Methodology For Complex Systems Research Articles

Tourism and sustainable development: a bibliometric and complex systems methodology approach

ABSTRACT Tourism is a significant economic activity, but its complex relationships with the environment and natural resources raise concerns about sustainability. This study explores the interplay between natural, cultural, and social capital in sustainable tourism development systems (STDS) using a Complex Systems methodology, specifically Causal Loop Diagrams (CLD). The results demonstrate that tourism management and development can enhance sustainable development, but tourism's impact is mixed. Positive impacts include increased local economic development, cultural tourism, and protected areas. Negative impacts include increased environmental pollution, negative impact on indigenous culture, and a complex relationship with social capital. This systemic model contributes to formulating policies for sustainable economic development in tourist destinations. It highlights the need for integrated management approaches that balance economic, environmental, and social objectives.

Modeling vulnerability and intervention targets in the Borderline Personality Disorder system: A network analysis of in silico and in vivo interventions.

Modeling psychopathology as a complex dynamic system represents Borderline Personality Disorder (BPD) as a constellation of symptoms (e.g., nodes) that feedback and self-sustain each other shaping a network structure. Through in silico interventions, we simulated the evolution of the BPD system by manipulating: 1) the connectivity strength between nodes (i.e., vulnerability), 2) the external disturbances (i.e., stress) and 3) the predisposition of symptoms to manifest. Similarly, using network analysis we evaluated the effect of an in vivo group psychotherapy to detect the symptoms modified by the intervention. We found that a network with greater connectivity strength between nodes (more vulnerable) showed a higher number of activated symptoms than networks with less strength connectivity. We also found that increases in stress affected more vulnerable networks compared to less vulnerable ones, while decreases in stress revealed a hysteresis effect in the most strongly connected networks. The in silico intervention to symptom alleviation revealed the relevance of nodes related to difficulty in anger regulation, nodes which were also detected as impacted by the in vivo intervention. The complex systems methodology is an alternative to the common cause model with which research has approached the BPD phenomenon.

A qualitative, network-centric method for modeling socio-technical systems, with applications to evaluating interventions on social media platforms to increase social equality

We propose and extend a qualitative, complex systems methodology from cognitive engineering, known as the abstraction hierarchy, to model how potential interventions that could be carried out by social media platforms might impact social equality. Social media platforms have come under considerable ire for their role in perpetuating social inequality. However, there is also significant evidence that platforms can play a role in reducing social inequality, e.g. through the promotion of social movements. Platforms’ role in producing or reducing social inequality is, moreover, not static; platforms can and often do take actions targeted at positive change. How can we develop tools to help us determine whether or not a potential platform change might actually work to increase social equality? Here, we present the abstraction hierarchy as a tool to help answer this question. Our primary contributions are two-fold. First, methodologically, we extend existing research on the abstraction hierarchy in cognitive engineering with principles from Network Science. Second, substantively, we illustrate the utility of this approach by using it to assess the potential effectiveness of a set of interventions, proposed in prior work, for how online dating websites can help mitigate social inequality.

Applying situational analysis to examine the impact of VOICES on people experiencing multiple disadvantage

Purpose This paper reports the use of situational analysis as a systems methodology to evaluate the voices of independence change and empowerment in the Stoke-on-Trent (VOICES) partnership project. Design/methodology/approach Using situational analysis and drawing on a range of secondary data sources, a three-stage conceptual mapping process provided a detailed picture of both the non-linear interlinkage and complexity of the local system that VOICES was working to influence, as well as the processes that shaped the experiences of those who act within the situation. Findings Data highlighted the systemic challenges facing VOICES customers (e.g. stigma and marginalisation and lack of legal literacy), progress made by VOICES in each of their priority areas and an overarching theme of VOICES promoting equity (rather than equality) to address failure demand in the system of support for people with multiple needs and disadvantage. Originality/value The authors present the novel application of situational analysis to demonstrate a substantial impact of VOICES while demonstrating the value of this methodology for complex systems thinking research and evaluation.

