Complex Adaptive Systems Perspective Research Articles

COVID-19 crisis – coping up strategies of companies to sustain in markets

Purpose Pandemics are frequent events, and the impact of each pandemic makes a strong and long-term effect on companies and markets. Given the potential impact of the COVID-19 pandemic, it is important to investigate the crisis from a different perspective to know how companies have sustained growth in markets. The purpose of this paper is to understand how profit-oriented customer-centric companies (small, medium and large) have responded and adapted to COVID-19 crisis, using the complexity theory. Design/methodology/approach Drawing upon the complexity theory, a humble attempt is made to develop theoretical propositions by conceptualizing companies as complex adaptive systems. The paper examines companies from three dimensions (i.e. internal mechanism, environment and coevolution). Findings Companies self-organize, emerge into new states and become adaptive to the changing environment. Companies create knowledge to understand the dynamic anatomy and design survival and growth strategies during and post COVID-19 era. Complex adaptive systems perspective provides companies with insights to deal with complex issues raised due to COVID-19 pandemic. They can handle the impact of pandemic efficiently with complex adaptive systems by developing and implementing appropriate strategies post-COVID-19. Originality/value The study reveals how companies evolve and emerge into as complex adaptive systems to adapt themselves to the highly dynamic environment, which are uncertain, unpredictable, nonlinear and multifaceted, in the context of COVID-19. Implications for theory and practice of viewing companies as complex adaptive systems and coevolving structures in the COVID-19 context are discussed.

The data sharing conundrum: revisiting established theory in the age of digital transformation

Purpose This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition for companies to capture emerging opportunities in supply chain management and for product-related servitization; however, there are ongoing concerns, and data are often perceived as the “new oil.” It is thus important to gain a better understanding of the determinants of firms’ decisions. Design/methodology/approach The authors develop an embedded case study analysis involving 16 firms within an extended supply network in the automotive industry. The authors focus on the peculiarities of the new context, as opposed to elements highlighted by research prior to the advent of the latest technologies. Abductive reasoning is applied to the theoretical foundations of the resource-based view, resource dependence theory and the complex adaptive systems perspective. Findings Data sharing is largely underpinned by factors identified prior to DT, such as data specificity, dependence dynamics and protection mechanisms and the dynamism of the business context. DT, however, can influence the extent of data sharing. New factors concern complementarities whenever data are pooled from different sources and digital platforms, as well as different forms of data ownership protection. Originality/value This study stresses that data sharing in the context of DT can be explained through established theoretical lenses, providing the integration of elements accounting for new technological opportunities.

Governing Smart City IoT Interventions: A Complex Adaptive Systems Perspective

Urban infrastructure systems (UIS) encompass physical infrastructure and human stakeholders, delivering essential services through distributed flow networks. These systems exhibit properties of Complex Adaptive Systems (CAS), such as self-organization and adaptivity, which makes them resilient to perturbations from the outside. Smart city strategies advocate for external technology interventions to improve the efficiency and sustainability of UIS. Internet of Things (IoT) is a key enabler for such strategies which helps to gather data from various infrastructure components and optimize flow networks in UIS. Although beneficial, such interventions often give rise to ethical concerns, underscoring the need for appropriate governance measures. In this study, we adopt a CAS perspective to analyse the ethical concerns of a proposed smart city IoT platform in the cities of Karnataka, India. Based on our analysis, we present a framework to aid city authorities in formulating appropriate strategies to govern Smart City IoT interventions in general.

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.

Resilience Assessment of Historical and Cultural Cities from the Perspective of Urban Complex Adaptive Systems

