Rahul Telang
Trustees Professor and Program Chair Carnegie Mellon University
- Pittsburgh PA
Rahul Telang is interested in how information and communication technologies (ICTs) information impact consumers, business and policies.
Biography
Areas of Expertise
Media Appearances
Scams and frauds: Here are the tactics criminals use on you in the age of AI and cryptocurrencies
The Conversation online
2025-09-18
Rahul Telang (Heinz College) explains the scam and fraud tactics criminals are using in the age of AI.
Hollywood plunges into all-out war on the heels of pandemic and a streaming revolution
ABC News online
2023-07-17
Rahul Telang, a Carnegie Mellon University professor and co-author of the book “Streaming, Sharing, Stealing: Big Data and the Future of Entertainment,” says an entire era of change was condensed into two years.
“What is happening right now was bound to happen. With streaming, the whole business got disrupted,” says Telang. “So naturally, they’re complaining, ‘We need our fair share.’ But how do you decide what’s a fair share? There has to be a transparency about where the money is coming from and where it’s going. Until this gets resolved, this issue will keep coming up.”
Ransomware, a love story
Lenovo Late Night I.T. online
2021-12-01
Ransomware attacks have reached record levels, and the breaches aren’t letting up. Two cybersecurity heavyweights talk threat intelligence, business continuity, crime as a service, and the unexpected upside of ransomware.
Is the cookie web tracker dying?
TheNextWeb online
2021-08-07
“When advertisements became popular, especially with Google and all these ad markets, then there was more momentum toward finding and tracking data because the advertising had to be personalized,” said Rahul Telang, a professor of information systems at Carnegie Mellon University.
What You Need To Know About Dark Data
Forbes online
2019-10-27
The concept of dark data sounds ominous, even sinister. But it is very important in the technology world. “To make it more relatable, dark data is like all of the photos on your devices,” said Sky Cassidy, who is the CEO of MountainTop Data. “Most of them will never be used or even viewed again, but they are there. So as for dark data, it’s all the information companies collect in their regular business processes, don’t use, have no plans to use, but will never throw out. It’s web logs, visitor tracking data, surveillance footage, email correspondences from past employees, and so much more.”
For most companies, there is usually an enormous amount of dark data. According to Rahul Telang, who is the professor of information systems at Carnegie Mellon University's Heinz College, its about 90% or so.
Success Of Net Neutrality Lawsuit Depends On Role Of Precedent In FCC Decisions
90.5 WESA online
2018-01-22
However, professor of information systems management at Carnegie Mellon University Rahul Telang said he believes that the FCC will be successful.
Rahul explained that in the initial installation of net neutrality in 2015, the Obama administration FCC exercised their right to label the internet as a telecommunication service, which requires heavy regulation. The current FCC has done the same thing, instead labeling the internet as an information system, which is lightly regulated.
Media
Social
Industry Expertise
Education
Carnegie Mellon University
Ph.D.
Industrial Administration (Information Systems)
2002
Carnegie Mellon University
M.S.
Industrial Administration (Information Systems)
1999
Indian Institute of Foreign Trade
M.B.A.
1997
Birla Institute of Technology and Science
B.E.
Electrical and Electronic Engineering
1994
Articles
When TV Becomes a Stream: Content Decisions of a Video On Demand Service
SSRN2020
Entertainment television today is being increasingly consumed via online video on demand (VOD) services. A VOD service is less constrained compared to the traditional (linear) TV in terms of the number of programs it can simultaneously offer, allowing its viewers to watch a program at a time of their choice. On the one hand, offering more programs can dilute the quality of the offered programs; while on the other, the service benefits from the time flexibility that viewers now have on their side. n this paper, we theoretically study how the ‘on-demand’feature affects the number of programs and the investment in their qualities (by a monopolist) when viewers are heterogeneous in their keenness to watch television programs, their preferred genre (taste preference) and, importantly, their preferred time to watch the programs (time preference).
Frontiers: virus shook the streaming star: estimating the COVID-19 impact on music consumption
Marketing Science2022
Many have speculated that the recent outbreak of COVID-19 has led to a surge in the use of online streaming services. However, this assumption has not been closely examined for music streaming services, the consumption patterns of which can be different from video streaming services. To provide insights into this question, we analyze Spotify’s streaming data for the weekly top 200 songs for two years in 60 countries between June 2018 and May 2020, along with varying lockdown policies and detailed daily mobility information from Google.
The impact of ride-hailing services on congestion: Evidence from indian cities
Manufacturing & Service Operations Management2023
Problem definition: Early research has documented significant growth in ride-hailing services worldwide and allied benefits. However, growing evidence of their negative externalities is leading to significant policy scrutiny. Despite demonstrated socioeconomic benefits and consumer surplus worth billions of dollars, cities are choosing to curb these services in a bid to mitigate first order urban mobility problems. Existing studies on the congestion effects of ride-hailing are limited, report mixed evidence, and exclusively focus on the United States, where the supply consists primarily of part-time drivers.
Incentive misalignments in programmatic advertising: Evidence from a randomized field experiment
Management Science2023
In programmatic advertising, firms outsource the bidding for ad impressions to ad platforms. Although firms are interested in targeting consumers that respond positively to advertising, ad platforms are usually rewarded for targeting consumers with high overall purchase probability. We develop a theoretical model that shows if consumers with high baseline purchase probability respond more positively to advertising, then firms and ad platforms agree on which consumers to target. If, conversely, consumers with low baseline purchase probability are the ones for which ads work best, then ad platforms target consumers that firms do not want to target—the incentives are misaligned.
The consequences of rating inflation on platforms: Evidence from a quasi-experiment
Information Systems Research2023
Informative online ratings enable digital platforms to reduce the search cost for buyers to find good sellers. However, rating inflation, a phenomenon in which average rating increases and rating variance across listings decreases, threatens the informativeness of ratings. We empirically identify the consequences of rating inflation by conducting a quasi-experiment with a digital platform that exogenously changed its rating display rule in a treated neighborhood, which resulted in rating inflation.
