How people make choices when outcome probabilities are unknown or ambiguous.
Probabilities: The study of the likelihood of an event occurring, which is crucial for decision-making under uncertainty.
Risk: The potential for a loss or decrease in value, which can be mitigated through various strategies, such as diversification or hedging.
Uncertainty: The lack of knowledge about the future, which can lead to unexpected outcomes and risks.
Heuristics and biases: The shortcuts and mental shortcuts that people use to make decisions, which may lead to errors in judgment.
Utility: The measure of an individual's satisfaction or well-being, which can be used to evaluate the desirability of different outcomes.
Value of information: The potential benefit of obtaining additional information before making a decision, which can help to reduce uncertainty.
Decision trees: The visual representation of decision-making processes, which can help to analyze and compare different options.
Game theory: The study of strategic decision-making in situations where several actors or players interact, which can help to understand the behavior of competitors.
Prospect theory: The theory analyzing the decision-making of individuals under risk, which suggests that people exhibit different attitudes toward gains and losses.
Bayesian analysis: The statistical method to update prior beliefs or information as new information becomes available, which can help make more informed decisions under uncertainty.
Empathy: The ability to understand and share the feelings of others, which can help to make more informed and ethical decisions when taking into consideration the impact of one's actions on others.
VUCA (volatility, uncertainty, complexity, ambiguity): The framework to understand and manage the challenges that arise when decision-making under uncertainty in a rapidly changing world.
Expected value decision-making: This involves assessing the likelihood of different outcomes and assigning a numerical value to each, then choosing the option with the highest expected value.
Prospect theory decision-making: This theory suggests that people’s decisions are influenced more by the potential gains or losses of an outcome than the objective probability of that outcome.
Regret theory decision-making: This theory suggests that people make decisions based on minimizing their potential regret about different outcomes.
Satisficing decision-making: This approach involves choosing the option that is “good enough” rather than trying to optimize for the best possible outcome.
Hindsight bias decision-making: This type of decision-making involves evaluating outcomes based on hindsight, which can lead to over- or underestimation of the likelihood of a given outcome.
Anchoring and adjustment decision-making: This approach involves starting with an initial estimate or “anchor” and then adjusting that estimate based on available information.
Availability heuristic decision-making: This approach involves making decisions based on the ease with which various options or outcomes come to mind.
Representativeness heuristic decision-making: This approach involves making decisions based on how closely each option matches a mental prototype or stereotype.
Confirmation bias decision-making: This approach involves seeking out information that confirms one’s pre-existing beliefs or hypotheses and discounting information that contradicts them.
Framing effect decision-making: This approach involves making different decisions based on how a given decision is presented or framed.