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.

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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Texas university's new flight academy opens at Houston Spaceport

cleared for takeoff

The vehicles may not have “student driver” stickers on them, but Texas Southern University has moved a dozen planes into its new training facility at the Houston Spaceport, opening the way for student flyers to use the facility.

TSU previously reached a deal with Houston Airports and the City of Houston in 2023 to house its prospective Flight Academy at Ellington Field. At the time, TSU had a small fleet of nine planes for student use, but a $5.5 million investment from the city greatly expanded the space available.

The Flight Academy includes a 20,000-square-foot hangar that serves as a TSU satellite campus. The school now has a fleet of 12 Cirrus SR20 aircraft that were acquired last year through state and alumni funding. An additional 4,500 square feet is used as classroom and office space. An 8,000-gallon fuel tank will support flight training operations.

TSU first launched its Aviation Science Management program in 1986 and added a professional pilot program in 2016. The school is now part of the United Airlines pipeline program and has also forged relationships with Delta and Southwest.

“I want to commend Texas Southern University and Houston Airports for their leadership and partnership in advancing aviation education right here in our city,” Houston City Councilwoman Dr. Carolyn Evans-Shabazz in a press release.

“It connects our students to high-paying, high-demand careers in aviation and aerospace. This is how we grow a city in the right way—by investing in workforce development, aligning education with industry and making sure our residents are prepared to lead in the industries of tomorrow. Houston is already a global leader in aerospace and projects like this strengthen that position even further, especially here at Ellington, where innovation and opportunity continue to take flight.”

The City of Houston signed an agreement to continue funding the academy for five years.

Amazon launches ultrafast, 30-minute delivery service across Houston

Amazon Now

More than 20 years after it redefined fast shipping, Amazon is preparing to raise the bar on consumer expectations again by offering to fulfill customers' most urgent product needs in Houston and other parts of the world in a half-hour or less for an extra fee.

The company, which revolutionized online shopping in 2005 with two-day deliveries for Prime members, is rapidly opening small order-processing hubs in dozens of U.S. and foreign cities to cater to shoppers who can't or don't want to wait for cough medicine to relieve flu symptoms or tomatoes for tonight's dinner salad.

The ultrafast service, called Amazon Now, first launched in India last June. Amazon says 30-minute deliveries now are also available in urban areas of the United States, Brazil, Mexico, Japan, the United Arab Emirates, the United Kingdom.

The mini-warehouses devoted to Amazon Now are about the size of a CVS drugstore. They stock about 3,500 products for expedited delivery, including beer, diapers, pet food, meat, nonprescription medications, playing cards and cellphone charging cables.

“We know that customers love speed and always have,” Beryl Tomay, Amazon’s head of transportation, told The Associated Press on Monday. “What we see customers doing, when we offer faster speeds, are they purchase more from Amazon. And Amazon becomes more top of mind for that or other types of items as well.”

In the U.S., the company first tested Amazon Now in Seattle, the home of its headquarters, and in Philadelphia. Most residents of the Dallas-Fort Worth area and Atlanta now have access as well. The service is also live in Dallas-Fort Worth, Denver, Minneapolis, Phoenix, Oklahoma City, Orlando, and dozens of other cities, Amazon said, with New York City and others expected by year-end.

The service charges for Amazon Now start at $3.99 for Prime members, who pay an annual fee of $139, and $13.99 for non-members. A $1.99 small basket fee applies to orders under $15, Amazon said.

The company's bet on a need for speed also comes as some consumers are rebelling against rushed deliveries as they weigh the potential impact on the environment and the workers tasked with preparing orders at a rapid rate.

Amazon’s approach
A relentless focus on speed helped Amazon build a logistics and e-commerce empire. After it made two days the new delivery time normal, Amazon moved into one-day and same-day deliveries for its Prime members. This spring, the company began making 90,000 products available in one hour or three hours at an extra cost.

The scaled down and sped up microhubs that are designed to handle 30-minute orders represent another step in Amazon's pursuit.

Only a handful of people prepare orders from aisles of shelves in the 5,000- to 10,000-square-foot facilities, unlike the sprawling fulfillment centers storing millions of items where Amazon employs a mix of human workers and robotics to pick and pack orders.

Amazon tailors the product inventory to each location and uses artificial intelligence and other technology to analyze what customers buy, as well as when and how often. The most popular U.S. purchases so far include soap, toothpaste, mouthwash, toilet plungers, bananas, limes and wireless earbuds, Amazon said.

The competition
Amazon’s attempt to up the instant gratification ante provides direct competition to on-demand food delivery platforms like Instacart, Uber Eats, DoorDash and Grubhub, which don't have the scale of the e-commerce titan, according to independent retail analyst Bruce Winder.

“What Amazon brings is their prowess in supply chain,” Winder said.

