What Investors Can Learn as Luckin Loses Its Buzz

Successful Startups Tell Good Stories. Sometimes They’re Just Fantasy.

Apr 03, 2020
Management

SMITH BRAIN TRUST –  Successful entrepreneurs are good storytellers – and in a way, they have to be. They’re selling a product, to consumers, to investors and potential shareholders, to everyone.

But sometimes – as appears to be the case with China’s buzzy internet startup coffee chain – the story is a little more fiction than nonfiction, says Maryland Smith’s Brent Goldfarb. “Sometimes it's fraud, which is typical for bubble stocks,” he says.

Shares of Luckin Coffee, the biggest domestic coffee chain in China, plunged nearly 80%, after its chief operating officer was accused by his own company of fabricating much of the chain’s reported sales in 2019.

The news shattered some illusions for fans of the chain, which went public in the United States last May. Luckin has seen surging store growth, but continuing financial losses.

At the end of 2019, the chain had 3,680 stores, up from just 1,189 the year prior. It was reporting some 9.3 million monthly transacting customers, up from 1.9 million. And its revenues were said to be up more than sixfold from the year earlier period, which at the time seemed encouraging. Maybe it was storytelling.

Goldfarb has had doubts from the start.

Goldfarb is an associate professor and the academic director of the Dingman Center for Entrepreneurship – and co-author with faculty colleague David A. Kirsch of "Bubbles and Crashes: The Boom and Bust of Technological Innovation."

Luckin is a traditional business, he said in late 2019. Luckin claimed to use artificial intelligence (AI) for operations in a way that would create efficiencies, and allow it to keep prices low – well below Starbucks, China’s coffee leader. But the prices, heavily subsidized by investors, have always seemed too low, Goldfarb says. “They are selling coffee, and I don't see this as a tech company,” he said.

“At the end of the day, Luckin will have to raise prices. It then becomes a question of how much demand will fall. The elasticity of demand is the key question, and how much they will need to raise prices.” The basic narrative is not dissimilar to companies such as Uber, Lyft and WeWork. All three have been framed as tech companies when, in essence, Uber and Lyft are taxi companies, and WeWork is a real estate company. The companies saw quick, expansive investor-fueled growth. However, despite their ubiquity, none has figured out how to turn a profit.

When narratives cannot be matched by reality, there is a strong incentive to say that they do. This is different from other fraudulent companies like Theranos only in details, not in kind. In both cases, a storyline was sold to investors that was too fantastic to be true, and in each case, details were manufactured to support that storyline. It’s an interesting question whether people such as former Theranos CEO Elizabeth Holmes or Luckin’s suspended COO Jian Liu set out to commit fraud, or simply constructed a storyline that was too distant from reality and then tried to create the favorable reality by fiat so as not to burst the bubble, Goldfarb says.

“There are enough investors who believe that (Luckin’s) growth can be converted into profits, or at least, greater fools will believe so,” Goldfarb said in 2019. “It's a great narrative – the market is very large, and growth is really astounding. The one thing we've learned with these sorts of ‘Get Big Fast’ strategies is that a lot has to go right for companies to turn a profit.”

And right now, for Luckin, too much is going wrong.

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About the Expert(s)

Brent Goldfarb

Dr. Brent Goldfarb is Associate Professor of Management and Entrepreneurship in the M&O Department at the University of Maryland's Robert H. Smith School of Business. Goldfarb's research focuses on how the production and exchange of technology differs from more traditional economic goods, with a focus on the implications on the role of startups in the economy. He focuses on such questions as how do markets and employer policies affect incentives to discover new commercially valuable technologies and when is it best to commercialize them through new technology-based firms? Why do radical technologies appear to be the domain of startups? And how big was the dot.com boom? Copies of Dr. Goldfarb's publications and working papers have been downloaded over 1200 times.

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