Rice University research shows the harmful impact of myths regarding motherhood, education, and professional agency. Photo via Getty Images

Gender wage discrimination remains a stubborn problem in the United States. On average, women are paid only 80 cents for every dollar paid to non-Hispanic white men, and far greater gaps persist for Latina, Black, and Native American women. Despite progress in recent decades, we have a long way to go on this issue. At the current rate, pay inequity will persist until the distant year of 2152.

What keeps us from bridging the wage gap?

In a peer-reviewed commentary regarding research that examines workplace victim-blaming, Rice University professor Mikki Hebl and former Rice Ph.D. students Shannon Cheng, Abigail Corrington, Linnea Ng and Ivy Watson interrogate the role victim-blaming plays in perpetuating the gender wage gap. According to Hebl and her team, harmful myths regarding women’s relation to the workplace cloud our understanding of why the wage gap exists to begin with. To combat the problem, they say, we must first identify and debunk such misconceptions. And then, organizational leaders must take tangible steps to implement nondiscriminatory practices.

Here are a few of the victim-blaming myths Hebl and her team attribute to the persisting gender wage gap:

Myth: Motherhood drives women to leave the workforce.

This idea doesn’t hold up under scrutiny. In 44 percent of families, women are breadwinners, and 75 percent of single mothers are sole breadwinners. On top of workplace labor, women also spend more time on service-related activities than men and an average of 65 more minutes per day on childcare and household maintenance. Moreover, mothers often face forms of workplace discrimination that fathers simply do not. The more prominent causes of women’s decision to exit are unrelated to motherhood, such as limited career opportunities and unsatisfying work environments.

Myth: Women work in less lucrative professions.

There certainly are male and female-dominated industries. But this myth suggests that women willingly opt for lower-paying careers. It also implies that some professions do not have a problem with wage inequity. But the pay gap persists across professions, and at every level. Even in female-dominated professions, women are paid less than men who share the same level of experience.

Myth: Women don’t have as much education or experience as men, and they don’t ask for what they want.

Women now hold more college and graduate degrees than men, but they continue earning less. And as women and men gain career experience, the gender pay gap widens. Indeed, the gap is largest at the executive level. In terms of women’s experience with promotions and salary increases, stereotypes and gender biases make it challenging for them to secure equal pay for equal work. Men and women are both inclined to ask for what they want, but salary negotiations often do not yield the same results for women as for men.

Victim-blaming myths like these prevent us from making progress on the issue of pay inequity. We must actively debunk them. But just as importantly, researchers argue, company leaders must put energy and resources toward addressing the problem.

Beyond deflating misconceptions about women and work, how can we change the status quo? Based on research, Hebl and her team offer these actionable strategies and suggestions:

  • Identify and remove barriers to pay equity (e.g., hold focus groups with women in the organization).
  • Provide equal growth opportunities (e.g., offer equal access to mentorship).
  • Strive toward work/life balance (e.g., subsidize or create on-site childcare).
  • Ensure nondiscriminatory policies (e.g., publish compensation ranges).
  • Promote male allyship (e.g., men in positions of influence advocate for equity).

This final strategy stands out as perhaps the most intriguing. It seems obvious to implement nondiscriminatory policies like transparency about promotion criteria. Such policies are essential for bridging the wage gap and building a culture of trust.

But what role, according to research, do male allies play in effecting a major societal and organizational change? At the very least, men can help debunk the myths that Hebl et al. describe. But more importantly, research shows that men are more likely to support gender causes when championed by other men. Male allies have immense power in advancing the cause of gender equality, which means their involvement is not just welcome but essential in the pursuit to make one dollar for men equal one dollar for women.

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This article originally ran on Rice Business Wisdom and was based on research from Michelle "Mikki" Hebl, the Martha and Henry Malcolm Lovett Chair of Psychology at Rice University and a professor of management at Jones Graduate School of Business.

A patent is an asset — one with a price associated with it when it comes to procuring a loan for your business. Photo via Getty Images

Rice research: What innovations can be used to borrow against?

