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Week - 1
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Course Introduction and Fundamental Concepts; Two-sided markets, cross-side network effects, and the critical mass (chicken-egg) problem. |
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Week - 2
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Platform Pricing Strategies; Cross-subsidization, penetration pricing, and analysis of user acquisition costs (burn rate). |
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Week - 3
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Trust Mechanisms and Reputation Systems; The role of trust in market design, rating systems, reputation inflation, and social biases. |
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Week - 4
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Algorithmic Management on Platforms; The invisible hand of ranking and matching algorithms on the market. |
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Week - 5
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AI Fundamentals for Economists; The logic of Reinforcement Learning (RL), exploration-exploitation trade-off. |
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Week - 6
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Algorithmic Pricing and Competition; Pricing algorithms and the risk of tacit collusion; analysis of the Calvano model. |
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Week - 7
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Recommender Systems and Consumer Welfare; Collaborative filtering, filter bubbles, and discussions on algorithmic diversity. |
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Week - 8
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Midterm Assessment and Case Analysis; Integrated analysis of platform strategies through real-world cases. |
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Week - 9
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Data Economy and Market Power; Data-driven network effects (data flywheel), data ownership, and barriers to entry |
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Week - 10
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The Privacy and Personalization Paradox; Targeted advertising, the iOS ATT case, and the economics of privacy technologies (differential privacy). |
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Week - 11
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The Gig Economy and Labor; Algorithmic control, surveillance capitalism, and the legal status of platform workers (gig workers). |
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Week - 12
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Digital Markets and Regulation I (Labor Focus); Discussions on the EU Platform Work Directive and demands for algorithmic transparency |
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Week - 13
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Digital Markets and Regulation II (Competition Focus); Digital Markets Act (DMA), self-preferencing, and interoperability. |
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Week - 14
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General Synthesis and Future Outlook; The AI Act, the impact of Generative AI on platforms, and end-of-term review. |
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