Complex Adaptive Systems Framework Research Articles

CO-EVOLUTIONARY DYNAMICS OF FINANCIAL INCLUSION OF GENERATION Z IN A SUB-SAHARAN DIGITAL FINANCIAL ECOSYSTEM

The growing digital consumerism in modern society is associated with higher expectations of customer experience, and as such the business environment is expected to co-evolve by developing more consumer-centric, sharing-based and fastpaced business models. This calls for deeper understanding of consumer aspirations and preferences in a given local context. Therefore, this paper explores the co-evolutionary dynamics of digital financial inclusion of Generation Z against a backdrop of limited understanding of the dynamic complexity of the financial business environment in the digital age. A case study of a digital financial ecosystem in Zambia within sub-Saharan Africa is then employed herein to reveal the co-evolutionary dynamics of financial inclusion of Generation Z within the framework of complex adaptive systems. For this purpose, a system dynamics modelling tool of Causal loop analysis is used to visualise the co-evolutionary dynamics. The paper has demonstrated that digital financial inclusion occurs within a continuum of co-evolutionary dynamics in which the financial institutions build consumer demand for digital financial services based on the participatory accountability and financial capability of the clientele. The paper concludes that digital financial inclusion is an emergent outcome of the complex adaptive behaviour of a financial business ecosystem in the increasingly digitising society. Therefore, development of inclusive financial business models must embrace the digital consumerism of the clientele, particularly in sub-Saharan Africa where there is a demographic boom of Generation Z with a growing propensity for digital consumerism.

Rethinking organizational change in the COVID-19 era

: Planned organizational change has a long history in formal organizations of all types. A model of planned organizational change from the existing literature can be used to identify a set of principles which can be offered for use during the current COVID-19 crisis, but this traditional model may not be fully adequate during this especially challenging period. A relatively new model from the field of complexity theory for organizations, Complex Adaptive Systems (CAS), offers promise for addressing the unique crisis conditions facing hospitals in the COVID-19 era. These conditions require constant assessment; ongoing high levels of communication; and iterative cycles of experimentation, reflection and learning, which can be better addressed in a CAS framework. Healthcare providers are experiencing periods of relative calm and interspersed crisis, which need to be proactively recognized and managed through sustained, “big picture” changes using timely combinations of traditional methods, complexity approaches, with the flexibility and ethical considerations of crisis management strategies built in. Successful crisis management requires leadership skills of those involved in decision-making at the local level, with a preference for the use of inclusive and adaptive leadership styles. Innovative strategies, teamwork, and crisis management models that have recently emerged may enable deeper systemic change in the long term. Any hospital or program in a healthcare system should be able to use this material to address a significant organizational change need.

Complex Adaptation in Audio Feedback Networks for the Synthesis of Music and Sounds

AbstractThis article presents recent outcomes of the author's research on musical complex adaptive systems (CASs). The first part focuses on the concepts of adaptation and complexity within the framework of CASs and suggests a rigorous placing of the concepts within the musical domain. This analysis involves a distinction of the notions of context and information between the engineering field of information theory and the philosophical one of radical constructivism. I conclude this section by showing that, in this approach, information and context are mutually determining.Then, I introduce a technique related to the notion of evolvability in biology and genetic algorithms and that has significantly increased the complexity and long-term variety in music systems during autonomous evolutions. This technique distributes adaptation across higher levels and allows the system to reorganize the relationships among its agents and their structure circularly while interpreting and constructing its context.To conclude, an autonomous live performance piece from 2019–2020, “Constructing Realities (Homage to Heinz von Foerster),” which implements the theories mentioned above, is described, showing DSP processes and techniques that relate to evolvability, autopoiesis, fitness, and complexity through agent-based modeling. This article is accompanied by a companion article discussing the technical aspects of information processing algorithms, which are an essential part for the implementation of music CASs: “Time-Domain Adaptive Algorithms for Low- and High-Level Audio Information Processing.”