Houston voices

For companies and leaders, patents represent important assets. They’re a marker of innovation and tech development. But patents do so much more than protect intellectual property. Firms increasingly deploy them as collateral to secure loans. Between 1995 and 2013, the number of patents pledged as loan collateral increased from about 10,000 to nearly 50,000. Forty percent of U.S. patenting firms have used patents as collateral.

However, patents are intangible assets, and their liquidity and liquidation value are difficult to assess. To evaluate an individual patent, lenders must consider the invention space to which the patent belongs. A patent’s linkage to prior inventions can provide important information for lenders, as the linkage affects the extent to which the patent under consideration may be redeployed and potentially purchased by other firms in the case of loan default.

Rice Business professor Yan Anthea Zhang examined more closely how this market operates and how both lenders and borrowers can make more informed decisions on which patents make appealing collateral. In their paper, “Which patents to use as loan collateral? The role of newness of patents' external technology linkage,” Zhang, who specializes in strategic management, and her co-authors studied the data on 107,180 U.S. semiconductor patents owned by 436 U.S. firms. The team focused on semiconductor patents because the semiconductor industry involves intensive innovation, which leads to many patent applications and grants. The market for semiconductor patents is an active and well-functioning market, given specialization in different stages of the innovation process and the growing technological market. Information on whether a patent was used as loan collateral came from the USPTO Patent Assignments Database.

Zhang and her colleagues argue that lenders prefer patents linked to prior inventions that are relatively new because these patents are riding on recent technology waves and are less likely to become obsolete. As a result, such patents are likely to remain deployable to other firms in the future. However, patents that are based upon too new prior inventions might not prove to be commercially viable and carry higher risk for lenders.

As a result of this research, Zhang and her colleagues found an inverted U-shape relationship to demonstrate the likelihood that a patent will be used as loan collateral. On one end, patents based upon the newest prior inventions, on the other, patents based upon mature prior inventions. The curve of the U-shape represents the sweet spot for patent collateral—the patents’ technological base is new enough to be relevant and competitive with other firms in its invention space, but not so new that it has yet to prove market success.

Zhang’s team also found that the impact of external linkage also varies depending on borrower attributes, especially the borrowers’ expertise in the invention space. If a borrower is a technological leader in the invention space, the market tends to give the borrower credit, and as a result, even if its patents are based upon very new prior inventions, its patents are still likely to be accepted as collateral.

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This article originally ran on Rice Business Wisdom and was based on research from Yan Anthea Zhang, the Fayez Sarofim Vanguard Professor of Management at Rice Business.

Here's how AI-based chat will effect research. Graphic by Miguel Tovar/University of Houston

University of Houston: Here's what intuitive AI and ChatGPT mean for research

HOUSTON VOICES

Researchers have to write extremely specific papers that require higher-order thinking — will an intuitive AI program like OpenAI’s ChatGPT be able to imitate the vocabulary, grammar and most importantly, content, that a scientist or researcher would want to publish? And should it be able to?

University of Houston’s Executive Director of the Research Integrity and Oversight (RIO) Office, Kirstin Holzschuh, puts it this way: “Scientists are out-of-the box thinkers – which is why they are so important to advancements in so many areas. ChatGPT, even with improved filters or as it continues to evolve, will never be able to replace the critical and creative thinking we need in these disciplines.”

“A toy, not a tool”

The Atlantic published, “ChatGPT Is Dumber Than You Think,” with a subtitle advising readers to “Treat it like a toy, not a tool.” The author, Ian Bogost, indulged in the already tired troupe of asking ChatGPT to write about “ChatGPT in the style of Ian Bogost.” The unimaginative but overall passable introduction to his article was proof that, “any responses it generates are likely to be shallow and lacking in depth and insight.”

Bogost expressed qualms similar to those of Ezra Klein, the podcaster behind, “A Skeptical Take on the AI Revolution.” Klein and his guest, NYU psychology and neural science professor Gary Marcus, mostly questioned the reliability and truthfulness of the chatbot. Marcus calls the synthesizing of its databases and the “original” text it produces nothing more than “cut and paste” and “pastiche.” The algorithm used by the program has been likened to auto-completion, as well.

