modules/module08.txt

MODULE NAME:
Module 08 – Optimization and Behavioral Economics

LEARNING OBJECTIVES:
- Use Excel's Solver to find optimal solutions to linear programming problems
- Describe classical notions of rationality (Homo Economicus)
- Define Behavioral Economics and its real-world applications
- Explain bounded rationality and prospect theory
- Identify situations in which people's decisions appear to be irrational (Fairness and System 1/2)

KEY POINTS:
• Optimization (Excel Solver): Quantitative tool with three components: Decision variables (choices), Constraints (limitations), and Objective function (goal to max/min).
• Classical Rationality: Assumes "Homo Economicus"—a person with perfect information, infinite time, and perfect self-control who always optimizes utility.
• Behavioral Economics: Applies psychological insights to explain why real human decision-making often deviates from classical models.
• Bounded Rationality: Herbert Simon's concept that humans "satisfice" (choose the first acceptable option) because of cognitive limits and time pressure.
• Prospect Theory: Kahneman & Tversky's finding that people value gains and losses differently; loss aversion means the pain of losing $100 is greater than the joy of gaining $100.
• Fairness (Ultimatum Game): Humans often reject profitable offers if they perceive them as unfair, prioritizing social equity over pure self-interest.
• System 1 vs. System 2: System 1 is fast, intuitive, and prone to heuristics; System 2 is slow, analytical, and effortful.
• Mindfulness in Optimization: Being aware of "System 1" impulses allows a manager to pause and engage "System 2" tools like Excel Solver for complex problems.
• Ethics in Behavioral Econ: Understanding "nudge" theory and fairness helps managers design systems that are both efficient and ethically sound for all stakeholders.