Complex Adaptive Systems Theory Research Articles

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.

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.

A fRAmework of the DetermInants of Arts aNd Cultural Engagement (RADIANCE): integrated insights from ecological, behavioural and complex adaptive systems theories

A fRAmework of the DetermInants of Arts aNd Cultural Engagement (RADIANCE): integrated insights from ecological, behavioural and complex adaptive systems theories

Human-land relationship in the construction of historical settlements based on Complex Adaptive System (CAS) theory: evidence from Shawan in Guangfu region, China

The relationship between humans and land environment within historical settlements reflects the intricate interplay between human societies, their construction activities, and the specific geographical contexts. Inadequate research into this relationship hinders a comprehensive understanding of the social spatial intricacies inherent in historical settlements. This paper adopts the theoretical framework of complex adaptive system and takes Shawan Ancient Town in Guangfu area of China as an example. Under the geographical background of sustainable land growth in the coastal zone, this study analyzed the subtle changes in the relationship between people and land during the historical construction, and the key findings of the investigation are threefold: (1) Land resources play a central role in the construction of human-land relationships in historical settlements. The geographical environment and social institutions serve as configuring factors in the formation and evolution of human-land relationships. These factors collectively determine the formation and evolution of human-land relationships. (2) Social space emerges as a pivotal manifestation of the human–environment relationship in historical settlements, transcending mere physical dimensions. Consequently, a holistic study of this relationship necessitates a comprehensive exploration not only of spatial configurations but also of the intricate interconnections among social bonds, structural formations, societal order, and settlement spatiality. (3) Drawing on the framework of complex adaptive systems theory, the study disentangles intricate elements within the human-land relationship of historical settlements. It distills and examines the manifestations of four intricate adaptive capacities—namely aggregation, non-linearity, flow, and diversity—alongside the mechanisms of tags, internal models, and fundamental building blocks. It is believed that the study of historical settlements in coastal areas needs to grasp the invariable social-spatial objects such as geographical environment, land form, local beliefs. Take it as a clue to sort out how other elements of change have iterated and transformed in the process of historical evolution, such as the rise and fall of families, land ownership changes and social class evolution. This paper explores the value connotation of historical settlements from the perspective of dialectic thinking of change and invariance with CAS theory, which has theoretical significance for protection of settlement's human-land relationship from the perspective of "social-spatial".

A Study on the Chinese-English Translation of Shaanxi Tourism Culture Based on the Theory of Complex Adaptive Systems

A Study on the Chinese-English Translation of Shaanxi Tourism Culture Based on the Theory of Complex Adaptive Systems

Empirical and simulated investigation of the solid waste reverse supply chain: A complex adaptive system perspective

Solid waste is increasing rapidly worldwide. In this study, the solid waste (household waste, construction and demolition waste and industrial waste) management systems are treated as reverse supply chain to analyze the critical operational issues based on complex adaptive system theory. At the single-layer, the complexity of the various nodes at a layer arises from rational decision-making and behavioral heterogeneity. The solid waste generation layer is employed as an example to investigate the complexity of node behavioral decisions. Regression analysis results reveal that both endogenous (Attitude, Subjective norm, and Perceived behavioral control) and exogenous factors (Economic incentive, Government supervision, Technical support) positively influence sorting behavior. The effect of Economic incentive (β=0.327P<0.001) and Attitude (β=0.249P<0.001) on sorting behavior are the largest. In the multi-layer system, different layers communicate with each other through the material and financial flows and have cross-layer impacts. An agent-based model is developed to investigate the multi-layer feedforward influence mechanism of changes in key layers (e.g., sorting rate, disposal rate) and the material and financial flows adaptive adjustment direction of the solid waste reverse supply chain. High rate of participation and accuracy of source sorting can shorten material flow paths and reduce storage and transportation costs. The increase in disposal rate encourages the transition of solid waste from backfill to resource utilization. This study provides a practice reference for solid waste reverse supply chain and related enterprises managers.

