Research from a former Rice University professor linked the size of CEO signatures to ego. CEOs with big egos entered into more risky, unreliable deals. Pexels

You've just been named CEO of a Fortune 500 company. Your ego fills the room. The laws of gravity don't apply to you.

And naturally, you want to make an impact. So you pour money into mergers and acquisitions, and when you're not trying to acquire another firm, you guide company resources into research and development. You're a genius, and the world will soon be clinging to your every new product.

The only problem: your company will likely underperform. Research by former Rice Business visiting professor Sean Wang (now at Cox School of Business as SMU), along with Nicholas Seybert of the University of Maryland and Charles Ham of Washington University at St. Louis, reveals the high costs of an out of control CEO ego.

The researchers' first challenge was establishing who could legitimately be called a narcissist. What does the term mean, exactly? While there are varying definitions, Wang's team focused on narcissism as a basic personality trait rather than a mental illness. As a personality trait, narcissism is associated with entitlement, vanity, authority, and a sense of superiority.

To spot narcissists, the team took a novel approach: they examined their research subjects' signatures. Signature size turns out to be a handy measure for egos, because it doesn't require participants to answer direct questions about their personalities — and because participants are unlikely to know that ego can affect something as simple as a signature.

Just having a big ego, though, does not a narcissist make. To validate a link between a person's signature and narcissism, the researchers asked 53 graduate business students to provide their signatures by signing a document, and then to take a personality survey that measured narcissism. The findings documented that indeed there was a strong correlation between signature size and narcissism.

Next, the researchers obtained data from prior psychology research on employee perceptions of 32 technology-firm CEOs. Of the 24 CEOS for whom the researchers also had signature samples, they found a significant correlation between narcissism and signature size.

Armed with these findings, Wang and his colleagues were able to extrapolate the narcissistic traits of thousands of CEOs whose signatures were readily available on proxy statements and other corporate documents. The researchers ultimately studied 741 CEOs from 411 firms during the period between 1992 and 2015, corresponding to 6,361 firm-year observations with a median of eight fiscal years per CEO.

They found a pronounced behavior pattern. Firms led by narcissistic CEOs invested more in high-exposure areas such as research and development and mergers and acquisitions, but shied away from routine capital expenditures for day-to-day productivity. This trend was even more pronounced during periods of financial slack, suggesting that narcissistic CEOs prefer an aggressive management style whenever possible. Financial productivity delivered by these narcissistic CEOs in terms of profitability was lower than their less egotistic counterparts.

The research has multiple implications. Narcissistic leaders, past research shows, are prone to make bad decisions — in part because they are bad listeners. As a result, they often dominate the decision process without incorporating feedback or ideas from others. Ironically, they mistakenly perceive this behavior as a signal of competence and strong leadership.

To counter these bad habits, the researchers say, during periods of financial sluggishness investors and corporate boards should combat excessive narcissist-led investment by pushing for higher dividend payouts. Given that narcissistic CEOs overinvest in R&D, investors also need to closely monitor whether such investments represent real innovation or just vanity. Finally, boards of directors should be aware that narcissistic leaders tend to command higher salaries — and consider whether their CEO falls into this category, and is essentially getting higher pay for inferior performance.

In short, to really be as boss as they see themselves, narcissistic corporate leaders need to recognize their tendencies and rigorously check their egos. Boards, meanwhile, should closely monitor their CEO's priorities in directing firm resources. It could be the writing on the wall.

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This article originally ran on Rice Business Wisdom.

Sean Wang is a former visiting assistant professor of accounting at Jones Graduate School of Business at Rice University. He is now an assistant professor at Cox School of Business at SMU.

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Houston doctor wins NIH grant to test virtual reality for ICU delirium

Virtual healing

Think of it like a reverse version of The Matrix. A person wakes up in a hospital bed and gets plugged into a virtual reality game world in order to heal.

While it may sound far-fetched, Dr. Hina Faisal, a Houston Methodist critical care specialist in the Department of Surgery, was recently awarded a $242,000 grant from the National Institute of Health to test the effects of VR games on patients coming out of major surgery in the intensive care unit (ICU).

