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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SpaceX to get more than 700 acres of Texas wildlife refuge in land swap

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A federal judge on Monday, September 21, refused to block the Trump administration from giving SpaceX more than 700 acres of wildlife refuge as part of a land swap in Texas, while environmental groups vowed to continue their legal challenge.

U.S. District Judge Fernando Rodriguez Jr. declined the plaintiffs' request for a preliminary injunction to prevent the parcel exchange, saying they failed to prove it would worsen ecological risks to a Gulf Coast region already transformed by billionaire Elon Musk’s rocket operations.

In June, the U.S. Fish and Wildlife Service approved moving forward with the deal with SpaceX, which would surrender 683 acres the company owns in exchange for the federal land in the Lower Rio Grande Valley National Wildlife Refuge. The 103,000-acre refuge spans four counties along the Texas border and is home to animal habitats and historical landmarks.

Maps show the land SpaceX would acquire would be closer to the company's launchpad near the U.S.-Mexico border.

The swap amounts to a gift of public lands to SpaceX, “clearing the way for bulldozers to tear into this wildlife refuge as soon as next week and turn a public treasure into a private payday,” said Laiken Jordahl, a spokesperson with the Center for Biological Diversity, which filed the lawsuit alongside other opponents including tribal groups. Jordahl said Monday that the litigation will continue even as the exchange goes forward.

“This court order is not the final word. These lands hold incredible spiritual, historical and conservation value for the people and wildlife of South Texas. We won’t stop fighting to keep this irreplaceable public wildlife refuge safe from SpaceX bulldozers,” Jordahl said in a statement.

The lawsuit asks the federal court to halt the exchange, which has worried SpaceX opponents in the area who have long criticized the company's expanding footprint over lost access to beaches and concerns over exploding rockets.

The Fish and Wildlife Service didn’t respond to a request for comment on Monday’s decision. Previously, a spokesperson had said the agency does not comment on ongoing litigation.

The agency issued a final environmental assessment report in June that determined the exchange would cause no significant impact to the area. The report said the federal government believed the acquisition would represent a “net conservation benefit” and provide “substantial long-term conservation value and improving landscape-scale habitat connectivity across refuges in South Texas.”

The judge said that the plaintiffs offered “relatively weak” evidence of environmental harm.

“While they rightfully argue that the preservation of wildlife and historical lands furthers the public interest, they present no evidence demonstrating that the Property will suffer aesthetic, environmental, cultural, or historical degradation during the pendency of this lawsuit,” Rodriguez wrote in his ruling.

In addition, the judge said a preliminary injunction would result in modifications to SpaceX’s development plans, “placing additional hardship on the company’s ability to meet milestones and contractual obligations.”

SpaceX did not return an email seeking comment on the judge's ruling.

The space exploration company first broke ground in Texas more than a decade ago and has expanded rapidly, so much that SpaceX employees last year voted to incorporate their own local government called Starbase.

Rice Alliance, Greentown name winners of Houston Energy and Climate Week pitch competitions

winner winners

Approximately 100 startups from around the world pitched their breakthrough technologies and businesses during Houston Energy and Climate Week, with a select few taking home top prizes and bragging rights.

Each year, investors at the Rice Alliance Energy Technology Venture Forum name the 10 most-promising startups. Greentown's Climatetech Summit also culminates in a pitch event, where member companies can earn cash prizes.

Here's who won at two of the week's anchor events and competitions.

Rice Alliance Energy Tech Venture Forum

The 23nd annual event was held Thursday, Sept. 17, at Rice University’s Jones Graduate School of Business. The most-promising companies were selected by industry experts and participating investors attending the event.

The 10 most-promising companies included:

  • Australia-based Aquafortus, which has developed a non-thermal liquid to liquid desalination technology for resource recovery from wastewater brine
  • Houston-based Focis AI, which converts industrial laser scans into a queryable digital twin of refineries and plants
  • Houston-based ironlattice, a semiconductor manufacturing company
  • Houston-based Licube, which has developed technology to produce ultra-high-purity lithium compounds for the fusion energy, pharmaceuticals, semiconductors and high-performance solid-state battery sectors
  • Houston-based Mars Materials, a clean chemical manufacturing business that is working to convert captured carbon into resources, such as carbon fiber and wastewater treatment chemicals
  • Dallas-based MCatalysis, which has developed a suite of proprietary microwave-driven catalysts to produce high-quality, ready-to-use fuels compatible with existing infrastructure
  • Oslo, Norway-based OTee, an automation machinery manufacturer
  • Houston-based Pike Robotics, which deploys its Wall-Eye robot to inspect hazardous tanks without taking assets offline
  • New Mexico-based Spiritus, a direct-air-capture (DAC) technology company
  • San Francisco-based UptimeAI Inc., which develops AI reasoning agents for industrial operations teams

Stellai won the People's Choice Award. The Norwegian company develops AI products for the waste management industry.