Challenges, trust and performance in virtual teams: examining the role of openness to experience and preference for virtual teams

Purpose Building on the complex adaptive systems (CAS) framework, this paper aims to investigate the detrimental effect of virtual teams’ (VTs) challenges and the upholding role of trust on the members’ ratings of VTs’ performance. Also, the study examines the mediating role of the preferences for VTs and investigates the moderating function of the openness to experience personality trait on the relationship between challenges, trust and preference for VTs. Design/methodology/approach Cross-sectional survey data were collected from a sample of 498 university students in Romania and path analysis was used for data analysis. Findings The results show evidence of the harmful effect of VTs’ challenges on members’ ratings of VTs’ performance and reveal that trust boosts members’ ratings of VTs’ performance. The findings highlight the mediating role of members’ preference for VTs and show evidence that the openness to experience personality trait strengthens the negative effect of the challenges on members’ preference for VTs. Research limitations/implications Given the cross-sectional design of the study, inferences regarding the causal relationship between the variables cannot be made, and further longitudinal research is called for. Originality/value The study builds on the CAS framework and addresses the call for research to explore the variables that might contribute or impede VTs’ performance.

A complex systems perspective of news recommender systems: Guiding emergent outcomes with feedback models.

Algorithms are increasingly making decisions regarding what news articles should be shown to online users. In recent times, unhealthy outcomes from these systems have been highlighted including their vulnerability to amplifying small differences and offering less choice to readers. In this paper we present and study a new class of feedback models that exhibit a variety of self-organizing behaviors. In addition to showing important emergent properties, our model generalizes the popular “top-N news recommender systems” in a manner that provides media managers a mechanism to guide the emergent outcomes to mitigate potentially unhealthy outcomes driven by the self-organizing dynamics. We use complex adaptive systems framework to model the popularity evolution of news articles. In particular, we use agent-based simulation to model a reader’s behavior at the microscopic level and study the impact of various simulation hyperparameters on overall emergent phenomena. This simulation exercise enables us to show how the feedback model can be used as an alternative recommender to conventional top-N systems. Finally, we present a design framework for multi-objective evolutionary optimization that enables recommendation systems to co-evolve with the changing online news readership landscape.

EXPLORING BLENDED LEARNING RELATIONSHIPS IN HIGHER EDUCATION USING A SYSTEMS-BASED FRAMEWORK

The adoption of a blended learning approach is increasing among higher education institutions with a significant amount of research that focuses on linear relationships. However, there is limited research on how the blended learning environment functions and interacts as a complex system. There is a need for more research that explores the relationships that exist within a blended learning environment using a system-based framework, such as the Complex Adaptive Blended Learning Systems (CABLS) framework. The purpose of this qualitative phenomenological study was to explore the perceived relationships that exist within the CABLS in a higher education blended learning environment. Interviews were conducted with the learner, teacher, institutional administrators, and learning support staff. A thematic analysis was used to identify themes to better understand stakeholder relationships within the CABLS framework. The results of this study seek to provide all stakeholders with a better understanding of the complex interdependent relationships within the CABLS framework to optimize a collaborative approach to blended learning.

A systematic assessment on COVID-19 preparedness and transition strategy in Bangladesh.

Rationale, aims, and objectivesThe COVID‐19 pandemic of 2020 has overpowered the most advanced health systems worldwide with thousands of daily deaths. The current study conducted a situation analysis on the pandemic preparedness of Bangladesh and provided recommendations on the transition to the new reality and gradual restoration of normalcy.MethodA complex adaptive system (CAS) framework was theorized based on four structural dimensions obtained from the crisis and complexity theory to help evaluate the health system of Bangladesh. Data sourced from published reports from the government, non‐governmental organizations, and mainstream media up to June 15, 2020 were used to conduct a qualitative analysis and visualize the spatial distribution of countrywide COVID‐19 cases.ResultsThe findings suggested that Bangladesh severely lacked the preparedness to tackle the spread of COVID‐19 with both short‐ and long‐term implications for health, the economy, and good governance. Absence of planning and coordination, disproportionate resource allocations, challenged infrastructure, adherence to bureaucratic delay, lack of synchronized risk communication, failing leadership of concerned authorities, and incoherent decision‐making have led to a precarious situation that will have dire ramifications causing many uncertainties in the coming days.ConclusionsImplementation of response protocols addressing the needs of the community and the stakeholders from the central level is urgently needed. The development of mechanisms for dynamic decision‐making based on regular feedback and long‐term planning for a smooth transition between the new reality and normalcy should also be urgently addressed in Bangladesh.

