11.2 Decision-Making Models

Decision-making models in cognitive psychology explore how we make choices. Normative models prescribe ideal decisions, while descriptive models explain real-world choices. These approaches highlight the gap between rational ideals and human limitations.

Rational choice theory assumes clear preferences and complete information. However, bounded rationality recognizes our cognitive constraints. This leads to satisficing and using heuristics. Different models suit various contexts, from quick personal choices to complex professional decisions.

Decision-Making Models in Cognitive Psychology

Normative vs descriptive decision models

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• Normative models prescribe ideal decision-making based on logic and math principles assume full rationality
• Descriptive models explain actual decision-making based on empirical observations account for cognitive biases and limitations
• Key differences: ideal vs realistic approaches, theoretical vs practical applications, prescriptive vs explanatory nature
• Examples: Expected Utility Theory (normative) vs Prospect Theory (descriptive)

Components of rational choice theory

• Preferences represent clear stable set of desires guide decision-making process
• Options encompass available choices or alternatives to be evaluated
• Consequences outline potential outcomes associated with each option
• Utility measures satisfaction or value derived from each consequence
• Assumptions include complete information, transitivity of preferences, independence of irrelevant alternatives
• Decision-making process involves:
  1. Identifying all possible options
  2. Evaluating consequences of each option
  3. Assigning utilities to consequences
  4. Choosing option with highest expected utility
• Examples: Consumer choosing between products, investor selecting stocks

Bounded rationality in decision-making

• Limited rationality due to cognitive constraints and environmental factors affects real-world decisions
• Satisficing involves choosing first satisfactory option rather than optimal one (job search)
• Heuristics serve as mental shortcuts to simplify complex decisions (availability heuristic)
• Cognitive limitations restrict information processing capacity impact decision quality
• Time constraints pressure quick decisions may lead to suboptimal choices (emergency situations)
• Limited information results in incomplete knowledge affects decision accuracy (medical diagnoses)
• Cognitive biases cause systematic deviations from rationality influence judgments (confirmation bias)
• Implications: decisions may not be optimal, emphasis on "good enough" solutions, recognition of human limitations

Effectiveness of decision models

• Personal contexts: Intuitive models effective for familiar, low-stakes decisions (choosing lunch)
  • Pros: Quick, based on experience
  • Cons: Prone to biases, may overlook important factors
• Professional contexts: Analytical models suitable for complex, high-stakes decisions (business strategy)
  • Pros: Systematic, evidence-based
  • Cons: Time-consuming, may overlook intuitive insights
• Societal domains: Collaborative models effective for decisions affecting diverse groups (public policy)
  • Pros: Inclusive, considers multiple perspectives
  • Cons: Slow, difficult to reach consensus
• Effectiveness criteria: decision quality, efficiency, adaptability, ethical considerations
• Hybrid approaches combine multiple models for balanced decision-making integrate intuitive and analytical thinking
• Examples: Using both data analysis and expert opinions in healthcare decisions, combining cost-benefit analysis with stakeholder input in urban planning