The Analysis of Time Management and Students’ Self-efficacy of Blended Learning: A Case Study of College English Course in the University of Science and Technology Liaoning

Background and Aim: This study delves into the realm of time management training within an English blended learning course, focusing on its influence on student self-efficacy and its subsequent effects on learning outcomes and perceptions. Anchored in the theories of Complex Adaptive Blended Learning Systems (CABLS), Goal Setting, and Self-efficacy, the research aims to uncover the combined impact of time management and self-efficacy enhancement on students' competence, and overall learning experiences. The objective is to assess how structured time management training, when integrated with blended learning strategies, can improve students’ self-efficacy. Materials and Methods: Employing a mixed-methods approach, this study utilizes quantitative tools such as independent samples t-tests and multilinear regression analyses to evaluate the intervention's effectiveness in altering student’ self-efficacy (SE) and other factors like engagement (EN), autonomous learning (AL), teachers’ support (TS), social influence (SI), intention to use (IU) and self-efficacy (SE) levels. The intervention includes time management training facilitated through the Xuexitong Platform, aiming to leverage the advantages of blended learning. This methodological framework allows for a comprehensive analysis of the training's impact, providing a robust evaluation of changes in student engagement, autonomous learning, teachers’ support, social influence, and self-efficacy. Results: The quantitative results revealed significant differences between the control and experimental groups in engagement (EN), autonomous learning (AL), teacher support (TS), social influence (SI), and self-efficacy (SE) except the factor intention to use (IU). In multilinear regression, engagement (EN), social influence (SI), and intention to use (IU) positively predicted higher self-efficacy, while autonomous learning (AL) had a minor negative effect. Teachers’ support (TS) lacked a statistically significant association with self-efficacy. The qualitative data supported and supplemented the findings, highlighting the above 6 factors’ improvement with high frequency in the related codings, and high occurrence of codings like improved in learning, enriching, interesting, growth, and motivation also showed the deep and multidimensional analysis of the findings, and managing time and goals effectively cultivated independence and responsibility. Overall, the qualitative insights provided nuanced, experiential perspectives complementing the quantitative model connecting factors like engagement, autonomous learning, teachers’ support, social influence, intention to use, and self-efficacy. Conclusion: This research demonstrates the pivotal role of structured time management training in enhancing educational outcomes within blended learning environments. By demonstrating the benefits of integrating time management training, the study contributes novel insights into improving students’ development. The findings advocate for the development of more effective educational strategies and instructional designs, emphasizing the complex interplay between various factors and their impact on self-efficacy, especially AI integrated into blended learning. The study paves the way for further investigations into the integration of time management training and other self-efficacy enhancement techniques in blended learning environments. In this way, it encourages researchers to explore the potential synergies between time management, goal setting, and self-efficacy enhancement strategies in various educational contexts. Moreover, the findings can inform the development of more effective educational strategies and instructional designs, leading to improved pedagogical practices and student learning experiences in the long run.

A complex-systems view on military decision making

ABSTRACT Military decision-making institutions are sociotechnical systems. They feature interactions among people applying technologies to enact roles within mission-oriented collectives. As sociotechnical systems, military institutions can be examined through the lens of complex adaptive systems (CAS) theory. This discussion applies the CAS perspective to reveal implications of integrating newer artificial intelligence (AI) technologies into military decision-making institutions. I begin by arguing that military adoption of AI is well-incentivised by the current defence landscape. Given these incentives, it would be useful to try to understand the likely effects of AI integration into military decision-making. Direct examinations of the new affordances and risks of new AI models is a natural mode of analysis for this. I discuss some low-hanging fruit in this tradition. However, I also maintain that such examinations can miss systemic impacts of AI reliance in decision-making workflows. By taking a complex systems view of AI integration, it is possible to glean non-intuitive insights, including, for example, that common policy concerns like preventing human deskilling or requiring algorithmic transparency may be overblown or counterproductive.

