Allowing employees to select their incentives increases both the quantity and quality of their ideas. Photo via Getty Images

Companies can increase not only the volume but also the quality of employee suggestions and ideas by offering rewards and a choice, according to a study we published in 2022.

We conducted the study on 345 telemarketers at a call center in Taiwan, which already had a suggestion program set up to solicit creative ideas to improve the organization. The company rewarded those who suggested ideas deemed the most valuable by giving them a trophy.

We wanted to see how tweaking the reward changed the quantity and quality of suggestions. So we invited the employees to submit ideas and that if their suggestions ranked among the top 20% most creative ideas – as evaluated by a team of managers and researchers – they would receive one of four rewards: US$80 in cash for themselves, $80 to share with colleagues, $80 to give to a preferred charitable organization or priority when selecting days off. About half of the employees were offered a choice of the four rewards they would receive for submitting ideas. We then randomly assigned one of the four rewards to the remaining employees.

In total, we received and evaluated 144 ideas over a one-month period.

We found that employees who were given a choice of reward submitted 86% more ideas than those who were told what they would be getting. Moreover, the average creativity score of their ideas was 82% higher. Overall, our suggestion program elicited double the number of ideas as the company’s own program and resulted in ideas that were ranked 84% more creative.

Why it matters

Soliciting employee ideas can be a key driver of innovation in organizations.

When employees share their ideas about products, services or policies using a suggestion program, an organization can take those ideas and refine and then implement them.

These implemented ideas can enhance an organization’s ability to adapt and compete. A 2003 study of 47 organizations found that ideas submitted to employee suggestion programs saved those organizations more than $624 million in a single year.

Our own study suggests small incentives could have a significant impact on the quantity and quality of those employee suggestions.

What’s next?

Research is still needed on whether there is an optimal number of rewards that organizations should offer to get more submissions. One past study found that when employees were asked to choose from a large set of rewards, they felt overwhelmed and produced few ideas.

Future research can also test whether our results can be found in other types of organizations, with employees in other types of jobs and in other parts of the world. We plan to examine these issues in our future studies of suggestion programs.


This article originally ran on Rice Business Wisdom and was based on research from Jing Zhou, the Mary Gibbs Jones Professor of Management and Psychology in Organizational Behavior at the Jones Graduate School of Business of Rice University.

Here's what you should learn from social media influencers for your own business marketing. Photo via Getty Images

Key business marketing tips to take from top social media creators, according to these Houston researchers

houston voices

Influencer marketing is booming, with companies allocating 10 to 25 percent of their advertising budgets to influencer-led strategies. Between 2016 and 2020, the number of sponsored posts rose from 1.26 million to 6.12 million, and overall spending in the past few years has grown by billions.

When partnering with online ambassadors, brands certainly want a large influencer audience. However, audience size does not necessarily reflect the amount influencers are paid. Influencers with similar-sized audiences can be paid very different amounts.

That’s partly because brands also want an engaged influencer audience. An influencer may have many followers, but if those followers don’t actively interact with content, the influencer’s reach is limited. Engagement metrics like comments, shares and “likes” are often a more reliable indicator of impact than follower count alone.

The problem brands face — no matter who the influencer is — is that sponsored posts typically see a plunge in engagement, making it difficult to measure their success. Very little research examines this effect and how influencers can mitigate it.

In a new study, Rice Business professors Jae Chung and Ajay Kalra take up this issue, along with Stanford professor Yu Ding. According to the researchers, one way of boosting engagement overall, even on sponsored content where engagement often falls, is for influencers to increase audience perceptions of authenticity, perceived similarity, and interpersonal curiosity.

Even in a world full of filters and careful staging, authenticity is a key differentiator for leaders, businesses and personalities. One powerful way of appearing true to one’s own personality or character is to effectively share life stories. But social media influencers walk a fine line between presenting their authentic selves and monetizing their platforms.

To attract followers and content sponsors, influencers must curate the images they share, the words they say, and the timing and cadence of their posts. It’s a delicate dance between providing value through a genuine audience connection and aligning with brand interests.

