CAS CS 591/791 - Fall 2012 - Electronic Commerce
Syllabus
Course Overview:
In spite of the Internet economy's rapid growth over the past two decades,
to roughly 10% of GDP
worldwide (with the US significantly lagging
most developed and some developing economies), the world of electronic commerce
has received relatively little attention in academia. It is true
that economists and management scientists have studied the characteristics
of successful and unsuccessful Internet firms, and that game theorists
and computer scientists have helped pioneer foundations such as the theory of
second-price auctions, and systems innovation, such as the realization of the
massive two-sided markets driven by search engine advertising and ad networks.
However, only recently
have experimentalists deeply tapped into the opportunity that unlike traditional markets,
many aspects of the electronic commerce marketplace are not only publicly
observable, but are readily available for online measurement and data collection.
Therefore, research on questions such as the prevalence of "sniping" on eBay,
the effectiveness of Groupon personalizing its daily deals for subscribers, or
the study of how landlords learn how to price inventory on AirBnB, can all be
evaluated via large-scale measurements, enabling studies that were not previously
possible.
In this class, we will consider electronic commerce from a broad and
inter-disciplinary perspective, reading seminal papers on theoretical
foundations and empirical findings written by the Computer Science, Information
Systems, Marketing, and Econ
communities; we plan to attract course participants and guest lecturers from
these various disciplines. Our goal, however, will then be to focus on quantitative
evaluation of the e-commerce marketplace, and to enable students to conduct
research in this area. A core competency that we will develop is fluency with big
data: experimental methods; best practices and techniques for data collection, data
mining, and statistical analysis; effective presentation of findings; as well as the
ethics of data collection. The capstone project of the course will be an individual or
team research project in which students conduct a quantitative measurement-driven analysis of
a computational aspect of an e-commerce firm or of consumer behavior with
respect to an e-commerce marketplace.
Prerequisites: This course is designed for students who are potentially
interested in pursuing a research career related to Electronic Commerce. Please note
that this course is not about entrepreneurship. While students' backgrounds will vary,
it is expected that students have completed an undergraduate major in an area related to
the course topics (such as CS, Econ, or Marketing). Seniors who have completed all
required coursework except for electives should seek the instructor's permission to enroll.
Class meeting time: Tues/Thurs 3:30-5:00, MCS 180 (Hariri Institute Conference Room).
Instructor:
Prof. John W. Byers
Email: byers @ cs . bu . edu [preferred]
Phone: 617-353-8925 [do not leave voice-mail; use e-mail instead]
Office Hours (Fall 2012): Mon 3:30 - 5 and Thurs 10-11:30, held in MCS 270
Course Requirements and Grading:
There will be three components of the grade in the class:
- Summarization of and in-class discussion of the readings in the course (25%).
- Quizzes and short homework problems (25%).
- Comprehensive, semester-long research project (50%).
For class, students will be expected to read and digest approximately two research papers per week, prior to lecture.
Students will submit short summaries and provide answers to basic questions about the papers prior to discussion.
For each major topic of the course, a group of students chosen in advance will serve as specialists on the topic --
they will be experts on the papers we are discussing, and will be expected to help facilitate the discussion,
brainstorm about research directions, and help with the presentation of the material (or with supplemental material).
To measure students' mastery of the material, we will have two in-class quizzes comprising short answer
problems, and perhaps some longer homework problems.
The capstone project for the course will be a semester-long research project, culminating in a writeup in the
style of a conference paper, and a presentation to the class, which most likely will take the form of a poster
at a class-wide poster session. The topic of the research project will be for students to conduct a
quantitative measurement-driven analysis of a computational aspect of an e-commerce firm or of consumer behavior
with respect to an e-commerce marketplace. Students may work alone or in teams of two, with the expected output
of the teams to be commensurately larger. Suggested project topics and project deadlines will be announced
after the first few weeks of the course. I will expect students in this class to take the project very
seriously and there will be regular interaction with the instructor outside of class to work on the projects ---
ideally, several/many of the projects in the class will eventually lead to publishable papers. A strong venue
for Computer Science students to target could be the experimental track of
the ACM Symposium on Electronic Commerce.
For economics students, the goal of the project would be to write a paper that could develop into a chapter of
the dissertation and potentially a job market paper. Ideally, the ideas in the paper could be developed into
work publishable at a top field or general interest journal.
