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Online bidding services were disrupting the auction industry when Pai-Ling Yin started pursuing her PhD in economics in 1997 at Stanford University. She seized on the data that these services generate to study and understand the new economy emerging from this industry in transition.
“The internet accelerates and scales up transactions,” said Yin. “All these auctions were happening online. I could watch what was happening. ‘Who is going to succeed? Who is going to fail? How is it going to shape the future?’”
These questions led Yin to a PhD thesis on the economics of online auctions for personal computers. They also framed her two decades in academia, where she researched and taught technology strategy, innovation, and entrepreneurship at Harvard Business School, the Massachusetts Institute of Technology (MIT) Sloan School of Management, Stanford’s Department of Economics, and the University of Southern California’s Marshall School of Business.
We are trying to think about, ‘What is the long-term value of any action we take? How do we make sure that we’re giving our customers the best experience?’
In 2021, her former advisor at Stanford, Pat Bajari, who is now chief economist and vice president of the Core AI team at Amazon, recruited her to join his team as a senior manager of research science. Core AI uses economics, statistics, and machine learning to understand and design the complex economy of Amazon buyers and sellers.
Today Yin manages a team of economists, program managers, and engineers tasked with helping internal partners across Amazon research questions about the economic impacts of their decisions.
“We are trying to think about, ‘What is the long-term value of any action we take? How do we make sure that we’re giving our customers the best experience? Of the many options we have to interact with customers, which seem to delight them the most?’” Yin explained.
For example, the team works with Amazon’s concessions department to model the best way to respond when a customer returns a product. There are a number of options; each has costs and benefits. Which one best assists customers shopping in the Amazon Store?
The highlight of the job, Yin said, is organizing teams of experts across disciplines such as operations, engineering, economics, and data science to answer these types of questions.
“We’re bringing the best of the best in all these different fields. Many are not my area of expertise. I’m learning every day and engaged in interesting discussions,” she said.
A lifelong learner
Yin, whose parents immigrated to the US from China via Taiwan, is the first US-born member of her immediate family. She completed undergraduate studies at Indiana University in Bloomington on a scholarship from the Wells Scholars Program and earned simultaneous degrees in economics, French, and mathematics, graduating summa cum laude in each.
During her junior year, she was selected as a Truman Scholar, which allowed her to pursue a master’s degree in regulation at the London School of Economics and Political Science. After her time in London, she went to Stanford and met Bajari.
“At the time, the internet was fairly new,” Yin said. “Online businesses had just started, and I was interested in all these new industries.”
Yin was at the forefront of a trend where trained economists end up teaching at business schools.
Her academic research and teaching career focused on the type of industrial organization (i.e., the structure of players in an industry) that emerges from innovation in technology, which can change the structure by changing the cost of entry and transactions in that industry.
“Any new innovation is going to create this new way of economic actors interacting,” Yin said of the industrial organization concept. “What players emerge? What new technologies are spawned from the original technology? How do industries now interact? How do buyers and sellers interact?”
While teaching technology strategy at MIT, Yin noticed an industrial organization emerging around mobile phones and apps following the introduction of the smartphone in 2007. The moment had echoes of the early days of online auctions. She was intrigued and began to study the mobile app economy from her office in Cambridge.
“The beginning of that whole industry was literally in South San Francisco, not even in the Bay Area,” she said. “All these little startups were finding these little, little offices and doing their things. And I really wanted to be out closer to the action.”
That desire to be at the center of the emerging mobile-computing industry led her back to Stanford, where she co-founded the Mobile Innovation Group with another of her former advisors, economist Tim Bresnahan. Yin’s research focused on entrepreneurship in the mobile-app industry as it emerged and evolved with competing mobile services.
This line of research led to a greater focus on entrepreneurship, which she taught at USC from 2016 until she started at Amazon.
While at USC, Yin co-created a required course for the MBA program on critical thinking. The curriculum is centered on helping students deal with ambiguity — how to make progress in the face of uncertainty. Her former students who are now at Amazon tell her that they regularly apply lessons learned from the course, such as taking a few minutes to ask one more question about a problem to advance their thinking.
“That was the spirit of the class,” she said. “What are these little tools that you might think of as small interventions, which are not going to get to optimum thinking but are going to get to better thinking? Then, as you practice those skills, you’ll get faster and better and, over time, develop that muscle.”
“As a teacher, Pai-Ling empowered her students to think outside the box — each answer begets a new question, and great solutions often come by probing wider and deeper,” said Darren Setiawan, a senior product manager at Amazon who was Yin’s student, teaching assistant, and research assistant at USC. “I was especially fond of her courses and often refer back to her frameworks when dealing with complex work — and life — decisions.”
Practice what you teach
When COVID-19 hit, Yin had been in academia for nearly two decades and was ready for a change. The opportunity to join Amazon brought with it a chance to put into practice her years of training as an economist and research scientist. For example, she brings short- and long-term thinking to the problems her team is asked to solve.
“In the short run, the problem is, what’s the cost-benefit analysis of the issue we’re facing now? But the world is dynamic and changing. You know that analysis has to be redone in a few years. How do we think about anticipating flexibility in the models that we’re creating?” she explained.
The teacher in her also embraces ambiguity and looks forward to the next big problem that her team gets to solve, whatever it is.
“That’s the exciting part,” she said.
Solving that problem, she noted, will require collaboration among people with a diverse set of expertise — economists, data scientists, psychologists, engineers, and program managers. That’s why she recommends that young scientists learn to appreciate the world through multiple lenses: the lenses of their specific areas of expertise as well as the lenses of their coworkers and colleagues.
“You have expertise, and that is wonderful,” she said, as if speaking to a group of newly minted PhDs. “But it is now your job to figure out where you can contribute and where you are going to learn from others. That approach will contribute to a richer life in both social and problem-solving ways.”
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