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PurposeBlockchain is a distributed ledger technology that uses cryptography to ensure transmission and access security, which provides solutions to numerous challenges to complex supply networks. The purpose of this paper is to empirically test the impact of blockchain implementation on shareholder value varying from internal and external complexity from the complex adaptive systems (CASs) perspective. It further explores how business diversification, supply chain (SC) concentration and environmental complexity affect the relationship between blockchain implementation and shareholder value.Design/methodology/approachBased on 138 blockchain implementation announcements of listed companies on the Chinese A-share stock market, the authors use event study methodology to evaluate the impact of blockchain implementation on shareholder value.FindingsThe results show that blockchain implementation has a positive impact on shareholder value, and this impact will be moderated by business diversification, SC concentration and environmental complexity. In addition, environmental complexity exerts a moderating effect on SC concentration. In the post hoc analysis, the authors further explore the impact of blockchain implementation on long-term operational performance.Originality/valueThis is the first research empirically examining the effect of blockchain implementation on shareholder value varying from internal and external complexity from the CASs perspective. This paper provides evidence of the different effects of blockchain implementation on short- and long-term performance. It adds to the interdisciplinary research of information systems (IS) and operations management (OM).

Communities' pre-disaster resistance, disaster response, and post-disaster recovery processes are all affected by the level of resilience. This manuscript proposes a framework for the study of factors influencing the resilience of mountain communities, with the aim of clarifying the direction of transmission of the influencing relationships of the factors and identifying the key influencing factors. The study explores the characteristics of resilience influences based on community resilience and complex adaptive systems theory, uses an expert survey method to determine the binary relationships between influencing factors, and uses adversarial interpretive structural modelling and social network analysis methods to analyse influencing factors in a hierarchical and networked manner. Finally, key factors are discussed from four composite theoretical perspectives. We found that (1) infrastructure has the most fundamental impact on the factors, (2) information access is most easily influenced by other factors, (3) residents’ place attachment and sense of belonging has a significant impact on other factors in resilience-building practices, and (4) emergency planning and management organisations play a bridging role in the system of influencing factors. The results can help community managers clarify resilience management priorities, allocate management resources more rationally, and provide theoretical guidance for improving community resilience.

Background Irrational use of antibiotics is proving to be a major concern to the health systems globally. This results in antibiotics resistance and increases health care costs. In Iran, despite many years of research, appreciable efforts, and policymaking to avoid irrational use of antibiotics, yet indicators show suboptimal use of antibiotics, pointing to an urgent need for adopting alternative approaches to further understand the problem and to offer new solutions. Applying the Complex Adaptive Systems (CAS) theory, to explore and research health systems and their challenges has become popular. Therefore, this study aimed to better understand the complexity of the irrational use of antibiotics in Iran and to propose potential solutions. Method This research utilized a CAS observatory tool to qualitatively collect and analyse data. Twenty interviews and two Focus Group discussions were conducted. The data was enriched with policy document reviews to fully understand the system. MAXQDA software was used to organize and analyze the data. Result We could identify several diverse and heterogeneous, yet highly interdependent agents operating at different levels in the antibiotics use system in Iran. The network structure and its adaptive emergent behavior, information flow, governing rules, feedback and values of the system, and the way they interact were identified. The findings described antibiotics use as emergent behavior that is formed by an interplay of many factors and agents over time. According to this study, insufficient and ineffective interaction and information flow regarding antibiotics between agents are among key causes of irrational antibiotics use in Iran. Results showed that effective rules to minimize irrational use of antibiotics are missing or can be easily disobeyed. The gaps and weaknesses of the system which need redesigning or modification were recognized as well. Conclusion The study suggests re-engineering the system by implementing several system-level changes including establishing strong, timely, and effective interactions between identified stakeholders, which facilitate information flow and provision of on-time feedback, and create win-win rules in a participatory manner with stakeholders and the distributed control system.

