Marketing Models

These models and simulations have been tagged “Marketing”.

This simple model describes how potential customers are converted into customers through advertising and word of mouth.
This simple model describes how potential customers are converted into customers through advertising and word of mouth.
Conceptual Model of Semantic Search Query from Google Analytics data.
Conceptual Model of Semantic Search Query from Google Analytics data.
A basic production model showing negative and positive loops, often called a balancing model. Thanks  Gene.
A basic production model showing negative and positive loops, often called a balancing model.
Thanks
Gene.
 Model Explanation  This complex system model visualizes relationships between
the investment on police and community and the change of youth crime rate in
Bourke, NSW. 

     

  Assumptions  

 Total number of youth population (aged 13 – 19 years old) in
Bourke: 1,000 

   

 80% of Bourke youth p
Model Explanation

This complex system model visualizes relationships between the investment on police and community and the change of youth crime rate in Bourke, NSW.

 

Assumptions

Total number of youth population (aged 13 – 19 years old) in Bourke: 1,000

 

80% of Bourke youth population are assumed to behave negatively.

50% of alienated teenagers are assumed to breach of law or rules.

70% of alienated youth who breach of law or rules will be arrested by police.

60% of teenagers arrested are assumed to be convicted and detained.

40% of teenagers arrested are assumed not to be convicted and detained.

70% of teenagers detained are assumed to participate in juvenile community programs after being released.

70% of teenagers participated in community programs will rehabilitate.

 

Variables

Drugs & Alcohol, Domestic violence, Long-term unemployment

Police expenses

Community funding

 

Conclusion

It can be seen that the number of alienated youth and the crime rate will decline over time when investing more on police and juvenile community programs.

 HOW A NEW COMMUNITY ENGAGEMENT INITATIVE MAY IMPACT YOUTH
CRIME IN THE TOWN OF BOURKE, NSW 

 MKT563 Assessment 4: 
Kari Steele  

   

  Aim of Simulation:    

 Bourke is a
town in which Youth are involved in high rates of criminal behaviour (Thompson,
2016).  This simulation focuses on how
imple

HOW A NEW COMMUNITY ENGAGEMENT INITATIVE MAY IMPACT YOUTH CRIME IN THE TOWN OF BOURKE, NSW

MKT563 Assessment 4:  Kari Steele 

 

Aim of Simulation: 

Bourke is a town in which Youth are involved in high rates of criminal behaviour (Thompson, 2016).  This simulation focuses on how implementation of a community engagement initiative may impact crime patterns of youths in Bourke.   The specific aim is to assess whether the town should initiate a program such as the Big Brothers Big Sisters Community-Based Mentoring (CBM) (Blueprints for Healthy Youth Development, 2018) program to reduce crime and antisocial behaviour (National Institute of Justice, n.d).  Big Brothers Big Sisters is a community mentoring program which matches a volunteer adult mentor to an at-risk child or adolescent to delay or reduce antisocial behaviours; improve academic success, attitudes and behaviours, peer and family relationships; strength self-concept; and provide social and cultural enrichment (Blueprints for Healthy Youth Development, 2018). 

 

Model Explanation:

An InsightMaker model is used to simulate the influence of Big Brothers Big Sisters Initiative on Criminal Behaviour (leading to 60% juvenile detention rates) with variables including participation rate and also drug and alcohol use.

Assumptions:

1/ ‘Youth’ are defined, for statistical purposes, as those persons between the ages of 15 and 24 (United Nations Department of Economic and Social Affairs, n.d).

2/ Youth population (15 – 24 years) makes up 14.1% of the total population of LGA Bourke which according to the most up-to-date freely available Census data (2008) is 3091 (Australian Bureau of Statistics, 2010).  Therefore, youth population has been calculated as 435 individuals.

3/ Big Brothers Big Sisters Program is assumed to impact LGA Bourke in a similar manner that has been shown in previous studies (Tierney, Grossman, and Resch, 2000) where initiative showed mentored youths in the program were 46% significantly less likely to initiate drug use and 27 percent less likely to initiate alcohol use, compared to control.  They were 32 less likely to have struct someone during the previous 12 months.  Compared to control group, the mentored youths earned higher grades, skipped fewer classes and fewer days of school and felt more competent about doing their schoolwork (non-significant).  Research also found that mentored youths, compared with control counterparts, displayed significantly better relationships with parents.  Emotional support among peers was higher than controls. 

Initial Values:

Youth Population = 435

Criminal Behaviour = 100

40% of youth population who commit a crime are non-convicted

60% of youth population who commit a crime are convicted

20% of youth involved in the Big Brothers Big Sisters Initiative are non-engaged

80% of youth involved in the Big Brothers Big Sisters Initiative are engaged

Variables:

The variables include ‘Participation Rate’ and ‘Drug and Alcohol Usage’.  These variables can be adjusted as these levels may be able to be impacted by other initiatives which the community can assess for introduction; these variables may also change in terms of rate over time.

