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As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.

As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.

As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.

As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.

As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.

As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.

As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.

As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.

As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.

As technology development or application evolves over time and the impact on the decision maker’s values takes place in the future, the technology portfolio planning and management process is fraught with uncertainty. In Chapter 6, we have used an aggregated expected value of the uncertain outcomes as a deterministic equivalent for the relationships between alternatives and values in the process. However, the deterministic equivalent is in many situations too aggregated for proper analysis, and the uncertainty effects need to be considered in greater detail. In this chapter, we will present major methods that will assist the decision maker in finding the best technology portfolio by explicitly analyzing the effects of uncertainty.