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Grid-Group Culture applied to Public Management based on Christopher Hood's 1998 book. plus excerpts from Schwartz and Thompson's 1990 Book Divided we stand. See also Managing Mess IM-11581 and FourCultures Blog and Wikipedia Cultural Theory of Risk
The Art of the State
5 months ago
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Archetype:  Success to the successful
The more pioneer seed being sold, the more corn is grown.  As more corn is grown, the more pioneer seeds are needed for the next harvest.  More people began using the pioneer seeds, less people used the Ghanaian seeds.  However, the pioneer seed is expensive, so not everyone could buy the pioneer seed.  The more people using Ghanaian corn seeds, less people were using pioneer seeds.  

Way out: 
The best way out of this would probably be to lower the price of the pioneer seed.  The pioneer seed produces more corn that is sweeter.  People prefer this corn over the corn from the Ghanaian seeds.  More people are using the pioneer seeds, so gradually Ghanaian seeds will no longer be used.  Lowering the price of pioneer seeds will make it available to more farmers.  This way, less farmers will go out of business from trying to compete with more sweeter corn.  

Sources:
 Randall, R. (2014, December 15). Are African farmers in danger of becoming slaves to patented seeds? | Genetic Literacy Project. Retrieved January 18, 2016, from https://www.geneticliteracyproject.org/2014/12/15/are-african-farmers-in-danger-of-becoming-slaves-to-patented-seeds/

Is 4-H trying to hook African farmers on costly seeds? (2014, November 17). Retrieved January 18, 2016, from http://grist.org/food/is-4-h-trying-to-hook-african-farmers-on-costly-seeds/

Butler, K. (n.d.). How America's favorite baby-goat club is helping Big Ag take over farming in Africa. Retrieved January 18, 2016, from http://www.motherjones.com/environment/2014/11/4h-africa-farming-dupont-hybrid-seeds 
4-H Club in Africa - Economical
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Summary of UNEP ecosystems services CBA 2011 article by Wegner and Pascual
Value and cost benefit analysis
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13 Start
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Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from SIR model(susceptible, infected, revovered) to find out the effect of covid-19 outbreak into economic outcomes via government policy.

Assumptions

The government policy is triggered when number of infected is more than ten.

The government policies will take negative effect into Covid-19 outbreaks and financial system

Parameters

We set some fixed and adjusted variables.
Covid-19 outbreak's parameter
Fixed parameters: Infection rate, Background disease, recovery rate.
Adjusted parameter: Immunity loss rate can be change from vaccination rate.

Government policy's parameters
Adjusted parameters: Testing rate(from 0.15 to 0.95), vaccination rate(from 0.3 to 1), travel ban(from 0 to 0.9), social distancing(from 0.1 to 0.8), Quarantine(from 0.1 to 0.9)

Economic's parameters
Fixed parameter: Tourism
Adjusted parameter: Economic growth rate(from 0.3 to 0.5)

Interesting insight

Increase vaccination rate and testing rate will decrease the number amount of infected case and a little bit more negative effect to economic system. However economic system still need a long time to recover in both cases.
BMA708_Assignment 3_ndkvo_520272_COVID-19 outbreak and Burnie economy
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Prosperity Loop v1.0
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​WIP Summary of 2020 article Monetary Sovereignty: Nature, Implementation, and Implications by Eric Tymoigne
Eric Tymoigne Monetary Sovereignty
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This page provides a structural analysis of POTUS Candidate Rand Paul's economic policy based on the information at:  https://www.randpaul.com/issue/spending-and-debt and also   https://www.randpaul.com/issue/taxes  The method used is Integrative Propositional Analysis (IPA) available: ​ http://scipolicy.org/uploads/3/4/6/9/3469675/wallis_white_paper_-_the_ipa_answer_2014.12.11.pdf
DRAFT IPA of Rand Paul Economic Policy
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I made this as an illustration of a piece of text I read in Regenerative Economics, household economics.
Unpaid Care
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Economic Systems
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THE 2017 MODEL (BY GUY LAKEMAN) EMPHASIZES THE PEAK IN POLLUTION BEING CREATED BY OVERPOPULATION WITH THE CARRYING CAPACITY OF ARABLE LAND NOW BEING 1.5 TIMES OVER A SUSTAINABLE FUTURE (PASSED IN 1990) AND NOW INCREASING IN LOSS OF HUMAN SUSTAINABILITY DUE TO SEA RISE AND EXTREME GLOBAL WATER RELOCATION IN WEATHER CHANGES IN FLOODS AND DROUGHTS AND EXTENDED TROPICAL AND HORSE LATTITUDE CYCLONE ACTIVITY AROUND HADLEY CELLS

THE MODEL IS ZONE SPECIFIC AS GLOBAL WEATHER IS NOT HOMOGENEOUS BUT A COLLECTION OF HEAT BUMBPS DEPENDENT ON POPULATION SIZE OF URBAN HEAT ISLANDS AND MASSED CONURBATIONS AND AGGLOMERATIONS 

The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

THIS MODEL BY GUY LAKEMAN, FROM METRICS OBTAINED USING A MORE COMPREHENSIVE VENSIM SOFTWARE MODEL, SHOWS CURRENT CONDITIONS CREATED BY THE LATEST WEATHER EXTREMES AND LOSS OF ARABLE LAND BY THE  ALBEDO EFECT MELTING THE POLAR CAPS TOGETHER WITH NORTHERN JETSTREAM SHIFT NORTHWARDS, AND A NECESSITY TO ACT BEFORE THERE IS HUGE SUFFERING.
BY SETTING THE NEW ECOLOGICAL POLICIES TO 2015 WE CAN SEE THAT SOME POPULATIONS CAN BE SAVED BUT CITIES WILL SUFFER MOST. 
CURRENT MARKET SATURATION PLATEAU OF SOLID PRODUCTS AND BEHAVIORAL SINK FACTORS ARE ALSO ADDED

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a low birth-rate, environmentally focused policy.