Improving quality in a complex primary care system-An example of refugee care and literature review.

Applying traditional industrial quality improvement (QI) methodologies to primary care is often inappropriate because primary care and its relationship to the healthcare macrosystem has many features of a complex adaptive system (CAS) that is particularly responsive to bottom-up rather than top-down management approaches. We report on a demonstration case study of improvements made in the Family Health Center (FHC) of the JPS Health Network in a refugee patient population that illustrate features of QI in a CAS framework as opposed to a traditional QI approach. We report on changes in health system utilization by new refugee patients of the FHC from 2016 to 2017. We review the literature and summarize relevant theoretical understandings of quality management in complex adaptive systems as it applies to this case example. Applying CAS principles in the FHC, utilization of the Emergency Department and Urgent Care Center by newly arrived refugee patients before their first clinic visit was reduced by more than half (total visits decreased from 31%-14% of the refugee patients). Our review of the literature demonstrates that traditional algorithmic top-down QI processes are most often unsuccessful in improving even a few single-disease metrics, and increases clinician burnout and penalizes clinicians who care for vulnerable patients. Improvement in a CAS occurs when front-line clinicians identify care gaps and are given the flexibility to learn and self-organize to enable new care processes to emerge, which are created from bottom-up leadership that utilize existing interdependencies and interact with the top levels of the organization through intelligent top-down causation. We give examples of early adapters who are better applying the principles of CAS change to their QI efforts. Meaningful improvement in primary care is more likely achieved when the impetus to implement change shifts from top-down to bottom-up.

Challenges in Caring for Unbefriended Residents in Long-term Care Homes: A Qualitative Study.

This study examined challenges experienced by long-term care staff in caring for unbefriended residents who are incapacitated and alone. These residents often are estranged from or have no living family or live geographically distant from them and require a public guardian as their surrogate decision-maker. To date, research on unbefriended older adults has focused on those living in acute care and community settings. Little is known about those living in long-term care homes. We conducted semi-structured interviews with 39 long-term care staff (e.g., registered nurses, care aides, social workers) and 3 public guardians. Staff were sampled from seven long-term care homes in Alberta, Canada. We analyzed interview transcripts using content analysis and then using the theoretical framework of complex adaptive systems. Long-term care staff experience challenges unique to unbefriended residents. Guardians' responsibilities did not fulfill unbefriended residents' needs, such as shopping for personal items or accompanying residents to appointments. Consequently, the guardians rely on long-term care staff, particularly care aides, to provide increased levels of care and support. These additional responsibilities, and organizational messages dissuading staff from providing preferential care, diminish quality of work life for staff. Long-term care homes are complex adaptive systems. Within these systems, we found organizational barriers for long-term care staff providing care to unbefriended residents. These barriers may be modifiable and could improve the quality of care for unbefriended residents and quality of life of staff. Implications for practice include adjusting public guardian scope of work, improving team communication, and compensating staff for additional care.

Operational Networks: Adaptation to Extreme Events in China.

Natural hazards pose an increasing challenge to public administrators, as the frequency, costs, and consequences of extreme events escalate in a complex, interdependent, world. This study examines organizational networks as instruments for mobilizing collective response to extreme events, but effective design has been elusive. Governments have focused on planned networks to anticipate risk before hazards occur; communities have formed emergent networks as voluntary efforts after the event. Using a framework of complex adaptive systems, we identify operational networks that adapt to their immediate context in real time, using technologies to support the search, exchange, and feedback of information to enable informed, collective action. Applying mixed research methods-documentary analysis of laws, policies, and procedures; content analysis of news articles; onsite observation; and semistructured interviews with experienced personnel-we document operational networks as a distinct form of multiorganizational response to urgent events that combines the structure of designated authority with the flexibility of information technologies. The integration of planned and emergent organizational forms into operational networks is measured through External/Internal (E/I) index analysis, based on empirical data collected on response systems that formed following the 2008 Wenchuan and 2013 Lushan earthquakes in the centralized administrative context of China. Findings show that planned networks provide the organizational structure and initial legitimacy essential for operational networks to form, but ready access to information technology-cell phones, short-wave radio systems, internet access-enables rapid communication and exchange of information essential for flexible adaptation in real time to meet urgent needs.