These smaller companies said they don't see Amazon as a threat, though, citing the hundreds of thousands of items they are able to deliver to users' doorsteps by partnering with various merchants and restaurants.

“DoorDash has a mission to empower grocers and retailers and augment their existing footprint, not to replace them,” DoorDash spokesperson Ali Musa said in an emailed statement. “We win only when they win, which is how we can offer over half a million grocery and retail items in under an hour across the country.”

Amazon also is in a race with Walmart to become the retailer that reliably gets orders to online shoppers in under an hour.

For an additional $10 on top of standard delivery charges, shoppers can place Walmart Express Delivery orders from among more than 100,000 products that are guaranteed to arrive in an hour. Many customers, however, are receiving the items under 30 minutes, Walmart CEO John Furner told analysts in February.

Domino's cautionary tale
Companies have promised deliveries in 30 minutes or less before, but the landscape also is littered with failed attempts to break the speed barrier.

The COVID-19 pandemic produced a flurry of companies that promised 10- to 15-minute grocery deliveries from microwarehouses in dense neighborhoods, according to Sucharita Kodali, an analyst at market research firm Forrester Research.

But soaring operating costs, low customer loyalty and the drying up of investor money ultimately caused most to fail before the pandemic was over, analysts said.

Domino’s in 1984 pushed a guarantee that customers would receive their pizzas for free if they weren't delivered in under a half-hour. The company amended the “30 minutes or it’s free” policy after two years, providing only a $3 discount for late deliveries.

The promotion helped Domino’s win market share, but it ended up tarnishing the company's reputation. It dropped the guarantee in December 1993 after a string of crashes and lawsuits involving drivers racing to meet the deadline.

Brad Jashinsky, a retail analyst at information technology research and consulting firm Gartner, said he thinks Amazon should take the pizza chain's experience as a cautionary tale.

“You get in trouble when you start overpromising something like that,” he said.

Amazon won't be making any time guarantees and instead plans to keep customers who chose the 30-minute delivery option updated on the progress of their orders, Tomay said.

“There's no rushing either in our building workers or the gig workers,” she said.

Taking it slow
Kodali thinks Amazon will need a lot of people placing orders around the same time from the same or adjacent apartment buildings for the 30-minute service to be cost-effective.

Consumers may appreciate rapid receipt of products like toilet paper and batteries, but retailers and logistics experts said they also see some online shoppers, especially members of Generation Z, choosing no-rush shipping for products they don't need in a hurry.

Amazon for several years has invited customers to skip one- or two-day delivery and to receive their orders on the same day in as few parcels as possible. Consolidating orders into fewer packages by electing to have them delivered at the same time cuts down on boxes, shipping envelopes and fuel use, analysts said.

“The millennials who came to age in an era that was on fast delivery came to expect it de facto, whereas ... Gen Z is more accepting of a slower speed than previous generations before them,” said Darby Meegan, a general manager at Flexport, a supply chain and logistics company that fulfills orders for thousands of online merchants.

Still, Amazon executives have cited positive early results for Amazon Now in India, where they said Prime members tripled their requests for 30-minute deliveries once they started using the service.

Amazon Now also is attracting more repeat American customers, Tomay said.

“It’s in early days and time will tell,” she said. “I think that it will be interesting to see how it evolves.”

Houston company partners on AI-powered medical support for space missions

AI in space

Houston-based Aexa Aerospace has partnered with SpacePort Australia (SPA) to build medical AI solutions for space crews.

Known as The Hamilton Project, the collaboration aims to complete the training and refinement of a “deductive medical AI model” designed to aid and treat astronauts and space travellers. With limited to no real-time access to doctors on Earth during space missions, the project's goal is to create an AI model that would serve as a medical resource.

“‘The Hamilton Project’ is a sophisticated AI model, integrating academic and clinical knowledge in a unique way,” Aexa founder and CEO Feranando De La Peña Llaca said in a news release. “It is paving the way for future autonomous attending.”

The project is named after NASA flight surgeon Dr. Douglas Hamilton, who participated in 50 missions.

SPA, an independent research organization, will bring its practical medical knowledge and clinical experience to The Hamilton Project, which builds on Australia’s rural and remote medical training programs. SPA founder Dr. Gabrielle Caswell brings 20 years of remote medicine experience that SPA believes will help address the issues that could be encountered in space.

“Rural general practitioners in Australia practice ‘pre-cradle to grave’ medicine, including areas considered sub-specialities in most western countries: OBYN, paediatrics, trauma management, anaesthetics, general surgery, mental health and geriatrics,” Caswell added in the release. “This broad clinical skill set encompasses all stages and phases of human life. And importantly practitioners are also trained in the management of severe trauma. "It is anticipated that doctors and medical staff will become embedded into missions, and all these skills will be required over time, to create successful space economic zones.”

Aexa Aerospace’s previous work includes developing holographic medical devices that have been trialled on the International Space Station. Read more here.

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