BMA 708 | Insight Maker

This model explains the difference between Mountain bikes riding compared to logging in the Tasmanian forests.

Logging allows the activity in the forest with a negative demand for timber providing an income (with the price variable). The deforestation variable shows us that over time, the forest will run out if the logging keeps going on this way.

Alternatively, mountain biking allows a demand of visitors who want to see the scenary. They increase the regional tourism which is good for the community as it involves other businesses around too. The charges paid by visitors and tourists allow an income for the activity which makes it productive over time and great for TAS.

As we stimulate the model, we can see that it is better to have more visitors and more tourists rather than more logging as it will be better over time.

Maylis - Simulation of Derby Mountain bikes riding versus logging

Maylis P

Overview:

This simulation will show the relationship between tree logging forestry and how this can affect mountain biking tourism in Derby Park Tasmania. The main goal of this simulation is to show these two industries can co-exist in the same environment, or increase in demand or production in one sector will affect the result of another.

Function of the model:

In comparison there are both pros and cons for both sectors working correspondently. Demand for derby park is caused by individual past experience when visiting the park or friends recommendation which increase in the number of demands. Increase in demands will increase in the number of visitors. When visitors visits the park they require make a purchase a bike and pay the park for using the park facilities. All this will adds up to bikers total spending when visiting Derby. When consumer spend it is booting the economy especially in the tourism sector. Similarly tree logging will also contribute financially towards the Tasmania economy. The regeneration stage is relatively low compare to the logging rate. The growth will not cover the loss which can cause some level of damage in the scenery of the park, affecting tourist to view when mountain biking. Visitors overall experience will have the impact towards the demand for mountain biking in derby park, if visitors experience is satisfied they will come back to visit again or visit with group of friends, even words of mouth recommendation will also increase the level of demand of visiting Derby.

Some key insights base on the simulation:

Based on the simulation of the two models we can see there are some key changes.

Tree logging increase will cause the disturbance of the natural scenery, thus change the overall experience of the visitors, decrease in the level of demand. Tree logging will also have negative impact towards the overall tourist experience thus affect the park facility and track. The natural scenery and the overall experience can affect their experience and if they would continue to recommend this area to friends to increase the demand.

Assignment 3 Derby mountain biking and the effect of logging - 586984

Kelly

This is a model which explains the difference between Mountain bikes riding compared to logging in the Tasmanian forests.

Simulation of Derby Mountain bikes riding versus logging

Maylis P

Overview

The model simulates how logging in with tourism(mountain biking) in Derby Tasmania.

How the model works.

Trees grow, loggers cut them in order to sell them because of demand for Timber.

Mountain cyclist depends on satisfaction and expectation. Satisfaction and Expectation depends on Scenery number of trees compared to visitor and Adventure number of trees and users. Park capacity limits the number of users. Local Business is influenced by the timber and number of Mountain Cyclist. Employment is influenced by the number of mountain cyclist and logging activity.

Simulation of Mountain Cyclist vs logging

Shu Wang

Overview

This model reflects the competition between mountain biking and the logging industry to determine the optimal point for coexistence to maximize the amount of state income.

How Does the Model Work

Both the logging and mountain tourism industries have the potential to boost Tasmania's economy. It is obvious that the logging industry sells timber to generate revenue and the mountain tourism industry will generate revenue through mountain bikers' spending including mountain bike equipment, mountain bike training expenses and park ticket expenses. Moreover, the logging activities have an impact on the forestry scenery to reduce the amount of park visitors. Meanwhile, the park's recommendations are impacted by the forest scenery and mountain biking experience. Furthermore, Government rules will restrict logging activities when the logging business cuts too many trees resulting in forest devastation.

Interesting insight

Although forestry may contribute significantly to Tasmania's economy, excessive logging will be decrease the forestry scenery to influence the visitors volume even through the amount of visitors is easily to exceed the park capacity. it indicate that tourism industry can always contribute more to the economy than forestry does, as long as the quantity of riders is consistent. The government should take into account the point of equilibrium between two industries.

