Your data center is either closer than you think or much farther away

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A map of U.S. data centers. Courtesy of Rice Businesses Wisdom

A new study shows why some facilities cluster in cities for speed and access, while others move to rural regions in search of scale and lower costs. Based on research by Tommy Pan Fang (Rice Business) and Shane Greenstein (Harvard).

Key findings:

  • Third-party colocation centers are physical facilities in close proximity to firms that use them, while cloud providers operate large data centers from a distance and sell access to virtualized computing resources as on‑demand services over the internet.
  • Hospitals and financial firms often require urban third-party centers for low latency and regulatory compliance, while batch processing and many AI workloads can operate more efficiently from lower-cost cloud hubs.
  • For policymakers trying to attract data centers, access to reliable power, water and high-capacity internet matter more than tax incentives.

Recent outages and the surge in AI-driven computing have made data center siting decisions more consequential than ever, especially as energy and water constraints tighten. Communities invest public dollars on the promise of jobs and growth, while firms weigh long-term commitments to land, power and connectivity.

Against that backdrop, a critical question comes into focus: Where do data centers get built — and what actually drives those decisions?

A new study by Tommy Pan Fang (Rice Business) and Shane Greenstein (Harvard Business School) provides the first large-scale statistical analysis of data center location strategies across the United States. It offers policymakers and firms a clearer starting point for understanding how different types of data centers respond to economic and strategic incentives.

Forthcoming in the journal Strategy Science, the study examines two major types of infrastructure: third-party colocation centers that lease server space to multiple firms, and hyperscale cloud centers owned by providers like Amazon, Google and Microsoft.

Two Models, Two Location Strategies

The study draws on pre-pandemic data from 2018 and 2019, a period of relative geographic stability in supply and demand. This window gives researchers a clean baseline before remote work, AI demand and new infrastructure pressures began reshaping internet traffic patterns.

The findings show that data centers follow a bifurcated geography. Third-party centers cluster in dense urban markets, where buyers prioritize proximity to customers despite higher land and operating costs. Cloud providers, by contrast, concentrate massive sites in a small number of lower-density regions, where electricity, land and construction are cheaper and economies of scale are easier to achieve.

Third-party data centers, in other words, follow demand. They locate in urban markets where firms in finance, healthcare and IT value low latency, secure storage, and compliance with regulatory standards.

Using county-level data, the researchers modeled how population density, industry mix and operating costs predict where new centers enter. Every U.S. metro with more than 700,000 residents had at least one third-party provider, while many mid-sized cities had none.

ImageThis pattern challenges common assumptions. Third-party facilities are more distributed across urban America than prevailing narratives suggest.

Customer proximity matters because some sectors cannot absorb delay. In critical operations, even slight pauses can have real consequences. For hospital systems, lag can affect performance and risk exposure. And in high-frequency trading, milliseconds can determine whether value is captured or lost in a transaction.

“For industries where speed is everything, being too far from the physical infrastructure can meaningfully affect performance and risk,” Pan Fang says. “Proximity isn’t optional for sectors that can’t absorb delay.”

The Economics of Distance

For cloud providers, the picture looks very different. Their decisions follow a logic shaped primarily by cost and scale. Because cloud services can be delivered from afar, firms tend to build enormous sites in low-density regions where power is cheap and land is abundant.

These facilities can draw hundreds of megawatts of electricity and operate with far fewer employees than urban centers. “The cloud can serve almost anywhere,” Pan Fang says, “so location is a question of cost before geography.”

The study finds that cloud infrastructure clusters around network backbones and energy economics, not talent pools. Well-known hubs like Ashburn, Virginia — often called “Data Center Alley” — reflect this logic, having benefited from early network infrastructure that made them natural convergence points for digital traffic.

Local governments often try to lure data centers with tax incentives, betting they will create high-tech jobs. But the study suggests other factors matter more to cloud providers, including construction costs, network connectivity and access to reliable, affordable electricity.

When cloud centers need a local presence, distance can sometimes become a constraint. Providers often address this by working alongside third-party operators. “Third-party centers can complement cloud firms when they need a foothold closer to customers,” Pan Fang says.

That hybrid pattern — massive regional hubs complementing strategic colocation — may define the next phase of data center growth.