A Network Perspective of the Ecosystem’s Health Provision Spectrum in the Tourist Trails of UNESCO Global Geoparks: Santo Sepulcro and Riacho do Meio Trails, Araripe UGG (NE of Brazil)

In this investigation, we formulated the Ecosystem’s Health Provision Spectrum and its centrality indicators, based on the identification of the Ecosystem Health Potentials and Opportunities on the trails of Santo Sepulcro and Riacho do Meio in the Araripe UNESCO Global Geopark (UGG), establishing a baseline for the promotion of green exercise and geotourism in the territory. Based on the network methodology for complex systems, we analyzed the closeness and strength of biotic, abiotic variables, nature phenomena, infrastructure, and sensory experiences in order to determine the configuration of these associations. In the Santo Sepulcro, regarding the association, two negative relations and two positive relations among the variables were highlighted; as for closeness and strength, Aquatic Diversity with the Scientific Values of Geodiversity stood out. In Riacho do Meio, we highlight three positive associations among the variables; as for connectivity, Biodiversity and Meteorological and Climate Exposure presented the highest values and, as for strength, the variables Biodiversity, Route Classification, and Aquatic Diversity were the most prominent. We conclude, based on the presented configuration, that the variables with greater connectivity act as hubs; if these variables are optimized, the network will present an acceptable theoretical configuration. However, neglecting central strength variables can cause the network to collapse.

Los sistemas complejos como herramienta para la sustentabilidad. Una visión desde la perspectiva de la Teoría Crítica.

The objective of the essay presented is to discuss the nature of the complex systems methodology as a useful tool for the analysis and management of sustainability. It is concluded that the construction of a model of complex socially sensitive systems is a pending and urgent objective to face the environmental collapse suffered by contemporary society.

Policy Modeling and Applications: State‐of‐the‐Art and Perspectives

The range of application of methodologies of complexity science, interdisciplinary by nature, has spread even more broadly across disciplines after the dawn of this century. Specifically, applications to public policy and corporate strategies have proliferated in tandem. This paper reviews the most used complex systems methodologies with an emphasis on public policy. We briefly present examples, pros, and cons of agent‐based modeling, network models, dynamical systems, data mining, and evolutionary game theory. Further, we illustrate some specific experiences of large applied projects in macroeconomics, urban systems, and infrastructure planning. We argue that agent‐based modeling has established itself as a strong tool within scientific realm. However, adoption by policy‐makers is still scarce. Considering the huge amount of exemplary, successful applications of complexity science across the most varied disciplines, we believe policy is ready to become an actual field of detailed and useful applications.

Development and Complex Dynamics at School Environment

In this work we use complex systems methodologies to analyze quantitatively the impact of an intervention involving cooperative and self-awareness activities on social interactions in children. The aim of this study is to evaluate behavioral plasticity of social relationships between peers in 6-7 year-olds who participated in the intervention conducted in a school context. The intervention consisted of 8 one-hour long sessions comprising mindfulness-based practices, collaborative activities that required cooperation, and perspective-taking instances in which children shared feelings, perceptions, and needs felt during the activities. We used complex network and game theory to evaluate pre-post-intervention variations. Social relationship was analyzed with a sociogram in both the intervention group and a control group which continued with regular classes. By means of the sociometric questionnaire we asked each child to mention which classmates he/she would choose as playmates and which he/she would not. Changes in the number of peers selected and rejected reflected changes in the pattern of social relationships pre-post-intervention. Our findings show that participating in the intervention positively modulated social interactions since we found an increase in the diversity and quality of positive links and a reduction in negative ones; a higher level of integration, indicated by enhanced positive networks where children with many positive connections tended to connect with those with few links; and more positive interactions between genders. These findings were not observed in the control group. Through the use of the mentioned methodologies, the current investigation provides new quantitative evidence of social network plasticity in children, an important topic which, to our knowledge, has been little studied. Results from this work indicate that positive transformations in social relationships can be fostered through the performance of this kind of intervention.

A new systems engineering structured assurance methodology for complex systems

As technology advances, systems behaviour becomes more difficult to predict and control, resulting in a lack of systems assurance across the supply chain. Here we describe a structured approach to address the assurance of complex systems developed and operated within highly regulated environments. The new approach is based on a methodology that can address both new and legacy systems, and influences system intervention. We propose an enterprise approach by observing the importance of all organisational contributions to a safe working system throughout the intended project life cycle. This research was catalysed by the need to address the certification of the F-35B stealth fighter for UK operations from 2012 onwards. We offer a pragmatic strategy to achieve systems control by adopting a holistic approach to systems engineering while promoting the development of an enabling environment that can determine system threats and enable appropriate controls. We propose a systematic coordination process to minimise the potential for ‘organisational drift’. This holistic approach to systems engineering and assurance is defined as ‘systems engineering structured assurance’. The methodology provides a confidence assessment for a particular product or system while remaining agnostic to regulatory constraints. The diligent completion of the methodology increases systems confidence and informs the regulatory environment.

