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Study of the self-and all the rest society

Economic Insight

12 months ago

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

Geoff McDonnell

8 3 months ago

Social pressures create {Youth Alienation}, leading to youth developing bad behaviours and committing crimes. This attracts {Police Enforcement} who will, in turn, engage the {Community Leadership} where they introduce programs that are designed to assist youth to prevent re-offending through the development of {Community Clubs}, which then contributes to {Community Development}.

{Police Enforcement} collaborates with {Educational Institutions} to boost retention, which translates to socio-economic progress through {Community Development}. On the other hand, criminals are detained and put through the {Court} system, where the offenders are removed from the community through {Imprisonment}. This results in a stable and safe environment, which aid support for {Community Development).

The role of {Community Leadership} in the system, particularly at the grassroots will result is huge savings in the economy, aiding economic growth. The {Community Leadership} collaborates with the {Employment & Justice Agencies}, translating into socio-economic progress {Community Development}

The Community Development Model

This model provides an understanding into the relationships and links between a range of variable units and fixed units, and how {Community Development} is supported.

As {Youth Alienation} rate increases, the {Crime} rate increases (both variables) demands police enforcement. {Police Enforcement} is a fixed variable as increase in police force is fixed over a period of time.

To increase efficiency, engages or collaborate with:

•{Community Leadership} (fixed and variable) – is fixed for a certain period, and becomes variable as youth criminal activities increases

•{Court} (variable) – as youth criminal activities increase, the court resources reman fixed. It then removes some offenders from the community and imprison them, creating peace and stability in the community

•{Educational Institutions} (variables) – as student retention increases, more institutions are needed.

Variables that are linked to the {Community Leadership} which include;

•{Youth Sports Clubs}

•{Employment & Justice Agencies}

•{Economic Preservation; and}

•{Educational Institutions}

Contribute/support {Community Development}. These are variables, as more youths are referred or engaged.

The {Community Leadership} and {Police Enforcement} collaborate, support and design community programs to reduce youth criminal activities, which could potentially reduce the justice system expenditure.

The relationship between these fixed and variable units create a sustainable Community Development.

The Community Development Model

Marshiah Mupinyuri

Circular equations WIP for Runy.

Added several versions of the model. Added a flow to make C increase. Added a factor to be able to change the value 0.5. Older version cloned at IM-46280

Clone of Circularity in Economic models

Runy Calmera

Socio-Economic Factors

Jenya Bogopolskiy

Ijssel Delta Final

B G

Model Explanation:

This system dynamics model visualises the impact on investment into policing and community engagement resources on the crime rates within the youth population of Bourke, NSW.
The model also adds in the variable of funding for safe houses. With a high rate of domestic violence, unfavorable home conditions and other socio-economic factors, many youth roam the streets with no safe place to go, which may lead to negative behaviour patterns.

Assumptions

Youth Population: 700
Total youth population in 2016 for Bourke LGA was 646 (ages 10-29). (Census, 2016) Figures rounded to 700 for purposes of this model simulation.

Constants:
70% registration and engagement rates for Community funded programs
30% attendance rate for Safe Houses
50% crime conviction rate

Variables

Positive and Negative Influences

The model shows a number of key variables that lead youth to become more vunerable to commit a crime (such as alienation, coming from households with domestic violence, boredom and socio-economic disadvantages such as low income), as well as the variables that enhance the youth's likelihood to be a contributing member of the community (developing trusted relationships and connections with others, and having a sense of self worth, purpose and pride in the community). These factors (positive and negative) are aggregated to a single rate of 50% each for the purposes of the simulation, however each individual situation would be unique.

Police Funding / Resources

Police funding and resources means the number of active police officers attending to criminal activities, as well as prevention tactics and education programs to reduce negative behaviour. The slider can be moved to increase or decrease policing levels to view the impact on conviction rates. Current policing levels are approx 40 police to a population of under 3000 in Bourke.

Crime Rate

Youth crime rates in Australia were 3.33% (2016). Acknowledging Bourke crime rates are much higher than average, a crime rate of 40% is set initially for this model, but can be varied using the sliders.

Community Program Funding / Resources

Community Program Funding and Resources means money, facilities and people to develop and support the running of programs such as enhancing employability through mentorship and training, recreational sports and clubs, and volunteering opportunities to give back to the community. As engagement levels in the community programs increase, the levels of crime decrease. The slider can be moved to increase or decrease funding levels to view the impact on youth registrations into the community programs.

Observations

Ideally the simulations should show that an increase in police funding reduces crime rates over time, allowing for more youth committing crimes to be convicted and subsequently rehabilitated, therefore decreasing the overall levels of youth at risk.