However, practical use cases are increasingly emerging, which blur the lines between technological novelty and professional utility. Whether writing working programming code or spitting out a rough draft of an essay, ChatGPT does have a formidable array of competencies. Even if just how competent it is remains to be seen. All this means that as researchers look for efficiencies in their work, ChatGPT and other AI tools will become increasingly appealing as they mature.

Pseudo-science and reproducibility

The Big Idea reached out to experts across the country to determine what might be the most pressing problems and what might be potential successes for research now that ChatGPT is readily accessible.

Holzschuh, stated that there are potential uses, but also potential misuses of ChatGPT in research: “AI’s usefulness in compiling research proposals or manuscripts is currently limited by the strength of its ability to differentiate true science from pseudo-science. From where does the bot pull its conclusions – peer-reviewed journals or internet ‘science’ with no basis in reproducibility?” It’s “likely a combination of both,” she says. Without clear attribution, ChatGPT is problematic as an information source.

Camille Nebeker is the Director of Research Ethics at University of California, San Diego, and a professor who specializes in human research ethics applied to emerging technologies. Nebeker agrees that because there is no way of citing the original sources that the chatbot is trained on, researchers need to be cautious about accepting the results it produces. That said, ChatGPT could help to avoid self-plagiarism, which could be a benefit to researchers. “With any use of technologies in research, whether they be chatbots or social media platforms or wearable sensors, researchers need to be aware of both the benefits and risks.”

Nebeker’s research team at UC San Diego is conducting research to examine the ethical, legal and social implications of digital health research, including studies that are using machine learning and artificial intelligence to advance human health and wellbeing.

Co-authorship

The conventional wisdom in academia is “when in doubt, cite your source.” ChatGPT even provides some language authors can use when acknowledging their use of the tool in their work: “The author generated this text in part with GPT-3, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication.” A short catchall statement in your paper will likely not pass muster.

Even when being as transparent as possible about how AI might be used in the course of research or in development of a manuscript, the question of authorship is still fraught. Holden Thorp, editor-in-chief of the Science, writes in Nature, that “we would not allow AI to be listed as an author on a paper we published, and use of AI-generated text without proper citation could be considered plagiarism.” Thorp went on to say that a co-author of an experiment must both consent to being a co-author and take responsibility for a study. “It’s really that second part on which the idea of giving an AI tool co-authorship really hits a roadblock,” Thorp said.

Informed consent

On NBC News, Camille Nebeker stated that she was concerned there was no informed consent given by the participants of a study that evaluated the use of a ChatGPT to support responses given to people using Koko, a mental health wellness program. ChatGPT wrote responses either in whole or in part to the participants seeking advice. “Informed consent is incredibly important for traditional research,” she said. If the company is not receiving federal money for the research, there isn’t requirement to obtain informed consent. “[Consent] is a cornerstone of ethical practices, but when you don’t have the requirement to do that, people could be involved in research without their consent, and that may compromise public trust in research.”

Nebeker went on to say that study information that is conveyed to a prospective research participant via the informed consent process may be improved with ChatGPT. For instance, understanding complex study information could be a barrier to informed consent and make voluntary participation in research more challenging. Research projects involve high-level vocabulary and comprehension, but informed consent is not valid if the participant can’t understand the risks, etc. “There is readability software, but it only rates the grade-level of the narrative, it does not rewrite any text for you,” Nebeker said. She believes that one could input an informed consent communication into ChatGPT and ask for it to be rewritten at a sixth to eighth grade level (which is the range that Institutional Review Boards prefer.)

Can it be used equitably?

Faculty from the Stanford Accelerator for Learning, like Victor Lee, are already strategizing ways for intuitive AI to be used. Says Lee, “We need the use of this technology to be ethical, equitable, and accountable.”