The five-year study will focus on older patients using mental stimulation techniques to reduce incidences of delirium. The award comes courtesy of the National Institute on Aging K76 Paul B. Beeson Emerging Leaders Career Development Award in Aging.

“As the population of older adults continues to grow, the need for effective, scalable interventions to prevent postoperative complications like delirium is more important than ever,” Faisal said in a news release.

ICU delirium is a serious condition that can lead to major complications and even death. Roughly 87 percent of patients who undergo major surgery involving intubation will experience some form of delirium coming out of anesthesia. Causes can range from infection to drug reactions. While many cases are mild, prolonged ICU delirium may prevent a patient from following medical advice or even cause them to hurt themselves.

Using VR games to treat delirium is a rapidly emerging and exciting branch of medicine. Studies show that VR games can help promote mental activity, memory and cognitive function. However, the full benefits are currently unknown as studies have been hampered by small patient populations.

Faisal believes that half of all ICU delirium cases are preventable through VR treatment. Currently, a general lack of knowledge and resources has been holding back the advancement of the treatment.

Hopefully, the work of Faisal in one of the busiest medical cities in the world can alleviate that problem as she spends the next half-decade plugging patients into games to aid in their healing.

Houston scientists develop breakthrough AI-driven process to design, decode genetic circuits

biotech breakthrough

Researchers at Rice University have developed an innovative process that uses artificial intelligence to better understand complex genetic circuits.

A study, published in the journal Nature, shows how the new technique, known as “Combining Long- and Short-range Sequencing to Investigate Genetic Complexity,” or CLASSIC, can generate and test millions of DNA designs at the same time, which, according to Rice.

The work was led by Rice’s Caleb Bashor, deputy director for the Rice Synthetic Biology Institute and member of the Ken Kennedy Institute. Bashor has been working with Kshitij Rai and Ronan O’Connell, co-first authors on the study, on the CLASSIC for over four years, according to a news release.

“Our work is the first demonstration that you can use AI for designing these circuits,” Bashor said in the release.

Genetic circuits program cells to perform specific functions. Finding the circuit that matches a desired function or performance "can be like looking for a needle in a haystack," Bashor explained. This work looked to find a solution to this long-standing challenge in synthetic biology.

First, the team developed a library of proof-of-concept genetic circuits. It then pooled the circuits and inserted them into human cells. Next, they used long-read and short-read DNA sequencing to create "a master map" that linked each circuit to how it performed.

The data was then used to train AI and machine learning models to analyze circuits and make accurate predictions for how untested circuits might perform.

“We end up with measurements for a lot of the possible designs but not all of them, and that is where building the (machine learning) model comes in,” O’Connell explained in the release. “We use the data to train a model that can understand this landscape and predict things we were not able to generate data on.”

Ultimately, the researchers believe the circuit characterization and AI-driven understanding can speed up synthetic biology, lead to faster development of biotechnology and potentially support more cell-based therapy breakthroughs by shedding new light on how gene circuits behave, according to Rice.

“We think AI/ML-driven design is the future of synthetic biology,” Bashor added in the release. “As we collect more data using CLASSIC, we can train more complex models to make predictions for how to design even more sophisticated and useful cellular biotechnology.”

The team at Rice also worked with Pankaj Mehta’s group in the department of physics at Boston University and Todd Treangen’s group in Rice’s computer science department. Research was supported by the National Institutes of Health, Office of Naval Research, the Robert J. Kleberg Jr. and Helen C. Kleberg Foundation, the American Heart Association, National Library of Medicine, the National Science Foundation, Rice’s Ken Kennedy Institute and the Rice Institute of Synthetic Biology.

James Collins, a biomedical engineer at MIT who helped establish synthetic biology as a field, added that CLASSIC is a new, defining milestone.

“Twenty-five years ago, those early circuits showed that we could program living cells, but they were built one at a time, each requiring months of tuning,” said Collins, who was one of the inventors of the toggle switch. “Bashor and colleagues have now delivered a transformative leap: CLASSIC brings high-throughput engineering to gene circuit design, allowing exploration of combinatorial spaces that were previously out of reach. Their platform doesn’t just accelerate the design-build-test-learn cycle; it redefines its scale, marking a new era of data-driven synthetic biology.”