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Do you like travelling? Find out how we can help make it more sustainable! Images used: Suitcase: http://vignette2.wikia.nocookie.net/animaljam/images/a/ab/Travel-suitcase_(1).png/revision/latest?cb=20140907211051 Fiji: http://cdn.newsapi.com.au/image/v1/91c1263a2a357b3673af8ff8362c0c8d?w

https://image.slidesharecdn.com/genderinintegratedsystemsresearchbycynthiamcdougallseniorscientistgenderequitythemeleader-150311041710-conversion-gate01/95/gender-in-integrated-systems-research-by-cynthia-mcdougall-senior-scientist-gender-equity-theme-leader-25-638.jpg?cb=1426065542

Sources:

https://www.statista.com/statistics/270422/forecast-for-2020-arrivals-of-foreign-tourists-worldwide/

http://www.sustainabletourism.net

Week 10 Lecture- Dr. David Tindall Lecture pdf

https://www.adb.org/countries/fiji/poverty

Economic Impact of Tourism on Fiji's Economy: Empirical Evidence from Computable General Equilibrium Model by Paresh Kumar Narayan

https://www.wttc.org/-/media/files/reports/economic%20impact%20research/countries%202015/fiji2015.pdf

http://sustainabletravel.org/our-work/regional-alliances/pacific/hotel-sustainable-resources-pacific/

http://reusegraywater.com/about-us/

Rubin, K.E., The Valuation of Hotels and Motels for Assessment Purposes, 1984

https://en.wikipedia.org/wiki/Leverage-point_modeling

Meadows, D.H., & Wright, D. (2009). Thinking in systems: a primer, London: Earthscan.

Sustainable Tourism (Final)

Claire Huang

Business Economic Sustainability

Phebe Rutledge

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

วช

meng

DPSIR Framework to Analyze EcoPeace Middle East's Good Water Neighbours Strategy

Alistair Chean

Model based on chapter 10 (opportunity cost) of the book Modeling Dynamic Economic Systems

Opportunity cost II

AR

3

This high-level simulation model presented by Jay Forrester in his book World Dynamics, simulates socio-economic-environmental world system. The world Model was created in a time where pollution and other negative effects of industrialization and economic growth started to become recognized in 1970. For this exam purpose, we have rebuilt the model to do some experiments and analyze the results.

World Model2

Ali Akhlaqi

Lakon_Energy Economics Fossil Fuel

Nick Lakon

Landwirtschaftliche Dürre Österreich

Linda Menk

WIP Summary of MIchael Hudson's Book Killing the Host: How Financial Parasites and Debt destroy the Global Economy

Killing the Host

Geoff McDonnell

4

A systems model of the relationships amongst economic situation, health situations and Covid-19 in Burnie, Tasmania.

Health situation

According to exposed and go out population decreases, the population of infected decreases after a stable high cases period.

Economic situation

When the infected population decreases, the population economic recovery increases over time, then become stable after a period of time.

BMA708 Assessment 3 Complex system

Jingyi Qiu

Michael Marmot's Eur J Epidemiol Essay 2017 See also IM-62760 Social determinants of health from Michael Marmot's ABC 2016 Boyer Lectures on Social Justice and the Health Gap

Social Justice, Epidemiology and Health Inequalities

Geoff McDonnell

The housing market is heavily dependent on two main factors; supply and demand. Both play a major role in determining an equilibrium price for both sellers and buyers in the real estate market.

Residents, or the general population of individuals, place significant reliance on financial institutions to provide sources of capital i.e mortgages, to fund their purchases of homes. The rate of interest charged by these organisations in turn gives buyers (consumers) purchasing power, creating demand.

Supply is made up of the number of houses in the market, and consequently, of these, the number of houses which are up for sale. As the prices of houses for sale increases, the demand for purchase of these properties decreases. Conversely, the lower price, the higher the demand. Once the market reaches an equilibrium point, to which buyers and sellers form an agreement, houses are sold accordingly. An underlying factor to consider is the cost of construction, which impacts producers, or suppliers in this instance, and thus the number of homes for sale, and the expected profit sellers hope to achieve.

The simulated graph highlights the common scenario within the housing market, to which we see that as price increases, the total number for houses for sale decreases, generating an opposite slope to the price. As the price for houses increases, the demand for the houses decreases and vice versa. The equilibrium is evident at time 14 whereby the price of houses and the number of houses for sale overlaps which in turn creates a market to which both buyers and sellers are happy.

