PhD Student

Ilan Morgenstern

PhD ’24
Ilan Morgenstern
Ilan Morgenstern
I have been lucky to have faculty advisors who I look up to as role models, so following their career path is a natural choice.
November 29, 2022

Ilan Morgenstern believes that it’s helpful to fail sometimes. In fact, in the world of research, being able to make mistakes is crucial — mistakes tell you which ideas are worth pursuing. It’s also important to make mistakes in front of the right people. As a PhD candidate working with Stanford GSB professors Daniela Saban and Kostas Bimpikis, Morgenstern says that he’s found advisors who are not only trusted resources, but friends he can be himself around.

“In most universities you will find faculty and colleagues that you have common interests with,” he says, “but here I was very lucky to find a group that had a lot of people that were a fit on the research interests, and also on a personal level — people I can not only work with and talk to, but also trust in and with whom I have good personal relationships.”

Born and raised in Mexico, Morgenstern studied applied math and economics at ITAM, one of the country’s leading universities. Morgenstern was drawn to Stanford, in part, for its faculty like Saban and Bimpikis, with whom he co-authored a paper on data privacy and competition.

He hopes that his research, which investigates questions around data collection, privacy, and the design of marketplaces and platforms, will allow individuals and firms to better understand how to interact with their own data, especially as privacy has become a central issue in the last few years.

How did you become interested in data privacy and technology?

When I started my PhD there was a lot of talk about regulating different types of data tracking technologies — especially in Europe, there was this big piece of legislation called the GDPR which enforces data collection rules to protect peoples’ privacy). California was also considering a piece of legislation along those lines, that they later enacted. At the same time, Apple started to advertise privacy as a feature of the iPhone. So at the time, consumers and governments were starting to care more about policies related to data privacy. And then we were also seeing the emergence of firms selling privacy to customers.

And while this was happening, some large tech companies were expanding by acquiring other companies. There were questions about the implications of allowing one of these big firms to buy other firms, which would help them gather more data about consumers and expand operations in other directions.

“I would say that my message around data is that maybe our views on privacy should be more nuanced.”

For example, Amazon had bought Whole Foods to expand in the grocery market. They had many reasons to do so, but perhaps one of them was to get more data about consumers’ offline shopping patterns, and in some sense build a link between its operations in the offline and the online world. I’m motivated by questions around moves like that: What were their incentives for expanding their reach? What are the implications of these types of market structures for consumers and for other firms?

You note that privacy protection is now a product feature. What are the implications of that?

Consumers have become more aware that some companies know more about them than they might be comfortable with and have developed privacy concerns. There’s some evidence that privacy-oriented regulation like the GDPR was making it harder for firms to gather data on consumers that care about their privacy because they would opt out of data-tracking. In turn, it was easier to track consumers that didn’t opt-out of data tracking or who appeared not to care about their privacy. So in that way, more was known about the less privacy-concerned consumers.

The same argument applies for products or services that limit data tracking. Firms may accumulate less data from consumers that opt-out of tracking but, on the other hand, may end up having cleaner data for consumers that still allow their data to be tracked.

Consumers may not be aware of ways their data could be used to serve their interests. What’s an example?

One thing that I’m currently working on is trying to frame privacy as not something that is black or white. What the research shows is that it might benefit consumers if companies have some, but not all, data. For instance, a lot of services that are available online or through social media are free to the consumer because of their data. By using the application or website, they generate data, and companies can use the data to sell ads. If we were back in a world a couple decades ago where companies weren’t as capable in using data, some services might not be available or might not be free. In that sense, consumers may pay a cost if we don’t allow firms to track any data.

So our personal data is the currency that we pay for a free product, like using Hulu without taking a subscription.

Yes, that’s one way of looking at it, in a similar way as you can watch Hulu with ads and “pay” with your time and attention. In our research specifically, we find that companies might be willing to sell some products at a discount with the hope that in doing so, consumers will generate new data that, in the future, firms can find some sort of value or information from. This is potentially a win-win in that consumers get a lower-cost product up front and a firm gleans more data down the line. It’s not a sure thing — and it’s important to remember that the setting or relationship between the firm and the consumers is really important. There are definitely scenarios in which consumers might be worse off in the end as companies acquire more data.

I would say that my message around data is that maybe our views on privacy should be more nuanced. It’s not that we should never allow for data collection or that consumers should always be worried. But my point is that it’s not always clear where consumers will be harmed and where they’ll be helped — there’s usually a trade-off between what they are getting for their data and what they are losing. There’s no general answer.

Earlier you brought up the consolidation of companies — how does this impact how firms collect and track data?

One thing we do in our research is compare what happens when firms cannot track data versus when they can, and what happens if consumers take into account whether their data is being tracked when making decisions.

Even if consumers don’t realize the value that firms can generate from their data, firms might still be incentivized to give them discounts or other benefits as a way to collect their data. Our research findings suggest that competition among firms is something we should study more closely. Suppose there’s only one firm, and only one option for consumers to buy products or services from. In terms of data generated by those purchases, it’s likely that it will be more negative for the consumer for a monopoly to have their data. On the other hand, if we instead have firms that compete for consumers’ purchases and their data, consumers may be better off.

Specifically, we find that when firms are competing, data-tracking mechanisms can still make the consumers better off because the competition will drive firms to lower their prices or give high discounts to consumers if they interact with firms. Whereas if there’s only a monopoly, there is less of an incentive to give the consumer any benefits because there’s no competition.

What’s your hope after you’re finished with your program? Where do you want to take your research?

I’ve really enjoyed my PhD; I have been able to pursue research projects that I’m excited about while working with a fantastic group of people from whom I’ve learned a lot. My hope is to get an academic position in a business school after I graduate. I’ve come to appreciate the freedom of being able to work on my own research questions that academic life allows, and the possibility of interacting with students and potentially impact their lives through teaching as well, so I want to continue along the academic path. I have been lucky to have very good faculty advisors who I look up to as role models, so following their career path is a natural choice as well.

Photos by Tricia Seibold

Ilan Morgenstern
Ilan Morgenstern
PhD ’24
Mexico City, Mexico
B.Sc. in Applied Mathematics, Instituto Tecnológico Autónomo de México (ITAM)
BA in Economics, ITAM
Field of Study
Operations, Information & Technology
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