Interesting Parameters

As can be seen by increasing the rate of participation to 90% we can see juvenile detention rate decreases with engagement (even with the 20% non-engagement of youths involved in program).  By moving the slider to 10% participation however you can see the criminal behaviour increase.   

Conclusion:

From the simulation, we can clearly see that the community of Bourke would benefit in terms of the Big Brothers Big Sisters Initiative decreasing criminal behaviour in youths (15 – 24 years of age) over a 5-year timeframe.  Further investigation regarding expenditure and logistics to implement such a program is warranted based on the simulation of impact.

 

References:

Australian Bureau of Statistics.  (2010).  Census Data for Bourke LGA.  Retrieved from www.abs.gov.au/AUSSTATS/abs@.nsf/Previousproducts/LGA11150Population/People12002-2006?opendocument&tabname=Summary&prodno=LGA11150&issue=2002-2006

 

Blueprints for Healthy Youth Development.  (2018).  Big Brothers Big Sisters of America Blueprints Program Rating: Promising, viewed 26 May 2018, <www.blueprintsprograms.com/evaluation-abstract/big-brothers-big-sisters-of-america>

 

National Institute of Justice.  (n.d.).  Program Profile: Big Brothers Big Sisters (BBBS) Community-Based Mentoring (CBM) Program, viewed 26th May 2018, <https://www.crimesolutions.gov/ProgramDetails.aspx?ID=112>

 

Tierney, J.P., Grossman, J.B., and Resch, N.L. (2000). Making a Difference: An Impact Study of Big Brothers/Big Sisters. Philadelphia, Pa.: Public/Private Ventures.
http://ppv.issuelab.org/resource/making_a_difference_an_impact_study_of_big_brothersbig_sisters_re_issue_of_1995_study

 

Thompson, G. (2016) Backing Bourke: How a radical new approach is saving young people from a life of crimeRetrieved from < www.abc.net.au/news/2016-09-19/four-corners-bourkes-experiment-in-justice-reinvestment/7855114>

 

United Nations Department of Economic and Social Affairs (UNDESA).  (n.d.).  Definition of Youth, viewed 24th May 2018, www.un.org/esa/socdev/documents/youth/fact-sheets/youth-definition.pdf

Simple customer growth stock and flow model that considers the impact of referrals, conversion rate and market size.
Simple customer growth stock and flow model that considers the impact of referrals, conversion rate and market size.
Free to air TV channels mostly receive income from sales of advertising. Advertising inventory gains value from TV channel ratings, that are created by high quality content. High quality content is created with investments and content promotion increases content awareness, thus increases TV channel
Free to air TV channels mostly receive income from sales of advertising. Advertising inventory gains value from TV channel ratings, that are created by high quality content. High quality content is created with investments and content promotion increases content awareness, thus increases TV channel appeal.
Advertising and promotion inventories share same space that is left after program is set up.
More over marketing has targets to increase TV channel appeal.
Sales department has targets to increase sales.
To make things more complicated program promos can be sold to have promotions.

What interactions arise in this situation?
What effects what?
Where do we have management point?

Situation and questions gave impulse for following CLD.
A very simple Bass model adopted from the Insight maker page
A very simple Bass model adopted from the Insight maker page
在提升銷售業績的過程中, 分析增強環路與調節環路:)    [增強環路1]:為了提升營業額,而投入更多行銷費用,品牌知名度上升,收入也持續增加 :))      [調節環路1]:當行銷支出越多時,會使產品的利潤下滑,也降低了整體銷售額能賺到的利潤!     [調節環路2]: 為了衝業績,工作時間就必須拉長,壓力變大導致工作效率下降而成長幅度趨緩! 
在提升銷售業績的過程中,
分析增強環路與調節環路:)

[增強環路1]:為了提升營業額,而投入更多行銷費用,品牌知名度上升,收入也持續增加 :)) 

[調節環路1]:當行銷支出越多時,會使產品的利潤下滑,也降低了整體銷售額能賺到的利潤!

[調節環路2]: 為了衝業績,工作時間就必須拉長,壓力變大導致工作效率下降而成長幅度趨緩! 


Assuming there are only product A &amp; B in the market (On the diagram, change the value of the transition "Choose C" into zero - as if Product C did not exist), there is a certain level of acceptance of product A and/or B. In this model, product B is less preferred than Product A. When Product C i
Assuming there are only product A & B in the market (On the diagram, change the value of the transition "Choose C" into zero - as if Product C did not exist), there is a certain level of acceptance of product A and/or B. In this model, product B is less preferred than Product A. When Product C is introduced into the market (on the diagram, change the value of the transition "Choose C" into a positive value (Since it is a probability, the value should be within 0 & 1 range only). With this introduction, you will see that Product B is replaced almost totally by Product C. This is called "decoy effect' in marketing.