Course Topics
- Course overview. Technical backdrop; e-commerce challenges and opportunities.
- Data analytics and useful statistical methods.
- Methods and practice of large-scale data collection.
- Auction design and mechanism design.
- User-generated content: mining, valuing, securing.
- Reputation and branding.
- Recommender systems and personalization.
- Social networks and user data.
- Ad auctions and search engine advertising.
- Emerging e-commerce business models: cookie tracking, targeted advertising.
Selected Course Readings and Links
-
Data analytics with Sage, and Sage notebooks.
-
J. Feigenbaum, D. Parkes, and D. Pennock,
"Computational Challenges
in E-Commerce", CACM, January 2009, 52(1), pp. 70-74.
-
Dan Ariely, Axel Ockenfels, and Alvin E. Roth,
"An Experimental
Analysis of Ending Rules in Internet Auctions", Rand Journal of Economics, 36, 4, Winter 2005, 891-908.
-
Ned Augenblick,
"Consumer and Producer
Behavior in the Market for Penny Auctions: A Theoretical and Empirical Analysis", Working paper.
-
John W. Byers, Michael Mitzenmacher and Georgios Zervas,
"Information Asymmetries in Pay-Per-Bid Auctions",
Proc. of 11th ACM Conf. on Electronic Commerce (EC '10),
Cambridge MA, June 2010.
-
JA Chevalier, D Mayzlin,
"The effect of word of mouth on sales: Online book reviews",
National Bureau of Economic Research, Working Paper 10148, December 2003.
-
Michael Luca, "Reviews, Reputation, and Revenue:
The Case of Yelp.com." Harvard Business School Working Paper, No. 12-016, September 2011.
-
D. Godes and J. C. Silva,
"Sequential
and Temporal Dynamics of Online Opinion", Marketing Science, August 2011.
-
John W. Byers, Michael Mitzenmacher and Georgios Zervas,
"Daily Deals: Prediction, Social Diffusion,
and Reputational Ramifications",
In Proc. of the Fifth ACM Int'l Conference on Web Search and Data
Mining, (WSDM 2012), Seattle, WA, February 2012.
-
Ansley Post, Vijit Shah, and Alan Mislove,
"Bazaar:
Strengthening user reputations in online marketplaces",
Proc. of the 8th Symposium on Networked Systems Design and Implementation (NSDI'11), Boston, MA, March 2011.
-
Chris Dellarocas, "The digitization of word of mouth:
Promise and challenges of online feedback mechanisms",
Management Science, 2003, 1407-1424
Project Starting Points: There are a number of interesting papers that appeared at
the 13th ACM Symposium on Electronic Commerce (EC '12) in June.
Below is a partial list. Links to papers are available at the EC website.
Any of these could make for an interesting project starting point.
-
Fabio Drucker and Lisa Fleischer, "Simple Sybil-Proof Mechanisms for Multi-Level Marketing".
-
Sharad Goel, Duncan Watts, Daniel Goldstein, "The Structure of Online Diffusion Networks".
-
Or Sheffet and Peter Bro Miltersen, "Send Mixed Signals - Earn more, Work less".
-
Flavio Chierichetti, Jon Kleinberg and Alessandro Panconesi, "How to Schedule a Cascade in an Arbitrary Graph".
-
John W. Byers, Michael Mitzenmacher and Georgios Zervas,
"The Groupon Effect on
Yelp Ratings: A Root Cause Analysis".
-
Mohammad Mahdian, Arpita Ghosh, Preston McAfee and Sergei Vassilvitskii,
"To match or not to match: Economics of cookie matching in online advertising".
-
Moshe Babaioff, Shahar Dobzinski, Sigal Oren and Aviv Zohar, "On Bitcoin and Red Balloons".
-
Abraham Othman and Tuomas Sandholm, "Profit-Charging Market Makers with Bounded Loss,
Vanishing Bid/Ask Spreads, and Unlimited Market Depth".
- Eytan Bakshy and Dean Eckles,
"Effects of Social Cues and Tie Strength in Social Advertising: Evidence from Field Experiments".
- Nicole Immorlica, Rachel Kranton and Greg Stoddard,
"Striving for Social Status".