Path defined directed graph vector (Pgraph) method for multibody dynamics

Dynamical modeling of complex systems may include multiple combinations of serial and tree topologies, as well as closed kinematic chain systems. Simulating of such systems is a costly task not only for run time but also for construction time when a model description and constraints are introduced. This paper presents a systematic framework of a construction time efficient modeling methodology for complex systems by introducing a path defined directed graph vector (\(\mathit{Pgraph}\)) and the associated methodology based on Linear Graph Theory (LGT). Updating of body coordinate frame vectors which can be a challenge in complex topology systems is easily performed using the proposed method. This technique is especially useful for systems changing topology, such as walking mechanisms where bilateral and unilateral constraints are conditionally embedded. Although this is a general methodology, to be combined with many dynamical modeling algorithms available in the literature, here we demonstrate it using Spatial Operator Algebra (SOA), which is a recursive algorithm based on the Newton–Euler formalism.

Expert views on applying complexity theory in evaluation: Opportunities and barriers

Interest in evaluating complexity appears to be on the rise. Increasing application of systems thinking and complex systems methodologies to evaluation can be seen in contents of journals and evaluation conferences. To date there has been little systematic examination of experiences of this application. This research considers the experience of 41 key informant participants with experience of complexity and systems approaches in evaluation. The results highlight institutional, political and social science factors that provide opportunities for further application. The following are identified as barriers to application: multiple definitions of complexity, the dominance of existing approaches, the purpose of evaluation and perception of resources required to apply complexity and systems approaches in evaluation. Where increasing the use of complexity and systems methodologies is a desired goal, this research suggests action regarding: how these methodologies are communicated; and evaluation training.

The Obesogenic Environment of Commercial Trucking: A Worksite Environmental Audit and Implications for Systems-Based Interventions

Background: Commercial trucker health is a vital public health concern. Enhanced understanding of the multiplicity, diversity, interdependence, and complexity of policies, resources, and stakeholders relevant to healthful living in trucking worksites can guide future interventions. Purpose: This article examines how the environmental attributes of commercial trucking worksites influence truck drivers' opportunities for healthful eating and active living and provides a preliminary discussion on how complexity science can help design more efficacious interventions. Methods: A 250-item audit instrument was used to measure the presence of corporate, social, and built environment attributes of 25 diverse trucking worksites that can influence food choices and physical activity of truckers. Results: Findings from truckstops, trucking terminals, warehouses, and highway rest areas along key transportation routes revealed that these worksites are severely burdened by structural and institutional barriers and essentially represent what can be called healthy living deserts. Discussion: Comprehensive interventions to address organizational barriers for health-supportive trucking worksites are critical because truck driver health has far-reaching ramifications for drivers and others. Translation to Health Education Practice: Because traditional worksite wellness programs for truckers have had limited success, the application of complex systems methodologies has an increased potential to advance high-leverage, sustainable intervention configurations.

A Review of Theoretical Perspectives in Cognitive Science on the Presence of 1/f Scaling in Coordinated Physiological and Cognitive Processes

Time series of human performances present fluctuations around a mean value. These fluctuations are typically considered as insignificant, and attributable to random noise. Over recent decades, it became clear that temporal fluctuations possess interesting properties, however, one of which the property of fractal 1/f scaling. 1/f scaling indicates that a measured process extends over a wide range of timescales, suggesting an assembly over multiple scales simultaneously. This paper reviews neurological, physiological, and cognitive studies that corroborate the claim that 1/f scaling is most clearly present in healthy, well-coordinated activities. Prominent hypotheses about the origins of 1/f scaling are confronted with these reviewed studies. It is concluded that 1/f scaling in living systems appears to reflect their genuine complex nature, rather than constituting a coincidental side-effect. The consequences of fractal dynamics extending from the small spatial and temporal scales (e.g., neurons) to the larger scales of human behavior and cognition, are vast, and impact the way in which relevant research questions may be approached. Rather than focusing on specialized isolable subsystems, using additive linear methodologies, nonlinear dynamics, more elegantly so, imply a complex systems methodology, thereby exploiting, rather than rejecting, mathematical concepts that enable describing large sets of natural phenomena.

Use of formal languages to consolidate a Holonic MAS methodology: a specification approach for analysing Problem and Agency domains

In complex systems, multiple aspects interact and influence each other. A vast number of entities are present in the system. Traditional modeling and simulation techniques fail to capture interactions between loosely coupled aspects of a complex distributed system. The objective of this work is to formalize and to specify a part of the Agent-oriented Software Process for Engineering Complex Systems methodology (Problem and Agency Domains) for modeling the holarchy of studied system by using a formal specification approch based on two formalisms: Petri Net and Object-Z language. Such a specification style facilitates the modeling of complex systems with both structural and behavioural aspects. Our generic approach is illustrated by applying it to FIRA Robot Soccer and is validated with the Symbolic Analysis Laboratory framework.