Due to the increasingly complex global climatic environment and the rapid development of China’s urban construction, China’s historical and cultural cities are experiencing an external impact as well as internal fragility. Representing the capacity of the urban system to address impact and pressure, resilience can effectively guarantee the sustainable development of historical and cultural cities. A scientific and reasonable resilience assessment system can guide the resilience construction of historical and cultural cities in an effort to effectively counter the impact and pressure they face. Therefore, it is necessary to research the resilience of historical and cultural cities. On the basis of the complex adaptive system (CAS), and by applying multiple assessment indicators, this paper established a resilience assessment system for China’s historical and cultural cities, comprising 38 indicators in six dimensions, to analyze the characteristics and the influencing mechanisms of the resilience of the historical and cultural cities and to reveal the inherent logic underlying their complex presentation. Using six historical and cultural cities in east China as an example, the study applied the assessment system to assess and analyze the different resilience levels of the cities. The comprehensive resilience of Changzhou City obtained the highest score at 0.64, indicating a higher degree of resilience; the scores of Yantai City, Huzhou City, and Nantong City were 0.59, 0.54, and 0.50, respectively, representing moderate degrees of resilience; the scores of Zhongshan City and Quzhou City were 0.44 and 0.40, respectively, exhibiting a lower degree of resilience. Moreover, the factors that result in an unbalanced development of urban resilience were explored from the perspectives of economy, system, and culture. The paper contains some significance in guiding the development of the resilience of historical and cultural cities.

Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome

BackgroundChronic Fatigue Syndrome patients suffer from symptoms that cannot be explained by a single underlying biological cause. It is sometimes claimed that these symptoms are a manifestation of a disrupted autonomic nervous system. Prior works studying this claim from the complex adaptive systems perspective, have observed a lower average complexity of physical activity patterns in chronic fatigue syndrome patients compared to healthy controls. To further study the robustness of such methods, we investigate the within-patient changes in complexity of activity over time. Furthermore, we explore how these changes might be related to changes in patient functioning.MethodsWe propose an extension of the allometric aggregation method, which characterises the complexity of a physiological signal by quantifying the evolution of its fractal dimension. We use it to investigate the temporal variations in within-patient complexity. To this end, physical activity patterns of 7 patients diagnosed with chronic fatigue syndrome were recorded over a period of 3 weeks. These recordings are accompanied by physicians’ judgements in terms of the patients’ weekly functioning.ResultsWe report significant within-patient variations in complexity over time. The obtained metrics are shown to depend on the range of timescales for which these are evaluated. We were unable to establish a consistent link between complexity and functioning on a week-by-week basis for the majority of the patients.ConclusionsThe considerable within-patient variations of the fractal dimension across scales and time force us to question the utility of previous studies that characterise long-term activity signals using a single static complexity metric. The complexity of a Chronic Fatigue Syndrome patient’s physical activity signal does not suffice to characterise their high-level functioning over time and has limited potential as an objective monitoring metric by itself.

Modeling post-Pleistocene megafauna extinctions as complex social-ecological systems

Abstract The role of human hunting behavior versus climate change in the mass extinction of megafauna during the Late Quaternary is much debated. To move beyond monocausal arguments, we treat human–megafauna–environment relationships as social–ecological systems from a complex adaptive systems perspective, to create an agent-based model that tests how human hunting may interact with environmental stress and animal life history to affect the probability of extinction. Using the extinction of Syncerus antiquus in South Africa at 12–10 ka as a loose inspirational case study, we parameterized a set of experiments to identify cross-feedbacks among environmental dynamics, prey life history, and human hunting pressure that affect extinction probability in a non-linear way. An important anthropogenic boundary condition emerges when hunting strategies interrupt prey animal breeding cycles. This effect is amplified in patchy, highly seasonal environments to increase the chances of extinction. This modeling approach to human behavior and biodiversity loss helps us understand how these types of cross-feedback effects and boundary conditions emerge as system components interact and change. We argue that this approach can help translate archaeological data and insight about past extinction for use in understanding and combating the current mass extinction crisis.

An Exploration of Dutch Dermatologists’ Experience and Satisfaction with Teledermatology: A Sociotechnical and Complex Adaptive System Perspective (Preprint)

An Exploration of Dutch Dermatologists’ Experience and Satisfaction with Teledermatology: A Sociotechnical and Complex Adaptive System Perspective (Preprint)

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.

Understanding response to perturbations in collaborative projects from a complex generative and adaptive systems perspective

Continuity in collaborative projects may be affected by perturbations originated by unknown or unexpected situations. This research addresses the knowledge gap related to how teams effectively overcome disruptions in collaborative projects in order to reach resilience. The study explores the relationships amongst three interconnected constructs— equivocality, governance, and interorganizational learning— as key factors to be considered during perturbations.A systemic perspective using the lenses of complex adaptive and generative systems (complexity theory) has been approached. Using a cross-case analysis, the research's contribution is summarized through a model that offers explanations into how a successful case (the LOCUTIOS project) overcame effectively two instances of perturbations, within a high-uncertainty context.The model proposes two different reaction patterns, characterized by different learning behaviours (adaptive or generative), governance approaches (complementarity or substitution), and role of equivocality (driver or barrier) to knowledge exploration. Highlights of various forms of resilience within collaborative projects when unknown unknowns arise were exposed.

