WHY REMOTE WORK COULD LEAD TO LESS INNOVATION - Kanebridge News
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WHY REMOTE WORK COULD LEAD TO LESS INNOVATION

Do chance encounters among employees of different Silicon Valley companies in coffee shops, restaurants and other public places lead to innovation? The answer is yes, say researchers who examined such “knowledge spillovers” in a study that may have implications for today’s work-from-home culture.

The researchers—Keith Chen of the University of California, Los Angeles, and David Atkin and Anton Popov of the Massachusetts Institute of Technology—tracked the locations of 425,000 phones using commercially available cellphone-location data. Though the data is anonymous and linked only to the unique ID number of each phone, the researchers surmised where the phone owners worked by looking at where the phones spent large parts of the workday, using a map of buildings occupied by Silicon Valley companies that have filed patents.

Examining instances where phone owners went outside the office and ended up near someone from another Silicon Valley company, they found 218 million episodes in which two workers from different companies were in the same place between September 2016 and November 2017.

For their study, they considered only situations in which both people were near each other for at least a half-hour, and used a probability technique to eliminate meetings that might have been arranged in advance. They also assumed that many of these people bumped into someone they already knew, such as a former colleague.

Sharing knowledge
Such chance meetings “may spark a conversation that leads to a transfer of knowledge or a collaboration,” the researchers wrote.

Next, the research team pulled up patent applications filed by the companies of the employees. Such applications list relevant patents from other companies in so-called patent citations. Patent citations are “one measure of which firms are influencing each other and how firms are sharing ideas,” says Prof. Chen, who studies behavioral economics and strategy at UCLA’s Anderson School of Management.

The researchers then worked backward in time. They looked for places where employees of a patent-filing company may have crossed paths with workers from companies cited in the patent application.

“We rewind the clock to a year before when they would have been developing this technology,” says Prof. Chen. “What school were they dropping their kids off at, what mall were they shopping at, what bar do they frequent. And you infer who was at that bar when they were there,” based on the phone-location data.

The goal, Prof. Chen says, is “to connect workers of the firm that is going to file the patent, at the establishment where we infer that patent was innovated, with what other workers they were interacting with.”

Next, the researchers calculated the overall number of such citations that appear to have been linked to unplanned encounters. The upshot: The researchers say that without these encounters, there would have been about 8% fewer cross-firm patent citations in the period covered by the phone-location data.

“There is a tremendous correlation between my workers’ meeting a lot with your workers, and my workers’ citing your workers’ patent,” says Prof. Chen.

The innovation boost from the encounters, by the team’s calculations, is about twice as large as a similar effect found by other research that looked for knowledge transfer based on whether two companies’ offices are near each other, Prof. Chen says.

Their study comes with some caveats. The researchers don’t know whether these employees actually spoke when they were in the same location, or, if they spoke, what they talked about. And they don’t know whether the workers’ jobs would have facilitated a tech discussion—they might have involved a Google HR staffer and an Apple maintenance person.

Still, the report shines a light on what some experts have long suspected: that random conversations involving people in similar industries can increase innovation.

Enrico Moretti, an economics professor at the University of California, Berkeley, says the study “significantly advances our understanding of knowledge spillovers and how they shape the geography of innovation.” Prof. Moretti, who says he has been working on the topic for 25 years, says, “I find this paper to be one of the most direct and convincing pieces of evidence on this question. It provides important insights into why Silicon Valley-style clusters of innovation exist.”

Remote work’s impact
Though the study involved cellphone data from before Covid, the researchers say it has implications for an era when many people work all or part of the time from home.

The researchers looked at people who occasionally worked from home in the study period, based on where their phones were located during daytime hours, and then at how that affected their probability of attending planned or serendipitous meetings with someone from another company who didn’t work from home, Prof. Chen says.

Looking at two hypothetical companies, the researchers extrapolated that if one-half of employees at each business work from home, their meetings of all types—serendipitous and planned—would fall 35% and patent citations between the companies would decline almost 12%.

“We think this means information exchange between firms is decreasing,” Prof. Chen says. “It is worrying. These businesses co-locate for a reason. If they can’t learn from each other, we think that is a big deal.”

“Presumably,” he adds, “an even bigger effect is the harm that it does to serendipity and flow of information and innovation within the firm.”