Using complex adaptive systems theory to guide the transition to DNP nurse anesthesia education.

The opportunities and challenges when transitioning from a master's to DNP in nurse anesthesia education are complemented by using a complex adaptive system (CAS) theory to guide the curricula modifications. Major functional changes included reorganizing the curriculum to incorporate AACN DNP Essentials, COA competencies and integrating the scholarly work of a DNP improvement project. These changes were infused while balancing the intensive clinical requirements of a nurse anesthesia curriculum. Highlights in the DNP curriculum included the driving theory of complex systems, ethical values, leadership development, evidence-based practice and adaptation to emergent situations found in nurse anesthesia practice. Goals were to produce a DNP graduate that is more reliant on strategy and vision rather than only tasks or operations. Using the CAS framework enabled our program to transition and prepare DNP graduates to contribute to improved organizational effectiveness and understand the importance of leading change to positively impact patient outcomes.

The Dynamics of Change Following Extreme Events: Transition, Scale, and Adaptation in Systems Under Stress

Whether and how organizations adapt to risk in changing contexts is a perennial problem in public administration. We explore this problem in a comparative analysis of four hurricanes that struck the Gulf Coast in 2005 and 2008: Hurricanes Katrina and Gustav in Louisiana and Hurricanes Rita and Ike in Texas. We use a framework of complex adaptive systems to assess what changes facilitate this transition in disaster contexts and what conditions inhibit adaptation. Methods include content and network analysis, including the calculation of E/I index scores. Findings suggest that investment in information technology and training in Louisiana following a perceived poor response to Katrina in 2005 led to adaptive performance in Gustav in 2008 in Louisiana, whereas minimal change following a perceived credible response to Rita in 2005 led to slower adaptation in response to Ike in 2008 in Texas.

A complex adaptive system framework of barriers and facilitators to integrated care

The International Journal of Integrated Care (IJIC) is an online, open-access, peer-reviewed scientific journal that publishes original articles in the field of integrated care on a continuous basis.IJIC has an Impact Factor of 5.120 (2020 JCR, received in June 2021)

Anticipatory Care in Potentially Preventable Hospitalizations: Making Data Sense of Complex Health Journeys.

Purpose: Potentially preventable hospitalizations (PPH) are minimized when adults (usually with multiple morbidities ± frailty) benefit from alternatives to emergency hospital use. A complex systems and anticipatory journey approach to PPH, the Patient Journey Record System (PaJR) is proposed.Application: PaJR is a web-based service supporting ≥weekly telephone calls by trained lay Care Guides (CG) to individuals at risk of PPH. The Victorian HealthLinks Chronic Care algorithm provides case finding from hospital big data. Prediction algorithms on call data helps optimize emergency hospital use through adaptive and anticipatory care. MonashWatch deployment incorporating PaJR is conducted by Monash Health in its Dandenong urban catchment area, Victoria, Australia.Theory: A Complex Adaptive Systems (CAS) framework underpins PaJR, and recognizes unique individual journeys, their dependence on historical and biopsychosocial influences, and difficult to predict tipping points. Rosen's modeling relationship and anticipation theory additionally informed the CAS framework with data sense-making and care delivery. PaJR uses perceptions of current and future health (interoception) through ongoing conversations to anticipate possible tipping points. This allows for possible timely intervention in trajectories in the biopsychosocial dimensions of patients as “particulars” in their unique trajectories.Evaluation: Monash Watch is actively monitoring 272 of 376 intervention patients, with 195 controls over 22 months (ongoing). Trajectories of poor health (SRH) and anticipation of worse/uncertain health (AH), and CG concerns statistically shifted at a tipping point, 3 days before admission in the subset who experienced ≥1 acute admission. The −3 day point was generally consistent across age and gender. Three randomly selected case studies demonstrate the processes of anticipatory and reactive care. PaJR-supported services achieved higher than pre-set targets—consistent reduction in acute bed days (20–25%) vs. target 10% and high levels of patient satisfaction.Discussion: Anticipatory care is an emerging trajectory data analytic approach that uses human sense-making as its core metric demonstrates improvements in processes and outcomes. Multiple sources can provide big data to inform trajectory care, however simple tailored data collections may prove effective if they embrace human interoception and anticipation. Admission risk may be addressed with a simple data collections including SRH, AH, and CG perceptions, where practical.Conclusion: Anticipatory care, as operationalized through PaJR approaches applied in MonashWatch, demonstrates processes and outcomes that successfully ameliorate PPH.

