How does supply chain decentralization drive disruptive innovation?: An Analytical Framework Based on Complex Adaptive Systems

Research on source-grid-load-storage coordination and urban power system resilience enhancement based on complex adaptive system theory

Emergence is a concept in complexity science that describes how many-body systems manifest novel higher-level properties, properties that can be described by replacing high-dimensional mechanisms with lower-dimensional effective variables and theories. This is captured by the idea 'More is Different'. Intelligence is a consummate emergent property manifesting increasingly efficient-cheaper and faster-uses of emergent capabilities to solve problems. This is captured by the idea 'Less is More'. In this paper, we first examine claims that Large Language Models exhibit emergent capabilities, reviewing several approaches to quantifying emergence, and secondly ask whether LLMs possess emergent intelligence. This article is part of the theme issue 'World models in natural and artificial intelligence'.

Complex Adaptive Systems and Individual Radiologist Responsibility.

The persistent failure of linear, plan-driven models to effect lasting organisational transformation necessitates a paradigm shift. Contemporary organisations, particularly in high-stakes environments such as healthcare, do not function as predictable machines but as Complex Adaptive Systems (CAS), in which change is inherently non-linear and emergent. This longitudinal, mixed-methods study investigates the central premise that micro-changes in leadership behaviour, such as subtle, sustained adjustments in daily practice, can act as a critical catalyst, precipitating significant and often discontinuous shifts in organisational culture and performance. Designed as a 24-month longitudinal mixed-methods study within a Malaysian healthcare organisation, this research will synthesise CAS theory, transformational leadership, and organisational culture theory to track the co-evolution of leadership and culture. A key methodological innovation will be the application of Cusp Catastrophe Modelling to formally test for threshold-based, non-linear transitions. Quantitative and qualitative data will be collected in parallel across four waves (Baseline, Month 8, Month 16, and Month 24) to map broad trends and probe lived experiences and mechanisms of change. The study is designed to address contemporary calls for rigour in microfoundations and in embedding research. The findings aim to advance theory by empirically modelling cultural emergence as a dynamic system and provide practitioners with a nuanced, evidence-based framework for fostering genuine adaptability in complex environments.

The emergent self: exploring the self from complexity science, panarchy and active inference

Violence is preventable, and the United Nations' Sustainable Development Goals set out violence prevention as a global priority-calling for countries to halve their violent death rates by 2030. Despite action since then, there has been limited progress in reducing violence globally. In this essay, we argue that current violence prevention efforts are being heavily shaped by reductionism-the now-dominant research paradigm across the sciences. We make the case that this reductionist philosophy has prematurely misguided violence research away from studying populations as a whole. We further argue that the mainstream statistical methods in violence research are reinforcing this reductionist bias by oversimplifying cause-effect relationships. After revisiting foundational principles in sociology and public health, and drawing on advances in social epidemiology and complexity science, we suggest that violence-at any level-is better understood as an emergent property of a complex system. We call on the field of violence research to return to a holistic lens to maximize gains in explanatory theory and better position the evidence to directly inform effective intervention strategies for reducing violence at scale. (Am J Public Health. 2026;116(5):722-731. https://doi.org/10.2105/AJPH.2025.308366).

The rapid expansion of artificial intelligence (AI) as a driver of technological innovation has intensified challenges related to governance, sustainability, and controllability within socio-technical systems. The relevance of this study lies in the growing mismatch between the increasing complexity of AI systems and the traditional regulatory and management frameworks applied to them. The purpose of the article is to substantiate a complexity-based interpretation of AI as a complex adaptive system and to identify management principles that support sustainable and responsible development. The study is based on qualitative literature analysis and philosophical synthesis of interdisciplinary research on artificial intelligence, complexity theory, and governance of socio-technical systems. The methodological framework relies on the concepts of complex adaptive systems, diachronic emergence, and Ashby’s law of requisite variety, which are applied to analyze nonlinearity, self-organization, and adaptability in modern AI technologies. The results show that rigid, rule-based models of regulation and control are insufficient for governing AI systems characterized by emergent behavior and dynamic evolution. Effective governance requires management mechanisms comparable in complexity to the systems being governed while preserving meaningful human oversight and institutional accountability. It frames adaptive governance as essential for aligning technological autonomy with sustainability and long-term societal safety objectives globally

Corrigendum to 'Complexity Science in Domestic Abuse Literature: A Systematic Scoping Review'.