Stanford’s approach will involve scheduling listening sessions and other opportunities to gather expertise directly from educators as to how to strike an effective balance between the use of these innovative technologies and its academic mission.

The Big Idea

Perhaps to sum it up best, Holzschuh concluded her take on the matter with this thought: “I believe we must proceed with significant caution in any but the most basic endeavors related to research proposals and manuscripts at this point until bot filters significantly mature.”

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

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

Houston research: Your tools can reflect your workplace skills

Houston voices

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.

Earnings report delays generally lead to drops in stock prices. Disclosure can soften this market reaction. Photo via Getty Images

Houston research: Is no news always bad news in market reports?

houston voices

Investors eagerly wait for the news in their earnings reports. When these reports don't appear on the expected date, investors worry — and stock prices often fall as a result. But what if managers could present late reports in a way that spared their companies?

Research by K. Ramesh, a professor at Rice Business, shows that managers' approach to late earnings reports can profoundly affect market reaction. When firms put off filing a report, it's up to managers to decide whether to speak up or stay quiet. Those who choose to talk about a postponement then must decide how, what and how much to say.

All earnings delays, whether they're attended by a statement or not, prompt negative market reaction, prior research suggests. But in his research, Ramesh, Herbert S. Autrey Professor of Accounting, wanted to learn more about the exact consequences of these late reports, and how managers can lessen the blowback.

To do this, Ramesh and a team of coauthors first looked at the incidence, timing and contents of a comprehensive sample of press releases announcing an earnings delay. Then they studied what those delays did to market value.

Conventional wisdom in the business press already suggested that investors viewed any announcement of a delayed earnings report as bad news. But finance theorists tell a more complicated story, one in which the market response might be partially shaped by managerial behavior. Subtle factors, they found, such as whether the impending delay is discussed or treated with silence, really can make a difference.

In the view of some theorists, merely announcing a delay can sometimes avert a drop in stock prices. Others argue that this isn’t necessarily the case, especially if the company discloses that the delay stemmed from legal concerns. The better approach: making it clear up front that reports aren't being postponed to hide disastrous information. But what if the information is indeed disastrous?

That may be the one case where disclosure won’t change much, Ramesh and his team found.

“Those companies that are in fact concealing disastrous results will experience no benefits (in the form of higher stock price) from revealing their true situation,” the research team wrote, “because the market will infer the worst from the manager’s decision not to announce the delay.” For this reason, they added, delayed earnings without a stated explanation prompt the most negative market reaction. As in so many areas of public relations, without a narrative, investors will infer a negative one of their own.

To better understand the impact of late reports, Ramesh and his coauthors built a comprehensive sample of 545 delay announcements by using a keyword search of the Dow Jones Factiva database between January 1, 1995, and December 31, 2009.

As conventional wisdom suggested, the study showed that announcements of late earnings reports led to negative market reactions. (Earlier studies have shown smaller firms are hit hardest by this dynamic, perhaps because investors assume large companies have more finely tuned financial reporting systems, so are less worried by their earnings delays).

Consistent with the anecdotal evidence, the average one-day abnormal stock return for the sample was -6.29 percent, while the median return was -2.27 percent. Both figures are economically and statistically significant.

The researchers next classified the announcements according to stated reason, dividing the delays into “Accounting” and “Non-Accounting” categories. “Accounting” explanations were subdivided into “Accounting Issue,” “Accounting Process” and “Rule Change.”

Meanwhile, “Non-Accounting” explanations were divided into “Business,” which linked the delay to some event such as divestitures or regulatory proceedings, and “Other,” which ranged from earthquakes to power outages. Finally, there were delays for no stated reason at all.

About two-thirds of the late announcements, the team found, were linked to accounting. When firms named a specific accounting issue as the cause for delay, the average abnormal return reached a statistically significant -8.15 percent. When managers explained that the accounting process was not complete, the average abnormal return was slightly lower, at -7.04 percent.

After accounting issues, business events drove most earnings delays. In theory, these events could have been either good or bad news. But the average abnormal return for the subsample was a statistically significant -3.74 percent — a reflection of the fact that most business events linked to late earnings reports tend to be negative.

