COMPM041 - Web Economics
Note: Whilst every effort is made to keep the syllabus and assessment records correct, the precise details must be checked with the lecturer(s).
|Code||COMPM041 (Also taught as: COMPGW02)|
|Prerequisites||Normally offered only to students in computer science related programmes because basic programming skills are required.|
|Taught By||Emine Yilmaz (50%) Jun Wang (50%)|
|Aims||The course is intended to provide an introduction of the computing systems and their economics for the production, distribution, and consumption of (digital) goods and services over the Internet and web. While the basic economic principles are covered to understand the business aspects of web-based services, the course is primarily focused on the computational and statistical methods for implementing, improving and optimizing the internet-based businesses, including algorithmic mechanism design, online auctions, user behavior targeting, yield management, dynamic pricing, cloud-sourcing, social media mining and attention economics. Practical applications such as Google’s online advertising, Ebay’s online auction, and Amazon’s cloud computing will also be covered and discussed.|
|Learning Outcomes||The students are expected to master both the theoretical and practical aspects of web economics. More specifically, the student will: |
- Web basics: HTTP, HTML5 referrer, Link and Click-through analysis, etc
- Basic Economic Principles and Economic analysis:
- Micro vs. Macro economics
- Basic elements of Supply and Demand
- Incentives: Game theory, and Auction theory
- Business Models in the Internet:
- auction and bidding (the Ebay Model, swoopo, and b2c and b2b auctions (alibaba)
- Subscription (Compulsory license, dropbox premier model, spotify, apple icloud, pay per use).
- Online retailing (Amazon, Apple Apps).
- digital goods & bundling
- Computational advertising
- Vickrey auction and the second price auction
- Search-based advertising, Contextual advertising and Behaviour targeting, Demand-side platform and Real-time bidding, Ad exchange and futures and options
- Digital Right Management, Spam/fraud control and Internet radio
- Computing as a service/utility
- Social media mining
Management and optimization
- Dynamical pricing models (air-tickets) and Yield management and scheduling (online advertising)
- Search engine optimization
- Attention economics and Personalization and Long tail
- Prediction market and its accuracy
- Human computing and Social computing systems
- Crowdsourcing and Amazon Mechanical Turk (MTurk) and Collective intelligence
- System design (ESP game, reCAPTCHA etc)
- Bittorrent and Peer-to-peer file sharing
Method of Delivery
A website or/and moodle webpage will be created for the course and the course materials such as lecture notes, sample codes, will be shared. By using moodle, students will also be able to discuss relevant ideas and have questions answered by the lecturer.
The module has the following assessment components:
- Written examination 2.5 hours (70%)
- Coursework (30%)
To pass this module, students must:
- Obtain an overall pass mark of 50% for all components combined;
- Obtain a minimum mark of 40% in each component worth ≥ 30% of the module as a whole.
 Noam Nisan (Editor), Tim Roughgarden (Editor), Eva Tardos (Editor), Vijay V. Vazirani (Editor), Algorithmic Game Theory, Cambridge University, 2007.
 David Easley and Jon Kleinberg, Networks, Crowds, and Markets: Reasoning About a Highly Connected World, Cambridge University Press, 2010
 R. Preston McAfee, Introduction to Economic Analysis www.mcafee.cc/Introecon/IEA.pdf
 Nir Vulkan, The Economics of e-Commerce, Princeton University Press, 2003
 Carl Shapiro, Hal R. Varian, Information rules: a strategic guide to the network economy, 1999