Tourism destinations increasingly face complex, interconnected crises that challenge adaptive capacity and long-term sustainability. Although resilience and agility have received growing attention in tourism research, their interaction within destination-scale Complex Adaptive Systems (CAS) remains under-theorized. Drawing on CAS theory, this study develops a scenario-informed conceptual approach that reconceptualizes crisis agility as a system-level initiating mechanism within urban tourism destinations. Using five illustrative crisis scenarios applied to a hypothetical destination (CityTourSim), the study examines how disturbances propagate across interconnected subsystems and how agility-related capacities activate recursive dynamics of sensing, coordination, reconfiguration, and learning. Based on cross-scenario pattern abstraction, the paper proposes an integrated framework linking crisis response to adaptive learning dynamics. The Agile Destination Crisis Response Framework (ADCRF) connects crisis characteristics to subsystem vulnerabilities and agility triggers, while the Tourism System Agility Loop (TSAL) conceptualizes feedback dynamics through which agile responses shape resilience development over time. The study argues that agility functions not merely as reactive flexibility but also as a governance-mediated initiating mechanism that influences resilience trajectories and sustainability outcomes. By theorizing agility, resilience, and sustainability as recursively interacting processes, the paper advances destination-level CAS scholarship and provides a process-oriented lens for adaptive tourism governance under systemic uncertainty.

Understanding the sustainable management of the complex adaptive tourism systems requires an integrated research approach that combines environmental processes with stakeholder behaviors. Agent-based modelling (ABM) has emerged as a pivotal tool for decoding the resilience, adaptability, and sustainability of tourism systems. However, the current application landscape, methodological limitations, and future research directions of ABM remain insufficiently synthesized, thereby constraining its full potential in advancing sustainable tourism management. This study examines 137 publications on the application of ABM in tourism research between 1989 and 2025, aiming to clarify the application characteristics and evolutionary trajectories. The results show the following: (1) ABM applications in tourism have become increasingly comprehensive and refined, evolving from simplistic simulations based on simplex agents and static spatial representations toward integrated models incorporating heterogeneous agents, fine-grained spatial environments, and multiple contextual factors. (2) Behavioral modeling has progressed from basic human–space interactions to complex, co-evolutionary dynamics among human, social, and ecological systems. (3) ABM applications exhibit context specificity: climate-sensitive scenarios emphasize resource dynamics and adaptation strategies; disaster-prone contexts focus on multi-agent responses and emergency management; conservation-oriented systems support sustainable policy development; and management-centric scenarios prioritize technological innovation and macro-level regulation. Future research should prioritize refining agent interactions through dynamic social network integration, incorporating cross-scale and long-distance system linkages, and strengthening the connection between theoretical modeling and real-world applications. This study would provide a comprehensive knowledge base for advancing the innovative application of ABM in sustainable tourism research and contribute to strengthening resilience, adaptive governance, and long-term sustainability within complex tourism systems.

Research on health system capacity to manage non-communicable diseases (NCDs) has largely focused on 'system hardware' such as infrastructure, workforce, and commodities. However, this overlooks the critical role of 'system software' elements, such as relationships, norms, and power, and the complex adaptive nature of health systems. This study aimed to explore how health system hardware and software elements interact to shape the capacity of the health system to deliver hypertension care in Kilifi County in the coastal region of Kenya. We conducted a cross-sectional qualitative study and collected data using document reviews (n = 13) and in-depth interviews with purposively selected front-line health workers (FLHWs) at five health facilities and health managers at county and national levels (n = 37). We applied a framework approach to data analysis, utilizing complex adaptive systems (CAS) theory as our analytic framework. Complex interactions of system hardware and software elements constrained the provision of hypertension care. Frequent medicines stockouts (hardware) stemmed from budgetary gaps, procurement delays, regulatory restrictions, and weak quantification practices (software). To mitigate medicines shortages, facilities employed adaptive responses such as inter-facility borrowing and sourcing from alternative suppliers (software). Access and continuity of care were enabled by organizational norms like dedicated hypertension clinic days (software) but undermined by inadequate consultation rooms, staff shortages (hardware) and limited training and support supervision (software). FLHWs' ideas to improve medication adherence were undermined by staff shortages (hardware) and inadequate support from facility managers (software), weakening service delivery. The application of CAS theory unpacked the hitherto underexplored aspects of health system capacity. System 'software' plays a central role in shaping health system capacity for hypertension care. Therefore, strengthening health system capacity for NCDs requires coordinated investment in both system hardware and software elements. Importantly, system strengthening interventions should consider the CAS nature of health systems to foster conditions for productive emergence.