Looking ahead, shifts in remote work, climate resilience, energy prices and AI-driven computing may reshape where new facilities go. Some workloads may move closer to users, while others may consolidate into large rural hubs. Emerging data-sovereignty rules could also redirect investment beyond the United States.

“The cloud feels weightless,” Pan Fang says, “but it rests on real choices about land, power and proximity.”

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This article originally appeared on Rice Business Wisdom. Written by Scott Pett.

Pan Fang and Greenstein (2025). “Where the Cloud Rests: The Economic Geography of Data Centers,” forthcoming in Strategy Science.

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Search trends predict future retail revenue up to three quarters in advance. Photo via Pexels

Forecasting retail sales just got smarter, thanks to Google searches

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Imagine being able to predict the future of retail sales — not with months-old economic reports, but with real-time digital breadcrumbs left behind by consumers. Thanks to new research from K. Ramesh (Rice Business) and Gary Lind (University of Pittsburgh), that future is already here.

Key findings

  • Search trends predict future retail revenue — up to three quarters ahead.
  • Markets don’t fully price in search-based insights, especially before earnings announcements.
  • Trading strategies using search data outperform traditional asset-pricing models by 2–3%.
  • Analysts often underuse this data, resulting in predictable forecast errors.
  • At the macro level, search trends closely track — and often lead — official retail sales and GDP.

Their study shows that Google search trends are powerful predictors of consumer demand, capable of forecasting U.S. retail sales up to three quarters in advance. The implications span industries and audiences — from Wall Street traders to Main Street retailers, and from data-driven CFOs to curious business students.

A smarter, faster crystal ball for retail demand

Retail sales drive nearly 70% of U.S. gross domestic product (GDP), making them one of the most important indicators of economic health. Yet traditional forecasting relies heavily on backward-looking data and broad economic indicators. Ramesh and Lind’s work offers a leap forward: search data from Google Trends — publicly available and easy to use — can offer a faster, more precise signal of where sales are headed.

“If you want to understand consumer demand,” says Ramesh, the Herbert S. Autrey Professor of Accounting at Rice Business, “look at what people are searching for — not just what companies report after the fact. These digital footprints can tell us where revenue is going, often before the market catches up.”

This low-cost approach stands in stark contrast to expensive alternatives, such as satellite images of parking lots, in-store foot traffic from mobile data, or retail scanner feeds — tools often reserved for hedge funds and large institutional investors. Google Trends offers a scalable, accessible option for anyone seeking insight into consumer behavior.

Why this matters for investors and analysts

The researchers analyzed search patterns for nearly 200 publicly traded U.S. retail companies between 2004 and 2019. They found that firms with rising search volumes tend to report higher revenues — often well before analysts or investors react.

In fact, investment strategies built around these trends earned 2–3% higher returns than traditional models would predict. And most of these gains were concentrated around earnings announcements — a sign that markets were slow to recognize what search data had already revealed.

The advantage is even more striking for companies that fly under Wall Street’s radar. For firms with limited analyst coverage, the predictive power of search data on stock performance was more than 80% stronger.

A new tool for analysts — if they’ll use it

Despite the clear signal in the data, the study finds that analysts routinely fail to incorporate search-based insights into their forecasts. That gap translates into missed revenue predictions and market inefficiencies — which sophisticated investors can exploit.

“The search data are out there,” says Lind, a Rice Business Ph.D. ’19 graduate now on faculty at Pitt Business. “They’re public, powerful, and free. Analysts who ignore them are missing an opportunity.”

The impact of this research extends well beyond equity markets. By aggregating Google search data across the retail sector, the authors found strong alignment with U.S. Census retail sales figures and GDP trends. In other words, these digital signals reflect not just firm-level interest, but macroeconomic momentum.

A data wake-up call

This makes search trends a potentially valuable early-warning system for policymakers, central banks, and anyone responsible for interpreting the economic landscape. During volatile or uncertain periods, such tools could offer precious foresight into shifting consumer behavior.

In a digital era where consumers research before they shop — whether online or in-store — it’s no surprise that their Google queries leave valuable clues. What’s surprising is how often businesses, investors, and even economists still overlook them, Ramesh says. “Search data is a goldmine. And it's just sitting there, waiting to be used.”