Assignment 3 the impact of logging on mountain bike industry Feixue Zhao

Zhao feixue

A Model of diffusion of innovation

Bass Model Intro

Mohammad Samiul Islam

Demo Insight

Yumin Li

1

Steven D'Alessandro

14

test

TEST maylis

Maylis P

Description:

Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from the SIR model(susceptible, infected, recovered) to determine the effect of the covid-19 outbreak on economic outcomes via government policy.

Assumptions:

The government policy is triggered when the number of infected is more than ten.

The government policies will take a negative effect on Covid-19 outbreaks and the financial system.

Parameters:

We set some fixed and adjusted variables.

Covid-19 outbreak's parameter

Fixed parameter: Background disease.

Adjusted parameters: Infection rate, recovery rate. Immunity loss rate can be changed from vaccination rate.

Government policy's parameters

Adjusted parameters: Testing rate(from 0.15 to 0.95), vaccination rate(from 0.3 to 1), travel ban(from 0 to 0.9), social distancing(from 0.1 to 0.8), Quarantine(from 0.1 to 0.9)

Economic's parameters

Fixed parameter: Tourism

Adjusted parameter: Economic growth rate(from 0.3 to 0.5)

Interesting insight

An increased vaccination rate and testing rate will decrease the number of infected cases and have a little more negative effect on the economic system. However, the financial system still needs a long time to recover in both cases.

BMA708_Assignment 3_Nguyen Dang Khoa Vo_520272_COVID-19 outbreak and Burnie economy

NGUYEN DANG KHOA VO

This model simulates the competition between logging versus adventure tourism(mountain bike riding) in Derby Tasmania. The purpose of this model is that focus on the relationship between the timber industry and mountain bike tourism in adventure. It also reflects how well these two industries co-exist.

How this model works

This model shows tree grow development. In order to maximize the profits from selling the logging, the demand for timbers will increase.

The mountain bike visits depend on past experience and recommendations. In addition, past experience and recommendations depend on Scenery, which is determined by the number of trees and visitors and adventure number. However, park capacity limits the number of use mountain bikes, because the convince of parking is a consideration for the visitors.

It seems like the high logging sale does not deter mountain bike activities. By reducing the parking capacity, visitor experience and number are increased. Because of the strong relationship between the mountain bike park and the explosion in visitor numbers. With the improvement in the number of visitors, the number of food and restaurants will go up as well. Because of the daily needs of the visitors.

Simulation of Derby Mountain bikes versus logging

Jayden Wu

This is a system dynamic model to describe relationship between local logging industry and biking tourism in Tasmanian Derby Mountain.

In the dynamic model, the left-hand side shows how Derby get income from local biking tourism. The biking visitors number are influenced by scenery evaluation which depend on local size of forest and influenced government policy support when Biking Tourism income is over 1000 unit. Biking visitors with good recommendation will also back to Mountain Derby and bring income for local in twice or more times. In the right-hand side, we found the income of logging industry was influenced by local logging growth rate and government policy if local Biking Tourism income is over 1000 unit. The increase of logging industry will also increase local employment which will influence employee cost. This factor will also affect total logging income in Derby Mountain.

The simulation results show, with governments support the Biking tourism will increase sharply in the first few years and finally instead local logging industry, at same time bring good environment and save local forest under local increase logging industry. The recommendation graph shows that, the number of good recommendation & bad recommendation for Derby Mountain biking tourism will also increase in high speed in front of few years with data fluctuation but finally maintain in a stable line. Last simulation graph shows that how policy factor influences logging and biking industry. The Government has strong support in local tourism, however, as number of tourists increase, the positive impact from government support will continue decrease. On the contrary, the government support influence will also decease to local logging industry when logging been instead by tourism.

Simulation Of Derby Mountain Bikes Versus logging

Zhuhang Wang

Test Maylis

Mountain bike vs logging

Maylis P

Summary:

This model shows the situation of Burnie in COVID 19. The assumed number of people death and recovered can be find in the model. It also shows how is the government policy influence the susceptible people and what factors will be affected by the government policy.

Assumption:

Most people follow the social distancing rule and a few people need quarantine. Economic growth rate is composed by industrial production, service industry and online economy.

Interesting insight:

Most infection happened in the group of people who do not follow the government policy. The online economy has a chance to growth fast during the COVID 19 period.

Burnie Situation in COVID 19

jialin liu

BMA 708 Models