Muddling through policymaking: A complex adaptive systems perspective on policy changes in a free maternal and child healthcare program in Enugu State, Nigeria.

Studies on the application of complex adaptive systems (CAS) framework to describe variations in free healthcare policies during implementation are limited. This study uses a CAS framework to explore interactions among actors and to explain how specific characteristics of CAS framework change in institutional designs of a Free Maternal and Child Healthcare Program (FMCHP) in Nigeria. A qualitative, case study approach was used to collect data on variations in features of FMCHP from policymakers (n = 16) and providers (n = 16) selected by purposeful sampling from the Ministry of Health and two health districts in Enugu State based on their posts in FMCHP, using semi-structured interview. Additional qualitative data were collected through document review. Main actors, their roles, incentives, and power were identified. Data were analyzed using thematic analysis guided by a CAS framework. Six core features of FMCHP changed during implementation, namely, revenue collection, the role of Ministry of Health, the role of the state teaching hospital, introduction of evidence of tax payment, provider payment process, and establishment of a Financial Monitoring Committee. Formal rules alone did not guarantee consistency and stability of policies. Power imbalances, coordination, and cooperation among actors affected fidelity of policy implementation. The CAS phenomena associated with these changes include path dependence, feedback, lever points, emergent behaviors, and phase transition. Managing changes in free healthcare policies requires recognizing the power shifts, nonlinearity of outcomes, unpredictable consequences and feedbacks, and addressing the context, adaptive behavior, and network of actors.

Emergent sustainability in open property regimes

Current theoretical models of the commons assert that common-pool resources can only be managed sustainably with clearly defined boundaries around both communities and the resources that they use. In these theoretical models, open access inevitably leads to a tragedy of the commons. However, in many open-access systems, use of common-pool resources seems to be sustainable over the long term (i.e., current resource use does not threaten use of common-pool resources for future generations). Here, we outline the conditions that support sustainable resource use in open property regimes. We use the conceptual framework of complex adaptive systems to explain how processes within and couplings between human and natural systems can lead to the emergence of efficient, equitable, and sustainable resource use. We illustrate these dynamics in eight case studies of different social–ecological systems, including mobile pastoralism, marine and freshwater fisheries, swidden agriculture, and desert foraging. Our theoretical framework identifies eight conditions that are critical for the emergence of sustainable use of common-pool resources in open property regimes. In addition, we explain how changes in boundary conditions may push open property regimes to either common property regimes or a tragedy of the commons. Our theoretical model of emergent sustainability helps us to understand the diversity and dynamics of property regimes across a wide range of social–ecological systems and explains the enigma of open access without a tragedy. We recommend that policy interventions in such self-organizing systems should focus on managing the conditions that are critical for the emergence and persistence of sustainability.

A review of agent-based modeling (ABM) concepts and some of its main applications in management science

We live in a very complex world where we face complex phenomena such as social norms and new technologies. To deal with such phenomena, social scientists often use reductionism approach where they reduce them to some lower-lever variables and model the relationships among them through a scheme of equations. This approach that is called equation based modeling (EBM) has some basic weaknesses in modeling real complex systems so that assumptions such as unbounded rationality and perfect information are strongly emphasized while adaptability and evolutionary nature of all engaged agents along with network effects go unaddressed. In tackling deficiencies of reductionism, the complex adaptive system (CAS) framework has been proven very influential in the past two decades. In contrast to reductionism, under CAS framework, complex phenomena are studied in an organic manner where their agents are supposed to be both boundedly rational and adaptive. As the most powerful methodology for CAS modeling, agent-based modeling (ABM) has gained a growing popularity among academics and practitioners. ABMs show how agents’ simple behavioral rules and their local interactions at micro-scale can generate surprisingly complex patterns at macro-scale. Despite a growing number of ABM publications, those researchers unfamiliar with it have to study a number of works to understand (1) why and what of ABM, (2) its differences with EBM (3) its main functionalities in scientific studies and (4) some of its applications in management science. So, this paper’s major contribution is to help researchers particularly those unfamiliar with ABM to get insights regarding its philosophy and use and gain a big picture of it.