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This article originally appeared on Rice Business Wisdom.

Lind and Ramesh, “Using Internet Search Data to Predict Aggregate Retail Sales and Enhance Firm-Level Revenue Expectations,” Contemporary Accounting Research (April 2025): 1-32. https://doi.org/10.1111/1911-3846.13043.

There's no crystal ball, but this researcher from Rice University is trying to see if some metrics work for economic forecasting. Photo via Getty Images

Houston researcher tries to crack the code on the Fed's data to determine economic outlook

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Research by Rice Business Professor K. Ramesh shows that the Fed appears to harvest qualitative information from the accounting disclosures that all public companies must file with the Securities and Exchange Commission.

These SEC filings are typically used by creditors, investors and others to make firm-level investing and financing decisions; and while they include business leaders’ sense of economic trends, they are never intended to guide macro-level policy decisions. But in a recent paper (“Externalities of Accounting Disclosures: Evidence from the Federal Reserve”), Ramesh and his colleagues provide persuasive evidence that the Fed nonetheless uses the qualitative information in SEC filings to help forecast the growth of macroeconomic variables like GDP and unemployment.

According to Ramesh, the study was made possible thanks to a decision the SEC made several years ago. The commission stores the reports submitted by public companies in an online database called EDGAR and records the IP address of any party that accesses them. More than a decade ago, the SEC began making partially anonymized forms of those IP addresses available to the public. But researchers eventually figured out how to deanonymize the addresses, which is precisely what Ramesh and his colleagues did in this study.

"We were able to reverse engineer and identify those IP addresses that belonged to Federal Reserve staff," Ramesh says.

The team ultimately assembled a data set containing more than 169,000 filings accessed by Fed staff between 2005 and 2015. They quickly realized that the Fed was interested only in filings submitted by a select group of industry leaders and financial institutions.

But if Ramesh and his colleagues now had a better idea of precisely which bellwether firms the Fed focused on, they still had no way of knowing exactly what Fed staffers had gleaned from the material they accessed. So the team decided to employ a measure called "tone" that captures the overall sentiment of a piece of text – whether positive, negative, or neutral.

Building on previous research that had identified a set of words with negatively toned financial reports, Ramesh and his colleagues examined the tone of all the SEC filings accessed by Fed staff between one meeting of the Federal Open Markets Committee (FOMC) and the next. The FOMC sets interest rates and guides monetary policy, and its meetings provide an opportunity for Fed officials to discuss growth forecasts and announce policy decisions.

The researchers then examined the Fed's growth forecasts to see if there was a relationship between the tone of the documents that Fed staff examined in the period between FOMC meetings and the forecasts they produced in advance of those meetings.

The team found close correlations between the tone of the reports accessed by the Fed and the agency’s forecasts of GDP, unemployment, housing starts and industrial production. The more negative the filings accessed prior to an FOMC meeting, for example, the gloomier the GDP forecast; the more positive the filings, the brighter the unemployment forecast.

Ramesh and his colleagues also compared the Fed's forecasts with those of the Society of Professional Forecasters (SPF), whose members span academia and industry. Intriguingly, the researchers found that while the errors in the SPF's forecasts could be attributed to the absence of the tonal information culled from the SEC filings, the errors in the Fed’s forecasts could not. This suggests both that the Fed was collecting qualitative information that the SPF was not—and that the agency was making remarkably efficient use of it.

"They weren’t leaving anything on the table," Ramesh says.

Having solved one mystery, Ramesh would like to focus on another; namely, how does the Fed identify bellwether firms in the first place?

Unfortunately, the SEC no longer makes IP address data publicly available, which means that Ramesh and his colleagues can no longer study which companies the Fed is most interested in. Nonetheless, Ramesh hopes to use the data they have already collected to build a model that can accurately predict which firms the Fed is most likely to follow. That would allow the team to continue studying the same companies that the Fed does, and, he says, “maybe come up with a way to track those firms in order to understand how the economy is going to move.”

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This article originally ran on Rice Business Wisdom and was based on research from K. Ramesh is Herbert S. Autrey Professor of Accounting at Jones Graduate School of Business at Rice University.