By BART ZIEGLER
Wed, May 17, 2023 4:31pmGrey Clock 3 min

Do chance encounters among employees of different Silicon Valley companies in coffee shops, restaurants and other public places lead to innovation? The answer is yes, say researchers who examined such “knowledge spillovers” in a study that may have implications for today’s work-from-home culture.

The researchers—Keith Chen of the University of California, Los Angeles, and David Atkin and Anton Popov of the Massachusetts Institute of Technology—tracked the locations of 425,000 phones using commercially available cellphone-location data. Though the data is anonymous and linked only to the unique ID number of each phone, the researchers surmised where the phone owners worked by looking at where the phones spent large parts of the workday, using a map of buildings occupied by Silicon Valley companies that have filed patents.

Examining instances where phone owners went outside the office and ended up near someone from another Silicon Valley company, they found 218 million episodes in which two workers from different companies were in the same place between September 2016 and November 2017.

For their study, they considered only situations in which both people were near each other for at least a half-hour, and used a probability technique to eliminate meetings that might have been arranged in advance. They also assumed that many of these people bumped into someone they already knew, such as a former colleague.

Sharing knowledge

Such chance meetings “may spark a conversation that leads to a transfer of knowledge or a collaboration,” the researchers wrote.

Next, the research team pulled up patent applications filed by the companies of the employees. Such applications list relevant patents from other companies in so-called patent citations. Patent citations are “one measure of which firms are influencing each other and how firms are sharing ideas,” says Prof. Chen, who studies behavioral economics and strategy at UCLA’s Anderson School of Management.

The researchers then worked backward in time. They looked for places where employees of a patent-filing company may have crossed paths with workers from companies cited in the patent application.

“We rewind the clock to a year before when they would have been developing this technology,” says Prof. Chen. “What school were they dropping their kids off at, what mall were they shopping at, what bar do they frequent. And you infer who was at that bar when they were there,” based on the phone-location data.

The goal, Prof. Chen says, is “to connect workers of the firm that is going to file the patent, at the establishment where we infer that patent was innovated, with what other workers they were interacting with.”

Next, the researchers calculated the overall number of such citations that appear to have been linked to unplanned encounters. The upshot: The researchers say that without these encounters, there would have been about 8% fewer cross-firm patent citations in the period covered by the phone-location data.

“There is a tremendous correlation between my workers’ meeting a lot with your workers, and my workers’ citing your workers’ patent,” says Prof. Chen.

The innovation boost from the encounters, by the team’s calculations, is about twice as large as a similar effect found by other research that looked for knowledge transfer based on whether two companies’ offices are near each other, Prof. Chen says.

Their study comes with some caveats. The researchers don’t know whether these employees actually spoke when they were in the same location, or, if they spoke, what they talked about. And they don’t know whether the workers’ jobs would have facilitated a tech discussion—they might have involved a Google HR staffer and an Apple maintenance person.

Still, the report shines a light on what some experts have long suspected: that random conversations involving people in similar industries can increase innovation.

Enrico Moretti, an economics professor at the University of California, Berkeley, says the study “significantly advances our understanding of knowledge spillovers and how they shape the geography of innovation.” Prof. Moretti, who says he has been working on the topic for 25 years, says, “I find this paper to be one of the most direct and convincing pieces of evidence on this question. It provides important insights into why Silicon Valley-style clusters of innovation exist.”

Remote work’s impact

Though the study involved cellphone data from before Covid, the researchers say it has implications for an era when many people work all or part of the time from home.

The researchers looked at people who occasionally worked from home in the study period, based on where their phones were located during daytime hours, and then at how that affected their probability of attending planned or serendipitous meetings with someone from another company who didn’t work from home, Prof. Chen says.

Looking at two hypothetical companies, the researchers extrapolated that if one-half of employees at each business work from home, their meetings of all types—serendipitous and planned—would fall 35% and patent citations between the companies would decline almost 12%.

“We think this means information exchange between firms is decreasing,” Prof. Chen says. “It is worrying. These businesses co-locate for a reason. If they can’t learn from each other, we think that is a big deal.”

“Presumably,” he adds, “an even bigger effect is the harm that it does to serendipity and flow of information and innovation within the firm.”



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These stocks are getting hit for a reason. Instead, focus on stocks that show ‘relative strength.’ Here’s how.