Here are three simple but powerful ways that influencers can boost engagement by highlighting close relationships:

  • Post photos that include one or two close friends or family members.
  • Mention friends and family in the caption.
  • Use first-person language (e.g., “I,” “my” and “we”).

Referencing close social ties is an especially powerful way to boost engagement. According to Professor Chung, “Intimate social ties can make influencers seem more authentic and sponsored messaging seem less transactional.” This effect holds true even when controlling for variables like gender, frequency of posting, use of emojis and hashtags, and audience familiarity with the influencer.

The team analyzed over 55,000 Instagram posts from 763 top influencers during the second half of 2019. One of their most distinctive findings is that, in terms of boosting audience engagement, the ideal number of faces in a photo is three — the influencer plus two friends or family members. For an Instagram audience, this numerical face count proves a surprisingly effective metric for assessing the closeness of relationships.

Influencers can also seem more genuine to followers by referencing intimate social ties in their captions. Terms like “grandpa,” “bestie” and “soulmate” give followers access to an inner circle usually reserved for loved ones, making them feel more connected and invested in the influencer’s world and worldview.

In one experiment, study participants were shown a series of Instagram posts supposedly written by actor Jessica Alba. Testing the impact of language on the perception of close ties, the researchers wrote three different captions for the same image. One caption mentions Alba’s daughter (“Styling by my daughter. Isn’t this outfit cute?”). Another references a distant tie (“Styling by designer Kelmen. Isn’t this outfit cute?”). A third post provided a baseline by indicating no ties at all.

Study participants were asked to select which posts they liked most. The results supported the research hypothesis. Posts mentioning close relationships are significantly more likable than posts mentioning distant ties or no ties.

The team also examined the impact of expressing emotion on Instagram. Does sharing feelings — either positive or negative — help or hurt audience engagement? Using the Linguistic Inquiry and Word Count (LIWC) language processing program, the researchers categorized and analyzed the strength and valence of emotion-related words and emojis (e.g., “love,” “nice,” “frustrated,” “sad”).

What they found is surprising. Expressing emotion boosts audience engagement, perhaps because it bridges a perceived gap of celebrity between influencer and audience. But what’s interesting is that negative emotions are more powerful than positive ones. According to the researchers’ dataset, negative emotions are expressed only 9.08 percent of the time, while positive feelings are shared 36.03 percent of the time. So, one way of interpreting the finding is that the comparative rarity of negative feeling could take some readers by surprise, and thereby incite a stronger sense of authenticity.

Importantly, all of these findings regarding audience engagement most likely apply to platforms where a gray line exists between private and public life.

And, on this note, the researchers warn against the potential for oversharing and exploiting family and friends for the sake of monetizing content.

But the study shows how brands can strategically sponsor posts that incorporate close ties in photos, express emotion, or share anecdotes in first-person language.

By quantifying tactics to achieve a greater perception of authenticity, the research provides valuable guidance on how to cut through the noise on social media. One of the paths to a more engaged audience, it turns out, runs through an influencer’s inner circle.


This article originally ran on Rice Business Wisdom and was based on research from Jaeyeon (Jae) Chung, an assistant professor of marketing at Rice Business, Yu Ding an assistant professor of marketing at Stanford Graduate School of Business, and Ajay Kalra, the Herbert S. Autrey Professor of Marketing at Rice Business.

Serious product reviewers need peers and audiences to see them as credible. But new research indicates that pursuing credibility may compromise the objectivity of their evaluations. Photo via Getty Images

Houston research: How social pressures are affecting digital product evaluations

houston voices

Theoretically, product evaluations should be impartial and unbiased. However, this assumption overlooks a crucial truth about product evaluators: They are human beings who are concerned about maintaining credibility with their audience, especially their peer evaluators.

Because evaluators must also care about being perceived as legitimate yet skillful themselves, certain social pressures are at play that potentially influence their product reviews.

Research by Minjae Kim (Rice Business) and Daniel DellaPosta (Penn State) takes up the question of how evaluators navigate those pressures. They find that in some cases, evaluators uphold majority opinion to appear legitimate and authoritative. In other contexts, they offer a contrasting viewpoint so that they seem more refined and sophisticated.