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Rice University launches new venture fund for university-affiliated startups

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Rice University has launched its new One Giant Leap Ventures Fund I, which will invest in the university’s spinouts and alumni-founded startups.

The early-stage institutional venture fund will function with a hybrid structure that allows for participation from traditional equity investors and philanthropic investors. According to the university, the fund will invest up to $500,000 per Rice-affiliated company.

To be considered eligible for funds, companies must use intellectual property licensed by the university or be led or founded by alumni.

One Giant Leap will draw on support and mentorship from Rice’s pool of 60,000 alumni and aims to create educational opportunities within the investment phases, work with graduate and undergraduate venture students, explore the scaling and commercialization of their ideas, and help investigate all the facets of venture capital.

“Rice alumni bring an extraordinary depth of experience as entrepreneurs, investors and industry leaders, and One Giant Leap creates new ways to put that expertise to work for the next generation of Rice innovators,” Stephen Bayer, vice president for development and alumni relations, said in a news release. “It strengthens the connection between our alumni and the university while giving them meaningful opportunities to mentor, advise and support Rice-affiliated companies as they grow.”

The fund held its first close in August and made its first investment into Rice brain health spinout Motif Neurotech. Led by Rice faculty member Jacob Robinson, Motif is working to commercialize a minimally invasive neurostimulator that targets treatment-resistant depression. In May, the FDA approved the company to move forward with its first clinical trial.

“Research produces breakthrough technologies and our academic environment forms outstanding entrepreneurs,” said Adrian Trömel, the fund’s managing director, a Rice alumnus and a startup founder who also serves as Rice’s interim chief innovation officer.

One Giant Leap joins the already long list of Rice-led programs that foster innovation, including the Liu Idea Labs for Innovation and Entrepreneurship’s Innovation Fellows and Summer Venture Studio, the Rice Alliance’s Business Plan Competition, the Ion District, Woodside Rice Decarbonization Accelerator, Rice Nexus, the Biotech Launchpad and RBL Ventures and its upcoming 200,000 square-foot research lab the Arc.

“With One Giant Leap, I am excited that we are creating a unique structure that brings together traditional investment and philanthropic participation to invest in and help catalyze our startups, engage the deep expertise within the Rice ecosystem and transform those strengths into real-world impact,” Trömel added in the release.

New statewide plan aims to eliminate cervical cancer in Texas by 2032

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MD Anderson, on behalf of a coalition of health systems, has announced a new plan to eliminate cervical cancer in Texas.

The five-year Texas Lone Star Cervical Cancer Elimination Plan was launched during the Cancer Prevention and Research Institute of Texas (CPRIT) 2026 Innovations Conference in Galveston this month.

The plan focuses on three major pillars with goals to be achieved by 2032:

  • HPV vaccination: Increase the percentage of Texas boys and girls up to date on human papillomavirus (HPV) vaccination by age 15 from 50.5 percent to 80 percent
  • Cervical cancer screening: Raise the share of Texas women up to date on cervical cancer screening from 64 percent to 80 percent
  • Timely follow-up, diagnosis and treatment: Ensure 80 percent of women receive diagnostic follow-up and treatment when needed through community outreach, patient navigation, provider training and survivorship support

Overall, the coalition wants to see fewer than four new cases of cervical cancer annually per 100,000 Texas women by 2032, according to a news release from MD Anderson. Currently, Texas has an incidence rate of 9.5 women per 100,000 diagnosed with cervical cancer, compared with 7.5 women per 100,000 nationally.

“Texas has the tools to prevent nearly every case of cervical cancer, but tools can save lives only when people can utilize them,” Dr. Ernest Hawk, vice president and division head of Cancer Prevention and Population Sciences at MD Anderson, said in the release. “The Lone Star Cervical Cancer Elimination Plan gives us a shared roadmap to vaccinate more of our children, screen more of our women and make sure every abnormal result leads to care. With innovations like HPV self-collection and the commitment of partners across the state, elimination is within reach.”

About 40 other hospitals, health care organizations and companies join MD Anderson in the coalition that launched the Lonestar Plan. Those based in Houston include Houston Methodist, Rice University, UTHealth Houston, Texas Children's Hospital, Houston Health Department and others.

