Catherine Yang
Associate Professor of Management
Research Expertise: Information technology, data mining, e-marketing, e-commerce
Associate Professor Catherine Yang focuses her research in the field of data mining, including web mining, market segmentation, predictive modeling, Internet marketing and formal modeling in e-commerce. She is interested in developing a way to better integrate data mining and Internet marketing to analyze consumer behavior, giving companies tools to make better choices for committing revenue streams to personalized and targeted advertising and marketing. Her research papers include “A Knowledge Driven Approach to the Evaluation of Online Personalization Systems,” “A Pattern-Based Approach to Segmenting Customer Transactions,” and “Free-Shipping Promotions and Internet Shopping.”
Most recently, Yang and her co-author Assistant Professor Balaji Padmanabhan of the University of South Florida have developed a method for identifying users based on their online browsing behavior. Their study “Clickprints on the Web: Are There Signatures in Web Browsing Data?” details formal methods to determine the optimal amount of user data that must be aggregated before unique clickprints can be deemed to exist. Their main objective: to deter online fraud, which costs the Internet economy billions of dollars annually. The same information could also be valuable for web marketers.
Yang earned her Ph.D. in operations and information management from the Wharton School at the University of Pennsylvania. Before earning her doctorate, she earned a M.A. in managerial science and applied economics from the Wharton School. She received her B.E. in management of information systems from the School of Economics and Management at Tsinghua University in China.
Room 3418
269 Business Intelligence Technologies – Data Mining
Data are a key source of intelligence and competitive advantage for business organizations. With the explosion of electronic data available to organizations and demand for better and faster decisions, the role of data-driven intelligence is becoming central.
Give Air Passengers an “Out” during Delays
Marketing Science, 2012
Instead of holding customers captive in an idled plane on a tarmac during unforeseen delays, airlines should give passengers the choice to leave or stay—and compensate them either way.
UC Davis Researchers: Give Airline Passengers Options
A study conducted by UC Davis researchers concludes airlines should give passengers options if flights are delayed on the tarmac. In addition to enhancing convenience, researchers said offering passengers the option to deplane and reboard or cancel or change tickets could stave off costly government regulation and increase customer loyalty, ultimately improving airline profits.
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Airlines Can Improve Bottom Line by Compensating Captive Passengers
(Davis, CA) — Instead of holding customers captive on a tarmac during unforeseen delays, airlines should give passengers the choice to leave or stay — and compensate them appropriately.
Discovery of Online Shopping Patterns across Websites
INFORMS Journal on Computing, 2011
In the online world, customers can easily navigate to different online stores to make purchases. The products purchased on one site are often associated with product purchases on other sites (e.g., a hotel reservation on one site and a car rental on another site). Whereas market basket analysis is often used to discover associations among products for brick-and-mortar stores, it is rarely applied in the online setting where consumers navigate among different online stores to buy products.
Product Selection for Promotion Planning
Knowledge and Information Systems, 2011
This paper by Assistant Professor Catherine Yang and co-author Chunhui Hao of the Chinese Academy of Sciences addresses a very important question—how to select the right products to promote in order to maximize promotional benefit.
Catherine Yang Awards
207 Management Information Systems
Information technologies are pervasive, and transform what they touch. This course covers questions such as: What technologies are critical to operations, marketing, decision making and e-business activities? How has the role of technology changed over time, and what factors govern the choice of IT applications? How does IT influence business strategy, and strategy in other areas such as marketing and operations? What are the key challenges in managing IT resources, and what factors limit business’ ability to exploit the latest information
Discovery of Periodic Patterns in Sequence Data: A Variance-based Approach
INFORMS Journal on Computing, 2011
In this paper, Assistant Professor Catherine Yang and co-authors Balaji Padmanabhan from the University of Southern Florida and Hongyan Liu and Xiaoyu Wang from Tsinghua University address the discovery of periodic patterns in sequence data. Building on prior work in this area, the authors present definitions and new methods for characterizing and identifying four types of periodic patterns.
Product Selection for Promotion Planning
Knowledge and Information Systems, 2011
In this paper, Assistant Professor Catherine Yang and co-author Chunhui Hao from the Chinese Academy of Sciences address a very important question—how to select the right products to promote in order to maximize promotional benefit.
Web User Behavioral Profiling for User Identification
Decision Support Systems, 2010
In this paper, Assistant Professor Catherine Yang proposes a simple, yet powerful approach to profile users’ web browsing behavior for the purpose of user identification. The importance of being able to identify users can be significant given a wide variety of applications in electronic commerce, such as product recommendation, personalized advertising, etc.
Toward User Patterns for Online Security: Observation Time and Online User Identification
Decision Support Systems, 2010
Research in biometrics suggests that the time period a specific trait is monitored over (i.e. observing speech or handwriting “long enough”) is useful for identification. Focusing on this aspect, this paper by Assistant Professor Catherine Yang and co-author Balaji Padmanabhan from the University of South Florida presents a data mining analysis of the effect of observation time period on user identification based on online user behavior.
Stick It Out or Walk Out: Customers as Captive Sardines
Marketing Science, 2009
High demand for a service means more revenue and more profits for the service provider. However, when peak demand is unpredictable and it occurs in a confined space (e.g., restaurants, resorts, trains, and airplanes), the service quality tends to decline. Customers are likely to have a bad experience because of longer wait times, overcrowded spaces and inattentive employees. That result: lost revenue because of customer dissatisfaction and defection. Whether the customer chooses to stick it out or walk out, future profits are in jeopardy.
The Online Customer: New Data Mining and Marketing Approaches
Cambria Press, 2006
In her recently published book, The Online Customer: New Data Mining and Marketing Approaches, Assistant Professor Catherine Yang details how data mining and marketing approaches can be used to study and solve Web marketing problems. The book uses a vast dataset of Web transactions from the largest online retailers, including Amazon.com. In particular, Yang shows how to integrate and compare statistical methods from marketing and data mining research.
Data Mining for Marketing Solutions
In her new book, The Online Customer, Assistant Professor Catherine Yang details how data mining and marketing approaches can be used to study marketing problems. The book uses a vast dataset of Web transactions from large Internet retailers.