The energy technology ventures selected to participate in the forum were named earlier this year. See the full list here, and read about last year's winners here.

Greentown Lab's Climatetech Summit

The annual summit was held Wednesday, Sept. 16, featured a number of Houston startups in its pitch competition and lighting pitch round. Judges included Dave Dreessen,, Jon Greene, Naval Preet Singh, Philip Llewellyn, Erin Madro, Justin Yeung, Jay Kim, Rawand Rasheed and Moji Karimi.

Pitch winners included:

  • First place: Elementium Materials' CEO Matthew Dawson, winning a $10,000 cash prize sponsored by TotalEnergies plus another $10,000 in legal services sponsored by Foley Hoag. The company develops advanced battery electrolytes. It is a Greentown Boston member; though Dawson is based in Houston.
  • Second place: Houston-based Solidec CEO and co-founder Ryan DuChanois, winning $5,000 in legal services sponsored by Foley Hoag. The company electrolyzes air, water and electricity into onsite hydrogen peroxide.

Lightening pitch winners included:

  • First place: Montana-based MagDrive Technologies, winning a $1,000 cash prize sponsored by Energy Transition Ventures. The company develops magnetically actuated, zero-emission valve systems that eliminate fugitive emissions and improve reliability.
  • Second place: Houston-based HEXASpec, winning a $500 cash prize sponsored by Foley Hoag. The company has created a new material to improve heat management for the semiconductor industry.

Read Greentown's recap of the summit here.

Houston Energy and Climate Week announced that the 2027 event will move to the spring, held April 4-10.

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This article originally appeared on our sister site, EnergyCapitalHTX.com.

Eli Lilly breaks ground on $6.5B pharmaceutical factory in Houston

lilly lands

Leading pharmaceutical company Eli Lilly broke ground today, Sept. 21, on its $6.5 billion manufacturing site at Houston's Generation Park.

The 236-acre, state-of-the art factory is expected to come online in 2030 and will manufacture Foundayo, the company's first synthetic oral GLP-1 medication, as well as other advanced therapeutics.

"We are thrilled to break ground on our latest ‘medicines made in America’ site in the great state of Texas," David Ricks, Lilly chair and CEO, said in a prepared statement. "This $6.5 billion investment will help change the game for tens of millions of people suffering from overweight, obesity and its consequences like diabetes. We will make and ship Lilly’s latest products from Texas to people here at home and around the world.”

Houston was up against more than 300 locations in the U.S. for the factory, as part of Lilly’s $50 billion investment in domestic medicine production that has launched 10 manufacturing sites since 2020. Lilly first announced Houston had been selected for the site last September.

Photo via gov.texas.gov

As Abbott mentioned, the site is expected to create hundreds of jobs, and will hire engineers, scientists, operations personnel and lab technicians once up and running. It will create 4,000 construction jobs while being built.

In an effort to support workforce development, Lilly also announced a $12.5 million commitment to Houston's San Jacinto College in addition to a $2.5 million charitable donation to the San Jacinto College Foundation. The funding will go toward hands-on training, equipment and facilities to support future technicians, operators, maintenance professionals, and other manufacturing talent, according to Lilly. The charitable donation will fund scholarships for students.

"This relationship will build a strong, sustainable talent pipeline for Lilly while creating meaningful, high-demand career opportunities across our region,” Brenda Hellyer, chancellor of San Jacinto College, said in the release.

"When you invest in a place like Houston, you invest in its people first," Edgardo Hernandez, executive vice president and president of Lilly Manufacturing Operations, added. "This facility will run on the talent of this community, powered by our relationship with San Jacinto College. We're hiring across the greater Houston area to help residents build careers close to home."

Rendering courtesy Eli Lilly

Lilly previously said it chose Generation Park, a 4,300-acre, master-planned commercial district near Lake Houston, because of factors such as financial incentives, access to utilities and transportation and the region’s business-friendly environment. Generation Park is home to campuses for San Jacinto College and Lone Star College.

Since Lilly first announced plans for the site, another fellow pharma giant has made plans to move into Generation Park. Bristol Myers Squibb Co. announced last month that it would build a $2.3 billion factory in the district. The site is expected to manufacture small molecule, biologic and antibody-drug conjugates and will also come online around 2030. Read more here.

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