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Moon Micro is a small manufacturer of servers that currently builds its entire product in Santa Clara, CA. As the market for servers has grown dramatically, the Santa Clara plant has reached capacity of 10,000 servers per year. Moon is considering two options to increase its capacity. The first option is to add 8,000 units of capacity to the Santa Clara plant at an annualized fixed cost of $8 million plus $600 labor per server. The second option is to have Molectron, an independent assembler, manufacture servers for Moon at a cost of $2000 for each server (excluding raw materials cost). Raw materials cost $9000 per server, and Moon sells each server for $16,000. Moon must make this decision for a two-year time horizon. During each year, demand for Moon servers has an 70 percent chance of increasing 40% from the year before and a 10% chance of remaining the same as the year before. Molectron's prices may change as well. They are fixed for the first year but have a 40% chance of increasing 10% in the second year and a 60% chance of remaining where they are. Use decision trees to determine whether Moon should add capacity to its Santa Clara plant or if it should outsource to Molectron. Please 1) Create one decision tree for in-house option and create one decision tree for outsourcing option. If you use a parameter, please explain what it is. 2) For each scenario in the decision tree, please give the details about demand, outsource price, revenue, cost, profit, probability, etc when applicable. All the output that you may indicate in the decision tree are needed to be presented (explained) first. 3) Given the discount rate 0.1, get the profit for each option of outsourcing or in-house. You have to include all the detailed work about the process.
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