This paper describes how two complementary theories from complexity science can guide the successful design and implementation of integrated systems of health and social care for older adults who need multiple forms of care. Specifically, it describes two related theories: "complex adaptive systems" (CAS) theory and "relational network theory" (RNT), which provide overlapping frameworks for understanding the structure and dynamic function of care systems and their components. The paper begins by showing how these theories can guide the integration of the structures, people, and processes that provide care to older adults with multiple care needs. Then, to illustrate their application, it describes the early years of the All-Inclusive Care for Older Adults ("ALICE") program, which has co-created and co-managed an evolving health and social care system for an aging population in New South Wales, Australia. As other populations of older adults around the world expand, such effective integration of multi-faceted care will be necessary to optimize their well-being and quality of life. Future applications of CAS and RNT to the design and implementation of integrated health and social care promises to improve the quality and the effectiveness of the care of other older populations that need multiple forms of care.

Simulation debriefing requires navigating dynamic interpersonal interactions, shifting roles, and emotionally charged learning environments. This paper frames debriefing as a complex adaptive system and examines how facilitators can apply emotional intelligence competencies to respond adaptively to uncertainty, competing agendas, and emergent challenges. By integrating systems thinking with the 4 domains of emotional intelligence, the paper offers applied strategies to support facilitator responsiveness, relational sensitivity, and adaptive learning during debriefing. This integrated perspective extends existing debriefing approaches by emphasizing real-time emotionally intelligent and relational decision-making as central to simulation-based education.

Complexity science investigates how complex systems behave and how we interact with them. Its implementation in clinical transfusion research is limited, even though human cells, organ systems, bodies, hospitals and blood supply systems are all examples of complex systems. Complexity science can help us to better understand the systems we study using novel and existing research methods. It also highlights that there is always unpredictability in complex systems, challenging us to both accept and cope with this uncertainty. This review provides a brief introduction of complex systems, explores why many transfusion-related research questions should be viewed through the lens of complexity and discusses how we can apply this perspective to transfusion research.

ABSTRACT Contemporary science and technology diplomacy often operates through leader‐centric, event‐driven, and weakly institutionalized arrangements, which are ill‐suited to domains marked by high interdependence, nonlinearity, and rapidly evolving knowledge. This article proposes Complex Adaptive Science and Technology Diplomacy (CASTD) not as a descriptive label for the field as a whole, but as a conditional analytical and institutional design framework for contexts in which conventional diplomatic instruments face structural limits. Rather than treating diplomacy as an episodic extension of foreign policy, the article suggests reconceiving it, under specific conditions of systemic risk and distributed authority, as a form of strategic infrastructure for governing uncertainty. Drawing on complexity science, polycentric governance, and critical perspectives on science diplomacy, the framework addresses persistent limitations in the literature, including conceptual ambiguity, technocratic depoliticization, and limited evaluability. CASTD identifies three interdependent capacities, adaptive governance, network orchestration, and integrative synthesis, and outlines how these can be operationalized through coordination architectures and structured learning processes. Illustrative cases indicate that durable cooperation depends less on episodic leadership than on reproducible and adaptable forms of coordination.

ABSTRACT Cross-national reviews of disability employment systems reveal fragmented, transactional approaches that produce placements rarely sustained. The Equilibrium Systems Model of Employment (ESME) reframes disability employment as a dynamic ecosystem of six interconnected domains: individuals, families, practitioners, employers, organisations, and governance, operating across four system levels. Drawing on complexity science, chaos theory, and ecological systems thinking, ESME argues that enduring outcomes arise when these domains work in balance rather than in isolation. Equilibrium enables small shifts, such as raised family expectations or employer flexibility, to generate cycles of inclusion, while imbalance reinforces fragmentation and churn. This paper positions ESME as both diagnostic and generative, aligning professional practice (PIE-CF), technical competence (ACRE), and organisational learning (CEQAF) with enabling policies. These mechanisms embed psychological safety, technical excellence, and continuous improvement, offering a coherent pathway for researchers, practitioners, and policymakers to create adaptive, person-centred employment ecosystems.