Government resource contributions to the private-not-for-profit sector in Uganda: evolution, adaptations and implications for universal health coverage

BackgroundA case study was prepared examining government resource contributions (GRCs) to private-not-for-profit (PNFP) providers in Uganda. It focuses on Primary Health Care (PHC) grants to the largest non-profit provider network, the Uganda Catholic Medical Bureau (UCMB), from 1997 to 2015. The framework of complex adaptive systems was used to explain changes in resource contributions and the relationship between the Government and UCMB.MethodsDocuments and key informant interviews with the important actors provided the main sources of qualitative data. Trends for GRCs and service outputs for the study period were constructed from existing databases used to monitor service inputs and outputs. The case study’s findings were validated during two meetings with a broad set of stakeholders.ResultsThree major phases were identified in the evolution of GRCs and the relationship between the Government and UCMB: 1) Initiation, 2) Rapid increase in GRCs, and 3) Declining GRCs. The main factors affecting the relationship’s evolution were: 1) Financial deficits at PNFP facilities, 2) advocacy by PNFP network leaders, 3) changes in the government financial resource envelope, 4) variations in the “good will” of government actors, and 5) changes in donor funding modalities. Responses to the above dynamics included changes in user fees, operational costs of PNFPs, and government expectations of UCMB. Quantitative findings showed a progressive increase in service outputs despite the declining value of GRCs during the study period.ConclusionsGRCs in Uganda have evolved influenced by various factors and the complex interactions between government and PNFPs. The Universal Health Coverage (UHC) agenda should pay attention to these factors and their interactions when shaping how governments work with PNFPs to advance UHC. GRCs could be leveraged to mitigate the financial burden on communities served by PNFPs. Governments seeking to advance UHC goals should explore policies to expand GRCs and other modalities to subsidize the operational costs of PNFPs.

A complex adaptive systems governance framework for regional supply networks

PurposeThis paper aims to propose an empirically grounded governance framework based on complex adaptive systems (CAS) principles to facilitate formation of well-connected regional supply chains that foster economic development, adaptability and resilience of mining regions.Design/methodology/approachThis study is an exploratory case study of the South Australian (SA) mining industry that includes 38 semi-structured interviews with the key stakeholders and structural analysis of the regional supply network (RSN).FindingsFindings demonstrate the applicability of the CAS framework as a structured approach to the governance of the mining industry regional supply chains. In particular, the findings exemplify the relationship between RSN governance, its structure and interconnectivity and their combined impact on the adaptability and resilience of mining regions.Research limitations/implicationsThe data set analysed in the current study is static. Longitudinal data would permit a deeper insight into the evolution of the RSN structure and connectivity. The validity of the proposed framework could be further strengthened by being applied to other industrial domains and geographical contexts.Practical/implicationsThe proposed framework offers a novel insight for regional policy-makers striving to create an environment that facilitates the formation of well-integrated regional supply chains in mining regions through more focussed policy and strategies.Originality/valueThe proposed framework is one of the first attempts to offer a holistic structured approach to governance of the regional supply chains based on CAS principles. With the current transformative changes in the global mining industry, policy-makers and supply chain practitioners have an urgent need to embrace CAS and network paradigms to remain competitive in the twenty-first century.

Aging and Evolution

Similar empirical patterns of behavior are found in seemingly very different fields which once put together account for a « big history » approach of aging and evolution. It is shown that known curves for the creep of metals, the reliability of industrial systems, the mortality and survival of biological entities, learning, the general adaptation syndrome, (neo-)Darwinian evolution and the expansion of the universe can be compared and allow to conceive a general adaptation framework of complex adaptive systems. Equations are proposed for four shapes of curves found in laboratory and/or observational practice which can then be transformed into each other in function of the properties to be put into evidence. An entropy production can be linked to the phenomena under scope. The « big history » approach allows to go from global to peculiar. It thus shows the importance of using the correct orders of magnitude for the involved parameters (time, stress, temperature, energy …) when analysing a specific phenomenon.