This Insight model is the last in a series of models that examine the dynamics of population growth and decline in a simple environment.  The first model can be found  here.   It follows on from a series of three Insights that introduce the basic concepts of Systems Dynamics that can be found  here
This Insight model is the last in a series of models that examine the dynamics of population growth and decline in a simple environment.  The first model can be found here.  It follows on from a series of three Insights that introduce the basic concepts of Systems Dynamics that can be found here.

The model refines the concept of carrying capacity by introducing dynamic resources that the population depends on to thrive.

The models are based on the activities from an Open University short course that can be accessed here.
This model simulates the economics of buying a home. It was created to compare buying a home against using investment returns to pay for rent. According to Micheal Finke, house prices typically run 20x monthly rental rates.      Try cloning this insight, setting the parameter values for real-world s
This model simulates the economics of buying a home. It was created to compare buying a home against using investment returns to pay for rent. According to Micheal Finke, house prices typically run 20x monthly rental rates. 

Try cloning this insight, setting the parameter values for real-world scenarios, and then running sensitivity analysis (see tools) to determine the likely wealth outcomes. Compare buying a home to renting. Note that each run will keep the parameters the same while simulating market volatility.

version 2.0
3 months ago
 Regulation of resource allocation to production in response to inventory adequacy and delivery delay. A non-price-mediated resource allocation system. From Sterman JD Business Dynamics p172 Fig 5-27

Regulation of resource allocation to production in response to inventory adequacy and delivery delay. A non-price-mediated resource allocation system. From Sterman JD Business Dynamics p172 Fig 5-27

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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 process
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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]-->
Any activity  requires the use of energy. Economic activity
is not possible without energy, 
especially fossil fuels. An increase in economic activity necessarily
leads to an increase in the use  fossil
fuels and greenhouse gas emissions. In addition there will   be a commensurate increase in waste
Any activity  requires the use of energy. Economic activity is not possible without energy,  especially fossil fuels. An increase in economic activity necessarily leads to an increase in the use  fossil fuels and greenhouse gas emissions. In addition there will   be a commensurate increase in waste products, pollution and heat. This is dictated by the laws of physics and unavoidable.  A problem arise when the cost of this degeneration caused by continual economic growth surpasses the benefit society derives from it. The ecological economist Professor Herman Daly (2014) explained that when the impact on the ecosystem is correctly measured, global growth has reached a point where the total private and social costs of economic growth outweigh the private and social benefits. In other words, more economic growth is making global society worse off overall - growth has become uneconomic! The model shows that eventually pressures will build up that counteract the perennial belief that all social ills can be solved with economic growth. 

Capitalism is in crisis and climate
change disruption is now beginning to hit the bottom line. Insurance companies
know this well. According to a report by the Bank of England, insured losses
have risen from $10 000 million in 1985 to $50 000 million in 2015. Climate change
cannot be reversed, and e
Capitalism is in crisis and climate change disruption is now beginning to hit the bottom line. Insurance companies know this well. According to a report by the Bank of England, insured losses have risen from $10 000 million in 1985 to $50 000 million in 2015. Climate change cannot be reversed, and extreme weather events  will undoubtedly get worse in the future strengthening the disruptive effects shown in the CLD.  Another dynamic is that companies will continue to automate and, as The Economic Policy Institute has shown, fail to reflect  productivity gains in workers' salaries. The result, stagnating salaries is disastrous for demand, given that capitalism needs endlessly rising demand and consumption. A further serious problem is that as climate change gets worse there will be increasing demands for companies to assume their responsibility and bear the costs of negative externalities.  The CLD shows these factors which are likely to lead to the collapse of the system: when capitalism can no longer generate 'capital' it has stopped to serves any useful purpose. 

Simulation of MTBF with controls   F(t) = 1 - e ^ -λt   Where    • F(t) is the probability of failure    • λ is the failure rate in 1/time unit (1/h, for example)   • t is the observed service life (h, for example)  The inverse curve is the trust time On the right the increase in failures brings its
Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
Clone of IM-91683 from jacqui and vincy Summary of paper map produced by participants at the compelling case for prevention workshop 6 june 2017.     Current premier version containing Story Steps and text for vincy to update. This is clone of 97129 via Vincy.
Clone of IM-91683 from jacqui and vincy Summary of paper map produced by participants at the compelling case for prevention workshop 6 june 2017. 

Current premier version containing Story Steps and text for vincy to update.
This is clone of 97129 via Vincy.
This Insight is used for simulating growth of a company with specified parameters.
This Insight is used for simulating growth of a company with specified parameters.
Description:   This is a system dynamics model of COVID-19 outbreak in Burnie which shows the process of infections and how  government responses, impact on the local economy.       First part is outbreak model, we can know that when people is infected, there are two situations. One is that he recov
Description:

This is a system dynamics model of COVID-19 outbreak in Burnie which shows the process of infections and how  government responses, impact on the local economy.  

First part is outbreak model, we can know that when people is infected, there are two situations. One is that he recovers from  treatment, but even if he recovered, the immunity loss rate increase, makes him to become infected again. The other situation is death. In this outbreak, the government's health policies (ban on non-essential trips, closure of non-essential retailers, limits on public gatherings and quarantine )  help to reduce the spread of the COVID-19 new cases. Moreover,  government legislation is dependent on  number of COVID-19 cases and testing rates. 

 Second part: the model of Govt legislation and economic impact. Gov policy can help to reduce infection rate and local economy at same way. The increase of number of COVID-19 cases has a negative impact on local Tourism industry and economic growth rate. On the other hand, Govt legislation also can be change when reported COVID-19 case are less or equal to 10.






10 months ago