A portion of those youth still at risk will move to the youth not at risk category through increased funding of safe houses (allowing a space for them to get out of the negative behaviour loop and away), whom them may consider registering into the community engagement programs. An increase in funding in community engagement programs will see more youth become more constructive members of the community, and that may in turn encourage youth at risk to seek out these programs as well by way of social and sub-cultural influences.

Justice & Community Support Investment and the Impacts on Bourke Youth Population

Sarah Vassallo

5

An initial study of the economics of single use coffee pods.

Helene D. Coffee Pod Investigation

Helene D.

This model is developed to simulate how Burnie can deal with a new outbreak of COVID-19 considering health and economic outcomes. The time limit of the simulation is 100 days when a stable circumstance is reached.

Stocks

There are four stocks involved in this model. Susceptible represents the number of people that potentially could be infected. Infected refers to the number of people infected at the moment. Recovered means the number of people that has been cured, but it could turn into susceptible given a specific period of time since the immunity does not seem everlasting. Death case refers to the total number of death since the beginning of outbreak. The sum of these four stocks add up to the initial population of the town.

Variables

There are four variables in grey colour that indicate rates or factors of infection, recovery, death or economic outcomes. They usually cannot be accurately identified until it happen, therefore they can be modified by the user to adjust for a better simulation outcome.

Immunity loss rate seems to be less relevant in this case because it is usually unsure and varies for individuals, therefore it is fixed in this model.

The most interesting variable in green represents the government policy, which in this situation should be shifting the financial resources to medical resources to control infection rate, reduce death rate and increase recovery rate. It is limited from 0 to 0.8 since a government cannot shift all of the resources. Bigger scale means more resources are shifted. The change of government policy will be well reflected in the economic outcome, users are encouraged to adjust it to see the change.

The economic outcome is the variable that roughly reflects the daily income of the whole town, which cannot be accurate but it does indicate the trend.

Assumptions:

The recovery of the infected won't happen until 30 days later since it is usually a long process. And the start of death will be delayed for 14 days considering the characteristic of the virus.

Economic outcome will be affected by the number of infected since the infected cannot normally perform financial activities.

Immunity effect is fixed at 30 days after recovery.

Interesting Insights:

In this model it is not hard to find that extreme government policy does not result in the best economic outcome, but the values in-between around 0.5 seems to reach the best financial outcome while the health issues are not compromised. That is why usually the government need to balance health and economic according to the circumstance.

New outbreak of COVID-19 in Burnie

Hank

Marine Tourism Task III - Great Blue Hole

Emma Malte Larsen

I propose we grow this sim model (or similar) over time to help ourselves better understand the opposing investment and austerity strategies now being advocated for the U.S. government. The hope is to build as simple a model as possible that subsumes the major underlying feedback loops that probably exist in the mental models of proponents of each of these positions. Starting this model was inspired by this Investment vs. Austerity discussion http://www.linkedin.com/groups/Investment-vs-Austerity-How-can-4582801.S.157876413

20120908a_InvestmentVsAusterity

Paul Newton

Scott Page's Aggregation diagram from Complexity and Sociology 2015 article see also IM-9115 and SA IM-1163

Macro micro dynamics

Geoff McDonnell

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

Guy Lakeman

26

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

Ray C

Health Determinants

Chelsea Poeppel

This model shows the COVID-19 outbreaks in Burnie and the Government intervention to alleviate the crisis and also how is the intervention affect the economy.

It is assumed that the Government intervention is triggered when the COVID-19 case is equal to or more than 10.

Government intervention - lock down the state, suppress the development of COVID-19 effectively. It is related to most of people stay at home to reduce the exposure in public area.

On the other hand, it also bring the economy of Burnie in the recession, as no tourists, no dining out activities and decrease in money spending in the city.

Clone of Burnie COVID-19 outbreaks and economic impacts_Pui Chu Daisy Cheung 524767

Lin Ling

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

Zilin Huang

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

Geoff McDonnell

2 months ago

GSGS_GREECE_GERMANY_MIGRATION_DRAFT

Dennis Hadjimichael

29 2 months ago

Simple model of the global economy, the global carbon cycle, and planetary energy balance.

The planetary energy balance model is a two-box model, with shallow and deep ocean heat reservoirs. The carbon cycle model is a 4-box model, with the atmosphere, shallow ocean, deep ocean, and terrestrial carbon.

The economic model is based on the Kaya identity, which decomposes CO2 emissions into population, GDP/capita, energy intensity of GDP, and carbon intensity of energy. It allows for temperature-related climate damages to both GDP and the growth rate of GDP.

This model was originally created by Bob Kopp (Rutgers University) in support of the SESYNC Climate Learning Project.