Curiously, the average abnormal return for the grouping classified as “Other” was almost nil — at 0.53 percent. This suggests that the market does not penalize managers for events outside of their control that have little, if any, relevance to firm performance.

“No Reason,” the researchers found, was the most damaging explanation of all. Seven percent of the sample, or 37 out of 545 delays, came without a stated reason. The average abnormal return for these was a significant -10.41 percent, a greater negative number than the returns for any of the other reasons.

So what should managers do when a deadline is going to be busted? Bite the bullet and disclose the reasons, Ramesh suggests. For one thing, it helps limit legal exposure and preserve credibility. When the reason for the late report is innocuous, explaining to investors can also mitigate the market's displeasure. A caveat: While informing investors that a power outage caused earnings delay will calm jitters, disclosure may not make a difference if the company just can’t balance its books.

It's human nature, apparently, to read no news as bad news. Relaying something—anything—about the cause of a late report seems to soothe investors' nerves by preventing them from filling the silence themselves.

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This article originally ran on Rice Business Wisdom and was based on research from K. Ramesh, Tiago Duarte-Silva, Huijing Fu and Christopher F. Noe. K. Ramesh is the Herbert S. Autrey Professor of Accounting at Jones Graduate School of Business at Rice University.

To err is human, after all. Graphic by Miguel Tovar/University of Houston

University of Houston: Navigating non-compliance and human error in research

houston voices

To comply is to obey, or conform to instruction or official requirements. In a perfect world, research non-compliance wouldn’t occur and following the rules would be a behavioral norm. But the reality is, to err is human.

To err is human

Often times the judgement of our own, and others, poor decision-making is rooted in the innate tendency to view things in black or white – categorizing behaviors as either right or wrong, good or bad, thus deeming them as either ethical or unethical.

But this way of thinking often conflicts with the gray world in which we exist. So what happens when research decisions land somewhere in the moral gray area?

Before answering, here are two situations to consider that involve the over-enrollment of research participants:

Case 1:
The IRB has approved a survey for 40 subjects. The PI realizes after the survey has been open for several weeks that she forgot to set a participant limit within the survey program and 60 subjects have completed the survey.

Case 2:

A study involving a new drug to control diabetes symptoms is approved to enroll 30 participants. The study doctor thinks the drug may be beneficial, so she continues enrolling, for a total of 80 subjects.

The devil is in the details

Why is over-enrollment of subjects considered non-compliance?

Many institutions have agreed, within their assurance to the U.S. Department of Health and Human Services (HHS), to apply the Common Rule to all human subjects research, whether the research is funded or not.

The Common Rule regulations found at 45 CFR 46.109(a) and 45 CFR 46.111 (1) state that the IRB shall review and have authority to approve, require modifications in (to secure approval), or disapprove all research activities. This includes the maximum number of research .

And what must the IRB review?

Under the above regulatory requirements, the IRB must evaluate all instances of non-compliance.

In these cases of over-enrollment, the IRB must review the number of subjects over-enrolled and assess any potential effects on additional subjects and/or the research, as well as determine if the noncompliant data may be used for research purposes.

What UH IRB says about Case 1:

While over-enrollment in a survey seems low-risk, depending on the content of the survey questions, the IRB could determine the issue to be more serious, such as for a study collecting data related to illegal substance use or questions about traumatic events (legal or psychological harm). The IRB must ensure that risks to subjects are minimized; only the number of subjects needed to statistically justify the research are approved. Depending on the number of subjects over-enrolled and the time period over which they participated, the non-compliance could also be considered continuing.

What UH IRB says about Case 2:

Investigational drug studies often pose more than minimal risk of harm to subjects. In these studies, it is even more critical to ensure that additional subjects are not exposed to potential harms without scientific justification

In a drug study, the PI may not continue a study based on opinion; the reason a physician is blinded to treatment assignment in many drug studies is to avoid potential bias.

Finding non-compliance: What can you do?

