Insight diagram
Environmental, social, and economic strategy integration for better business ideas
Insight diagram
This model illustrates the current practice and consequences of government spending. Following the direction of the arrows from right to left the model shows the following sequence based on current practice:

Government Spending at a certain point leads to spending in excess of tax receipts. This will automatically lead to the issue of treasuries in the belief that the excess spending must be financed by borrowing (although the government has the capacity to create  money). This in turn will increase the national debt.

 Consequences that follow from this practice:

1) That national debt increases whenever the government spends in excess of tax receipts.

2) That the government must pay interest on the debt issued, which in turn increases and reinforces the need for government spending.

3) That the interest paid on treasuries will increase private sector income.

There is an alternative view, supported by Modern Monetary Theory, of how government spending can proceed. Please see this  Insight: 

https://insightmaker.com/insight/19954

Government Spending (Current Practice)
Insight diagram
A Model for COVID-19 outbreak
AT3
Insight diagram
Causal loop representations of macroeconomics taken from the System Dynamics literature contrasted with Forrester's main analysis of social and business organization layers See also Saeed's Forrester Economics IM-183285
Macroeconomics causal loop diagrams
8 4 weeks ago
Insight diagram
Government and economic systems, and their effect on climate change
Insight diagram

This paper aims at describing a case where system dynamics modeling was used to evaluate the effects of information and material supply lead-time variation on sales contributions margins and operating cash conversion cycle of a commodity export business.  An empirical dynamic model, loaded with econometric theory of price effect on competitive demand, was used to describe the input data.  The model simulation outputs proved themselves relevant in analyzing the complex interconnections of multiple variables affecting  the profitability in a commercial routine, supporting the decision process among sales managers.

SDR Case study System dynamic modelling
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An initial study of the economics of single use coffee pods.
Helene D. Coffee Pod Investigation
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Description for Each Simulation Tag:

CRISIS:
- Price increasing dramatically, surpasses average detached home price of 3 million in 3 years if left unaddressed
- Housing Demand by potential buyer population will increase due to unmet financial means (Interest rate and price too high). To secure housing, the outflow is linked to price that is affected by supply and demand.
- Total occupied homes will decrease as empty homes purchased by foreign investors for "house flipping" increase and doubles within 5 years.

DEMAND:
-  Demand for housing in Vancouver will increase, but the amount of people motivated to buy with financial means "buyer population", will decrease in correlation.

SUPPLY:
- Prices do not follow traditional supply and demand concepts. Supply of houses on the market is increasing but, as shown, unable to sell because of unaffordability.

SYSTEMS MODEL LOGISTICS:
- Split into demand and supply with interlinked links
- Supply is a feedback system with sold houses branching off into empty housing or occupied housing
- All flows and stocks are linked with the intention that as market price changes, so will various system dynamics
- Used various functions to simulate a more diverse and accurate system

Sustainability: Economic (prices, housing market), Social (motivation to buy and sell)
Crisis Model - Vancouver Housing Crisis
Insight diagram

This model is designed for the local government of Burnie, Tasmania, aiming to help with balancing COIVD-19 and economic impacts during a possible outbreak. 

The model has been developed based upon the SIR model (Susceptible, Infected, Recovered) model used in epidemiology. 

It lists several possible actions that can be taken by the government during a COVID-19 outbreak and provide the economic impact simulation. 

The model allow users to Change the government policies factors (Strength of Policies) and simulate the total economic impact.

Interestingly, the government plicies largely help with controlling the COVID outbreak. However, the stronger the policies are, the larger impact on local economy

Burnie Covid Model, Zilin Huang 533476
Insight diagram
WFA4133 Graham-Schaefer model with variable F & Econmics
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State Goverment Fiscal Policy model
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Nobody seems to notice bubbles until they burst. One possible reason is that those caught up in a bubble are completely blinded by the grip, the overpowering logic and force excerted by the positive feedback loop that drives it. Financial bubbles occur time and time again - and nobody seems to learn. Another example on a different time scale is an argument that spins out of control and ends in violence. The participants seem to be blind to the consequences; the immediate and imperative logic of the feedback loop imposes itself. The vortex created by the feedback loop even seems to draw in outsiders, such as new investors. Is this the reason why we don't notice bubbles? This explanation is meant to stimulate discussion!

