Which statement best describes the use of a decision tree in evaluating capacity expansion decisions?

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Multiple Choice

Which statement best describes the use of a decision tree in evaluating capacity expansion decisions?

Explanation:
Decision trees are used to map out choices under uncertainty and to quantify the impact of different options by weighing possible outcomes. When evaluating capacity expansion, you can lay out the different expansion levels (for example, small, medium, or large) and, for each one, outline the probable future demand, costs, and prices that would follow. Each outcome comes with a probability and a payoff, so you can calculate a probability-weighted expected payoff for every expansion level. The level with the highest expected payoff becomes the recommended choice, because this approach directly compares how different expansion paths are likely to perform on average, given uncertainty. This approach doesn’t guarantee profits, remove all risk, or ensure a growing market—those are external factors. The decision tree’s strength is in structuring options and calculating their expected values to guide the decision.

Decision trees are used to map out choices under uncertainty and to quantify the impact of different options by weighing possible outcomes. When evaluating capacity expansion, you can lay out the different expansion levels (for example, small, medium, or large) and, for each one, outline the probable future demand, costs, and prices that would follow. Each outcome comes with a probability and a payoff, so you can calculate a probability-weighted expected payoff for every expansion level. The level with the highest expected payoff becomes the recommended choice, because this approach directly compares how different expansion paths are likely to perform on average, given uncertainty.

This approach doesn’t guarantee profits, remove all risk, or ensure a growing market—those are external factors. The decision tree’s strength is in structuring options and calculating their expected values to guide the decision.

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