2017 Weather & Climate Extreme Loss of Arable Land and Ocean Fertility by Guy Lakeman - The World3+ Model: Forecaster
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Assignment 3 – Complex Systems

 Ryan Salvaggio - 43668070

 

The Model

This model conceptualizes the effects on a real-estate market-model utilizing agent based modelling. This model utilizes basic economic principles of supply and demand.

The model bases itself on two Agents - one being ‘Customers’ of the real estate market model, whilst the other being the Real estate itself, coined 'Houses'.

Consumers (Demand)

The Agent population, ‘Consumers’ specifies the total amount of people whom can potentially become buyers within the market. This is limited to 30 for conceptual purposes. The Agent ‘Consumer’ exists in two states, either being an ‘Active Customer’ (Active) or an ‘Inactive Customer’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Budget’ of the Consumer meets the desired price of the marketplace, this is specified through the variable ‘Budget’ defining the probability that this transition will occur – this is adjustable by the user indicating a highly resistive or by accepting the market. ‘Budget’s probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state an ‘Active consumer’ will attempt to find the closest ‘For sale household’, this is represented and carried out through the ‘Enter’ action.  Upon finding a household the consumer and house will both return to their respected inactive state thus repeating the process.

Demand – ‘Count of active customers – demand’ is then calculated by a count of Consumers transitioned and currently in the Active state. A high demand would be indicative through a high ‘Budget’ responsiveness whilst a low demand would be indicative of a low ‘Budget’ responsiveness. The increase in Price and hence supply of household thus reduces demand and vise versa.  

House (Supply)

The Agent population, ‘Houses’ specifies the total amount of households that can potentially become for sale within the market. This is limited to 112 for conceptual purposes. The Agent ‘House’ exists in two states, either being ‘For Sale’ (Active) or ‘Not for Sale’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Motivation to Sell’ of the House is satisfied, this satisfaction is specified by a set probability that this transition will occur – this is adjustable by the user indicating a highly responsive or restricted house market. ‘Motivation to sell’ probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state a ‘For Sale’ house will wait for an ‘Active Customer’ ‘this is represented and carried out through the ‘Search’ action. Upon completion of the action both states become inactive and the process continues.

Supply – ‘Count of houses for sale –supply’ is then calculated by a count of Houses ‘For Sale’ that are currently in the active state. Ultimately a high Motivation to sell would sharply increase supply, whilst a low motivation would have the adverse effects.  

Movement Speed

Movement speed – describes the base movement rate of Consumers. This variable describes the transition into the ‘Inactive’ state of a consumer, ultimately when a household is found and purchased. Movement speed affects both demand and supply in the sense that the transitioning of stages is quickened and more responsive. (Indicated by a more rigid demand and supply curve).

Market Price

In economics Price is a linear function (straight line) of the proportion of houses for sale (positive slope), and also a linear function of the proportion of buyers (negative slope).Therefore , the variable ‘Market Price’ is calculated by 10 * the portion of ‘House’ in the active state (which is the supply) over the portion of ‘Consumers’ in the active state (which is the demand) Ultimately this presents the economic principles  that as Supply is directly related to Price and demand is inversely related to Price.

Note

Each simulation (with the same settings) will present a different and unique simulation. I have set a Random Boolean to the active component that randomizes the amount of Customers or houses that begin in their active state. The probability is only 0.008 but is useful in describing the effects on the market from various position’s and seeing unique models.  

References

https://www.youtube.com/watch?v=ynuoZQbqeUg - Your First ABM/Part II

https://insightmaker.com/insight/35714/Foraging-Model

Assignment 3 - Ryan Salvaggio 43668070
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This Insight Maker model illustrates the complex relationships involved in the destruction of rainforests. The reinforcing loop emphasizes the destructive cycle where economic development leads to increased deforestation, while the balancing loop highlights the negative consequences on biodiversity, climate, and economic activities, attempting to counteract the destructive forces. The model serves as a simplified representation to better understand the interconnected factors contributing to rainforest destruction and the importance of considering feedback loops in addressing environmental issues.
Destruction of Rainforests
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Economic model
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Green lines: positive relationships
Red lines: negative relationships

Spill
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Economic model
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Laying out and testing before coupling to main model (which is Final Project)
Socio-Economic Factors
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241004_economic growth model structure_SFD
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Plans
2 days ago
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An initial study of the economics of single use coffee pods.
Helene D. Coffee Pod Investigation
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GSGS4610_FastFashion_FinalModel
4 months ago
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Economical Factors of Science: C8
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Fig 4. The Casual Loop Diagram of the Socio-Political and Economic Subsystems