Clone of Simple Climate-Carbon-Economic Model

Ana Belén Ríos CArmona

Economic Model

Luke Geise

Socio-economic

Taylor Gariepy

3. PROBLEMAS e PERGUNTAS SOBRE projetos de SISTEMA INTEGRADO DE GESTÃO CUSTOS , INVESTIMENTOS BASEADO MODELOS MATEMÁTICOS: veja https://docs.google.com/document/d/1oGmItBcErhVF0PWuI37AnpP3n8Up3Zu45W7QB1MMbcY/edit?usp=sharing

Projeto de investimentos , custos e viabilidade econômico de LCC

A planta foi dimensionada para produzir 9.000 Ton/ano da Resina usando o matéria prima

LCC , operando 24h/dia, durante os três turnos por 300 dias/anuais. O preço do produto de projeto de lcc

veja o prova html aula passados

1. Calcule o investimento em planta (If) usando o método rápido e investimento em

equipamento (Ie) baseado no método de lang. Admita valor de N e f1 de acordo com o fluxograma do processo.

Dados fornecidos: Entrada (alimentação)-sólido; Saída-líquido;

Equipamentos principais da produção: Destilador e fermentador.

2. Calcule o investimento fixo total pelo método chilton através das estimativas dos investimentos fixos diretos: Tubulação, instrumentação, estrutura física, planta de serviço e conexões entre unidades; e investimentos fixos indiretos. Tome como base o investimento em equipamentos.

veja dados na prova html simulados sobre fator chiltons , modelos de lang , decico , chiltons e dados na prova html

3. Calcule o custo de mão-de- obra direta e indireta baseando-se no fluxograma de processo , atualizando o valor salário mínimo e nos salários:

Valor do salário mínimo = R$180,00

Engenheiro químico = 10 salários mínimos

Operador industrial = 3 salários mínimos

Administração:

Gerente = 8 salários mínimos

Auxiliar de escritório = 3 salários mínimos

Secretária = 2 salários mínimos

Dados fornecidos: Considere os encargos sociais de 65% sobre o salário base. Mão-de- obra

indireta seja 20% da mão-de- obra direta. O custo de mão-de- obra indireta engloba

manutenção.

4. Calcule os custos fixos abaixo, baseando-se pelo método Sebrae:

Dados

4.1 Depreciação = 10%If

4.2 Manutenção = 3%If

4.3 Seguro = 1%If

4.4 Imposto = 2%If

5. Calcule o custo de consumo anual de matéria-prima de acordo com os dados , veja prova html a seguir

5.2 Calcule o custo unitário de matéria prima sendo 80% do valor do custo total anual da

matéria-prima. , dados , veja na link enunciados e prova html

6. Calcule os custos totais:

6.1 Encargos anuais

6.2 Administração = 0.6 (mão-de- obra direta + mão-de- obra indireta + encargos anuais)

6.3 Suprimentos = 0.15 (Manutenção)

6.4 Calcule os custos fixos

6.5 Calcule os custos variáveis

6.6 Calcule os custos variáveis

* Os custos fixos englobam administração

Custo variável = custo de matéria – prima + custo de utilitários + custo de suprimentos.

Custo de suprimentos é 10% da mão-de- obra direta.

Depreciação = 10% do investimento fixo.

7. Estimar o ponto de equilíbrio em quantidade e em porcentagem baseado em dados obtidos de custo variável unitário) e Custo fixo do problema 06.

8. Estime os itens da análise de investimento:

– Taxa de retorno de engenharia simples

– Tempo de retorno

– % de lucro em relação ao preço de venda

– Lucro após o imposto de renda

– Lucratividade

– Rentabilidade

– Fluxo de caixa

9. Estimar potencial econômico de projeto de perdas devido ao baixo rendimento de operação em nível de 90% de rendimento máximo em vez de 98%.

Dados de consumos de materiais e energia obtidos via uso de calculadora usando quiz html de modelos já apresentados aula passos

NOME E DESCRIÇÃO

LINK

TAMANHO

Prova1validacao.:Investimento Fixo e Tomada de Decisões Rápidas

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184101

33 KB

Prova.2 Validacao .Investimento fixo método Lang

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184144

32 KB

Prova 3 :Investimento Fixo método Chilton

ihttps://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184169

33 KB

Prova4:Custo Fixo

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184189

32 KB

Prova 5::Custo de mao de obra

customaohtm custo de mao de obra

33 KB

Prova 6 Validao : Custo de mat,comb e enegia

CustoMat prima , energia

34 KB

Prova 7 Custo total

custo de operacional de producao

33 KB

Prova 8 Ponto deEquilibrio

ponto de eqilibrioibrio

32 KB

Prova 9:Analise de lucro e beneficios

Fluxo de caixa

33 KB

gestao economical planta resina fenolicas lcc .Modelos e resultados validados validado via planilhas

Pagandai V Pannir Selvam

SSM Lionfish Management PT2 revised with Storytelling

RRamos

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