What about adaptiveness? The case of organisational resilience and cognition

This paper makes the very simple, perhaps straightforward point that adaptiveness cannot be taken for granted when analysing a complex system. The paradigm of Complex Adaptive Systems (CAS) theory makes it clear that a key feature of complex systems is the ability to adapt to changes in their environment. This is, indeed, relevant to many systems (e.g., living and social systems) since change is embedded in the way in which systems evolve over time. At the same time, adaptiveness is a strong assumption to make, since it prioritises change over stability and it can be a straight jacket, especially when it comes to studying complexity in the context of human social organising. By using a Case Study, this paper highlights the limits of a focus on adaptiveness and pushes for a more “neutral” perspective that allows researchers to appreciate a wider set of mechanisms, norms, and behaviours pertaining to complex social systems.

Complex Adaptive System Theory, Agent-Based Modeling, and Simulation in Dominant Technology Formation

Complex Adaptive System Theory, Agent-Based Modeling, and Simulation in Dominant Technology Formation

Retracted: Identification of Driving Factors of Scientific and Technological Innovation in the New Material Industry Based on the Theory of Complex Adaptive System: Taking the Construction of Green Innovation System as an Example

Retracted: Identification of Driving Factors of Scientific and Technological Innovation in the New Material Industry Based on the Theory of Complex Adaptive System: Taking the Construction of Green Innovation System as an Example

Retracted: Earthquake Disaster Rescue Model Based on Complex Adaptive System Theory

Retracted: Earthquake Disaster Rescue Model Based on Complex Adaptive System Theory

Using artificial intelligence to advance sustainable development in industrial markets: A complex adaptive systems perspective

The vast complexity involved in dealing responsibly with sustainable development is daunting. Such complexity increases significantly due to the interdependencies and trade-offs associated with the 17 UN Sustainable Development Goals (SDGs). To address sustainability across multiple domains, recent advances in technology and innovative adaptations offer some promise, as exemplified by the increased prominence of artificial intelligence (AI) in the marketplace. However, as more industrial firms leverage AI to address sustainable development goals, it becomes even more critical for them to account for these interdependencies and trade-offs among the SDGs. Relatively few existing studies guide industrial marketers in accounting for these interdependencies when deploying AI-enabled solutions. Herein, guided by complex adaptive systems theory and principles of systems engineering, the authors introduce a responsible AI deployment model that articulates key steps in the development and deployment of AI solutions to advance sustainable development firms.

The Dynamics of Interorganizational Collaboration in Disaster Management: A Network Study Based on Flood Disasters in China

Interorganizational collaboration networks have become an important tool for disaster management. However, research on how different organizations can effectively collaborate throughout the entire disaster management process in centralized states such as China is scarce. This study begins to fill this lacuna by investigating interorganizational collaboration in different phases of disaster management and analyzing changes in the structure of the networks constructed during the preparedness and response phases of the 2020 flood disaster in Hubei Province, China. Building on the complex adaptive systems (CAS) theory, we argue that interorganizational collaboration changes dynamically according to its tasks and requirements. In the preparedness phase, interorganizational collaborations primarily follow established plans and choose horizontal self-organized collaboration mechanisms. However, when the urgent information and resource requirements increase in the response phase, many organizations choose vertical mandatory collaboration mechanisms. We found that organizations at the central and provincial levels in China were well positioned to coordinate information and resources and strengthen the interorganizational collaboration and communication that is crucial in disaster management. These findings contribute to the study of interorganizational collaboration networks in disaster management.