In this example, we assume that Product A is a selection priority. Product B is only considered when the customers are unhappy with Product A (with a probability). Therefore, at the initial stage, product B starts at a lower position than Product A. For that reason, product B also suffers some disadvantages as its growth is likely to be determined by the number of unhappy customers of Product A.  

By manipulating the value of the transition "Choose C" you will see that the higher it is, the more likely that Product C will surpass Product B while performance of Product A is unchanged. It implies that as the owner of Product C - and as a late comer, for instance, you just need to deal with Product B and take over its market share. 

Note that we assume the three products have no differences, except that Product A is the first consideration of the customers.  
This is a model developed with Sarah's and Duncan's help on the 16/5/2017
This is a model developed with Sarah's and Duncan's help on the 16/5/2017
ABM approach to Bass Model of diffusion with a detractor state.    Still a work in progress.
ABM approach to Bass Model of diffusion with a detractor state.

Still a work in progress.
    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 violen

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.

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My first Insight Maker experiment. A straightforward model in which we start with a fixed number of prospects, convert them into customers, then lose some who become former customers.
My first Insight Maker experiment. A straightforward model in which we start with a fixed number of prospects, convert them into customers, then lose some who become former customers.
 The model simulates youth crime and program that has impacted on the levels of crime committed.
The model simulates youth crime and program that has impacted on the levels of crime committed.

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This model is looking at the youth in the town of Bourke, in NSW Australia. It has been designed to look at the impacts that the police force and community engagement can have on the youth in Bourke, specifically in relation to the crime rates within the town and what factors impact on this, including unemployment and drug and alcohol use.

 

Assumptions:

<!--[if !supportLists]-->-       <!--[endif]-->Total youth in Bourke = 25,000

<!--[if !supportLists]-->-       <!--[endif]-->Currently in Jail = 15,500

<!--[if !supportLists]-->-       <!--[endif]-->Currently in rehabilitation = 6,500

<!--[if !supportLists]-->-       <!--[endif]-->Youth who participate in a Community program and complete it = 75%

<!--[if !supportLists]-->-       <!--[endif]-->Youth with antisocial behaviour = 2,000

<!--[if !supportLists]-->-       <!--[endif]-->Youth with drug and alcohol problems = 6,500

<!--[if !supportLists]-->-       <!--[endif]-->Unemployment = 10,000

<!--[if !supportLists]-->-       <!--[endif]-->Youth placed into rehab due to drugs = 1,500

  

The youth in Bourke enter into a community program, and 75% of youth complete the program and return to the total youth. The 25% that do not complete become disengaged and wind up in jail. They complete a rehabilitation program and return to the community after 6 months. Youth with unemployment are impacted by drug and alcohol use and they are either detected by the police and placed into the rehabilitation program, or they are not detected and continue on a cycle of unemployment and drug and alcohol use.

 

The Government funding goes into the community programs and into the jail. The police force impacts on the disengaged youth entering into jail, the youth who become rehabilitated and detecting the drug and alcohol use of the youth.

 

There are two graphs in particular that are called out in this model. They are:

<!--[if !supportLists]-->1)   <!--[endif]-->Youth in Jail and Disengagement

<!--[if !supportLists]-->2)   <!--[endif]-->Youth in the Community Program and Youth Completing the Program

 

When looking at graph number one with the sliders on 100 Police Staff Members and $50,000 Government Funding you can see that the more youth that complete the program, the less youth there are in jail. We can identify that the completion of the program decreases the amount of youth in jail.

 

When these sliders are decreased to their lowest with 5 police staff members and $5,000 of government funding we see that the time it takes for the completion of community programs to be surpass the youth in jail occurs after 11 years as opposed to 7 years in the previous graph.

 

 The second graph identifies when the sliders are at their highest the delay and time it takes to engage the youth in the rehabilitation program vs. the youth in the community program, and that the youth entering into the programs and completing match up to one another. When the sliders are at there lowest the rehabilitation sits much lower at all times and the time taken to increase the amount of youth completing the program is substantially longer.

Overall this model stimulates the importance on not only the police force and government funding, but the two working alongside one another for optimum results for the youth in Bourke. 

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The need to spend time doing chargeable work, in balance and/or conflict with the need to spend time doing marketing to ensure a continuing workload into the future.
The need to spend time doing chargeable work, in balance and/or conflict with the need to spend time doing marketing to ensure a continuing workload into the future.
The need to spend time doing chargeable work, in balance and/or conflict with the need to spend time doing marketing to ensure a continuing workload into the future.
The need to spend time doing chargeable work, in balance and/or conflict with the need to spend time doing marketing to ensure a continuing workload into the future.
Stock and flow model to capture relationship between different factors that impact store demo performance
Stock and flow model to capture relationship between different factors that impact store demo performance