By KEN SHREVE
Wed, Jun 12, 2024 4 min

A lot of investors get stock-picking wrong before they even get started: Instead of targeting the top-performing stocks in the market, they focus on the laggards—widely known companies that look as if they are on sale after a period of stock-price weakness.

But these weak performers usually are going down for good reasons, such as for deteriorating sales and earnings, market-share losses or mutual-fund managers who are unwinding positions.

Decades of Investor’s Business Daily research shows these aren’t the stocks that tend to become stock-market leaders. The stocks that reward investors with handsome gains for months or years are more often  already  the strongest price performers, usually because of outstanding earnings and sales growth and increasing fund ownership.

Of course, many investors already chase performance and pour money into winning stocks. So how can a discerning investor find the winning stocks that have more room to run?

Enter “relative strength”—the notion that strength begets more strength. Relative strength measures stocks’ recent performance relative to the overall market. Investing in stocks with high relative strength means going with the winners, rather than picking stocks in hopes of a rebound. Why bet on a last-place team when you can wager on the leader?

One of the easiest ways to identify the strongest price performers is with IBD’s Relative Strength Rating. Ranked on a scale of 1-99, a stock with an RS rating of 99 has outperformed 99% of all stocks based on 12-month price performance.

How to use the metric

To capitalise on relative strength, an investor’s search should be focused on stocks with RS ratings of at least 80.

But beware: While the goal is to buy stocks that are performing better than the overall market, stocks with the highest RS ratings aren’t  always  the best to buy. No doubt, some stocks extend rallies for years. But others will be too far into their price run-up and ready to start a longer-term price decline.

Thus, there is a limit to chasing performance. To avoid this pitfall, investors should focus on stocks that have strong relative strength but have seen a moderate price decline and are just coming out of weeks or months of trading within a limited range. This range will vary by stock, but IBD research shows that most good trading patterns can show declines of up to one-third.

Here, a relative strength line on a chart may be helpful for confirming an RS rating’s buy signal. Offered on some stock-charting tools, including IBD’s, the line is a way to visualise relative strength by comparing a stock’s price performance relative to the movement of the S&P 500 or other benchmark.

When the line is sloping upward, it means the stock is outperforming the benchmark. When it is sloping downward, the stock is lagging behind the benchmark. One reason the RS line is helpful is that the line can rise even when a stock price is falling, meaning its value is falling at a slower pace than the benchmark.

A case study

The value of relative strength could be seen in Google parent Alphabet in January 2020, when its RS rating was 89 before it started a 10-month run when the stock rose 64%. Meta Platforms ’ RS rating was 96 before the Facebook parent hit new highs in March 2023 and ran up 65% in four months. Abercrombie & Fitch , one of 2023’s best-performing stocks, had a 94 rating before it soared 342% in nine months starting in June 2023.

Those stocks weren’t flukes. In a study of the biggest stock-market winners from the early 1950s through 2008, the average RS rating of the best performers before they began their major price runs was 87.

To see relative strength in action, consider Nvidia . The chip stock was an established leader, having shot up 365% from its October 2022 low to its high of $504.48 in late August 2023.

But then it spent the next four months rangebound—giving up some ground, then gaining some back. Through this period, shares held between $392.30 and the August peak, declining no more than 22% from top to bottom.

On Jan. 8, Nvidia broke out of its trading range to new highs. The previous session, Nvidia’s RS rating was 97. And that week, the stock’s relative strength line hit new highs. The catalyst: Investors cheered the company’s update on its latest advancements in artificial intelligence.

Nvidia then rose 16% on Feb. 22 after the company said earnings for the January-ended quarter soared 486% year over year to $5.16 a share. Revenue more than tripled to $22.1 billion. It also significantly raised its earnings and revenue guidance for the quarter that was to end in April. In all, Nvidia climbed 89% from Jan. 5 to its March 7 close.

And the stock has continued to run up, surging past $1,000 a share in late May after the company exceeded that guidance for the April-ended quarter and delivered record revenue of $26 billion and record net profit of $14.88 billion.

Ken Shreve  is a senior markets writer at Investor’s Business Daily. Follow him on X  @IBD_KShreve  for more stock-market analysis and insights, or contact him at  ken.shreve@investors.com .