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The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

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.

This paper aims to use systems mapping as a tool to develop an organisation-wide approach to public mental health to inform strategic direction within a national public health agency.

Two workshops were facilitated with internal staff from a wide range of public health policy teams working in small groups to produce paper-based maps. These were collated and refined by the project team and digitised.

The approach engaged a range of teams in forming a shared understanding and producing a complex system map of the influences on population mental health and well-being, where current policy initiatives were addressing them and what the gaps and priorities were. Participants valued the approach which led to further study and organisational commitment to the whole system working as part of national public mental health strategy.

The approach was limited to internal stakeholders and wider engagement with other sectors and community members would help further the application of complex system approaches to public mental health.

It was a valuable process for developing a whole-organisation approach and stimulating thinking and practice in complex system approaches. The paper provides a practical example of how to apply systems mapping and its benefits for organising public mental health practice.

The purpose of this paper is to contribute to the understanding of systems thinking and its value for strategic foresight and scenario planning to address disruptive forces from the outside, with the outbreak of COVID19 as a case study.

This conceptual paper concisely discusses the notion of systems thinking and the concept of complex adaptive systems and puts this in the context of contemporary society in general and travel and tourism in particular. Strategic foresight and scenario planning are introduced as an approach to anticipate disruptions in the complex adaptive travel and tourism system.

As COVID-19 has demonstrated, travel and tourism is sensitive for disruptions from the outside. To ensure long-term resilience and sustainability, a systems approach embedded in strategic foresight and scenario planning is emphasised.

Strategic foresight and scenario planning is a competence that can be learned.

Given the present status of COVID-19 and other disruptors on travel and tourism, a resilient approach to the future is necessary; thus, the value of this viewpoint paper is the proposition of an adaptive capacity system. This paper offers advice to understand and manage complexity and adaptive systems.

Decisions taken during the early design of adaptive façades involving kinetic, active and responsive envelope for complex commercial buildings have a substantial effect on inclusive building functioning and the comfort level of inhabitants. This study aims to present the application of an analytic network process (ANP) model indicating the order of priority for high performance criteria that must be taken into account in the assessment of the performance of adaptive façade systems for complex commercial buildings.

The nominal group technique (NGT) stimulating and refining group judgments are used to find and categorize relevant high performance attributes of the adaptive façade systems and their relative pair-wise significance scores. An ANP model is applied to prioritize these high performance objectives and criteria for the adaptive façade systems.

Embodied energy and CO₂ emission, sustainability, energy saving, daylight and operation maintenance were as the most likely and crucial high performance criteria. The criteria and the weights presented in this study could be used as guidelines for evaluating the performance of adaptive façade systems for commercial buildings in planning and design phases.

This research primarily provides the required actions and evaluations for design managers in accomplishing a high performance adaptive façade system, with the support of an ANP method. Before beginning the adaptive façade system of a building design process, the design manager must determine the significance of each of these attributes as high performance primacies will affect the results all through the entire design process.

In this research, a relatively innovative, systematic and practical approach is proposed to sustain the decision-making procedure for evaluation of the high performance criteria of adaptive façade systems in complex commercial buildings.

Based on complex network theory, a method for critical elements identification of China Railway High-speed 2 (CRH2) train system is introduced in this paper.

First, two methods, reliability theory and complex theory, are introduced, and the advantages and disadvantages for their application in identifying critical elements of high-speed train system are summarized. Second, a multi-layer multi-granularity network model including virtual and actual nodes is proposed, and the corresponding fusion rules for the same nodes in different layers are given.

Finally, taking CRH2 train system as an example, the critical elements are identified by using complex network theory, which provides a reference for train operation and maintenance.

A method of identifying key elements of CRH2 train system based on integrated importance indices is introduced, which is a meaningful extension of the application of complex network theory to identify key components.

This paper considers supply chain management organizations with the aid of 'chaotic systems theory' developed originally in physics and mathematics. Since innovations in supply chain management are vital for organizational survival 'complex systems theory' may assist in fine-tuning managerial philosophies that provide stability in supply chain management because it is on the boundary of chaos that the greatest innovational creativity occurs. Neither 'management by rigid objectives' (MBO) nor 'management by instruction' (MBI) will be suitable for the information society of the twenty-first century because chaotic social systems will no longer be effectively managed. However, the capacity for self-organization will be derived essentially from how supply chain management members accept a shared set of values or principles for action-'management by values' (MBV). Complex systems theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organizes is attributable to the appearance of the 'strange attractor' and provides the ideal basis for creativity and innovation in the twenty-first century. In the self-organized state of chaos, social members are not confined to narrow roles and gradually develop their capacity for differentiation and relationships, growing progressively towards their maximum potential contribution to the efficiency of the organization. In this meaning, values act as organizers of 'attractors' of disorder, which, in the theory of chaos, are systems represented by usually regular geometric configurations that predict the long-term behavior of complex systems. In supply chain management organizations (as in all kinds of social systems) the initial principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of the system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is heading based on its rules of motion. In supply chain management organizations that cultivate or shares values of autonomy, responsibility, independence, innovation, creativity, and proactivity, the risk of short-term chaos is mitigated by external complexities that organizations are currently confronting. The strategy is to alter the supply chain management's surroundings so that they can benefit from management by values (MBV).

How a micro-founded discipline such as economics could deal with the increasing global economic reality? This question has been asked frequently since the last economic crisis that appeared in 2008. In this challenging context, some commentators have turned their attention to a new area of knowledge coming from physics: econophysics which mainly focuses on a macro-analysis of economic systems. By showing that concepts used by econophysicists are consistent with an existing economic knowledge (developed by J.S. Mill), the purpose of this paper is to claim that an interdisciplinary perspective is possible between these two communities.

The authors propose a historical and conceptual analysis of the key concept of emergence to emphasize the potential bridge between econophysics and economics.

Six methodological arguments will be developed in order to show the existence of conceptual bridges as a necessary condition for the elaboration of a common language between economists and econophysics which would not be superfluous, in this challenging context, to clarify the growing complexity of economic phenomena.

Although the economics and econophysics study same the complex economic phenomena, very few collaborations exist between them. This paper paves a conceptual/methodological path for more collaboration between the two fields.

Crowdfunding (CF) is a digital-financial innovation that, bypassing credit crisis, bank system rigidities and constraints of the capital market, is allowing new ventures and established companies to get the needed funds to support innovations. After one decade of research, mainly focused on relations between variables and outcomes of the CF campaign, the literature shows methodological lacks about the study of its overall behavior. These reflect into a weak theoretical understanding and inconsistent managerial guidance, leading to a 27% success ratio of campaigns. To bridge this gap, this paper embraces a “complex system” perspective of the CF campaign, able to explore the system's behavior of a campaign over time, in light of its causal loop structure.

By adopting and following the document model building (DMB) methodology, a set of 26 variables and mutual causal relations modeled the system “Crowdfunding campaign” and a data set based on them and crafted to model the “Crowdfunding campaign” with a causal loop diagram. Finally, system archetypes have been used to link the causal loop structure with qualitative trends of CF's behavior (i.e. the raised capital over time).

The research brought to 26 variables making the system a “Crowdfunding campaign.” The variables influence each other, thus showing a set of feedback loops, whose structure determines the behavior of the CF campaign. The causal loop structure is traced back to three system archetypes, presiding the behavior in three stages of the campaign.

The value of this paper is both methodological and theoretical. First, the DMB methodology has been expanded and reinforced concerning previous applications; second, we carried out a causation analysis, unlike the common correlation analysis; further, we created a theoretical model of a “Crowdfunding Campaign” unlike the common empirical models built on CF platform's data.