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Model Explanation

The model to be simulate the possible crime patterns among the youth population of Bourke, where levels of alienation, policing and community engagement expenditure can be manipulated. Here the youth in Bourke have a minimum percentage of the interested participated on the community activities which government aims to improve their lifestyle and therefore they can specified on the reduce the rate of criminal activity.

Assumption:

The assumption of the 2530 youth of the Bourke n the population susceptible to committing crime and simulations of criminal tendencies are only based on the factor presented, no external influences

Variable:

Alienation includes any factors that can increase the like hood of youth to commit crime such as exposure to domestic violence, household income, education level, and family background community engagement expenditure is the total monies budgeted into community activities to develop youths in and out of growth detention policing is the amount of police placed onto patrol in the town of Bourke to reinforce safety and that the law is abided.

Stocks:

conviction rate is set to 60% A growth detention sentence for convicted criminals is set to 3 months the top 30% of the most server offenders are sent to rehabilitation for 3 months, to which they return to Bourke assuming in a better state and less likely to repeat a petty crime community activities are set to last 3 months to be calculating the align with the seasons: sporting club of the growth of community participants have 20% change of being disengaged as it may not align with their interests investments into policing are felt immediately & community engagement expenditure has a delay of 3 months.

Finding the interest:

1. Alienation of the set maximum value is 0.2, policing and community engagement set to minimum shows a simulation where by all criminals are in town rather than being expedited and placed into growth detention even after a base value on the 500 youth placed into growth detention- this shouts that budget is required to control the overwhelming number of criminal youth as they overrun brouke.

2. Set of community activity they can identified the 0.01 policing to max & alienation to max. The lack of social crime has caused much trouble among young people. The Police Immigration Police has not been deployed to the city of town, which has such a crime rate. Growth prevention can only last a long time, and all young people cannot be rehabilitated, so if they continue to commit crimes.

3. It plays an important role in considering the crime of young people. In order to keep the criminal activity minimal, the bulk of the budgets in police and social involvement among young people must be put at risk. Realistically, budget in a small town is an important factor, it may be engagement.

4. To be set the police value 0.2, and engaged alienation expenditure value 0.04 of the community activities that can use of improve the youth in town of Bourke

MKT563_Big_Data_2018

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The model takes into account clothing production and textile waste on a global scale while incorporating Vancouver's own "Fast Fashion" issue into the model.

Please refer to the notes for each variable and stock to see which links were hidden from the model.

Part 2: Our solution for the issue surrounding "Fast Fashion" focuses on increasing individuals education about sustainability and how they can help reduce negative impacts on the environment by shopping less, recycling and donating. This effect of education on sustainability is seen in the "Online Shopping" equation where the impact of "Education on Sustainability" is increased by x1.5 which impacts the entire model. Furthermore, components of the feedback loop on the right are also influenced by increasing education on sustainability and thus, those values were altered accordingly. These values were chosen arbitrarily by taking into account that doubling any value is not realistic so the change should be between x1.0 and x2.0.

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Assignment 3: Bourke Crime and Community Development

This complex systems model depicts the impact of factors such as violence and community programs on the youth of Bourke. The time scale is in months and shows the next 6 years. The model aims to show how by altering expenditure in different areas, the town of Bourke can decrease crime and increase their population involvement in community programs. This model is intended to be dynamic to allow the user to change certain variables to see changes in impact

The town of Bourke has a population of 3634 people, 903 of which are classified as youth (being 0-24 inclusive) (ABS, 2016 census).

This population starts with all youths in three differing stocks:

- 703 in Youth

- 100 in Juvenile Detention

- 100 in Rehabilitation

Assumptions:

This model makes many assumptions that would not necessarily uphold in reality.

- Only the youth of the town are committing crimes.

- All convicted youths spend 6 months in juvenile detention.

- All convicted youths must go to rehabilitation after juvenile detention and spend 2 months there.

- The risk rate impacts upon every youth committing a crime and is a broad term covering effects such as abuse.

- No gaol effect, youths do not return to town with a tendency to re- commit a crime.

