilitate a collaborative problem solving approach where multiple perspectives are leveraged. In this conceptual paper, we critique the effectiveness of earlier leadership models in tackling complex organizational issues. We then examine one promising model, adaptive leadership, in detail and propose that this model provides a leadership approach for addressing current organizational realities. The model, proposed and developed over the last two decades, fundamentally supports the assumption of leadership by multiple stakeholders, with the formulation of the leadership dependent on the emergent problem. Adaptive leadership, with its focus on collaborative problem-solving utilizing multiple perspectives, is especially applicable to large organizations faced with solving complex problems involving many stakeholders.

Pandemics are frequent events, and the impact of each pandemic makes a strong and long-term effect on companies and markets. Given the potential impact of the COVID-19 pandemic, it is important to investigate the crisis from a different perspective to know how companies have sustained growth in markets. The purpose of this paper is to understand how profit-oriented customer-centric companies (small, medium and large) have responded and adapted to COVID-19 crisis, using the complexity theory.

Drawing upon the complexity theory, a humble attempt is made to develop theoretical propositions by conceptualizing companies as complex adaptive systems. The paper examines companies from three dimensions (i.e. internal mechanism, environment and coevolution).

Companies self-organize, emerge into new states and become adaptive to the changing environment. Companies create knowledge to understand the dynamic anatomy and design survival and growth strategies during and post COVID-19 era. Complex adaptive systems perspective provides companies with insights to deal with complex issues raised due to COVID-19 pandemic. They can handle the impact of pandemic efficiently with complex adaptive systems by developing and implementing appropriate strategies post-COVID-19.

The study reveals how companies evolve and emerge into as complex adaptive systems to adapt themselves to the highly dynamic environment, which are uncertain, unpredictable, nonlinear and multifaceted, in the context of COVID-19. Implications for theory and practice of viewing companies as complex adaptive systems and coevolving structures in the COVID-19 context are discussed.

The purpose of this paper is to develop a conceptual framework for extending an understanding of resilience in complex adaptive system (CAS) such as supply chains using the adaptive cycle framework. The adaptive cycle framework may help explain change and the long term dynamics and resilience in supply chain networks. Adaptive cycles assume that dynamic systems such as supply chain networks go through stages of growth, development, collapse and reorientation. Adaptive cycles suggest that the resilience of a complex adaptive system such as supply chains are not fixed but expand and contract over time and resilience requires such systems to navigate each of the cycles’ four stages successfully.

This research uses the adaptive cycle framework to explain supply chain resilience (SCRES). It explores the phases of the adaptive cycle, its pathologies and key properties and links these to competences and behaviors that are important for system and SCRES. The study develops a conceptual framework linking adaptive cycles to SCRES. The goal is to extend dynamic theories of SCRES by borrowing from the adaptive cycle framework. We review the literature on the adaptive cycle framework, its properties and link these to SCRES.

The key insight is that the adaptive cycle concept can broaden our understanding of SCRES beyond focal scales, including cross-scale resilience. As a framework, the adaptive cycle can explain the mechanisms that support or prevent resilience in supply chains. Adaptive cycles may also give us new insights into the sort of competences required to avoid stagnation, promote system renewal as resilience expands and contracts over time.

The adaptive cycle may move our discussion of resilience beyond engineering and ecological resilience to include evolutionary resilience. While the first two presently dominates our theorizing on SCRES, evolutionary resilience may be more insightful than both are. Adaptive cycles capture the idea of change, adaptation and transformation and allow us to explore cross-scale resilience.

Knowing how to prepare for and overcoming key pathologies associated with each stage of the adaptive cycle can broaden our repertoire of strategies for managing SCRES across time. Human agency is important for preventing systems from crossing critical thresholds into imminent collapse. More importantly, disruptions may present an opportunity for innovation and renewal for building more resilience supply chains.

This research is one of the few studies that have applied the adaptive cycle concept to SCRES and extends our understanding of the dynamic structure of SCRES

This study aims to investigate the multiple influence paths or underlying mechanisms of entrepreneurial leadership (EL) on adaptive innovation from the perspectives of organizational learning and resource management, drawing on complex adaptive system theory.

With a questionnaire survey of 317 senior and middle managers from different firms in China, structural equation modeling was used to test the hypothesized conceptual model, and bootstrapping method was employed to examine the multiple mediating effects.

Results indicate that EL has a significant and positive effect on adaptive innovation. This relationship is partially mediated through exploitative learning, exploratory learning, resource bricolage and boundary-spanning integration, respectively. The impact of EL on adaptive innovation is also sequentially transmitted through exploitative learning and resource bricolage or exploratory learning and boundary-spanning integration.

Adaptive innovation has become a firm competition strategy to cope with dynamic changes in current uncertain environment where EL can play its effectiveness to engage firms in such innovation activities. However, the question of why and how EL drives adaptive innovation has yet to be discussed. This study highlights the innovation effectiveness of EL and the triggering process of adaptive innovation, and contributes to several countermeasures for firms to implement leadership and innovation practices responding to uncertain environment.