Tim Derdenger
Associate Professor of Marketing and Strategy Carnegie Mellon University
- Pittsburgh PA
Biography
Prior to Carnegie Mellon, Tim earned his Ph.D. in Economics from the University of Southern California and a B.B.A. from The George Washington University. His research interests are divided into two areas: the study of technology and sports markets. Within technology, his research focuses on platform markets with emphasis on bundling, tying and exclusive arrangements in dynamic environments as well as empirical methodologies to estimate dynamic demand models for technology products using aggregate sales data. With sports markets, his research is centered around celebrity endorsements and how to optimize their impact on product sales.
He has publications in Journal of Marketing Research, Marketing Science, Management Science, Quantitative Marketing and Economics, Marketing Letters, and Customer Needs and Solutions. He is also an Associate Editor for Management Science (Marketing), a guest associate editor for the Journal of Marketing Research and a former member of the editorial review board for Marketing Science.
Areas of Expertise
Media Appearances
How hosting the NFL Draft has long boosted a city’s market value
The Independent online
2026-04-07
When the NFL draft arrives in Pittsburgh in April 2026, city officials are sure to tout projected economic impact figures. They will likely point to the US$73 million generated by Green Bay, Wisconsin, and the surrounding area in 2025, the $213 million generated by Detroit in 2024, or the $164 million by Kansas City the year prior.
I’m a sports marketing researcher who studies the economics of celebrity endorsements, and I view these short-term, direct economic impact numbers with skepticism.
(Tim Derdenger authored this article. Read the piece to hear more about his expert take on a city's benefit of hosting a mega-event)
Dating choices or draft picks — the cognitive science behind either is similar, CMU professors say
TribLive online
2026-04-10
Tim Derdenger, a marketing and strategy professor, says planning is key when scouts and analysts determine their moves in the NFL Draft. But that also comes with planning for the unplanned, he said.
“You have to have a plan in place to adapt to the fluidity of the draft,” Derdenger said. That plan comes to light when you have the right culture in place.”
(Read more of his expert commentary in the article)
Why this CMU professor says NIL has created more parity in college football
Pittsburgh Post-Gazette online
2025-08-30
Tim Derdenger’s research with co-author Ivan Li found that NIL has led to more parity in college football, with closer games, more upsets and greater talent distribution.
“[NIL has] led to fantastic outcomes for college football,” Derdenger told the Post-Gazette. “It's brought more competition into the league and into the games. It's great for fans. It's great for the players.”
(Read the article for more expert commentary from Tim Derdenger)
Media
Social
Industry Expertise
Accomplishments
Poets & Quants for Undergrads: Top 50 Undergraduate Business Professors
2025-12-01
“Derdenger’s classes simulate real-world situations, and his research directly applies to solving contemporary business problems. This is exactly the type of professor an undergraduate in business needs – someone who can create a learning environment where ideas, theories, and strategies can be applied to actual situations, not just business cases or simulations...” – Dr. John Gasper
2025 George Leland Bach Excellence in MBA Teaching Award Winner
2025-05-09
Voted on by the graduating MBA class.
Education
University of Southern California
Ph.D.
Economics
University of Southern California
M.A.
Economics
The George Washington University
B.B.A.
Business Administration
Links
Articles
Does Personalized Pricing Increase Competition? Evidence from NIL in College Football
Management ScienceIvan Li, Tim Derdenger
2025-09-08
We investigate the impact of personalized pricing through Name, Image, and Likeness (NIL) rights within college athletics on the recruitment of high school football players by college programs. We focus on whether the new policy disrupts competitive balance by increasing the concentration of talent among top-ranked institutions. Using a data set that encompasses pre- and post-NIL recruitment patterns to examine the distribution of 3, 4, and 5* recruits at college football programs, we find a notable increase in the dispersion of talent. Contrary to the hypothesis that NIL would lead to a “rich get richer” dynamic, we observe a tendency for lower-ranked football programs to attract higher-quality recruits post-NIL, especially among 5- and lower ranked 4* athletes. Furthermore, we show that post-NIL 3* recruits are sacrificing schooling for NIL money and are attending colleges that are less selective and have lower SAT class averages and whose graduates earn a lower mid-career income. We also do not find evidence that schools that spend more money on football are attracting better talent post-NIL. Competitiveness improves post-NIL as sportsbooks set smaller point differentials even after controlling for talent, performance, and the transfer portal. Ultimately, this study offers a comprehensive examination of NIL’s short-term effects on competitive balance and sets the stage for ongoing research into the long-term consequences of this landmark policy change.
CCP Estimation of Dynamic Discrete Choice Demand Models with Segment Level Data and Continuous Unobserved Heterogeneity: Rethinking EV Subsidies vs. Infrastructure
Marketing ScienceCheng Chou, Tim Derdenger
2025-03-21
When multiple groups of consumers reside in the same market, we determine that we can write each group’s conditional choice probabilities (CCPs) as a function of unobserved consumer heterogeneity. Moreover, we can specify choice probabilities of one group as a function of another by shifting the unobserved component. Armed with our novel CCP estimator, we develop an approach to identify and estimate a dynamic discrete demand model for durable goods with nonrandom attrition of consumers and continuous unobserved consumer heterogeneity but without the usual need for value function approximation or reducing the dimension of state space by ad hoc behavioral assumptions. We illustrate the empirical value of our method by estimating consumer demand for electric vehicles (EVs) in the state of Washington during the period of 2016–2019. We also determine the impact of a different federal tax credit based on the electric range of a car rather than the size of the battery, which was the existing policy during the data period, and we evaluate how best to seed a nascent market that presents indirect network effects to drive faster adoption. Should the government incentivize adoption through consumer tax credits or through EV infrastructure?