If the number of subjects enrolled exceeds the number approved by the IRB, a finding of non-compliance is justified. The IRB will review the numbers, the Principal Investigator’s reasons for over-enrollment and assess what procedures were conducted in these subjects. Often over-enrollment is inadvertent, however the committee also has the ultimate authority to determine whether the data may be used for research purposes.

Corrective actions, such as continuing education of the PI and/or study team to ensure this issue does not occur again in the future, are often required. In the most serious cases, the IRB may suspend or terminate approval.

If the non-compliance rises to the level of being serious (harms or has the potential to harm subjects or others) and/or continuing in nature, it must be reported to federal oversight agencies such as the Health and Human Services Office for Human Research Protections (OHRP) and the FDA. These agencies ensure that the institution is monitoring for these activities and puts appropriate fixes in place.

The importance of intetrity

Non-compliant research can be due to inadvertent errors or deliberate acts of noncompliance. The results could be the same. Human subjects could be harmed. Funding and reputation at an institution conducting research could be negatively affected. In times of reduced federal funding for basic research, there are direct financial costs to the agencies when funds and resources are misused.

The responsibility of ensuring that research protocols are adhered to rests upon the shoulders of the researchers involved.

If you were a member on the IRB, what would you consider to be appropriate consequences for the PI in these situations?

It’s important to note that non-compliance, whether it’s a “little white lie/inadvertent error” or a deliberate violation of the approved protocol can undermine the integrity of both the research process and the academic research enterprise.

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This article originally appeared on the University of Houston's The Big Idea. Nitiya Spearman, the author of this post, is the internal communications coordinator for the UH Division of Research.

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KBR names C-suite duo to lead $5.3B government services spinoff

new leaders

In advance of the spinoff of its Mission Technology Solutions unit, Houston-based KBR has made two C-suite hires for the new business.

Michael LaRouche is coming aboard as president and CEO of the spinoff, currently called SpinCo, on Sept. 26. Nicholas Veasey is joining as executive vice president and chief financial officer on July 1.

“Michael and Nick bring a highly complementary combination of operational leadership, financial expertise, and mission-driven experience, and together they will accelerate our impact for stakeholders,” Stuart Bradie, chairman, president and CEO of publicly traded KBR, said in a news release.

LaRouche currently is CEO of Serco North America, a Herndon, Virginia-based government services contractor. Veasey most recently was CFO of MAG Aerospace, a Fairfax, Virginia-based defense contractor.

SpinCo, a government services contractor, will launch with more than $5.3 billion in annual revenue and 20,000 employees. KBR’s total headcount is around 36,000. Branding for SpinCo, including a formal name, will be revealed in July.

“SpinCo is positioned as a top-tier provider of differentiated technology solutions, anchored by deep mission expertise, global scale, and a relentless commitment to delivering for our customers,” LaRouche says.

After the spinoff, the slimmed-down KBR will focus on its Sustainable Technology Solutions business, a provider of energy and industrial technology that generated $2.5 billion in revenue in 2025. Bradie will remain chairman, president and CEO of the business.

Both SpinCo and the new KBR will be public companies. The spinoff is scheduled to be completed in January.

Experts: Houston's VC ecosystem has set the foundation — now we need scale

guest column

Fervo Energy went public earlier this summer. The Houston geothermal company priced its IPO at $27 per share, raised $1.89 billion, and opened the next morning at a market capitalization north of $10 billion. By most measures, it is the largest venture-backed cleantech IPO in history and an unambiguous win for Houston. It’s also a useful moment to look at where Houston's venture ecosystem stands and where it can go. The highlight: Houston's venture ecosystem has real foundations and, with increased company formation activity, can grow into the scale our city's ambitions deserve.

A Houston energy story in the national recovery

The recent uptick in Houston venture activity follows national trends. U.S. venture deal count contracted roughly 22 percent from its 2021 peak through 2024 before rebounding to about 16,700 rounds in 2025. Houston's 23 percent increase in VC funding from 2023 to 2024 is part of a national recovery of comparable magnitude over the same time window.