The exercise of power permeates global governance processes, making power a critical concept for understanding, explaining, and influencing the intersection of global governance and health. This article briefly presents and discusses three well-established conceptualizations of power—Dahl’s, Bourdieu’s, and Barnett and Duvall’s—from different disciplines, finding that each is important for understanding global governance but none is sufficient. The conceptualization of power itself needs to be expanded to include the multiple ways in which one actor can influence the thinking or actions of others. I further argue that global governance processes exhibit features of complex adaptive systems, the analysis of which requires taking into account multiple types of power. Building on established frameworks, the article then offers an expanded typology of eight kinds of power: physical, economic, structural, institutional, moral, discursive, expert, and network. The typology is derived from and illustrated by examples from global health, but may be applicable to global governance more broadly. Finally, one seemingly contradictory – and cautiously optimistic – conclusion emerges from this typology: multiple types of power can mutually reinforce tremendous power disparities in global health; but at the same time, such disparities are not necessarily absolute or immutable. Further research on the complex interaction of multiple types of power is needed for a better understanding of global governance and health.

The global countryside constitutes a complex social–ecological system undergoing profound transformation. Understanding how such systems navigate transitions and achieve resilient, sustainable outcomes requires examining the interactions and adaptive behaviors of multiple actors. This study investigates the restructuring of rural China through a complex adaptive systems lens, focusing on the county of Lin’an in Zhejiang Province. We employ a middle-range theory and process-tracing approach to analyze the co-evolutionary pathways shaped by the interactions among three key agents: local governments, enterprises, and village communities. Our findings reveal distinct yet interdependent behavioral logics—local governments and enterprises primarily exhibit instrumental rationality, driven by political performance and profit maximization, respectively, while villages demonstrate value-rational behavior anchored in communal well-being and territorial identity. Crucially, this study identifies the emergence of a vital integrative mechanism, the “village operator” model, underpinned by the collective economy. This institutional innovation facilitates the synergistic linkage of interests and the integration of endogenous and exogenous resources, thereby mitigating conflicts and alienation. We argue that this multi-agent collaboration drives a synergistic restructuring of spatial, economic, and social subsystems. The case demonstrates that sustainable rural revitalization hinges not on the dominance of a single logic, but on the emergence of adaptive governance structures that effectively coordinate diverse actor logics. This process fosters systemic resilience, enabling the rural system to adapt to external pressures and internal changes. The Lin’an experience offers a transferable framework for understanding how coordinated multi-agent interactions can guide complex social–ecological systems toward sustainable transitions.

Traditional villages embody tangible repositories of historical, cultural, and geographical heritage, and their sustainable and authentic development poses a global challenge. By applying complex adaptive system (CAS) theory via a bottom–up approach, we analyze traditional settlements using China’s Zheshui village as a representative case. Road networks and spatial configurations were examined through image analysis (ImageJ 1.54 p, Depthmap+ Beta 1.0), integrating space syntax, box-counting dimension, and point-density analysis to decode hierarchical point-line-plane structures. Key findings reveal that building units self-similarly aggregate into courtyards under landmark constraints, with courtyards further coalescing into villages. Road systems function as adaptive agents that facilitate nodal information flow while exhibiting fluidity and diversity. The village emerges as a macro-scale complex system from the building-unit level, displaying cross-scale self-similarity, yet intrinsic diversity in architecture and roads underlies its core complexity. BTM topic modeling of tourist sentiment—identifying tourists as novel adaptive agents—predictively guides strategies for enhanced cultural dissemination and public infrastructure. By establishing a CAS-driven internal generative mechanism, this work offers a novel methodological framework for authentic conservation and sustainable development.

Climate change is a consequence of our difficulty to manage the currently conflicts and contradictions. It is configured as a process that makes human life on Earth increasingly uninhabitable, making the relationship between the Earth’s ecosystem and humanity increasingly difficult. A fundamental cause of the climate change is the way in which economic wealth is produced and distributed. The current economy produces also ecological and social poverty. The adaptive reuse of cultural assets is proposed in the general framework of the Green New Deal of European Union, assuming the circular economy model for re-integrating economy into ecology. The aim of the paper is to identify how to transform a died heritage site into a living system, to be managed as a complex adaptive system, discussing the ways in which adaptive reuse can be implemented as the entry point for implementing the circular city. 

