5.1 Rational Choice and Bounded Rationality

Rational Choice Theory and Bounded Rationality are key models in decision-making. They offer contrasting views on how people make choices, with Rational Choice assuming perfect information and utility maximization, while Bounded Rationality acknowledges cognitive limits.

These models shape our understanding of decision-making in various fields. They highlight the tension between ideal rationality and real-world constraints, influencing how we analyze and predict human behavior in complex situations.

Rational Choice Theory

Assumptions and Principles

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• Rational Choice Theory assumes individuals make decisions based on a rational assessment of costs and benefits
• Individuals are assumed to have well-defined preferences and the ability to rank alternatives based on those preferences
• Decisions are made with the goal of maximizing utility, which is a measure of satisfaction or benefit derived from a choice
• Perfect information is assumed, meaning individuals have complete knowledge about the alternatives, their outcomes, and the associated probabilities

Utility Maximization

• Utility maximization is the central principle of Rational Choice Theory
• Individuals are assumed to choose the alternative that provides the highest level of utility or satisfaction
• Utility can be measured in various ways, such as monetary value, happiness, or other forms of benefit
• The concept of marginal utility is important, which refers to the additional utility gained from consuming one more unit of a good or service
• Individuals are expected to make decisions that maximize their total utility, considering the costs and benefits of each alternative

Limitations and Criticisms

• The assumption of perfect information is often unrealistic, as individuals rarely have complete knowledge about all alternatives and their outcomes
• Rational Choice Theory does not account for the influence of emotions, social norms, or other non-rational factors on decision-making
• The theory assumes individuals have stable and well-defined preferences, which may not always be the case in reality
• Critics argue that the theory oversimplifies human behavior and fails to capture the complexity of real-world decision-making processes

Bounded Rationality

Concept and Definition

• Bounded Rationality is an alternative to Rational Choice Theory, proposed by Herbert A. Simon
• It recognizes the limitations of human cognitive abilities and the presence of incomplete information in decision-making
• Individuals are assumed to have limited computational capacity and face constraints in processing information
• Bounded Rationality suggests that individuals make decisions based on simplified models of reality, rather than perfect optimization

Satisficing

• Satisficing is a key concept in Bounded Rationality, introduced by Herbert A. Simon
• It refers to the process of making decisions that are "good enough" rather than optimal
• Individuals set an aspiration level, which is a minimum acceptable outcome, and choose the first alternative that meets or exceeds that level
• Satisficing is a more realistic approach to decision-making, as it acknowledges the limitations of human cognitive abilities and the costs of searching for optimal solutions

Cognitive Limitations and Heuristics

• Bounded Rationality emphasizes the cognitive limitations that individuals face when making decisions
• These limitations include limited attention, memory, and computational capacity
• To cope with these limitations, individuals often rely on heuristics, which are simple rules of thumb or mental shortcuts
• Heuristics allow individuals to make decisions quickly and efficiently, but they can also lead to biases and errors in judgment
• Examples of heuristics include the availability heuristic (judging the likelihood of an event based on how easily examples come to mind) and the representativeness heuristic (judging the probability of an event based on how similar it is to a typical case)

Decision-Making Under Uncertainty

Concept and Definition

• Decision-Making Under Uncertainty refers to situations where individuals must make choices without complete information about the outcomes or probabilities
• In these situations, individuals face risk (known probabilities) or ambiguity (unknown probabilities)
• Decision-Making Under Uncertainty is a common challenge in real-world settings, such as business, finance, and public policy

Prospect Theory

• Prospect Theory is a behavioral model of decision-making under uncertainty, developed by Daniel Kahneman and Amos Tversky
• It challenges the assumptions of Rational Choice Theory and incorporates psychological insights into decision-making
• Prospect Theory suggests that individuals evaluate outcomes relative to a reference point, typically the status quo
• The theory proposes that individuals are loss-averse, meaning they are more sensitive to losses than to equivalent gains
• Probability weighting is another key concept in Prospect Theory, which suggests that individuals overweight small probabilities and underweight large probabilities
• Prospect Theory helps explain various observed phenomena, such as the endowment effect (the tendency to value items more when they are owned) and the framing effect (the influence of how a decision problem is presented on the choices made)