Complex Adaptive Systems Research Articles

A Hierarchical Model for Complex Adaptive System: From Adaptive Agent to AI Society

As complex adaptive system involves human and social factors (e.g., changing demands, competition and collaboration among agents), accurately modeling the complex features of adaptive agents and AI society is crucial for the effective analysis and governance of complex adaptive systems. However, existing modeling methods struggle to accurately represent these complex features, there is a gap between existing technologies and complex features modeling. In this context, this paper proposes a hierarchical model based on the computational experiments method, which consists of four layers (i.e., L1, L2, L3 and L4) modeling the autonomous, evolutionary, interactive, and emergent features respectively from adaptive agent to AI society. Additionally, taking intelligent transportation system as an example, a computational experiments system is constructed to demonstrate the effectiveness of the proposed model. This model builds a bridge between complex feature modeling and various technologies, thereby offering theoretical support for further research in complex adaptive systems.

The Dark Side of GVC Resilience: A Complex Adaptive System View

The Dark Side of GVC Resilience: A Complex Adaptive System View

The coevolution of corporate capabilities in intellectual property management and technological innovation

PurposeIn this study, we investigate how capability in managing intellectual property may be treated as a type of “dynamic capability,” and we seek to understand how, when it is linked to the new technology development capability of a complex technological organization, these two types of dynamic capabilities may coevolve.Design/methodology/approachWe conducted a longitudinal empirical case study of Airbus, incorporating an abductive research methodology that required investigating theory and empirical data concurrently and iteratively. The data, ranging over a period of two decades from 2000 to 2021, was collected from four different sources, including interviews, internal company documents, publicly available information and patent data.FindingsOur main findings are that the capabilities and roles of the Intellectual Property function in Airbus and their interaction with the company's Technology function have indeed influenced the overall innovation strategy of the organization, and that three coevolutionary phases may be identified in the interactive development of the two functions.Research limitations/implicationsOur investigation into how new technology development and intellectual property (IP) management capabilities coevolve within complex technological organizations, exemplified by Airbus, provides significant theoretical and practical implications. Theoretically, it enhances understanding of capability co-development dynamics in complex organizations, particularly in strategic IP management. Practically, it suggests aligning IP strategy with overall corporate objectives and optimizing organizational structures to promote collaboration and efficiency across IP and technology teams. This alignment may foster innovation, maximize the value of intellectual assets and strengthen collaborations, positioning organizations for long-term success in competitive landscapes.Originality/valueThis study makes a fresh contribution to the innovation studies literature by showing how if intellectual property management is treated as a core function of a complex technological organization – rather than simply as a vehicle for protecting new inventions and products after the fact or simply as a constituent part of the organization's legal function – it may contribute proactively to the organization's technological innovation performance. We also address the current gap in the academic literature for a clear understanding of the processes by which different function-specific dynamic capabilities may coevolve in a complex organization operating as part of a dynamic and complex adaptive system.

BIRDS COMMUNITY AS A COMPLEX ADAPTIVE SYSTEM: SPATIO- TEMPORAL PATTERNS IN AN PERUVIAN ANDEAN AGROECOSYSTEM

The interpretation of biological communities as complex adaptive systems aims to demonstrate their ecological patterns at different scales and their environmental relationships. In this survey, we analyzed species diversity and alternative stable states patterns of the bird community in an Andean agroecosystem located on the central-western slope of the Peruvian Andes (Cajatambo District, Lima - Peru), on a temporal and spatio-temporal scale. We evaluated their bird community through 24 line transects, located in seven plant formations along two ecoregions, between 2 700 and 4 600 masl, during the dry and rainy seasons of 2015 and 2016. The temporal patterns did not show differences in species diversity between seasons. We determined the existence of a single temporary alternative stable states; however, we evidenced changes in their species composition between dry and rainy seasons, suggesting a greater functional redundancy in dry season than rainy season due to temporal variability of small granivore-insectivore species. Regarding the spatio-temporal patterns, the plant formations of Polylepis forests, some scrubs and agricultural lands presented high values of species diversity. In addition, we determined eight alternative stable states in relation to one or more plant formations and seasonality. Finally, a higher proportion of regime changes was found in the community alternative stable states located in the Meso-Andean ecoregion as opposed to the Puna-Humid ecoregion, which would suggest that this bird community has a greater self- organization and adaptability in the face of environmental stochasticity.