The energy sector is where Houston exhibits unique trends—and where the story turns clearly positive. (Houston's strong health and space sectors deserve their own separate consideration.) By deal count, energy-related rounds have accounted for 15 to 20 percent of Houston activity, roughly consistent over the past few years.

By capital, energy's share surged from about 14 percent in 2023 to over 60 percent in 2025, driven by a small number of large Houston-headquartered rounds, primarily in geothermal and related technologies. Fervo is the obvious anchor, but Sage Geosystems, Quaise Energy, Zeta Energy, Vaulted Deep, Applied Carbon and Mariana Minerals have all closed meaningful rounds. Houston is concentrated and accelerating as an energy capital market, an invaluable position to build upon.

From foundation to scale

The institutional pieces are in place. Greentown Labs, Activate, the Ion and others have built sector-specialized infrastructure most cities would struggle to assemble. Fervo itself is an alum of both Activate and Greentown Labs. Mercury Fund closed its $160 million Fund V, its largest ever. Houston Angel Network, GOOSE Capital, Fathom Fund, and broader pre-seed and seed capital coverage are here. The Houston $10 million-plus Series A list now includes 40 rounds since 2021, which break roughly into two eras. While 2021 to 2022 was biotech-heavy, with companies like Sporos Bioventures, RadioMedix, Cellenkos and Coya Therapeutics, 2024 to 2025 has tilted clearly toward energy, climate, and critical minerals, with Vaulted Deep, Applied Carbon, Mariana Minerals, Sage Geosystems and Ignis H2 Energy among them.

What’s less developed is the volume of seed-stage companies flowing into that capital. Imagine a dozen more Fervos coming out of that infrastructure over the next decade, each generating jobs, recycled founder capital, and the next wave of operators and angel investors. That is the kind of opportunity Houston has within reach if we build the company-formation pipeline to feed it. To be relevant on the national stage as a venture market, and to drive an economy the size of Houston's into the 2030s, the city needs to be doing closer to 20 Series A rounds per month rather than per year. That throughput implies roughly 1,000 seed rounds per year, feeding the funnel at a 20 percent to 30 percent graduation rate. Reaching such throughput depends on how many new founders Houston produces and how quickly our innovation ecosystem can help them achieve lift-off.

Houston in context

The comparative picture brings the scaling challenge into focus. Between 2021 and 2024, Houston-area startups closed between 126 and 153 disclosed venture rounds per year, against a national count between 9,854 and 14,125. That places Houston at a little over 1 percent of the U.S. deal count. For comparison, Austin ran about three times Houston's deal count each year.

At the Series A level, Houston closed between 12 and 24 rounds in any given year. The median Houston Series A across the period was about $10.7 million, compared with $15.4 million in San Francisco. Houston founders are raising fewer and smaller Series A rounds than founders in peer metros, which points directly to where Houston has the most room to grow.

The unicorn picture tells the same story. From 2021 through 2025, the U.S. produced 590 venture-backed unicorns. Four were Houston-based: Solugen and Axiom Space in 2021, Cart.com in 2023, and Fervo Energy in 2024. Adding HighRadius from 2020 brings Houston's all-time total to five. Austin added 19 over the same five-year window. The path from here is to make Houston's entries on lists like these less the exception and more the rule.

Where this leads

Houston has a real opportunity to become the deepest, most credible energy and climate capital market in the country, with the company formation, talent and operator density to support it. The data shows the foundation is already in place. Fervo, Solugen and the growing roster of energy-adjacent Series A graduates are proof. Fervo's IPO is the first of what should be many. Houston has not had a venture-backed cleantech liquidity event of this scale before, and the city now has one to reference, recruit against and build on. With increased company formation at the seed and pre-seed stages, a Fervo-scale outcome need not be a generational event in Houston, but instead, it can become part of a chain reaction powering the city's economy.