- No further external factors than those given.

- There cannot be zero expenditure in any of the fields.

The stocks:

Each stock depicts a different action or place that an individual youth may find themselves in.

These stocks include:

- Youth (the youths living in Bourke, where youths are if they are not committing crimes or in community programs)

- Petty Crime (crimes committed by the youths of Bourke such as stealing)

- Juvenile Detention (where convicted youths go)

- Rehabilitation

- Community Programs

The variables:

- Community Expenditure (parameter 0.1-0.4)

- Law Enforcement Expenditure (parameter 0.1-0.6)

- Rehabilitation Expenditure (parameter 0.1-0.4)

- Risk Rate (not adjustable but alters with Law Enforcement Expenditure)

Sliders on each of the expenditure variables have been provided. These variables indicate the percentage of the criminal minimising budget for Bourke.

Note that to be realistic, one should make the three differing sliders be equal to 1, in order to show 100% of expenditure

Base Parameter Settings:

- Law Enforcement Expenditure = 0.5

- Community Expenditure = 0.25

- Rehabilitation Expenditure = 0.25

Interesting Parameter Settings:

- When Law Enforcement is at 0.45 and Community and Rehabilitation at 0.3 and 0.25 (in either order) then convicted and not-convicted values are the same. If Law Enforcement expenditure goes any lower then the number of convicted youths is less than those not-convicted and vice versa if the expenditure is increased.

- When Law Enforcement is at 0.2 and Community and Rehabilitation at 0.4 each then the increase in community programs and decrease in crime and thus detention occurs in a shorter and more rapid time frame. This shows that crime can be minimised in this model almost entirely through community initiatives.

- Alternatively, when Law Enforcement is at 0.6 and Community and Rehabilitation at 0.2 each then the increase in community programs and decrease in crime occurs over a longer time period with more incremental change.

Population Source:

http://www.censusdata.abs.gov.au/census_services/getproduct/census/2016/quickstat/LGA11150?opendocument

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Coefficients assigned to make model work rather than being based on any evidence.

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Provided further interest and funding, this basic capability model may further de-abstracted and built out to: higher provenance levels -- coupled with increased factorization, rigorous causal inclusion and improved parameterization.

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CO₂e Metrics: Uses 100-year global warming potential (GWP) to convert non-CO₂ greenhouse gases into CO₂ equivalents, consistent with the model's timeframe.

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By adjusting the slider below you can observe the work process

without any work in process limitations (WIP Limits),
with process step specific WIP Limits* (work state WIP limits),
with Kanban Token and Replenishment Token based on the Tameflow approach (a form of drum-buffer-rope)
with Drum Buffer Rope** scheduling method.

* Well know in (agile) Kanban

** Known in the physical world of factory production

The simulation and the comparison between the different scheduling approaches can be seen here -> https://youtu.be/xXvdVkxeMMQ

The "Tameflow approach" using Kanban Token and Replenishment Token as well as the Drum Buffer Rope method take the Constraint (the weakest link of the work process) into consideration when pulling in new work items into the delivery "system".

Feel free to play around and recognize the different effects of work scheduling methods.

If you have questions or feedback get in touch via twitter @swilluda

The work flow itself

Look at the simulation as if you would look on a kanban board.

The simulation mimics a "typical" feature delivery process on portfolio level.

From left to right you find the following ten process steps.

Ideas
Selected ideas (waiting)
Initiate and pitch
Waiting for preparation
Prepare
Waiting for delivery
Deliver
Waiting for closure
Close and communicate
Closed

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[Pink]: Demand of total residential household and business waste and energy demands on the system.

[Green]: Physical waste produced by human activity in the region.

[Teal]: The outflow of energy produced through waste recycling and its impact of energy production and demand in the region. The Durham-York Energy Center (DYEC) is a facility that combusts garbage into energy which is highlighted in teal, which accumulates with energy produced.

[Orange]: Total energy produced through all means of power generation including modelling of the impact that recycling waste has.

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Overall, this model examines and compares waste accumulation to energy production and the release of emissions.

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