Purpose This research aims to investigate the effect of buyer−supplier self-organization on triadic relational performance. In addition, this study examines the moderating role of organizational ambidexterity, run by the logistics service provider (LSP), in the relationship between buyer−supplier self-organization and relational performance. Design/methodology/approach The basis of this research is founded on complex adaptive system theory (CAS), enhanced by the tenets of the substitutive approach and complementarity theory (CT). Building on this grounding, this study developed a questionnaire and conducted research in 350 supply chains. Findings The results demonstrate that buyer−supplier self-organization has a positive effect on triadic relational performance. Interestingly, the conclusions obtained highlight the moderating role of organizational ambidexterity, administered by the LSP. More specifically, substitutive LSP ambidexterity exhibits a negative moderating effect between buyer−supplier self-organization and relational performance. In contrast, complementary LSP ambidexterity indicates a positive moderating effect between buyer−supplier self-organization and triadic relational performance. Research limitations/implications To date, organizational ambidexterity has primarily been studied at the individual firm level, without considering its potential influence on other organizations within a network. Accordingly, a more targeted set of variables may be needed to measure ambidexterity as enacted by one firm and its impact on other supply chain partners. Furthermore, beyond the substitutive and complementary approaches used in this study, alternative methods, such as additive or polynomial regression techniques, can be used to capture and quantify ambidexterity. These approaches may effectively extend and complement the findings of this research. Practical implications This study shows that proximity to the market and end customers is a critical factor when considering the role of the LSP within triads. Specifically, organizational ambidexterity, exercised by the logistics service provider, moderates the relationship between buyer−supplier self-organization and triadic relational performance. Consequently, managers at both the buyer and supplier firms should strive to maintain a balanced organizational structure, ensuring it is neither overly formal nor excessively loose. This study further indicates that the logistics service provider can play a pivotal role in achieving this balance. Social implications The findings suggest that promoting buyer−supplier self-organization within transitive triads can strengthen trust, collaboration and shared responsibility. Moreover, the moderating effect of organizational ambidexterity exercised by LSPs indicates that organizations capable of balancing efficiency-focused and innovation-focused practices can cultivate more inclusive and adaptive work environments. Such environments may enhance employee engagement, provide greater learning opportunities and support skill development across organizational boundaries, thereby improving relational performance. Originality/value Given the increasing interest in the role of LSP in supply chains, this study investigates how buyer−supplier self-organization is moderated by organizational ambidexterity to produce superior relational performance.

The article substantiates a system of fundamental principles that form the methodological basis of a conceptual model of innovative development of customs processes in the context of digital transformation of the public sector. The relevance of the study is determined by the need for a systematic approach to the modernization of customs administration, which will ensure a balance between the simplification of trade procedures and the improvement of control efficiency in the dynamic environment of international trade. The purpose of the article is to form a comprehensive system of interrelated principles that define the conceptual guidelines for the innovative development of customs processes. The theoretical basis of the study is general systems theory, concepts of socio-technical systems, the theory of complex adaptive systems, concepts of business ecosystems, and human-centered design. The article details six key principles: systematicity (considering customs processes as a complex socio-technical system with multiple interrelationships), multilevelness (structuring at the technological, process, management, and institutional levels), ecosystem orientation (consideration of the interaction of all stakeholders), adaptability (flexible response to changes in the external environment), interoperability (ensuring effective interaction between systems and participants), and human-centeredness (focusing on the needs of users and staff). It has been proven that these principles form an interconnected system, where each supports and reinforces the others, ensuring the comprehensiveness, consistency, and sustainability of innovative transformations. A conceptual scheme of interaction between the principles has been proposed, and practical tools for their application at all stages of the innovation cycle have been identified. The practical significance of the study lies in the formation of a methodological basis for the development of strategies for the digital transformation of customs processes, taking into account international standards and best practices.

Diabetes prevalence in Kenya is rising, yet care remains constrained by fragmented service delivery, shortages of trained health workers, limited access to diagnostics and medicines, and weak integration of diabetes education and nutrition counselling. These challenges reflect underlying system dynamics that are insufficiently captured by linear assessments. This narrative review synthesised evidence published between 2015 and 2025 and examined diabetes care in Kenya through a systems-thinking approach combining the WHO Health System Building Blocks (HSBB) and the Intervention-Level Framework (ILF). The combined framework enabled classification of system weaknesses according to subsystem (e.g. governance, workforce, financing) and depth of leverage (from structural elements to paradigms). Twenty-eight studies met the inclusion criteria. Across all HSBB domains, recurrent problems, such as inconsistent policy implementation, shortages of trained staff, supply-chain disruptions, insufficient financing, and weak information systems, interacted through reinforcing feedback loops that reduced continuity, quality, and equity of care. Nutrition-related findings appeared less frequently but highlighted significant gaps in diabetes self-management education, food access, and cultural norms. Application of the HSBB-ILF framework revealed that many barriers extend beyond structural deficits (ILF Level 1) into deeper system features including weak feedback mechanisms (Level 2), fragmented organisational arrangements (Level 3), unstable or reactive system goals (Level 4), and entrenched paradigms that deprioritize NCDs (Level 5). Diabetes care in Kenya functions as a complex adaptive system in which structural, organisational, financial, and sociocultural factors interact to shape outcomes. Sustainable improvement will require coordinated, multi-level strategies that strengthen governance, workforce capacity, supply chains, and information systems while also addressing community realities, food insecurity, and cultural beliefs. The HSBB-ILF combination proved valuable for identifying leverage points that could inform more integrated and equitable approaches to diabetes nutrition care.