Pretend a movie critic gives an uplifting review of a widely overlooked film. By departing from the aesthetic judgments of cinema aficionados, the reviewer risks losing credibility with their audience. Not only does the reviewer fail to understand this specific film, the audience might say; they fail to understand film and filmmaking, broadly.

But it’s also conceivable, in other situations, that the dissenting evaluator will come across as uniquely perceptive.

What makes the difference between these conflicting perceptions?

Partly, it depends on how niche or mainstream the product is. With large-audience products, Kim and DellaPosta hypothesize, evaluators are more willing to contradict widespread opinion. (Without a large audience, contradicting opinions are like the sound of a tree that falls in a forest without anyone nearby to hear.)

The perceived classiness of the product can affect the evaluator’s approach, as well. It’s easier to dissent from majority opinion on products deemed “lowbrow” than those deemed “highbrow.” Kim and DellaPosta suggest it’s more of a risk to downgrade a “highbrow” product that seems to require more sophisticated taste (e.g., classical music) and easier to downgrade a highly rated yet “lowbrow” product that seems easier to appreciate (e.g., a blockbuster movie).

Thus, the “safe spot” for disagreeing with established opinion is when a product has already been thoroughly and highly reviewed yet appears easier to understand. In that case, evaluators might sense an opportunity to stand out, rather than try to fit in. But disagreeing with something just for the sake of disagreeing can make people think you’re not a fair or reasonable evaluator. To avoid that perception, it might be better to agree with the high rating.

To test their hypotheses, Kim and DellaPosta used data from beer enthusiast site, an online platform where amateur evaluators review beers while also engaging with other users. Online reviewers publicly rate and describe their impressions of a variety of beers, from craft to mainstream.

The data set included 1.66 million user-submitted reviews of American-produced beers, including 82,077 unique beers, 4,302 brewers, 47,561 reviewers and 103 unique styles of beer. The reviews spanned from December 2000 to September 2015.

When the researchers compared scores given to the same beer over time, they confirmed their hypothesis about the conditions under which evaluators contradict the majority opinion. On average, reviewers were more inclined to contradict the majority opinions for a beer that had been highly rated and widely reviewed. When reviewers considered a particular brew to be a “lowbrow,” downgrading occurred to an even greater extent.

Kim and DellaPosta’s research has implications for both producers and consumers. Both groups should be aware of the social dynamics involved in product evaluation. The research suggests that reviews and ratings are as much about elevating the people who make them as they are about product quality.

Making evaluators identifiable and non-anonymous may help increase accountability for what they say online — a seemingly positive thing. But Kim and DellaPosta reveal a potential downside: Knowing who evaluators are, Kim says, “might warp the ratings in ways that depart from true objective quality.”


This article originally ran on Rice Business Wisdom and was based on research from Minjae Kim, assistant professor of Management – Organizational Behavior at Rice Business, and Daniel DellaPosta, associate professor of Sociology and Social Data Analytics at Pennsylvania State University.

Researchers created a mathematical model that helps transplant centers make decisions about when to move forward with a matching donor and when to wait. This work can potentially help decision making in other industries. Photo via Getty Images

Houston researchers build life-saving decision making mathematical model with big potential

houston voices

To wait, or not to wait? That is the question — or at least it might be, if you need a kidney transplant.

Nearly 89,000 Americans with chronic kidney disease are on a waitlist for a new organ, and an estimated 13 people die each day while awaiting a transplant. But there are real costs to matching patients with the first donor that becomes available, just as there are equally real costs to having them wait in hopes of finding a better one.

Recently, Rice Business professor Süleyman Kerimov and colleagues at Stanford University and Northwestern University developed a mathematical model that helps clarify when it's best to match patients to donors as quickly as possible and when it's best to wait.

Their findings, which appear in two papers published in Management Science and Operations Research, respectively, could help optimize all manner of matching markets in which participants seek to connect with potential partners based on mutual compatibility — a sprawling category that encompasses everything from e-commerce platforms to labor markets that match employees with employers.

Kerimov and his colleagues focused on programs that match live kidney donors with people who need transplants. Live donors typically volunteer to give one of their kidneys to a loved one. But biological differences between a donor and their intended recipient can render the pair incompatible.

