These models and simulations have been tagged “Tourism”.
It is a model simulating
logging and adventure tourism (mountain bike riding) competition in Derby,
Tasmania. It is a chance for northeast Tasmania to become an exciting, new, world-class
product for the mountain bike tourism industry, which drives local economic
Simulation borrowed from the
Easter Island simulation.
l Trees grow; we cut them down because of demand for Timber and sell the
l The mountain bike visits depend on previous experience and suggestions.
l Previous experience and suggestions depend on the number of trees
compared to visitors and adventure number of trees and users. Park capacity
limits the number of mountain bike trail users.
l The employment opportunity depends on the mountain bike demand and demand
Mountain biking appears to be
unaffected by heavy logging. The visitor experience and numbers are improved by
reducing park capacity. The main issue is that any success with the mountain
bike park increases visitor numbers. A high timber price is also required to
balance the park's popularity. Mountain biking appears to require only a narrow
corridor; that is, single-track mountain bike trails are enough. The employment is a measure of the economic acting, a recession or growth trends.
The model shows the industry connection and conflict between Forestry and Mountain Tourism in Derby, Tasmania. The objective of this simulation is to find out the balance point for co-exist.
How Does the Model Work?
Both industries can provide economic contribution to Tasmania. Firstly, selling timbers through logging would generate income. Also, spendings from mountain bike riders would generate incomes. However, low tree regrowth rate can not cover up logging, which influences the beautiful vistas and riders' experiences. While satisfaction and expectation depend on vistas and experience, the demand of mountain biking would be influenced through repeat visits and world of mouth as well.
Although forestry can provide a great amount of economic contribution to Tasmania, over logging goes against ESG framework as well as creating conflict with mountain tourism. As long as the number of rider visits is stable, tourism can always provide a greater economic contribution compared to forestry. Therefore, the government should consider the balance point between two industries.
This model simulates logging and mountain biking competition in Derby, Tasmania. The Simulation is referenced to simulate Derby mountain biking with logging.
The tourism industry is represented on the model's left side, and the logging industry is on the right side. Interactions between these two industries generate tax revenues. Logging and tourism have different growth rates regarding people working/consuming. The initial values of these two industries in the model are not fixed but increase yearly due to inflation or economic growth.
From the perspective of tourism, as the number of tourists keeps growing, the number of people who choose to ride in Derby City also gradually increases. And the people who ride rate the ride. The negative feedback feeds back into the cycling population. Similarly, positive cycling reviews lead to more customer visits. And all the customers will create a revenue through tourism, and a certain proportion of the income will become tourism tax.
From a logging perspective, it is very similar to the tourism industry. As the number of people working in the industry is forecast to increase, the industry's overall size is predicted to grow. And as the industry's size continues to rise, the taxes on the logging industry will also continue to rise. Since logging is an industry, the tax contribution will be more significant than the tourism excise tax.
This model assumption is illustrated below:
1. The amount of tax reflects the level of industrial development.
2. The goal of reducing carbon emissions lets us always pay attention to the environmental damage caused by the logging industry.
3. The government's regulatory goal is to increase overall income while ensuring the environment.
4. Logging will lead to environmental damage, which will decrease the number of tourists.
This model is based on tourism tax revenue versus logging tax revenue. Tourism tax revenue is more incredible than logging tax revenue, indicating a better environment. As a result of government policy, the logging industry will be heavily developed in the short term. Growth in the logging industry will increase by 40%. A growth rate of 0.8 and 0.6 of the original is obtained when logging taxes are 2 and 4 times higher than tourism taxes.
Furthermore, tourism tax and logging tax also act on the positive rate, which is the probability that customers give a positive evaluation. The over-development of the logging industry will lead to the destruction of environmental resources and further affect the tourism industry. The logging tax will also affect the tourism Ride Rate, which is the probability that all tourism customers will choose Derby city.
This model more accurately reflects logging and tourism's natural growth and ties the two industries together environmentally. Two ways of development are evident in the two industries. Compared to tourism, logging shows an upward spiral influenced by government policies. Government attitudes also affect tourism revenue, but more by the logging industry.
This model displays the
conflict between the tourism and timber industry in Derby, Tasmania. It becomes
a problem for the government officials when choosing the future policy direction.
Our aim is to construct a model for simulation and find a equilibrium point to
maximize the state benefit.
How Does the Model
The key factor of the model is the value
of the policy variable. It can take values between -1 and +1. The more it is close
to +1 means that the policy government takes is more tourism-friendly. The more
it is close to -1 means that the policy government takes is more timber-friendly.
the policy variable, there are three sections for the model.
We assume that there exist a population
which contains the whole potential customers. The potential customers will make
bike trips to Derby at a relatively stable rate. The input policy value will
affect the satisfaction rate for the tourists. Some of them will provide
positive feedbacks and become our potential customers again. On the other hand,
those had bad experience will no longer make trips to Derby. All the tourists
make consumption every month and part of the expense will become the tourism revenue.
The average expense variable is also provided in this section.
Section 2: The timber
The input policy variable will also affect
the employment in the timber industry. It will partially determine the industry
growth rate. Like the tourism, the sales/industry scale will generate monthly revenue
for the industry at a given rate.
Section 3: The state
The revenue from the two industries will
be added up. Our aim is to adjust the policy value to maximize the state benefit.
Excessive logging may lead to environmental
problems and it isn’t the best option for the whole state benefit. Based on the
pre-set parameters and the model, we can see that the revenue contribution from
the tourism is also considerable. According to our results, the policy value
should be around 0.31, which represents the tourism-friendly policy.