Bubbles and Feedback Loops
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The Logistic Map is a polynomial mapping (equivalently, recurrence relation) of degree 2, often cited as an archetypal example of how complex, chaotic behaviour can arise from very simple non-linear dynamical equations. The map was popularized in a seminal 1976 paper by the biologist Robert May, in part as a discrete-time demographic model analogous to the logistic equation first created by Pierre François Verhulst

Mathematically, the logistic map is written

where:

 is a number between zero and one, and represents the ratio of existing population to the maximum possible population at year n, and hence x0 represents the initial ratio of population to max. population (at year 0)r is a positive number, and represents a combined rate for reproduction and starvation.
For approximate Continuous Behavior set 'R Base' to a small number like 0.125To generate a bifurcation diagram, set 'r base' to 2 and 'r ramp' to 1
To demonstrate sensitivity to initial conditions, try two runs with 'r base' set to 3 and 'Initial X' of 0.5 and 0.501, then look at first ~20 time steps

The Logistic Map
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A system diagram for the Mojave Desert including example socio-economic factors for an assignment at OSU- RNG 341.
Mojave Desert System Diagram with SES
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Theory of Structural Change for IAMO Research Group


The part-whole paradigm

Examples of research issues addressed here include the path dependence of farm structures, regime shifts in land-system change, as well as transitional processes in the evolution of farm structures and innovation systems. All these issues feature counter-intuitive systemic properties that could not have been predicted using standard agricultural economics tools. The key strength of the research group in regard to the part-whole paradigm is the internationally renowned expertise in the agent-based modelling of agricultural policy. (More on what happened here until now / is happening now)

The system-environment paradigm

This paradigm is represented by conceptual research drawing inspiration from Niklas Luhmann’s theory of “complexity-reducing” and “operationally closed” social systems. The attributes of complexity reduction and operational closure are shown to generate sustainability problems, conflicts, social dilemmas, ethical issues, and divergent mental models. The organizing idea explaining these phenomena is the complexity-sustainability trade-off, i.e., the tendency of the operationally closed systems to develop excessive internal complexity that overstrains the carrying capacity of the environment. Until now, the conceptual work along these lines has focused on developing the systems-theoretic principles of ecological degradation and highlighted the sustainability-enhancing role of nonprofit organizations and corporate social responsibility. Another overarching topic has been the analysis of connections between Luhmann’s social systems theory and the evolutionary economics approaches, such as those of Thorstein Veblen and Kenneth Boulding. <!--[if gte mso 9]> Normal 0 false false false DE X-NONE X-NONE <![endif]--><!--[if gte mso 9]> <![endif]--><!--[if gte mso 10]> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-ansi-language:DE;} <![endif]-->
Structure Change Model - IAMO
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Ijssel Delta Final
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Economic Cost-Benefit Analysis- Roadkill Mitigation
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Socio-Economic Factors
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Economic capital growth in a system constrained by a non-renewable resource, Figure 37 from Thinking in Systems by Donella H. Meadows

Economic Capital Growth - Resource Constrained
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Clone of Pesticide Use in Central America for Lab work


This model is an attempt to simulate what is commonly referred to as the “pesticide treadmill” in agriculture and how it played out in the cotton industry in Central America after the Second World War until around the 1990s.

The cotton industry expanded dramatically in Central America after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This expansion was accompanied by a huge increase in industrial pesticide application which would eventually become the downfall of the industry.

The primary pest for cotton production, bol weevil, became increasingly resistant to chemical pesticides as they were applied each year. The application of pesticides also caused new pests to appear, such as leafworms, cotton aphids and whitefly, which in turn further fuelled increased application of pesticides. 

The treadmill resulted in massive increases in pesticide applications: in the early years they were only applied a few times per season, but this application rose to up to 40 applications per season by the 1970s; accounting for over 50% of the costs of production in some regions. 

The skyrocketing costs associated with increasing pesticide use were one of the key factors that led to the dramatic decline of the cotton industry in Central America: decreasing from its peak in the 1970s to less than 100,000 hectares in the 1990s. “In its wake, economic ruin and environmental devastation were left” as once thriving towns became ghost towns, and once fertile soils were wasted, eroded and abandoned (Lappe, 1998). 

Sources: Douglas L. Murray (1994), Cultivating Crisis: The Human Cost of Pesticides in Latin America, pp35-41; Francis Moore Lappe et al (1998), World Hunger: 12 Myths, 2nd Edition, pp54-55.

Clone of Clone of REM 221 - Causal Loop diagramming
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GSGS_HW2_GREENING_THE_GHETTO
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Tese CO2 Supply_CTCP - bloco A