Kidney exchange programs solve this problem by swapping donors amongst different patient-donor pairs, choreographing a kind of kidney-transplant square dance aimed at finding a compatible partner for every willing donor.

In countries such as Canada and the Netherlands, kidney-matching programs perform a batch of matches every few months (called periodic policies). American programs, meanwhile, tend to perform daily matches (called greedy policies). Both models seek to produce the greatest number of high-quality transplants possible, but they each have advantages and disadvantages.

Less frequent matches in a periodic policy allow more patient-donor pairs to accumulate in the kidney exchange network, creating potential for better matches over time. But this approach risks making some patients sicker as they wait for a better match that might never appear.

Arranging feasible matches as soon as they become available in a greedy policy avoids that predicament. But it means passing up the opportunity to make a potentially better match that could represent the possibility of a longer, healthier life.

Balancing these trade-offs is tricky. There is no way of predicting precisely when a patient-donor pair with a particular set of characteristics will show up at the kidney-exchange network. And in the world of organ transplants, there are no do-overs.

Kerimov and his colleagues have constructed a mathematical model that represents a simplified version of a kidney exchange network.

Within the model, the researchers could dictate which patient-donor pairs could be matched with one another. They can also assign different values to individual matches based on the number of life years they provide. And they can establish the probability that various kinds of patient-donor pairs with particular characteristics might arrive at the network and queue up for a transplant at any given time.

Having set those parameters, the researchers applied different matching policies and compared the results. As it turns out, the answer to whether one should wait or not is: It depends.

To determine which policies generated the best outcomes — i.e., performing matches either daily or periodically — the researchers calculated the difference between the total value in life years that could possibly be generated within the network and the amount generated by a specific policy at a particular point in time. The goal was to keep that number, evocatively dubbed "all-time regret," as small as possible over both the short and long term.

In their first paper, Kerimov and his team explored a complex network in which donor kidneys could be swapped amongst three or more patient-donor pairs. When such multiway matches were possible, the cost of applying a daily-match policy turned out to be onerous. Using all available matches as quickly as possible eliminated the chance of later performing potentially higher-value matches.

Instead, the researchers found they could minimize regret by applying a periodic policy that required waiting for a certain number of patient-donor pairs to arrive before attempting to match them. The model even allowed the team to calculate precisely how long to wait between matchmaking sessions to get the best possible results.

In their second paper, however, the team looked at a simpler network in which kidneys could only be swapped between two donor-patient pairs. Here, their findings contradicted the first: Applying a daily-match policy minimized regret; a periodic matching process yielded no benefit whatsoever.

To their surprise, the researchers discovered they could design a foolproof algorithm for making two-way matches in simple networks. The algorithm employed a ranked list of possible match types; and the researchers found that no matter how many patient-donor pairs of various kinds randomly arrived at the network, the best choice was always simply to perform the highest-ranked match on the list.

In future research, Kerimov hopes to refine the model by feeding it data on real patient-donor pairs that have participated in actual kidney exchange programs. This would allow him to create a more realistic network, more accurately calculate the likelihood that particular kinds of patient-donor pairs will show up, and assign values to matches based not only on life years but also on rarity and difficulty. (Certain blood types and antibody profiles, for example, are rarer or more difficult to match than others.)

But Kerimov already suspects that in a real-world situation, the wisest course of action will be to alternate between periodic and greedy policies as circumstances dictate. In a simple region within a kidney exchange network that only allows for two-way matches, pursuing a greedy policy that involves taking the first match that appears on a fixed menu of options would be the best choice. In a more complex region that allows three-way matches, however, pursuing a periodic matching policy that involves waiting to make rarer and more difficult matches would ultimately offer more patients more years of healthy life.

The benefits of choosing flexibly between greedy and periodic policies should hold for any kind of matching market that can be represented by a network with simpler and more complex regions, such as a logistics system that matches online orders to delivery trucks or a carpooling system that matches passengers with drivers across different parts of a city.


This article originally ran on Rice Business Wisdom and was based on research from Süleyman Kerimov, an assistant professor of management – operations management in the Jones Graduate School of Business at Rice University.

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

houston voices

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.”


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.

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.


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.