Yönetişim ile İnsani Gelişmişliğin Sürdürülebilirliği: Ülkelerin Nitel Karşılaştırmalı Analizi

This study examines the sustainability of human development through various governance configurations using a qualitative comparative analysis of countries from a complex adaptive systems perspective. The World Bank's six governance dimensions are used, and 11 unique configurations are identified for different levels of human development. The research reveals that the relationship between governance and human development is complex and context-specific, with different governance models contributing to different outcomes. The results suggest that a universal governance approach is not effective in promoting human development, and it is crucial to customize policy interventions based on the specific governance dynamics of each country. This study contributes to the existing literature on the significance of governance in the context of sustainable development and highlights the need for tailored strategies that consider the intricate relationship between different governance dimensions to effectively promote sustainable human development.

The Interplay Between Supply Chain Resilience and Climate Change

Supply chains – a web of organisations and actors from raw material to consumption – are no longer linear; they instead make up a network of interconnected and overlapping global suppliers. Simultaneously, climate change has become one of, if not the greatest challenge of the modern world, materialised by increasing temperatures and sea levels, and intensified extreme weather events. This era of increased turbulence needs new ways of thinking to build resilience strategies in the face of such disruptions. Supply chain resilience (SCR) strategies have typically been based on an equilibrium-seeking system whereby the goal is to bounce back to the pre-disruption state or bounce forward to a better state. This research borrows the Complex Adaptive Systems (CAS) perspective which acknowledges the environment as a continuously evolving system that responds to multiscale interactions and feedback between different actors. This CAS perspective of SCR seeks to maintain the core functionality by adapting, evolving, and transforming to the dynamic environment. This research aims to explore the interrelationship between SCR and climate change across multiple temporal and spatial scales through multiple case studies. In this presentation, I will display initial findings from the pilot study focusing on three cases of New Zealand multinationals. These findings are formed exclusively through secondary data collected from case study, company reports and documents, press releases and databases, which will later be used to complement interviews and focus groups with companies’ executives. I will demonstrate how increased collaboration and agility along the supply chain is needed in the face of increasing climate related disruptions. Given that supply chain interactions are a major contributor to climate change, this presentation also intends to explore ways in which supply chains can operate more sustainability as part of a continuously evolving process of resiliency.

Blockchain implementation and shareholder value: a complex adaptive systems perspective

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).

A bottom-up approach for community load prediction based on multi-agent model

Accurate prediction of community load is a prerequisite for community-scale demand matching and energy management. However, community-scale load prediction methods are challenging in characterizing complex energy-use scenarios caused by different building types and complicated occupant behaviors. The occupant behavior is the primary source of discrepancy between the predicted and realistic building performance, and this discrepancy will further widen on the community scale. This paper established the community occupant agent model (COAM) to generate occupancy data. The model delineates the agent system boundary from the perspective of complex adaptive systems (CAS). Anylogic was used to randomize and represent the decision behavior of community occupants. The bottom-up community building energy modeling (CBEM) workflow was applied to the case community of Xi'an (China). The measured and simulated values of the community building occupancy were compared, indicating the model's ability to reflect the interactions between single occupants and community building. The case community heating loads under different heating patterns were analyzed, and the workflow performance was evaluated. The proposed method might guide the district energy system to formulate the management strategy in the energy planning stage.

