The secret to finding the best business locations
How a physicist identified prime business locations by studying the relationships between retailers.
By Jessica Seid, CNNMoney.com staff writer

NEW YORK (CNNMoney.com) -- A conversation following dinner with a friend about two years ago sparked the idea that maybe a model could be used to find potentially successful locations for new businesses.

"Physicists think they can make a model out of almost everything," said Pablo Jensen, author of Network-based predictions of retail store commercial categories and optimal locations.

But since then, he has proved that the relationship between businesses can not only be quantified but also applied to real cities and towns to find optimal locations for stores, which has been empirically tested in Jensen's home base of Lyon, France.

"Thanks to the quantification of retail store interactions I can construct a mathematical index to automatically detect promising locations for retail stores," Jensen wrote in his paper.

After collaborating with an economics laboratory in Lyon, Jensen found that interactions between stores were analogous to attractions and repulsions between atoms.

For example, bakeries repel other bakeries and second-hand stores. But bakeries attract drug stores and butchers.

As Jensen put it, a butcher would be a friend to a bakery, but other bakeries are enemies. From there he could determine the potential success of various locations in the city.

"When you look at a location for a bakery you look for more friends than enemies. A location with many friends and few enemies is a good location."

Sounds cute, but would Jensen's theory stand up to empirical tests?

By comparing data on bakeries in Lyon between 2003 and 2005, Jensen examined the number and location of bakeries that opened as well as closed during that time.

And it turned out that the bakeries that closed were on the low quality sites, with more enemies than friends, and the new bakeries that opened, on average, were on good potential sites, as classified by the index.

Now the chamber of commerce in Lyon is using Jensen's index to help small business owners determine the best place to open their stores and Jensen hopes to develop the model for other cities and towns in Europe and eventually in the U.S.

"I think (Jensen's model) could be helpful but you have to be careful," cautioned Giovanni Coratolo, director of small business policy at the U.S. Chamber of Commerce.

While "location is life or death," Coratolo said, "there are still subjective values that have to be taken into account in starting a business."

But will the model one day be able to explain the proximity of so many Starbucks (Charts) in New York City?

"I don't know," Jensen said. "In principal you would expect there to be repulsion because they are too close."

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Most stock quote data provided by BATS. Market indices are shown in real time, except for the DJIA, which is delayed by two minutes. All times are ET. Disclaimer.

Morningstar: © 2014 Morningstar, Inc. All Rights Reserved.

Factset: FactSet Research Systems Inc. 2014. All rights reserved.

Chicago Mercantile Association: Certain market data is the property of Chicago Mercantile Exchange Inc. and its licensors. All rights reserved.

Dow Jones: The Dow Jones branded indices are proprietary to and are calculated, distributed and marketed by DJI Opco, a subsidiary of S&P Dow Jones Indices LLC and have been licensed for use to S&P Opco, LLC and CNN. Standard & Poor's and S&P are registered trademarks of Standard & Poor’s Financial Services LLC and Dow Jones is a registered trademark of Dow Jones Trademark Holdings LLC. All content of the Dow Jones branded indices © S&P Dow Jones Indices LLC 2014 and/or its affiliates.