Clone of The effect of Supply and Demand on the Housing Market Assignment 3 (43323871)

Tanwa Arpornthip

Vicious economic circle of Aboriginal people

Akshat Bansal

Barangay IRAWAN Systems Model

Biophysical, Socio-cultural & Economic Data of Bgy. IRAWAN

Sitti Mashita J. Kilis

This model is developed to simulate how Burnie can deal with a new outbreak of COVID-19 considering health and economic outcomes. The time limit of the simulation is 100 days when a stable circumstance is reached.

Stocks

There are four stocks involved in this model. Susceptible represents the number of people that potentially could be infected. Infected refers to the number of people infected at the moment. Recovered means the number of people that has been cured, but it could turn into susceptible given a specific period of time since the immunity does not seem everlasting. Death case refers to the total number of death since the beginning of outbreak. The sum of these four stocks add up to the initial population of the town.

Variables

There are four variables in grey colour that indicate rates or factors of infection, recovery, death or economic outcomes. They usually cannot be accurately identified until it happen, therefore they can be modified by the user to adjust for a better simulation outcome.

Immunity loss rate seems to be less relevant in this case because it is usually unsure and varies for individuals, therefore it is fixed in this model.

The most interesting variable in green represents the government policy, which in this situation should be shifting the financial resources to medical resources to control infection rate, reduce death rate and increase recovery rate. It is limited from 0 to 0.8 since a government cannot shift all of the resources. Bigger scale means more resources are shifted. The change of government policy will be well reflected in the economic outcome, users are encouraged to adjust it to see the change.

The economic outcome is the variable that roughly reflects the daily income of the whole town, which cannot be accurate but it does indicate the trend.

Assumptions:

The recovery of the infected won't happen until 30 days later since it is usually a long process. And the start of death will be delayed for 14 days considering the characteristic of the virus.

Economic outcome will be affected by the number of infected since the infected cannot normally perform financial activities.

Immunity effect is fixed at 30 days after recovery.

Interesting Insights:

In this model it is not hard to find that extreme government policy does not result in the best economic outcome, but the values in-between around 0.5 seems to reach the best financial outcome while the health issues are not compromised. That is why usually the government need to balance health and economic according to the circumstance.

New outbreak of COVID-19 in Burnie

Hank

Fig 17.15 p700 Causal structure of commercial real estate markets of Case Study from John Sterman's 2000 Business Dynamics Book

Boom and bust in Commercial Real Estate

Geoff McDonnell

3

Overview of Part E Ch 20 to 24 of Mitchell Wray and Watts Textbook see IM-164967 for book overview

Economic policy in an open economy

Geoff McDonnell

8

Here I've translated the macoreconomic rule 'SPENDING = INCOME = OUTPUT, WHICH DRIVES EMPLOYMENT' into a negative feedback loop by adding an explicit goal of Output and Employment. As shown in 'Investment and Output 1', all the income earned has to be spent to maintain output and employment. Any shorfall in spending can be made up by any of the three sectors that contribute to total output. However, when spending/investment by the private sector is too small to maintain the required level of overall spending and the exports do not contribute enough to compensate for this shortfall then only the government can save the day through Net Spending, i.e. spending more than it collects in tax revenue. Taxation at any rate, according to Modern Monetary Theory (MMT) does not serve the purpose of financing spending but can be used legitimately to slow down an overheating economy. I have not taken into account 'structural reforms', which are often subject to the 'Fallacy of Composition' and of dubious value, at least in a recessive climate, according to MMT.

Investment and Output 2

Hanns-Jürgen Hodann

ECONOMIC INEQUALITY IN SOUTH DAKOTA

Jacinda Maassen

Clone of Economics Fast Fashion

Katrine Ken

11 last month

Major Transition Exposition: Big Map of Choices

Robert L. Brown

30

Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from SIR model(susceptible, infected, revovered) to find out the effect of covid-19 outbreak into economic outcomes via government policy.

Assumptions

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

The government policies will take negative effect into Covid-19 outbreaks and financial system

Parameters

We set some fixed and adjusted variables.

Covid-19 outbreak's parameter

Fixed parameters: Infection rate, Background disease, recovery rate.

Adjusted parameter: Immunity loss rate can be change 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

Increase vaccination rate and testing rate will decrease the number amount of infected case and a little bit more negative effect to economic system. However economic system still need a long time to recover in both cases.

BMA708_Assignment 3_ndkvo_520272_COVID-19 outbreak and Burnie economy