Financial Engineering in Complex Dynamic Systems

This paper explores the dynamic nature of financial markets through the lens of complex adaptive systems (CAS) theory, aiming to provide a comprehensive understanding of how financial markets deviate from the Efficient Market Hypothesis in extreme events such as bubbles and crashes. Traditional economic models often struggle to capture the intricate dynamics of 'self-organizing' financial markets, particularly the interaction between supply and demand in the face of evolving risks. CAS theory offers a promising framework for modeling asset prices, emphasizing the interconnectedness and adaptability of various agents within the system. The literature review highlights the significance of CAS theory in understanding the collective adaptation that emerges from interactions among heterogeneous agents. Notably, researchers such as Holland (1995) and Axelrod (1997) have demonstrated how simple agent-level rules can lead to sophisticated, self-organizing behaviors at the system level, resulting in more efficient outcomes. This paper also discusses the pivotal role of financial engineering in enhancing the adaptive capacity of socioeconomic systems under extreme stress. In an increasingly unpredictable world characterized by natural disasters, economic crises, and other unforeseen events, risk management serves as a vital mechanism for volatility mitigation and financial protection. By spreading risk collectively through hedging strategies, financial engineering not only provides portfolio security but also contributes to the resilience of financial and economic systems. By merging insights from CAS theory and the role of financial engineering in increasing adaptive capacity, this paper contributes to a more comprehensive understanding of the risk dynamics in financial markets impacting economic activities. Financial engineering tools mitigate negative shocks and reduce the severity of recessionary cycles. An attempt is made to explain how collective adaptation can lead to more efficient risk management and pricing, ultimately helping policymakers, fund managers, and researchers navigate the complexities of modern financial markets and fortify socioeconomic systems against extreme stressors.

Research on the Relationship Between Informational Team Faultline and Team Resilience-Team Leader Member Exchange and Team Member Exchange as Mechanism.

This study aims to investigate how a team can be resilient in the face of crisis and adversity. This empirical study adopted a quantitative research method. The data were collected by questionnaire survey, and the stats analysis package in R language and AMOS 23 were used for empirical analysis of 98 teams. Based on complex adaptive system theory and conservation of resources theory, this study was constructed the theoretical framework of "environmental influence - team exchange - team resilience" with informational team faultline (ITF) as independent variable, team leader member exchange (TLMX) and team member exchange (TMX) as mediating and moderating variables, and team resilience as dependent variable in the context of Chinese culture. We found that the ITF had a significant negative effect on the team resilience. TLMX and TMX played partial mediating role between ITF and team resilience. In addition, TLMX and TMX played moderating role between ITF and team resilience, that is, weakening the negative influence of ITF on team resilience. This study contributes to clarify the mechanism of the influence of ITF on team resilience, and provide reference for team leaders to improve team resilience in the face of adversity.

Psychological well-being of small enterprise employees: a multi-theoretical perspective

PurposeThis paper aims to suggest a multi-theoretical explanation using a success story to explain psychological well-being (PWB) among employees of K.C, a small enterprise found in Uganda, a developing country in Africa.Design/methodology/approachThe study used qualitative methodology. Based on in-depth interviews with K.C employees, a story was developed describing the practical experience, focusing on the context, actions, results and lessons learnt. Regarding the sample size, the saturation point was attained on the seventh participant.FindingsFindings reveal that employees that possess psychological capital set targets and generate avenues that allow them to achieve set goals, with personal initiative that makes them proactive to accomplish work tasks and individual adaptability that enables them to adjust their emotions and behavior to fit in a complex working environment, which makes them to think, feel and act positively. Furthermore, several theories, including broaden and build, personal initiative and complex adaptive systems theory, explain the manifestations of PWB of employees in small enterprises.Research limitations/implicationsThe study was limited by focusing on the context of a small enterprise. Future research may investigate other study contexts whose findings might be different. In addition, the study being hypothetical lacked statistical testing. It would be a meaningful effort if future studies statistically tested the suggested model. Irrespective of the limitations, the findings of this study remain significant.Practical implicationsIn practice, employees may replicate these findings to nurture PWB which eventually contributes to enterprises’ success. This could provide answers to the psychological challenges experienced by employees of small enterprises, especially in the African developing countries like Uganda where this is a major challenge. Specifically, the workers of K.C enterprise may depend on their PWB to deal with workplace challenges and sustain the enterprise’s performance.Social implicationsSocially, there is need to embrace positive social relationships among employees at the work place which will translate into well-being of society.Originality/valueThis paper is exceptional because it uses a success story showing practical experiences of how PWB of employees in small enterprises is nurtured in Uganda. In addition, a multi-theoretical perspective is used to explain the manifestations in the story, which is the greatest contribution of this paper. Further, a conceptual model is still proposed, depicting psychological capital, personal initiative and individual adaptability as antecedents of PWB.