Ad Placement 300x100
Ad Placement 300x600

CultureMap Emails are Awesome

Houston-based lunar mission's rocky landing and what it means for America's return to the moon

houston, we have a problem

A private U.S. lunar lander tipped over at touchdown and ended up on its side near the moon’s south pole, hampering communications, company officials said Friday.

Intuitive Machines initially believed its six-footed lander, Odysseus, was upright after Thursday's touchdown. But CEO Steve Altemus said Friday the craft “caught a foot in the surface," falling onto its side and, quite possibly, leaning against a rock. He said it was coming in too fast and may have snapped a leg.

“So far, we have quite a bit of operational capability even though we’re tipped over," he told reporters.

But some antennas were pointed toward the surface, limiting flight controllers' ability to get data down, Altemus said. The antennas were stationed high on the 14-foot (4.3-meter) lander to facilitate communications at the hilly, cratered and shadowed south polar region.

Odysseus — the first U.S. lander in more than 50 years — is thought to be within a few miles (kilometers) of its intended landing site near the Malapert A crater, less than 200 miles (300 kilometers) from the south pole. NASA, the main customer, wanted to get as close as possible to the pole to scout out the area before astronauts show up later this decade.

NASA's Lunar Reconnaissance Orbiter will attempt to pinpoint the lander's location, as it flies overhead this weekend.

With Thursday’s touchdown, Intuitive Machines became the first private business to pull off a moon landing, a feat previously achieved by only five countries. Japan was the latest country to score a landing, but its lander also ended up on its side last month.

Odysseus' mission was sponsored in large part by NASA, whose experiments were on board. NASA paid $118 million for the delivery under a program meant to jump-start the lunar economy.

One of the NASA experiments was pressed into service when the lander's navigation system did not kick in. Intuitive Machines caught the problem in advance when it tried to use its lasers to improve the lander's orbit. Otherwise, flight controllers would not have discovered the failure until it was too late, just five minutes before touchdown.

“Serendipity is absolutely the right word,” mission director Tim Crain said.

It turns out that a switch was not flipped before flight, preventing the system's activation in space.

Launched last week from Florida, Odysseus took an extra lap around the moon Thursday to allow time for the last-minute switch to NASA's laser system, which saved the day, officials noted.

Another experiment, a cube with four cameras, was supposed to pop off 30 seconds before touchdown to capture pictures of Odysseus’ landing. But Embry-Riddle Aeronautical University’s EagleCam was deliberately powered off during the final descent because of the navigation switch and stayed attached to the lander.

Embry-Riddle's Troy Henderson said his team will try to release EagleCam in the coming days, so it can photograph the lander from roughly 26 feet (8 meters) away.

"Getting that final picture of the lander on the surface is still an incredibly important task for us,” Henderson told The Associated Press.

Intuitive Machines anticipates just another week of operations on the moon for the solar-powered lander — nine or 10 days at most — before lunar nightfall hits.

The company was the second business to aim for the moon under NASA's commercial lunar services program. Last month, Pittsburgh's Astrobotic Technology gave it a shot, but a fuel leak on the lander cut the mission short and the craft ended up crashing back to Earth.

Until Thursday, the U.S. had not landed on the moon since Apollo 17's Gene Cernan and Harrison Schmitt closed out NASA's famed moon-landing program in December 1972. NASA's new effort to return astronauts to the moon is named Artemis after Apollo's mythological twin sister. The first Artemis crew landing is planned for 2026 at the earliest.

3 female Houston innovators to know this week

who's who

Editor's note: Welcome to another Monday edition of Innovators to Know. Today I'm introducing you to three Houstonians to read up about — three individuals behind recent innovation and startup news stories in Houston as reported by InnovationMap. Learn more about them and their recent news below by clicking on each article.

Emma Konet, co-founder and CTO of Tierra Climate

Emma Konet, co-founder and CTO of Tierra Climate, joins the Houston Innovators Podcast. Photo via LinkedIn

If the energy transition is going to be successful, the energy storage space needs to be equipped to support both the increased volume of energy needed and new energies. And Emma Konet and her software company, Tierra Climate, are targeting one part of the equation: the market.

"To me, it's very clear that we need to build a lot of energy storage in order to transition the grid," Konet says on the Houston Innovators Podcast. "The problems that I saw were really on the market side of things." Read more.