Despite a profusion of literature on complex adaptive system (CAS) definitions, it is still challenging to definitely answer whether a given system is or is not a CAS. The challenge generally lies in deciding where the boundaries lie between a complex system (CS) and a CAS. In this work, we propose a novel definition for CASs in the form of a concise, robust, and scientific algorithmic framework. The definition allows a two-stage evaluation of a system to first determine whether it meets complexity-related attributes before exploring a series of attributes related to adaptivity, including autonomy, memory, self-organisation, and emergence. We demonstrate the appropriateness of the definition by applying it to two case studies in the medical and supply chain domains. We envision that the proposed algorithmic approach can provide an efficient auditing tool to determine whether a system is a CAS, also providing insights for the relevant communities to optimise their processes and organisational structures.

Policy Points An onslaught of policies from the federal government, states, the insurance industry, and professional organizations continually requires primary care practices to make substantial changes; however, ineffective leadership at the practice level can impede the dissemination and scale‐up of these policies. The inability of primary care practice leadership to respond to ongoing policy demands has resulted in moral distress and clinician burnout. Investments are needed to develop interventions and educational opportunities that target a broad array of leadership attributes. Context Over the past several decades, health care in the United States has undergone substantial and rapid change. At the heart of this change is an assumption that a more robust primary care infrastructure helps achieve the quadruple aim of improved care, better patient experience, reduced cost, and improved work life of health care providers. Practice‐level leadership is essential to succeed in this rapidly changing environment. Complex adaptive systems theory offers a lens for understanding important leadership attributes. Methods A review of the literature on leadership from a complex adaptive system perspective identified nine leadership attributes hypothesized to support practice change: motivating others to engage in change, managing abuse of power and social influence, assuring psychological safety, enhancing communication and information sharing, generating a learning organization, instilling a collective mind, cultivating teamwork, fostering emergent leaders, and encouraging boundary spanning. Through a secondary qualitative analysis, we applied these attributes to nine practices ranking high on both a practice learning and leadership scale from the Learning from Effective Ambulatory Practice (LEAP) project to see if and how these attributes manifest in high‐performing innovative practices. Findings We found all nine attributes identified from the literature were evident and seemed important during a time of change and innovation. We identified two additional attributes—anticipating the future and developing formal processes—that we found to be important. Complexity science suggests a hypothesized developmental model in which some attributes are foundational and necessary for the emergence of others. Conclusions Successful primary care practices exhibit a diversity of strong local leadership attributes. To meet the realities of a rapidly changing health care environment, training of current and future primary care leaders needs to be more comprehensive and move beyond motivating others and developing effective teams.

In this paper, we show that the characteristics of complex adaptive systems support the original interpretation of the bioeconomy of Georgescu-Roegen: the current use of natural resources by industrialized societies is incompatible with the regeneration processes of ecological systems. Elaborating the concept of societal identity, using a biosemiotics reading of the social theory of Luhmann, we show that the current social identity is sustained by implausible sociotechnical imaginaries, including the European Union’s interpretation of the bioeconomy as a panacea for green growth. We argue that the current widespread perception of polycrisis is a sign that, on the tangible side of biosemiotic process, social practices urgently need change. On the notional side, however, society is (still) incapable of relinquishing the set of sociotechnical imaginaries grounded in the American and Cartesian dreams (the promethean ideology) firmly locked in its collective memory. This incongruity has produced information disorder in the sustainability discourse. We conclude that the EU endorsement of the concept of the circular (bio)economy as a strategy for perpetual economic growth decoupled from resource use represents a desperate attempt to maintain the status quo through the endorsement of an integrated set of noble lies.