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Stephanie T. Schmidt, PhD, is the founder of a stealth startup, a Venture Fellow at Energy Transition Ventures, and an Executive MBA candidate at Rice University's Jones Graduate School of Business. Lawson Gow is the Chief Operating Officer of Greentown Labs. The full Houston VC landscape report is available at Energy Transition Ventures and CleanTech.Org.

Sources: Crunchbase, PitchBook-NVCA, Carta

8 can't-miss Houston business and innovation events for July

where to be

Editor's note: Summer is in full swing in Houston, but the city's innovation ecosystem isn't slowing down. This month brings AI workshops, energy and manufacturing discussions, entrepreneur-focused networking, and opportunities to connect with investors and industry leaders. Here’s what not to miss and how to register. Please note: this article may be updated to add more events.

July 7 — How Oil and Gas Professionals are Building Wealth Smarter

Hear from oil and gas professionals on how to preserve wealth at this event put on by Financial Advice Center. The conversation will touch on topics like investing, taxes and retirement planning.

This event is Tuesday, July 7, from noon-1 p.m. at the Ion. Register here.

July 7 — What AI, Cybersecurity, and Tequila Have in Common.

Join Blue People and Alpfa Houston for this engaging presentation on the advantages and risks associated with AI at the latest installment of Tech + Tequila Talk. Cybersecurity veteran Reynaldo Gonzalez will lead the conversation.

This event is Tuesday, July 7, from 5-7 p.m. at the Ion. Register here.

July 7 — Speed to Market: Houston’s Advanced Manufacturing Edge

The Greater Houston Partnership presents a forum that explores what allows advanced manufacturing projects in Houston to move from concept to operation, where delays and bottlenecks occur, and more. Industry leaders Jennifer Clement from CliftonLarsonAllen LLP and Sarah Janes from San Jacinto College will lead the discussion.

This event is Tuesday, July 7, from 11:30 a.m.-1 p.m. at the Partnership Tower. Register here.

July 9 — Capital Connections Summit

Houston City College Center for Entrepreneurship will host the Capital Connections Summit this month, with a panel discussion focused on access to capital and technical assistance for small businesses and entrepreneurs. The event will be moderated by the U.S. Small Business Administration Houston District Office and will feature lenders, nonprofit microlenders, business advisors, and entrepreneurial support organizations. A live Q&A will follow the panel.

This event is Thursday, July 9, from 11 a.m.-1:30 p.m. at Houston City College Central Campus. Register here.

July 9 — Upstream: Digital Tech Meetup at Second Draught

Join Timbergrove at this month's gathering of energy, operations and technology professionals from across the upstream ecosystem. Discuss challenges, explore new ideas and network over pizza and beer at Second Draught.

This event is Thursday, July 9, from 5:30–8 p.m. at the Ion. Register here.

July 14 — Why Networking Isn’t Turning Into Deals, And What To Do Instead

Jada Powell, founder of Powell Consulting Group, will break down why networking often fails to convert into deals and what companies can do differently to turn conversations into qualified opportunities. Powell works with oil and gas, energy, and industrial companies on business development solutions. This session is part of the monthly Pipeline Series: How Oil & Gas Companies Actually Grow Revenue.

This event is Tuesday, July 14, from noon-1 p.m. at the Ion. Register here.

July 15 — From Pilot to Performance: Building Your AI Procurement Roadmap

It's not too late to join in on the GHP's two-part AI series on moving from experimentation to implementation. In session two, explore how procurement and supply chain leaders can scale AI responsibly to create long-term business value. This event will be led by Cassye Cook Provost, founder and principal of RossGrigsby Consultancy.

This virtual event is Wednesday, July 15, from 8:30-10 a.m. Register here.

July 30 — Rice University Summer Engineering Innovation Program - Demo Day 2026

Meet the young minds and see the final team project presentations from Rice University’s Summer Engineering Innovation Program. The 10-week program challenges Rice students to solve real-world challenges using AI, digital engineering, model-based systems engineering and Industry 4.0 technologies.

This event is Thursday, July 30, from 6-8 p.m. at the Ion. Find more information here.