A new methodology for complex systems using n-dimensional finite elements

In this article a new methodology is developed, for the modelling of complex systems where the number of variables and relationships can be high. This methodology allows an efficient work on a n-dimensional hypercube and its computational implementation, a fact that was not possible through a generalisation of the 2-dimensional methodology developed in [10]. The methodology allows obtaining representation models of a function or relationship, z=u(x1,x2,...... ,xn) obtained from the interpolation defined in an n-dimensional finite element model. The interpolation function implies the use of some initial conditions, what in the defined methodology implies the coincidence between the values of the function in a finite number of points zi,xi^1,xi^2,xi^3,......,xi^ni=1,.2,...,p. As usually when a finite element model of representation is used, the function is obtained in a finite set of points, called nodes [22]. In this case, this is done by solving an optimisation problem based on the search of the minimum of an error function defined generically in any finite element model defined in the hypercube. The computational implementation of the methodology allows obtaining families of mathematical models that represent the relationships. From each obtained model several information parameters are also considered, as roughness and stability.

Assessing the human-environment relationship: a complex-systems methodology to modelling climate change

Climate change is at the forefront of scientific investigation and socio-political decision-making. The world community of scientists concur with the fact that human activities are both contributing to and affected by changes in the environment that influence the overall well-being of the world population. Importantly, these changes do not discriminate as to region or inhabitants. The body of research has measured climate change via modelling that incorporates the laws of physics and climate data. Neglected in these models is a significant factor: the global human population is increasing at an unprecedented rate that will further stress these geological and ecological variations. This research proffers a complex-systems modelling methodology for climate change to assess current and future concerns, intricately linked facets or pieces, of the human-environment relationship. It requires an interdisciplinary approach to research and model development that combines expertise from the social sciences and disciplines.

A complex systems methodology to transition management

There is a general sense of urgency that major technological transitions are required for sustainable development. Such transitions are best perceived as involving multiple transition steps along a transition path. Due to the path dependent and irreversible nature of innovation in complex technologies, an initial transition step along some preferred path may cut off paths that later may turn out to be more desirable. For these reasons, initial transition steps should allow for future flexibility, where we define flexibility as robustness regarding changing evidence and changing preferences. We propose a technology assessment methodology based on rugged fitness landscapes, which identifies the flexibility of initial transition steps in complex technologies. We illustrate our methodology by an empirical application to 2,646 possible future car systems.

Computational Shelf-Life Dating: Complex Systems Approaches to Food Quality and Safety

Shelf-life is defined as the time that a product is acceptable and meets the consumers expectations regarding food quality. It is the result of the conjunction of all services in production, distribution, and consumption. Shelf-life dating is one of the most difficult tasks in food engineering. Market pressure has lead to the implementation of shelf-life by sensory analyses, which may not reflect the full quality spectra. Moreover, traditional methods for shelf-life dating and small-scale distribution chain tests cannot reproduce in a laboratory the real conditions of storage, distribution, and consumption on food quality. Today, food engineers are facing the challenges to monitor, diagnose, and control the quality and safety of food products. The advent of nanotechnology, multivariate sensors, information systems, and complex systems will revolutionize the way we manage, distribute, and consume foods. The informed consumer demands foods, under the legal standards, at low cost, high standards of nutritional, sensory, and health benefits. To accommodate the new paradigms, we herein present a critical review of shelf-life dating approaches with special emphasis in computational systems and future trends on complex systems methodologies applied to the prediction of food quality and safety.

Bayesian Stockpile Reliability Methodology for Complex Systems

Bayesian Stockpile Reliability Methodology for Complex Systems

A Stochastic Concurrent Constraint Based Framework to Model and Verify Biological Systems


 
 
 Abstract
 Concurrent process calculi are powerful formalisms for modelling concurrent systems. The mathematical style underlying process cal- culi allow to both model and verify properties of a system, thus pro- viding a concrete design methodology for complex systems. ntcc , a constraints-based calculus for modeling temporal non-deterministic and asynchronous behaviour of processes has been proposed recently. Process interactions in ntcc can be determined by partial informa- tion (i.e. constraints) accumulated in a global store. ntcc has also an associated temporal logic with a proof system that can be conve- niently used to formally verify temporal properties of processes. We are interested in using ntcc to model the activity of genes in biological systems. In order to account for issues such as the basal rate of re- actions or binding affinities of molecular components, we believe that stochastic features must be added to the calculus. In this paper we propose an extension of ntcc with various stochastic constructs. We describe the syntax and semantics of this extension together with the new temporal logic and proof system associated with it. We show the relevance of the added features by modelling a non trivial biological system: the gene expression mechanisms of the λ virus. We argue that this model is both more elaborate and compact than the stochastic πcalculus model proposed recently for the same system.