Adapted from Fig 12.1 p.476 of the Book James A. Forte ( 2007), Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice; Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

X-Axis

The X-Axis shows the time. It begins in 2015 in the month of October and continues for 36 consecutive years. 

Y-Axis

There are 2 Y-Axis on this model. The left hand side relates to the price, demand, and supply, while the right hand side solely lists the population.

As you could see, this town has a population of 100,000 residents to-date. The bottom of the model shows a population loop that produces an exponential growth rate of 2.5%. This dynamic and growing city populates approximately 240,000 residents after 36 years.

The model consists of 2 folders named: Buyers/Consumers & Suppliers/Producers. This first folder represents the 'Demand'. It includes a buyers growth rate, buyers interest increase and decrease, a price demand and the demand price. The formulas form an exponential rise in demand due to the rapid and continuous increase in population in this new city. As population increases, so does the demand from buyers. 

The second folder conveys the supply of houses. It includes a sophisticated loop of real estate. Residents who own houses in the market decide to sell the home. This becomes the Houses for sale, also known as the 'supply'. Those houses are sold and the sold houses re-enter the market and the loop continues. 

The supply has an inverse relationship with the price. When prices drop, supplies drop because the demand goes up. And when the price goes up, so does the supply. This will represent the growth of new houses in the market. 

Note: The price is based on monthly rent rates.

The price is dependant on many variables. Most importantly, the supply and demand. It also includes factors such as expectations & the economic value of the house. I have included a stable, 'good' economic value for all homes as this fictional town is in a stable and growing area.

Price fluctuates throughout the entire simulation, however it also goes up in price. Over the years houses continue to rise in price while they regularly fluctuate. For example, in 2018 (3 years later), the max price for a home was: $4254.7 and min price was: $852.98. On the other hand, in October 2051 (36 years later), the max price was: $14906 and the min price was: $7661. (This is based on the following data: Houses for Sale: 500, Houses that have sold: 100, Houses in the Market: 730).

There are 3 sliders on the bottom that could be altered. The simulation would react accordingly. The 3 sliders include changeable data on:

- Houses for Sale.

- Houses that have Sold.

- Houses in the Market.

This causal loop diagram illustrates the interconnected factors affecting the economic empowerment of Congolese refugee women in Rwanda, with economic dependency as the central problem reinforced by limited access to vocational training, employment opportunities, and financial services. The diagram shows two key reinforcing loops: one where vocational training leads to employment and income generation, which reduces dependency and improves access to further training (R1), and another where income generation builds self-confidence and skills recognition, leading to better employment opportunities (R2), while language barriers and cultural constraints act as inhibiting factors throughout the system.

This simulation model demonstrates the outbreak of Covid-19 in Burnie, Tasmania and how the corresponding government’s responses affect the spreading of Covid-19. Meanwhile, this model also shows how the economy in Burnie is influenced by the impacts of both Covid-19 and government policies.

This simulation contains some relevant variables as follow:

Variables in Covid-19 outbreaks: (1) Infection rate, (2) Recovery rate, (3) Death rate, (4) Immunity loss rate

Variables in Government policies: (1) Vaccination rate, (2) Lockdown, (3) Travel ban, (4)Quarantine

Variables in Economy: (1) E-commerce business, (2) Unemployment rate, (3) Economic growth rate.

Government responses would be triggered when reported Covid-19 cases are at least 10.

The government policies reduce the spreading of Covid-19, but they would also limit economic development at the same time due to the negative impact of the policies on the economy is greater than the positive impact.

The increase in reported Covid-19 cases would negatively affect economic growth.

The first finding is that the death number would keep increasing even though the infection rate has decreased, but with stronger government policies (such as implementing a coefficient over 25%), no more death numbers will occur caused by Covid-19.

The second finding is that as government policies limit business activities, with the increasing number of reported Covid-19 cases, economic growth will suffer a severe blow even if e-commerce grows, it can’t make up for this economic loss.

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)