A Hybrid Modelling Framework for E-Commerce Supply Chain Simulation: Complex Adaptive Systems Perspective

A Hybrid Modelling Framework for E-Commerce Supply Chain Simulation: Complex Adaptive Systems Perspective

Navigating Turbulent Environments: Exploring Resilience in SMEs through Complex Adaptive Systems Perspective

This study seeks to explore how owner–managers of small and medium-sized enterprises navigate a constantly changing and turbulent environment following a traumatic experience and how they build resilience in their organizations by drawing upon memories through a complex adaptive system lens. Specifically, this study investigates the major factors shaping the management strategies of SMEs operating in the infrastructure construction sector in North Cyprus, where foreign aid/the patron country is the primary source of financing and therefore the major driver of strategies. To gather primary data, semistructured interviews were conducted with owner–managers of grade 1 construction SMEs, who can participate in internationally financed public projects. A qualitative approach using thematic analysis was adopted, and findings indicate that the most influential factor shaping the management strategies of SMEs in North Cyprus is the macro characteristics of the sociopolitical environment. These characteristics evoke memories for owner–managers and lead to a dissipative approach towards managing their SMEs, creating resilience in the face of North Cyprus’ ever-changing political environment.

Correction: An artificial intelligence-driven learning analytics method to examine the collaborative problem-solving process from the complex adaptive systems perspective

Correction: An artificial intelligence-driven learning analytics method to examine the collaborative problem-solving process from the complex adaptive systems perspective

Heat-as-a-Service (HaaS): a Complex Adaptive Systems perspective on servitization

Servitization increases uncertainty and complexity in manufacturing firms by introducing dynamic interdependencies within and between organisations. This study proposes the conceptual lens of Complex Adaptive Systems (CAS) to frame manufacturers’ service delivery systems and a hybrid simulation approach to explore the dynamic interdependencies of their servitization journeys. The case of a boiler manufacturer transforming to a provider of Heat-as-a-Service (HaaS) is used to examine the dynamic interdependencies between the growth of a service business, digitalisation efforts and operational efficiency as well as the interaction between the emerging service- and existing product business. The findings indicate that the manufacturer will experience an initial ‘cost-shock’ which will significantly decline as service delivery optimises and diagnostic accuracy improves. The study contributes to the servitization literature by introducing CAS as a theoretical perspective and hybrid modelling as a practical approach to explore and reconcile the strategic and operational dimensions of servitization.

Sustaining school improvement initiatives: advice from educational leaders

ABSTRACT There are reports about school improvement initiatives that have been successfully implemented and evaluated within relatively brief time scales. However, many initiatives do not survive over longer terms. Our purpose in this study was to identify successful strategies for achieving long-term school improvement. We interviewed 12 leaders at four educational sites. We adopted complex adaptive systems perspectives to analyse the interview transcripts, provide rich descriptions of contexts, illustrate examples of practices, and synthesise participants’ accounts to highlight key areas for attention and action. Participants described purposeful programme selection with clear goals, strategic staff leadership and continuous professional education, accountable professional networks, data sharing and feedback, time and resource management, distributed multilevel leadership, and a supportive school culture. We recommend adopting a complex adaptive systems perspective to communicate and facilitate processes of change, including planning, enacting, and evaluating school improvement as a continuous long-term process rather than as an end product of any singular initiative.

An artificial intelligence-driven learning analytics method to examine the collaborative problem-solving process from the complex adaptive systems perspective

Collaborative problem solving (CPS) enables student groups to complete learning tasks, construct knowledge, and solve problems. Previous research has argued the importance of examining the complexity of CPS, including its multimodality, dynamics, and synergy from the complex adaptive systems perspective. However, there is limited empirical research examining the adaptive and temporal characteristics of CPS, which may have led to an oversimplified representation of the real complexity of the CPS process. To expand our understanding of the nature of CPS in online interaction settings, the present research collected multimodal process and performance data (i.e., speech, computer screen recordings, concept map data) and proposed a three-layered analytical framework that integrated AI algorithms with learning analytics to analyze the regularity of groups’ collaboration patterns. The results surfaced three types of collaborative patterns in groups, namely the behaviour-oriented collaborative pattern (Type 1) associated with medium-level performance, the communication-behaviour-synergistic collaborative pattern (Type 2) associated with high-level performance, and the communication-oriented collaborative pattern (Type 3) associated with low-level performance. This research further highlighted the multimodal, dynamic, and synergistic characteristics of groups’ collaborative patterns to explain the emergence of an adaptive, self-organizing system during the CPS process. According to the empirical research results, theoretical, pedagogical, and analytical implications were discussed to guide the future research and practice of CPS.