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Economic growth model v.1, delay function
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From Walrave ISDC2014 paper Counteracting the success trap in publically owned corporations. Similar to the ordinary (efficiency focussed) and dynamic capabilities (explore) insight described by David Teece
See also evolution and brain control insight
Explore or Exploit
Insight diagram
Causal loop structure of system dynamics models of the business cycle and the Kondratieff long wave from Gene Bellinger's AI gemini prompts mc and mr Jan2026 From MIT Sloan school work esp Forrester and Sterman
Short and Long Business and Economic Cycles
9 months ago
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WFA4133 Graham-Schaefer model with harvest & economics
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Map of SD work on Samuelson's 1939 model of the business cycle. See also D-memo D-2311-2 Gilbert Low 1976 and IM-165713. An alernative to the Ch 26 Macroeconomics textbook exposition.  From Gil Low's Multiplier Accelerator Model of Business Cycles, Ch 4 of Elements of the System Dynamics Method Book edited by Jorgen Randers 1976 (MIT Press) and 1980 (Productivity Press)
Samuelson multiplier accelerator model
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Overview of Part G Ch 27 to 30 of Mitchell Wray and Watts Textbook see IM-164967 for book overview
History of Macroeconomic Thought
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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

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
Insight diagram
How education causes the gap between socio-economic status?
Educación_universidad
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Socio-Economic Factors
Insight diagram
A simple budget planning system.  What additional complexities can you add?
ISD Savings Plan - Science Intro
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Economic Cost-Benefit Analysis- Roadkill Mitigation
Insight diagram
nuclear_economic
Insight diagram
FORCED GROWTH GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION 
 BEWARE pushing increased growth blows the system!
(governments are trying to push growth on already unstable systems !)

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept and flawed strategy of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

FORCED GROWTH INTO TURBULENCE
Insight diagram
This page provides a structural analysis of POTUS Candidate Scott Walker based on the information at: https://www.scottwalker.com/news/why-i%E2%80%99m-running-president   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 Scott Walker Economic Policy
Insight diagram
The simulation integrates or sums (INTEG) the Nj population, with a change of Delta N in each generation, starting with an initial value of 5.
The equation for DeltaN is a version of 
Nj+1 = Nj  + mu (1- Nj / Nmax ) Nj
the maximum population is set to be one million, and the growth rate constant mu = 3.
 
Nj: is the “number of items” in our current generation.

Delta Nj: is the “change in number of items” as we go from the present generation into the next generation. This is just the number of items born minus the number of items who have died.

mu: is the growth or birth rate parameter, similar to that in the exponential growth and decay model. However, as we extend our model it will no longer be the actual growth rate, but rather just a constant that tends to control the actual growth rate without being directly proportional to it.

F(Nj) = mu(1‐Nj/Nmax): is our model for the effective “growth rate”, a rate that decreases as the number of items approaches the maximum allowed by external factors such as food supply, disease or predation. (You can think of mu as the growth or birth rate in the absence of population pressure from other items.) We write this rate as F(Nj), which is a mathematical way of saying F is affected by the number of items, i.e., “F is a function of Nj”. It combines both growth and all the various environmental constraints on growth into a single function. This is a good approach to modeling; start with something that works (exponential growth) and then modify it incrementally, while still incorporating the working model.

Nj+1 = Nj + Delta Nj : This is a mathematical way to say, “The new number of items equals the old number of items plus the change in number of items”.

Nj/Nmax: is what fraction a population has reached of the maximum "carrying capacity" allowed by the external environment. We use this fraction to change the overall growth rate of the population. In the real world, as well as in our model, it is possible for a population to be greater than the maximum population (which is usually an average of many years), at least for a short period of time. This means that we can expect fluctuations in which Nj/Nmax is greater than 1.

This equation is a form of what is known as the logistic map or equation. It is a map because it "maps'' the population in one year into the population of the next year. It is "logistic'' in the military sense of supplying a population with its needs. It a nonlinear equation because it contains a term proportional to Nj^2 and not just Nj. The logistic map equation is also an example of discrete mathematics. It is discrete because the time variable j assumes just integer values, and consequently the variables Nj+1 and Nj do not change continuously into each other, as would a function N(t). In addition to the variables Nj and j, the equation also contains the two parameters mu, the growth rate, and Nmax, the maximum population. You can think of these as "constants'' whose values are determined from external sources and remain fixed as one year of items gets mapped into the next year. However, as part of viewing the computer as a laboratory in which to experiment, and as part of the scientific process, you should vary the parameters in order to explore how the model reacts to changes in them.
POPULATION LOGISTIC MAP (WITH FEEDBACK)
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A framework exploring flood risk management in a developing city, under the old paradigm of control - characterised by narrowly defined goals and an over-reliance on hard-engineered structural solutions.
Urban flood risk (control paradigm)
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CLD ofClimate Change & Economic Activity
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This model is based off Meadows economic capital with reinforcing growth loop constrained by a renewable resource model.
Tourism Simulator
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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
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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
Insight diagram
Socio-economic