Antecedents of sustainable agricultural supply chain financing for achieving food security in resource‐constrained developing economies: A complex adaptive systems theory perspective

AbstractThe aim of this research is to examine what antecedents of supply chain financing (SCF) should be overcome to ensure that the agricultural supply chain from preplanting to postharvesting generates enough food to achieve sustainable food security in developing countries. Drawing from complex adaptive systems (CAS) theory, we develop and test a model of how a prospective and challenging financing scheme navigates complex social and repayment systems to achieve sustainable SCF. The results of the study show that a challenging financing scheme must navigate complex social and repayment systems to achieve sustainable SCF, while a prospective financing scheme even though it shows a positive influence on sustainable SCF, its effect is higher when it is able to navigate these. The study hence concludes that for agricultural SCF schemes to lead to sustainable food security, they must be accessible and appropriate to the needs of the community, overcome default risk and cumbersome financial arrangements and be able to navigate the complex social and repayment systems. The study recommends that financing schemes should establish proximity to farming communities and engage farmers to determine appropriate funds for different stages among others.

BIRDS COMMUNITY AS A COMPLEX ADAPTIVE SYSTEM SPATIO- TEMPORAL PATTERNS IN AN PERUVIAN ANDEAN AGROECOSYSTEM

The interpretation of biological communities as complex adaptive systems aims to demonstrate their ecological patterns at different scales and their environmental relationships. In this survey, we analyzed species diversity and alternative stable states patterns of the bird community in an Andean agroecosystem located on the central-western slope of the Peruvian Andes (Cajatambo District, Lima - Peru), on a temporal and spatio-temporal scale. We evaluated their bird community through 24 line transects, located in seven plant formations along two ecoregions, between 2 700 and 4 600 masl, during the dry and rainy seasons of 2015 and 2016. The temporal patterns did not show differences in species diversity between seasons. We determined the existence of a single temporary alternative stable states; however, we evidenced changes in their species composition between dry and rainy seasons, suggesting a greater functional redundancy in dry season than rainy season due to temporal variability of small granivore-insectivore species. Regarding the spatio-temporal patterns, the plant formations of Polylepis forests, some scrubs and agricultural lands presented high values of species diversity. In addition, we determined eight alternative stable states in relation to one or more plant formations and seasonality. Finally, a higher proportion of regime changes was found in the community alternative stable states located in the Meso-Andean ecoregion as opposed to the Puna-Humid ecoregion, which would suggest that this bird community has a greater self- organization and adaptability in the face of environmental stochasticity.

Internet of Things (IoT) for Environmental Monitoring

Purpose: The general objective of this study was to explore the Internet of Things for environmental monitoring. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to the Internet of Things for environmental monitoring. Preliminary empirical review revealed that IoT technologies have significantly enhanced environmental management practices by revolutionizing data collection and analysis across various ecosystems. By integrating IoT sensors with existing monitoring frameworks, real-time data on air and water quality, agriculture, wildlife habitats, and urban green spaces was efficiently gathered. This data facilitated proactive decision-making, early detection of environmental risks, and evidence-based policy formulation to address climate change, biodiversity conservation, and sustainable resource management challenges. Despite challenges like data security and interoperability, collaborative efforts among stakeholders paved the way for more effective environmental monitoring and sustainable development initiatives globally. Unique Contribution to Theory, Practice and Policy: The Complex Adaptive Systems Theory, Diffusion of Innovations Theory and Resource Dependence Theory may be used to anchor future studies on the Internet of Things technology. The study provided several recommendations that contributed significantly to theory, practice, and policy in environmental management. The study emphasized interdisciplinary approaches to enhance theoretical frameworks, advocating for advanced models and algorithms integrating IoT with environmental science and data analytics. In practice, it recommended widespread adoption of IoT-enabled sensor networks with enhanced capabilities for precise and reliable data collection. Policy-wise, the study called for regulatory frameworks supporting IoT integration, data standards, and international cooperation to address global environmental challenges collaboratively. Capacity building and continuous research and development were also highlighted to optimize IoT technologies for sustainable environmental monitoring and management globally.