The CPRIT also announced its Texans Conquer Cancer Awards and its CPRIT Champion awards during the Innovations Conference this week. Several are based in Houston, including:

  • Zhiqiang An, co-founder of CrossBridge Bio, Director of the Texas Therapeutics Institute, and Vice President of Drug Discovery at the University of Texas Health Science Center at Houston
  • Dr. Abbey Berenson, Director of the UTMB Center for Interdisciplinary Research in Women's Health Care
  • Dr. Michael Taylor, Chair of Pediatric Neuro-Oncology at Texas Children's Cancer and Hematology Center and Director of Texas Children's Pediatric Brain Tumor Research Program

To date, the CPRIT has awarded more than $4.2 billion in grants to fight cancer in the state. Over the summer, it awarded four $2 million grants to institutions in Houston and Bryan for the creation or expansion of “core” cancer research facilities.

Texas Medical Center Innovation recently announced that its $2 million grant would renew its Accelerator for Cancer Therapeutics for five years. Read more from TMCi about the renewal here.

Announcing the 2026 Houston Innovation Awards finalists

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InnovationMap is proud to reveal the finalists for the 2026 Houston Innovation Awards.

The sixth annual Houston Innovation Awards program returns in an all-digital format this fall to honor the best of Houston's innovation ecosystem, including startups, entrepreneurs, mentors, and more.

Finalists were determined by our esteemed panel of judges, comprised of past award winners and InnovationMap editorial leadership.

The panel reviewed applications across 10 prestigious categories to determine our finalists. They will select the winner for each category, except for Startup of the Year, which will be chosen by the public via online voting launching later this month.

We will announce the honoree of our annual Trailblazer Award in the coming weeks, then stay tuned as we unveil all of this year's winners on InnovationMap.com in mid-November.

Get to know our finalists in more detail through editorial spotlights leading up to the winner announcement. Without further ado, here are the 2026 Houston Innovation Awards finalists:

Minority-founded Business

Honoring an innovative startup founded or co-founded by BIPOC or LGBTQ+ representation:

  • AI Made Fun
  • Deep Anchor Solutions
  • HEXAspec
  • Prana Surgical
  • Torres Orbital Mining Inc.

Female-founded Business

Honoring an innovative startup founded or co-founded by a woman:

  • Adair
  • ARIX Technologies
  • Bairitone Health
  • FlowCellutions
  • ParaDocs Health

Energy Transition Business

Honoring an innovative startup providing a solution within renewables, climatetech, clean energy, alternative materials, circular economy and beyond:

  • Capwell Services
  • FlowCellutions
  • Hertha Metals
  • Mars Materials
  • Solidec

Health Tech Business

Honoring an innovative startup within the health and medical technology sectors:

  • Bairitone Health
  • InformAI Inc.
  • Prana Surgical
  • Skybound MedTech

Deep Tech Business

Honoring an innovative startup providing technology solutions based on substantial scientific or engineering challenges, including those in the AI, robotics and space sectors:

  • Casimir
  • Focis AI
  • Machine Saver Inc.
  • Square Robot
  • Venus Aerospace

Startup of the Year (People's Choice)

Honoring a startup celebrating a recent milestone or success. The winner will be selected by the community via an online voting experience:

  • Fluxworks
  • IronLattice
  • Lumino
  • Progress Report
  • Rosarium Health
  • Thread
  • TokenRoster

Scaleup of the Year

Honoring an innovative later-stage startup that's recently reached a significant milestone in company growth:

  • Erock
  • Hertha Metals
  • Venus Aerospace

Incubator/Accelerator of the Year

Honoring a local incubator or accelerator that is championing and fueling the growth of Houston startups:

  • Activate
  • Impact Hub Houston
  • MarMo Innovation

Mentor of the Year

Honoring an individual who dedicates their time and expertise to guide and support budding entrepreneurs:

  • Al Danto, Rice University
  • Eric Rubenstein, New Climate Ventures
  • Jeremy Pitts, Activate
  • Joe Alapat, Liongard
  • Kyle Judah, Rice University's Liu Idea Lab for Innovation & Entrepreneurship
  • Rachel Bickham, Bickham Services Unlimited LLC

Trailblazer Recipient

  • To be announced
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