Cindy Taff, CEO of Sage Geosystems

Houston-based Sage Geosystems announced the first close of $17 million round led by Chesapeake Energy Corp. Photo courtesy of Sage

A Houston geothermal startup has announced the close of its series A round of funding.

Houston-based Sage Geosystems announced the first close of $17 million round led by Chesapeake Energy Corp. The proceeds aim to fund its first commercial geopressured geothermal system facility, which will be built in Texas in Q4 of 2024. According to the company, the facility will be the first of its kind.

“The first close of our Series A funding and our commercial facility are significant milestones in our mission to make geopressured geothermal system technologies a reality,” Cindy Taff, CEO of Sage Geosystems, says. Read more.

Clemmie Martin, chief of staff at The Cannon

With seven locations across the Houston area, The Cannon's digital technology allows its members a streamlined connection. Photo courtesy of The Cannon

After collaborating over the years, The Cannon has acquired a Houston startup's digital platform technology to become a "physical-digital hybrid" community.

Village Insights, a Houston startup, worked with The Cannon to create and launch its digital community platform Cannon Connect. Now, The Cannon has officially acquired the business. The terms of the deal were not disclosed.

“The integration of a world-class onsite member experience and Cannon Connect’s superior virtual resource network creates a seamless, streamlined environment for member organizations,” Clemmie Martin, The Cannon’s newly appointed chief of staff, says in the release. “Cannon Connect and this acquisition have paved new pathways to access and success for all.” Read more.

Texas organization grants $68.5M to Houston institutions for recruitment, research

Three prominent institutions in Houston will be able to snag a trio of high-profile cancer researchers thanks to $12 million in new funding from the Cancer Prevention and Research Institute of Texas.

The biggest recruitment award — $6 million — went to the University of Texas MD Anderson Center to lure researcher Xiling Shen away from the Terasaki Institute for Biomedical Innovation in Los Angeles.

Shen is chief scientific officer at the nonprofit Terasaki Institute. His lab there studies precision medicine, including treatments for cancer, from a “systems biology perspective.”

He also is co-founder and former CEO of Xilis, a Durham, North Carolina-based oncology therapy startup that raised $70 million in series A funding in 2021. Before joining the institute in 2021, the Stanford University graduate was an associate professor at Duke University in Durham.

Shen and Xilis aren’t strangers to MD Anderson.

In 2023, MD Anderson said it planned to use Xilis’ propriety MicroOrganoSphere (MOS) technology for development of novel cancer therapies.

“Our research suggests the MOS platform has the potential to offer new capabilities and to improve the efficiency of developing innovative drugs and cell therapies over current … models, which we hope will bring medicines to patients more quickly,” Shen said in an MD Anderson news release.

Here are the two other Cancer Prevention and Research Institute of Texas (CPRIT) awards that will bring noted cancer researchers to Houston:

  • $4 million to attract David Sarlah to Rice University from the University of Illinois, where he is an associate professor of chemistry. Sarlah’s work includes applying the principles of chemistry to creation of new cancer therapies.
  • $2 million to lure Vishnu Dileep to the Baylor College of Medicine from the Massachusetts Institute of Technology (MIT), where he is a postdoctoral fellow. His work includes the study of cancer genomes.

CPRIT also handed out more than $56.5 million in grants and awards to seven institutions in the Houston area. Here’s the rundown:

  • MD Anderson Cancer Center — Nearly $25.6 million
  • Baylor College of Medicine — Nearly $11.5 million
  • University of Texas Health Science Center at Houston — More than $6 million
  • Rice University — $4 million
  • University of Texas Medical Branch at Galveston — More than $3.5 million
  • Methodist Hospital Research Institute — More than $3.3 million
  • University of Houston — $1.4 million

Dr. Pavan Reddy, a CPRIT scholar who is a professor at the Baylor College of Medicine and director of its Dan L Duncan Comprehensive Cancer Care Center, says the CPRIT funding “will help our investigators take chances and explore bold ideas to make innovative discoveries.”

The Houston-area funding was part of nearly $99 million in grants and awards that CPRIT recently approved.