Entropy and the Idea of God(s): A Philosophical Approach to Religion as a Complex Adaptive System

Entropy and the Idea of God(s): A Philosophical Approach to Religion as a Complex Adaptive System

Dealing with the ever-increasing intricacies of mega and complex projects: a survey of AAMI Park

Complexity science brings together differing paradigms and thoughts. It has attracted academic interest as a means of understanding complex social and technological phenomena. The emergence of increasingly complex building design, construction, and technologies is posing numerous challenges for professionals. This paper utilizes complexity science, and the practical application of complexity theories, to holistically evaluate the development of a unique major sporting stadium, known as AAMI Park, Melbourne, Australia. The authors assess this project’s complexity and rank it on a complexity scale to illustrate the level of knowledge and expertise required to deliver such projects. AAMI Park’s most dominant and complex feature, the bio-frame roof, which was innovative at the time, posed unique challenges, and therefore, authors also evaluate the constraints and specific project delivery methods developed to best manage its complications. Since the adaptive management approach was used for this project, this paper assesses this approach to recommend enhanced delivery methodologies for similar future projects. Further, since the design of this project was the first of a kind, the authors seek to identify the level of project complexity and its success through the lens of complexity theory.

Towards dynamic decision-making in government as service organization: insights from systems thinking

Purpose Service organizations operate in an increasingly complex and uncertain context that makes decision-making challenging. Despite well-recognized changes in the operational context of government as service organization, service literature has given surprisingly limited attention to what these changes imply for organizational decision-making. This study aims to face with the lack of fit of decision-making theorizing with the reality, within which most service practitioners operate, in order to foster the relevance of decision-making in service research and properly approach the false assumptions and misguided instructions for action. Design/methodology/approach To rectify the situation, the purpose of this paper is to advance a more holistic understanding of decision-making in government as service organization. The authors do so by reviewing the sparse, though insightful, prior literature on decision-making in service research and identifying four foundational assumptions of decision-making in the service context, that radically differ from the traditional assumptions of decision-making within the wider management literature. Findings The authors contribute to service research by further advancing the emerging dynamic understanding of decision-making by developing eight systems thinking-informed research propositions and a connected research agenda. In doing so, the paper offers the essential ground work that can revitalize the field of service management and equip it for facing the challenges that government as service organization is encountering in the 21st century. Originality/value The formulated eight research propositions demonstrate that decision-making in a government as service organization occurs within complex adaptive systems composed of multiple subsystems and is characterized by a high degree of unpredictability. It is a process influenced by multiple actors part of the system and subsystems, through multiple feedback loops, where the implications of prior decisions inform the future decisions.

Consilience of healthcare legislation, complexity science & computational analysis

Our US Health Care System (HCS) has evolved from simple to complex and needs reform. Thus far, all legislative initiatives have failed to result in establishing a friendly, cost-effective, quality healthcare system. The question becomes, can Complexity Science (CS) and computational analytic platform modeling be used to help create better Health Care Policies (HCP) and reform our all too complex HCS? Modeling has been used in many diverse disciplines but has yet to be utilized in preemptive evaluation of major US legislative HCPs. Review of US Health Care Policy History (HCPH) viewed in the context of a Complex Adaptive System(CAS) reveals how, unanticipated historical events, politics, social, and personal leadership have tangentially shaped our US HCPs. Future construction of HCPs with the help of CS, and preemptive computational modeling (CM) techniques, will hopefully yield stronger conclusions in legislative HCP construction and advance our US HCS into one with dynamic resilience.

Societies with fission-fusion dynamics as complex adaptive systems: the importance of scale.

In this article, we argue that social systems with fission-fusion (FF) dynamics are best characterized within a complex adaptive systems (CAS) framework. We discuss how different endogenous and exogenous factors drive scale-dependent network properties across temporal, spatial and social domains. Importantly, this view treats the dynamics themselves as objects of study, rather than variously defined notions of static 'social groups' that have hitherto dominated thinking in behavioural ecology. CAS approaches allow us to interrogate FF dynamics in taxa that do not conform to more traditional conceptualizations of sociality and encourage us to pose new types of questions regarding the sources of stability and change in social systems, distinguishing regular variations from those that would lead to system-level reorganization. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Coherence-controlled chaotic soliton bunch

Controlling the coherence of chaotic soliton bunch holds the promise to explore novel light-matter interactions and manipulate dynamic events such as rogue waves. However, the coherence control of chaotic soliton bunch remains challenging, as there is a lack of dynamic equilibrium mechanism for stochastic soliton interactions. Here, we develop a strategy to effectively control the coherence of chaotic soliton bunch in a laser. We show that by introducing a lumped fourth-order-dispersion (FOD), the soliton oscillating tails can be formed and generate the potential barriers among the chaotic solitons. The repulsive force between neighboring solitons enabled by the potential barriers gives rise to an alleviation of the soliton fusion/annihilation from stochastic interactions, endowing the capability to control the coherence in chaotic soliton bunch. We envision that this result provides a promising test-bed for a variety of dynamical complexity science and brings new insights into the nonlinear behavior of chaotic laser sources.

