Algorithmic Pricing Decision: Ethics vs. Revenue Trade-offs
Analyze real-world personalization pricing scenarios, evaluate ethical implications, and justify pricing decisions using data insights
You're a pricing strategist at an e-commerce platform. You've identified that high-income users in urban areas show 40% higher price elasticity tolerance for luxury goods. Your ML model recommends dynamic pricing. Your CEO wants 15% Q3 revenue growth. Regulators are watching. How do you implement the pricing model? A user disputes their price and requests data access. What do you do? Your bias audit reveals the ML model recommends 12% higher prices for users on mobile devices (correlated with lower income). Next move? Sum of outcomes (0-20); >15 = ethical Sum of outcomes (0-20); >14 = defensible If ethical_score >=…
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