150 words agree or disagree to each question Q1 Simulation models incorporate the uncertainty in input variab
150 words agree or disagree to each question
Simulation models incorporate the uncertainty in input variables and tracks the resulting output variables of interest. The distribution of results enables us to analyze how varying inputs can alter and influence the results of outputs. In our text, we are introduced to simulation models that can be applied to four general areas: operations, financial activity, marketing, and games of chance. Operation models are used in applications for manufacturing or service companies, like determining optimal bids for a contract based on expected profits. Financial models are used to simulate financial applications like future cash flows, stock prices, and interest rates. Marketing models are used to simulate applications like consumer preferences, loyalty, and purchasing habits. Models used to simulate games of chance can be used to analyze the random chances of gambling games or sporting contests.
I read an article by analyst Gaya Herrington, who was researching the original prediction from MIT researchers in 1972 who used a computer program to predict when society would collapse. Herrington compared the data from 1972 with the decades of new data we have now to determine if the MIT prediction still held up. She used new input variables that examined population, fertility rates, mortality rates, industrial output, food production, services, non-renewable resources, persistent pollution, human welfare, and ecological footprint. It is an interesting read that shows how simulation models can be applied to just about anything. For example, we can use computer simulations to predict future weather patterns. Simulations can model the various weather paths that can be projected and apply past information to determine which scenario will most likely occur.
Herrington, G. (2020). Update to limits to growth: Comparing the World3 model with empirical data. Journal of Industrial Ecology 2020, 1–13. https://doi.org/10.1111/jiec.13084
This week's post is one of the most exciting topics we have covered so far. A simulation model "uses a mathematical description, or model, of a real system in the form of a computer program" (Thomas, 2019). This simulation model requires the input of equations while providing solutions or relationships of one system based on the behavior of another system (Thomas, 2019).
A simulation model is used for many different reasons such as cancer treatment, how to respond to unforeseen viruses and diseases i.e. Covid 19, religion, etc. (Thomas, 2019). According to Mike Thomas one of the best ways a simulation model is used is to test new technology to guarantee cost-efficiency, which is also faster than creating a prototype for that technology (Thomas, 2019). Simulation models are a great tool to prevent businesses from taking significant risks while running a simulation allows them to assess risks to make effective decisions. An example of a simulation model that I found the most appropriate was the crash test conducted on a new vehicle (Thomas, 2019). A simulation model is used when a new vehicle is built to test its durability and safety, allowing multiple scenarios to be tested. The process of simulation modeling allows companies to optimize performance (Thomas, 2019). With the use of simulation, we can analyze a world of possibilities, but we can also better understand the world we are currently living in. It is a way for businesses to plan for the future and replicate scenarios that are real possibilities.
Thomas, M. (2019). A Deep Dive Into the World of Computer Simulation. Built in. Retrieved from: What is Computer Simulation and How Does it Work? | Built In.
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