Towards a unified ontology of cybernetics: bridging mechanology and CAS for cooperative societies through thematic synthesis

PurposeThis paper aims to conceptually unite an ontology of cybernetics, bridging living and technical systems, to facilitate future epistemological and theoretical advancements applicable to highly technical societies by crafting a set of definitions that elucidate the nature of the world in which these systems operate.Design/methodology/approachThe research uses a thematic synthesis of two systems/cybernetic traditions: complex adaptive systems and mechanology. The primary sources for this research were the main theses and correlated papers published in the Simondon case for mechanology, and the seminal literature preselected by the Santa Fe Institute for complex adaptive systems.FindingsThe study proposes the following concepts: Individuation: the emergence of new properties in an individual composed of synergistically related parts; Technical evolution: the notion that technical objects evolve into living beings; circular causality: the notion that feedback and feedforward processes shape the organisation and structure of systems and their relationship with the environment; The milieu refers to the part of the environment that has a relationship of co-production, co-dependency, and co-evolution with systems. Metastability is a state that transcends stability and instability and motivates changes in the system. Transduction is the cumulative process of individuation in which systems change structure and organization to maintain operational coherence with their surroundings.Originality/valueThe concepts the paper identifies can serve as a starting point for an extended study on the ontology of cybernetics or as the basis for an evolutionary epistemology both in humans and machines.

Complexity Theory Approach to Innovation Ecosystems

Purpose: By nowadays, in addition to the innovation systems definitions, the research area of innovation ecosystems operation is also developing significantly. The aim of the research is to examine how the concept of the innovation ecosystem and the conceptual scope of complexity theory are related. Theoretical reference: The paper gives an overview of development of innovation ecosystems literature, and also introduces summary of general systems theory. The authors point out that the joint discussion of the two areas are very rare in the related research works. There are few examples of referring Complex Adaptive Systems as potential approach for innovation ecosystems, but detailed theoretical analysis of the topic is limited. Method: The paper analyses the relationship and possible overlap of fields of innovation ecosystems and complexity theory by evaluation of findings of content analysis and a keyword-based method. As part of the methodology presented, the research of the theme is carried out from two aspects. First, based on review-type and theoretical works, a content analysis was made to define specific key feature word sets in both innovation ecosystems and complex theory areas. Then, based on these keyword set, validation was executed based on abstracts of selected papers in order to define possible relations of the two fields. Results and Conclusion: As a result of the research, authors draw conclusions about the relationship between the definition of innovation ecosystems and complexity theory. Both the joint keywords and the non-relevant words have been pointed out. The authors concluded that there is apparent theoretical relation of the two areas from content point of view, based on analysis of relevant scientific papers. Implications of research: The outcomes of the research fundamentally influence the treatment of innovation ecosystems, which has been traditionally assumed linear, deterministic and controllable behaviour. Introducing the potential of complex systems allow opening new aspects to manage such challenges of innovation ecosystems which could not been handled in the usual way. Originality/value: The joint discussion of the topic of innovation ecosystems and complex systems theory is rather rare in the related scientific works. The novelty of the current paper is the systematic approach defined for this analysis purpose and way of validation of the pre-defined keyword set through abstracts of relevant papers. The present research addressed the preliminary discussion of the given research question, further research and analysis can be made based on larger-scale paper base.

Quantifying the uncertainty of LLM hallucination spreading in complex adaptive social networks

Large language models (LLMs) are becoming a significant source of content generation in social networks, which is a typical complex adaptive system (CAS). However, due to their hallucinatory nature, LLMs produce false information that can spread through social networks, which will impact the stability of the whole society. The uncertainty of LLMs false information spread within social networks is attributable to the diversity of individual behaviors, intricate interconnectivity, and dynamic network structures. Quantifying the uncertainty of false information spread by LLMs in social networks is beneficial for preemptively devising strategies to defend against threats. To address these challenges, we propose an LLMs hallucination-aware dynamic modeling method via agent-based probability distributions, spread popularity and community affiliation, to quantify the uncertain spreading of LLMs hallucination in social networks. We set up the node attributes and behaviors in the model based on real-world data. For evaluation, we consider the spreaders, informed people, discerning and unwilling non-spreaders as indicators, and quantified the spreading under different LLMs task situations, such as QA, dialogue, and summarization, as well as LLMs versions. Furthermore, we conduct experiments using real-world LLM hallucination data combined with social network features to ensure the validity of the proposed quantifying scheme.

