Owning or even imagining that you own an object linked to a particular task can make you feel — and act — more like an adept. Photo via Getty Images

Want to get better at a task? It may be possible to shop — or imagine — your way to success.

Just pretending to shop for items associated with certain skills (for example, a fancy calculator) may actually improve your performance in areas related to that skill (in this case, math).

That’s because our identities are highly influenced by our possessions — which we often experience as part of ourselves. As a result, this activation of an identity by our possessions, even imaginary ones, can enhance performance. For example, one study found that by using a pen labeled “MIT” on GRE exams, students scored higher than those using a standard Pilot pen, particularly when they believed that their inner ability was fixed, and that they had to rely on external products to improve their ability.

In 2018, Rice Business professor Jaeyeon Chung and Gita V. Johar of Columbia University took a close look at the implications of this human quirk.

In a series of experiments, Chung and Johar found that the product-related activation of our identities (e.g., calculator ownership awakening an inner math prodigy) can actually de-activate our identities unrelated to the product, and undermine performance in other tasks.

For example, shopping for a calculator could make you perform better on a math test, but worse on a creative-writing essay.

Merely owning an item, the scholars discovered, is only part of the equation. Self-concept clarity — that is, the strength and clarity of one’s personal beliefs — makes a difference as well. A person whose self-concept is well-defined, consistent, and stable is less likely to be influenced by external factors such as possessions.

To measure the phenomenon, Chung and her colleague devised a series of experiments. The results showed that when a person merely imagines an item she longs to own, two inner changes occur: Identities related to the product are awakened, and identities unrelated to the desired object are stifled. Strikingly, these changes have measurable consequences on the performance of tasks.

But how do you awaken an inner self through possession, and measure its effects? The team found an ingenious approach: They assigned people to a control group or an experimental group, and then asked them to peruse an online IKEA. The control group was told to shop for items to go in a senior citizen home. The experimental group shopped for items to go into their own homes.

The experimental group, who got to imagine items such as a MALM bed in their own bedrooms, were more likely to think of themselves as artistic designers than were their counterparts, the imaginary retirement home shoppers. The exercise, in other words, had activated participants’ art-related identities.

Next, Chung and Johar asked everyone to complete a math task. The experimental group scored lower at this than did those in the control group. Their newly awakened identities as design mavens had undermined their ability to solve math problems, apparently because they were unrelated to the fetching Scandinavian décor they’d imagined owning.

The researchers then took another approach. Asking one group of participants to imagine owning a calculator, they activated that group’s “math identity.” They then asked all the participants to engage in a short IQ test. Though there was only one test, the researchers labeled it two different ways, indicating to some participants that the test measured math skills, and to others that it measured creative writing skills.

Despite the test being exactly the same, the would-be calculator owners performed markedly worse when they thought they were doing a creative writing project than when they thought the test measured their math skills. Why, exactly? The researchers concluded that imagining owning a piece of math-y technology and activating their “math person identities” tamped down participants’ “creative writer” identities — so much so that it actually degraded their performance in that area.

In a third experiment, Chung and Johar asked a group to envision calculators that they actually owned, rather than simply imagining buying one. Again, the group that felt ownership regarding a math tool performed better on tasks that seemed math-related, but worse on tasks that seemed unrelated to math. The finding was robust when the task itself was exactly the same and the only difference how the task was labeled.

Interestingly, identity activation and performance were influenced by the participants’ level of self-concept clarity. Some people have a clear and consistent self-view that does not vary over time; these are individuals who are less likely to rely on their possessions or other environmental stimuli to infer who they are. These individuals were less likely to be affected by the “ownership” of a calculator.

In other words, self-concept clarity limited the power of ownership on identity activation and performance. Chung and Johar’s findings offer practical implications for both business and academia. Owning or even imagining that you own an object linked to a particular task can make you feel — and act — more like an adept.

So the next time you have a big quantitative test coming up, consider browsing for a high-end calculator first — and unwinding with your oil paints or “Infinite Jest” when you’re done. For best results, of course, take the test with your Rice-labeled pen.

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This article originally ran on Rice Business Wisdom and was based on research from Jaeyeon (Jae) Chung is an assistant professor of marketing at Jones Graduate School of Business at Rice University.

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Houston unicorn closes $421M to fuel first phase of flagship energy project

Heating Up

Houston geothermal unicorn Fervo Energy has closed $421 million in non-recourse debt financing for the first phase of its flagship Cape Station project in Beaver County, Utah.

Fervo believes Cape Station can meet the needs of surging power demand from data centers, domestic manufacturing and an energy market aiming to use clean and reliable power. According to the company, Cape Station will begin delivering its first power to the grid this year and is expected to reach approximately 100 megwatts of operating capacity by early 2027. Fervo added that it plans to scale to 500 megawatts.

The $421 million financing package includes a $309 million construction-to-term loan, a $61 million tax credit bridge loan, and a $51 million letter of credit facility. The facilities will fund the remaining construction costs for the first phase of Cape Station, and will also support the project’s counterparty credit support requirements.