Evaluation of Urban Resilience of China’s Three Major Urban Agglomerations Using Complex Adaptive System Theory

By 2050, a majority of the global population will reside in urban agglomerations. Intensifying natural hazards are posing serious challenges to populations within the urban agglomerations. Therefore, it is critical to evaluate the resilience of urban agglomerations to natural hazards. However, the urban resilience of China’s three major urban agglomerations, Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and Guangdong–Hong Kong–Macao Greater Bay Area (GHMB), is not properly determined. To enhance the evaluation of comprehensive resilience in complex urban agglomerations and improve adaptability in the face of uncertain risks, this paper adopts the theory of complex adaptive systems to reveal the driving factors behind resilience. We developed a model for measuring disaster severity, exposure, bearing capacity, recoverability, and learnability. Furthermore, spatial autocorrelation analysis was employed to explore the distribution patterns of resilience and devise strategies for enhancement. The results indicate that the average urban resilience value of the three major urban agglomerations was 0.5061. The average urban resilience values for BTH, YRD, and GHMB are 0.5331, 0.5116, and 0.4612. We found BTH having the highest resilience level, followed by YRD and GHMB. Within BTH, the resilience level was the highest in the northern part of BTH, but the overall resilience of the southern cities should be improved by enhancing Shijiazhuang’s central role. We also found higher resilience level in northwest YRD than in southeast YRD due to lower population density and lower disaster exposure in northwest YRD. However, we found obscure spatial patterns of urban resilience within GHMB, i.e., higher urban resilience in east and west GHMB and lower urban resilience level in central GHMB. This study presents different urban resilience levels over three urban agglomerations, providing background information for urban planning and urban mitigation to natural disasters in a warming climate.

Advance Care Planning in Primary Care: A Step toward Normalizing the Conversation.

Despite the number of advance care planning (ACP) conversation guides and tools, ACP conversations are not common in healthcare. In this quality improvement project, we took a different approach and applied complex adaptive systems theory to develop an intervention that emerged from the users (family physicians) themselves - a standardized e-form with prompts. By listening to the users, we were able to integrate ACP best practices, including shifting the focus of ACP conversations from treatment decisions to patient values, in a way that met both users' and patients' needs, addressed barriers and will help normalize ACP conversations in primary care. The intervention was designed for any patient and family physician and may have utility for other family practice groups.

Research on the collaborative evolution process of information in public health emergencies based on complex adaptive system theory and social network analysis: a case study of the COVID-19 pandemic.

This review aimed to elucidate the significance of information collaboration in the prevention and control of public health emergencies, and its evolutionary pathway guided by the theory of complex adaptive systems. The study employed time-slicing techniques and social network analysis to translate the dynamic evolution of information collaboration into a stage-based static representation. Data were collected from January to April 2020, focusing on the COVID-19 pandemic. Python was used to amass data from diverse sources including government portals, public commentary, social organizations, market updates, and healthcare institutions. Post data collection, the structures, collaboration objectives, and participating entities within each time slice were explored using social network analysis. The findings suggest that the law of evolution for information collaboration in public health emergencies primarily starts with small-scale collaboration, grows to full-scale in the middle phase, and then reverts to small-scale in the final phase. The network's complexity increases initially and then gradually decreases, mirroring changes in collaboration tasks, objectives, and strategies. The dynamic pattern of information collaboration highlighted in this study offers valuable insights for enhancing emergency management capabilities. Recognizing the evolving nature of information collaboration can significantly improve information processing efficiency during public health crises.