The Shape of Change

2021 ◽  
pp. 49-75
Author(s):  
Manish Arora ◽  
Paul Curtin ◽  
Austen Curtin ◽  
Christine Austin ◽  
Alessandro Giuliani
Keyword(s):  
Human Physiology ◽  
Environmental Medicine ◽  
Complex Systems ◽  
System Dynamics ◽  
Functional Perspective ◽  
Constant Change

Chapter 3 introduce the first central principle of Environmental Biodynamics—that complex systems cannot interact directly, nor exist in isolation. It also introduces the corollary principle that although the interface is composed of constant change (i.e., processes) it retains a quantifiable topography—the shape of change—driven by stochastic, deterministic, or chaotic processes. The implication of this, from the perspective of environmental medicine, is that the environment and human physiology are integrated via an interface. An interface emerges wherever the measurement of one system’s state intrinsically includes inputs from another system. And thus, to understand how the environment influences us, and vice versa, environmental medicine must adopt a functional perspective that focuses on the organization of system dynamics and complexity. This is achieved by characterizing the deterministic, stochastic, and chaotic processes that shape environmental homeostasis.

A system dynamics model for near-miss reporting in complex systems

2021 ◽  
Vol 142 ◽  
pp. 105368
Author(s):  
Nikhil Bugalia ◽  
Yu Maemura ◽  
Kazumasa Ozawa
Keyword(s):  
Complex Systems ◽  
System Dynamics ◽  
Near Miss ◽  
System Dynamics Model ◽  
Dynamics Model

scholarly journals Using community-based system dynamics modeling to understand the complex systems that influence health in cities: The SALURBAL study

2019 ◽  
Vol 60 ◽  
pp. 102215 ◽  
Author(s):  
Brent A. Langellier ◽  
Jill A. Kuhlberg ◽  
Ellis A. Ballard ◽  
S. Claire Slesinski ◽  
Ivana Stankov ◽  
...  
Keyword(s):  
Complex Systems ◽  
System Dynamics ◽  
System Dynamics Modeling ◽  
Dynamics Modeling ◽  
Community Based

The Lens of “Thingness”

2021 ◽  
pp. 22-48
Author(s):  
Manish Arora ◽  
Paul Curtin ◽  
Austen Curtin ◽  
Christine Austin ◽  
Alessandro Giuliani
Keyword(s):  
Human Physiology ◽  
Temporal Dynamics ◽  
Source Code ◽  
Building Blocks ◽  
Dynamic Processes ◽  
Medical Sciences ◽  
Human Environment ◽  
Human Organs ◽  
Functional Perspective ◽  
Perceived Importance

Environmental medicine and related fields have developed from a structural perspective that assigns a static, anatomical “thingness” to our physiology and our environment. This viewpoint arises from a reductionist school of thought and foundational biomedical discoveries such as the discovery that human organs are made up of cells organized as tissues or that our DNA is the source “code” for the building blocks of life. As a consequence of these discoveries and their perceived importance, medical sciences have organized the study of the human body into the study of component parts. Attempts to incorporate time into existing structural perspectives have often taken the form of multiple structural analyses laced together as a circuit operating in a series of connections. Such approaches ignore that humans and their environment are temporally dynamic processes. Environmental Biodynamics argues for a functional perspective that rejects the reductionist view of human physiology and the human environment. In stark contrast to the prevalent structural paradigms, this approach places temporal dynamics at its core.

Environmental Biodynamics

2021 ◽  
Author(s):  
Manish Arora ◽  
Paul Curtin ◽  
Austen Curtin ◽  
Christine Austin ◽  
Alessandro Giuliani ◽  
...  
Keyword(s):  
Complex System ◽  
Human Physiology ◽  
Complex Systems ◽  
Boundary Conditions ◽  
Information Exchange ◽  
Temporal Dynamics ◽  
Health Sciences ◽  
Environmental Health Sciences ◽  
System Information

The book provides a new conceptual framework to explain the interaction of complex systems, specifically humans and their environment. It proposes that human physiology and the environment do not “connect” with each other in a direct, unidirectional manner, like a beaker pouring water into a cup. Rather, the authors propose the Biodynamic Interface Conjecture with the central axiom that complex systems cannot interact directly or exist in isolation due to temporally embedded functional interdependencies within and between systems. The authors propose that human physiology and the environment contribute to the formation of an interface, and by doing so they give rise to an intermediary that guides the interaction by letting some influences pass between the systems while restricting others. This proposition counters many structural approaches that assume that complex systems, such as the environment and humans, can transfer information directly between them while remaining discrete entities. Although developed for environmental health sciences, the conjecture has broader implications for the study of complex system interactions across various levels of organization, and the central role of time and temporal dynamics in system-to-system information exchange. This conjecture also argues against causal paradigms that (incorrectly) assume that systems are distinct entities interacting directly and ignore boundary conditions, and organizational levels, and complexity inherent in biological and environmental systems.