"I've got yer back": A community art and anatomy project.

This article describes a community collaborative project, "I've got yer back," that utilized the craft of needle felting to raise awareness and develop understanding of the anatomy of the human spine. The project took place in 2023 and engaged with participants from across the United Kingdom and abroad and its completion was timed to coincide with National Back Health Awareness week in October 2023. We describe the process of creating a vertebra using needle felt and examine how the particularities of the process and the use of the sense of touch helped participants notice and understand the complex form of the human vertebra. We consider how the project encompassed creative processes of hands-on learning to enhance knowledge about this aspect of human anatomy. We discuss how the project evolved to include public and academic participation in a shared goal and argue for the effectiveness of seemingly simple and straightforward art or craft workshops in teaching relatively complex science. The article includes detailed feedback from participants who reflect on the process of learning through making and how it went on to affect individuals in very different, and sometimes very personal, ways.

Laying train tracks en route: How institutional education leaders navigate complexity during mandated curriculum change.

Institutional education leaders serve key roles in leading major curricular change within residency education, yet little is known about how they accomplish these goals on the ground. Change management principles have predominantly been developed and described in the hierarchical context of management science and corporate settings. However, the non-hierarchical, complex and adaptive features of health professions education may render these traditional change management models inadequate. We explored how institutional educational leaders navigate the complex residency education system in implementing a major curricular change. Using constructivist grounded theory, we conducted and iteratively analysed semi-structured interviews with 11 institutional education leaders from across Canada who were responsible for leading the nationally mandated curricular change to competency-based residency education. Thematic analysis was performed iteratively using constant comparison. Leaders managing the change process focused on two priorities: steering the direction of the change process as it evolved and maintaining the momentum amongst stakeholders to move forward steadily. Four common threats and opportunities impacted the focus on direction and momentum: multiplicity of contexts, innovation, resistance and distractions. In response, leaders utilised various tactics and harnessed diverse leadership styles to manage these challenges accordingly. We identified a change framework that offers a more contextually nuanced understanding of curricular change in residency education that has not been described in the change management literature generated by the management sector. Institutional education leaders focused on maintaining the direction and momentum, while constantly assessing and adapting to evolving, uncertain and complex conditions. Our findings provide a simple and practical foundation to support leadership education in curricular change as well as researchers in developing further change theories in complex adaptive health professions education systems.

Youth and climate crisis: participation and learning in complex, adaptive systems

AbstractThe Friday for Future school strikes have vividly demonstrated young people’s concern for the rapidly deteriorating life and survival chances of future generations of human and nonhuman beings. The young people’s ambivalence between despair and hope, feelings of powerlessness and empowerment challenge us to recognise the complexity and dynamic not only of ecosystems but of socio-ecological systems and to question the mechanistic and linear thinking often prevalent in youth research and education science. This thinkbite invites readers to consider young people’s experiences with the climate crisis and (climate change) education through the perspective of Complex Adaptive System Theory to open up learning space for more wholesome and creative responses to the challenge.

Exploring spatial segregation induced by competition avoidance as driving mechanism for emergent coexistence in microbial communities.

This study investigates the role of spatial segregation, prompted by competition avoidance, as a key mechanism for emergent coexistence within microbial communities. Recognizing these communities as complex adaptive systems, we challenge the sufficiency of mean-field pairwise interaction models, and we consider the impact of spatial dynamics. We developed an individual-based spatial simulation depicting bacterial movement through a pattern of random walks influenced by competition avoidance, leading to the formation of spatially segregated clusters. This model was integrated with a Lotka-Volterra metapopulation framework focused on competitive interactions. Our findings reveal that spatial segregation combined with low diffusion rates and high compositional heterogeneity among patches can lead to emergent coexistence in microbial communities. This reveals a novel mechanism underpinning the formation of stable, coexisting microbe clusters, which is nonetheless incapable of promoting coexistence in the case of isolated pairs of species. This study underscores the importance of considering spatial factors in understanding the dynamics of microbial ecosystems.