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R&D: The key to breaking through plateaus for tech firms

ROI - Return on Ideas - Spring 2026
IT firms face greater growth swings, but sustained R&D investment can serve as a powerful safeguard against revenue stalls.

Fast growth is often the hallmark of information technology companies. But that speed comes with risk.

New research co-authored by Sunil Mithas, professor of information systems at the University of South Florida, finds that IT-producing firms are more likely than non-IT companies to experience sudden slowdowns in revenue growth, known as “revenue stalls.” The study, published in MIS Quarterly, analyzes more than 1,400 large publicly traded U.S. firms from 1950 to 2015.

A revenue stall occurs when a company’s growth rate drops sharply after a sustained period of expansion. For example, Intel, once a world leader in microprocessors, stalled beginning in 2012. Cisco also saw a slowdown in 2007. In contrast, Apple and Colgate-Palmolive grew significantly during the same period without any stalls.

The researchers found that IT firms face a significantly higher risk of these stall events than non-IT firms. The reason: intense competition, rapid technological change, and constant market turbulence that define the sector.

The study shows that research and development spending is especially effective at combating stall risk for IT companies. Because these firms depend heavily on intangible assets — technical expertise, intellectual property and human capital — R&D investments more strongly cushion them against revenue slowdowns than similar investments do in other industries.

The findings point to potential strategies to mitigate stalls. Researchers suggest managers should identify the reasons for the stall — such as increased competition or changes in customer preferences for products and services — and tailor their R&D investment to address these reasons.

Although the study used data through 2015, the findings provide an indirect explanation for planned investments of hundreds of billions of dollars in artificial intelligence by big tech firms to potentially avoid revenue stalls.

Authors: Terence J.V. Saldanha, University of Georgia; Sunil Mithas, University of South Florida; Raveesh Mayya, New York University.

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