Systems approach to complex systems modelling with special regards to tourism

Kybernetes ◽  
2006 ◽  
Vol 35 (7/8) ◽  
pp. 1048-1058 ◽  
Author(s):  
Tadeja Jere Lazanski ◽  
Miroljub Kljajić
Keyword(s):  
Complex Systems ◽  
System Dynamics ◽  
Systems Approach ◽  
Quantitative Model ◽  
Point Of View ◽  
Verbal Description ◽  
Content Type ◽  
Qualitative Models ◽  
Complex Systems Modelling ◽  
Global And Local

PurposeThe importance of context dependent modelling of complex systems, depending on the observer's point of view will be discussed. Thus, context is synonymous for the content of a problem in a frame of the goals, starting points and ways to achieve these aims. In this light, difficulties of model validation and a general method how to overcome them was discussed. The relations among subject – object – model in the light of a systems approach; Charles Sanders Peirce's triad principle and the semiotic principle of communication was presented.Design/methodology/approachThe appropriateness of a system dynamics methodology, which is due to its transparency and clarity an excellent tool for modelling of complex systems.FindingsIn the paper the equivalence of different methodologies was shown, whose differences and similarities can be judged only in context of a problem and the aims of researches. For illustration, the methodology is applied to a tourism system, which possesses the typical properties of global and local organisations. A verbal description of a tourism problem is followed by a causal loop diagram, which helps to discuss the problem categorically.Practical implicationsAs the methodology is implemented using quantitative model and POWERSIM tools; it offers the solution of national tourism strategy implication, selected from different scenarios.Originality/valueThis paper presents a simulation model of the tourism in a frame of system dynamics, developed from qualitative models, as an illustration of the discussed methodology.

Policy boomerang in technical education: a system dynamics perspective

2017 ◽  
Vol 14 (2) ◽  
pp. 143-161 ◽  
Author(s):  
Lalit Upadhayay ◽  
Prem Vrat
Keyword(s):  
Complex Systems ◽  
System Dynamics ◽  
Education System ◽  
Technical Education ◽  
Causal Structure ◽  
Content Type ◽  
Long Term Stability ◽  
Boomerang Effect ◽  
Stable Growth ◽  
Collapse Behavior

Purpose The Indian technical education has experienced an exponential growth since 1995. However, the technical education system was not able to sustain it and the enrollments, particularly in engineering, fell down considerably. The purpose of this paper is to analyze the growth of Indian technical education from system dynamics (SD) perspective. Design/methodology/approach Technical education is a complex system in which the outcome of a decision comes with a third order delay. SD is an appropriate tool to analyze the causal structure and behavior of complex systems. This study developed an analogy from the physics of a boomerang to do the comparative assessment of “sudden overshoot and collapse” phase in the growth of Indian technical education. Further, it compared the technical education growth with the Gartner hype cycle. The growth model of Indian technical education was developed using SD software STELLA (version 10.0). Findings The model was simulated for five different policy scenarios. The outcome of the SD analysis shows that the “goal-seeking behaviour,” which produces stable growth without hampering quality, is the best proposition amongst all scenarios considered in the study. It identifies policies which will enable long-term stability in the Indian technical education system as well as policies which will lead to perpetual instability in the system. Research limitations/implications The study conducted will encourage researchers to use SD in analyzing complex systems for sustainability and in the selection of appropriate policies. Originality/value The paper uses boomerang analogy for analyzing the growth in engineering enrollments and highlights the presence of “the boomerang effect,” a term coined by the authors for sudden overshoot and collapse behavior, in the causal structure which is injurious to the education system.

scholarly journals The technology of using fuzzy cognitive maps from a mathematical point of view

2021 ◽  
pp. 1-22
Author(s):  
Yuri Germanovich Rykov
Keyword(s):  
Complex Systems ◽  
System Dynamics ◽  
Cognitive Maps ◽  
Cognitive Map ◽  
Point Of View ◽  
Fuzzy Cognitive Maps ◽  
Generalized System ◽  
Computational Procedures ◽  
The Relationship ◽  
Theoretical Results

A broader view of the technology of fuzzy cognitive maps is described, in which the cognitive map is considered as a carrier of computational procedures. This approach can be described as a generalized system dynamics. This interpretation makes it easier to obtain theoretical results that can characterize the behavior of complex systems. In particular, in the case of simple computational procedures, the relationship between the degree of influence of factors and the structure of the system, namely, the presence of connecting paths and cycles in the corresponding digraph, is clarified.

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