Coordinating lead arrangers include Barclays, BBVA, HSBC, MUFG, RBC and Société Générale, with additional participation from Bank of America, J.P. Morgan and Sumitomo Mitsui Trust Bank, Limited, New York Branch.

“As demand for firm, clean, affordable power accelerates, EGS (Enhanced Geothermal Systems) is set to become a core energy asset class for infrastructure lenders,” Sean Pollock, managing director, project Finance at RBC Capital Markets, said in a news release. “Fervo is pioneering this step change with Cape Station, a vital contribution to American energy security that RBC is proud to support.”

The oversubscribed financing marks Cape Station’s shift from early-stage and bridge funding to a long-term, non-recourse capital structure, according to the news release.

“Non-recourse financing has historically been considered out of reach for first-of-a-kind projects,” David Ulrey, CFO of Fervo Energy, said in a news release. “Cape Station disrupts that narrative. With proven oil and gas technology paired with AI-enabled drilling and exploration, robust commercial offtake, operational consistency, and an unrelenting focus on health and safety, we have shown that EGS is a highly bankable asset class.”

Fervo continues to be one of the top-funded startups in the Houston area. The company has raised about $1.5 billion prior to the latest $421 million. It also closed a $462 million Series E in December.

According to Axios Pro, Fervo filed for an IPO that would value the company between $2 billion and $3 billion in January.

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This article first appeared on EnergyCapitalHTX.com.

Houston food giant Sysco to acquire competitor in $29 billion deal

Mergers & Acquisitions

Sysco, the nation's largest food distributor, will acquire supplier Restaurant Depot in a deal worth more than $29 billion.

The acquisition would create a closer link between Sysco and its customers that right now turn to Restaurant Depot for supplies needed quickly in an industry segment known as “cash-and-carry wholesale.”

Sysco, based in Houston, serves more than 700,000 restaurants, hospitals, schools, and hotels, supplying them with everything from butter and eggs to napkins. Those goods are typically acquired ahead of time based on how much traffic that restaurants typically see.

Restaurant Depot offers memberships to mom-and-pop restaurants and other businesses, giving them access to warehouses stocked with supplies for when they run short of what they've purchased from suppliers like Sysco.

It is a fast growing and high-margin segment that will likely mean thousands of restaurants will rely increasingly on Sysco for day-to-day needs.

Restaurant Depot shareholders will receive $21.6 billion in cash and 91.5 million Sysco shares. Based on Sysco’s closing share price of $81.80 as of March 27, 2026, the deal has an enterprise value of about $29.1 billion.

Restaurant Depot was founded in Brooklyn in 1976. The family-run business then known as Jetro Restaurant Depot, has become the nation's largest cash-and-carry wholesaler.

The boards of both companies have approved the acquisition, but it would still need regulatory approval.

Shares of Sysco Corp. tumbled 13% Monday to $71.26, an initial decline some industry analysts expected given the cost of the deal.

Houston researcher builds radar to make self-driving cars safer

eyes on the road

A Rice University researcher is giving autonomous vehicles an “extra set of eyes.”

Current autonomous vehicles (AVs) can have an incomplete view of their surroundings, and challenges like pedestrian movement, low-light conditions and adverse weather only compound these visibility limitations.

Kun Woo Cho, a postdoctoral researcher in the lab of Rice professor of electrical and computer engineering Ashutosh Sabharwal, has developed EyeDAR to help address such issues and enhance the vehicles’ sensing accuracy. Her research was supported in part by the National Science Foundation.

The EyeDAR is an orange-sized, low-power, millimeter-wave radar that could be placed at streetlights and intersections. Its design was inspired by that of the human eye. Researchers envision that the low-cost sensors could help ensure that AVs always pick up on emergent obstacles, even when the vehicles are not within proper range for their onboard sensors and when visibility is limited.

“Current automotive sensor systems like cameras and lidar struggle with poor visibility such as you would encounter due to rain or fog or in low-lighting conditions,” Cho said in a news release. “Radar, on the other hand, operates reliably in all weather and lighting conditions and can even see through obstacles.”

Signals from a typical radar system scatter when they encounter an obstacle. Some of the signal is reflected back to the source, but most of it is often lost. In the case of AVs, this means that "pedestrians emerging from behind large vehicles, cars creeping forward at intersections or cyclists approaching at odd angles can easily go unnoticed," according to Rice.

EyeDAR, however, works to capture lost radar reflections, determine their direction and report them back to the AV in a sequence of 0s and 1s.

“Like blinking Morse code,” Cho added. “EyeDAR is a talking sensor⎯it is a first instance of integrating radar sensing and communication functionality in a single design.”

After testing, EyeDAR was able to resolve target directions 200 times faster than conventional radar designs.

While EyeDAR currently targets risks associated with AVs, particularly in high-traffic urban areas, researchers also believe the technology behind it could complement artificial intelligence efforts and be integrated into robots, drones and wearable platforms.

“EyeDAR is an example of what I like to call ‘analog computing,’” Cho added in the release. “Over the past two decades, people have been focusing on the digital and software side of computation, and the analog, hardware side has been lagging behind. I want to explore this overlooked analog design space.”