Research Roundup: March 2024

Balancing Team Performance With Individual Needs

How can leaders prevent good team performance from coming at the expense of individual well-being—or vice versa? Striking the right balance between both is the topic of a study published in the Journal of Organizational Behavior.

During the COVID-19 pandemic, five researchers asked 69 people working across 12 teams to keep qualitative diaries of their experiences. Additionally, participants completed questionnaires that measured their individual work engagement and risk of burnout, as well as team viability, team satisfaction, and the quality of interpersonal relationships among team members.

The researchers found that many participants prioritized team performance over their own needs, which increased their risk of burnout. That said, when teams engaged in reflection—both as individuals and as groups—they reported greater well-being and team performance. 

These results show that, when organizations survey employees to measure morale, they must understand that high employee morale may not translate to strong team performance. However, if they encourage teams to engage in reflective time, members will share their experiences and concerns, allowing everyone to adapt practices accordingly. However, according to the study, teams that engage in such group reflection are in the minority.

“Working life is now very individual-oriented, which means that the team may be forgotten altogether. That has an impact on the viability of organizations for the long haul,” says lead author Emma Nordbäck, assistant professor in the department of management and organization at the Hanken School of Economics at the University of Helsinki.

For this reason, she adds, team leaders should prioritize communication and reflection among team members, so everyone can be aware of problems early on and make informed compromises that promote individual and team well-being. For example, if members report feeling overwhelmed by too many team-based communications, they can set policies that aim to keep everyone informed without sacrificing individual focus time.

Nordbäck’s co-authors include Niina Nurmi, assistant professor of organizational design and leadership at Aalto University in Finland; Jennifer Gibbs, professor in the department of communication at the University of California in Santa Barbara; Maggie Boyraz, associate professor of management at California State University, San Bernadino; and Minna Logemann, assistant professor of communication studies at the City University of New York in New York City.

“Relationships between people are one of our strongest motivators,” adds Nurmi, who points to herself and her co-authors as examples. “We’re long-standing friends and meet as a research fivesome at a conference once a year. When we did research together, we always focused on the welfare issues first. It’s always worth taking the time to reflect.”

Using AI to Detect Misleading Medical News

Two researchers at the University of New Hampshire’s Peter T. Paul College of Business and Economics in Durham are exploring the potential for artificial intelligence (AI) to help people without formal medical training better detect medical misinformation.

Ermira Zifla and Burcu Eke Rubini, both assistant professors of decision sciences, asked a panel of healthcare experts to evaluate news stories and press releases on new healthcare treatments that had appeared in the media from 2013 to 2018. The panel based their evaluations on 10 criteria, such as the cost and benefits of the new treatment or test, its potential harm, the availability of the procedure, and the independence of the sources where the news appeared.

Based on the panel’s expert input, Zifla and Rubini developed an algorithm that they used to train machine models to classify the same 10 aspects of the news stories as “satisfactory” or “not satisfactory.” The researchers then asked 254 laypeople to read the same articles and then use the 10 criteria to rate them as “satisfactory” or “not satisfactory.”

They found that participants rated articles as satisfactory more often than the algorithm. Given that finding, a “decision-support tool” such as the one developed for the study could help laypeople make “more informed assessments of online health news” and “better evaluate … the credibility and relevance of online health information,” the co-authors write.

“The way most people think about fake news is something that's completely fabricated, but, especially in healthcare, it doesn’t need to be fake. It could be that maybe [media outlets are] not mentioning something,” says Zifla. “In the study, we’re not making claims about the intent of the news organizations that put these out. But if things are left out, there should be a way to look at that.” 

Their paper, “Multi-criteria evaluation of health news stories,” appears in the May 2024 issue of Decision Support Systems.

What Factors Affect Research Productivity?

A research team recently surveyed 4,300 professors across multiple disciplines at more than 150 institutions in the United States to discover what factors truly impact a professor’s research output. The main takeaway: Traditional measures of academic productivity—such as the number of annual publications, number of citations, and grant funding—do not take into account other equally important factors that affect the time professors can devote to scholarship.

The eight-person team—led by Kyle Myers, assistant professor at Harvard Business School (HBS)—asked professors about their “rank and tenure status, demands on their time, funding, salaries, and other socio-demographic and household-related factors,” according to an article on the HBS Working Knowledge website. Rather than look solely at a professor’s total research output, the team was particularly interested in each professor’s “per-hour research output,” which the researchers argue is a more accurate measure of a professor’s true research productivity.

As the study points out, some professors spend more time than others on teaching, advising, outreach, or administrative tasks. If so, their total research output will likely be lower, even though their per-hour research output is high. This is just as true for tenured professors, often thought to have more freedom to take risks in their research. If they are focused on longer-term projects, such as conducting longitudinal studies or writing books, their total research output might also suffer.

Among the study’s main findings, “Professors with higher gross output (i.e., annual publications) are not always more productive on a per-research-hour basis because of substantial variation in professors’ time allocations.”

The study also measures each respondent’s risk aversion using what the researchers call a “Bohr-Edison” score. At the lower end of the scoring scale is Niels Bohr-type research (basic, low-risk, directed to other academics); at the higher end is Thomas Edison-type research (applied, high-risk, directed to policymakers and practitioners).

When the researchers broke down respondents’ average Bohr-Edison scores by field, scholars in mathematics were the least risk-tolerant, while those in agriculture were the most risk-tolerant. Those in business were slightly above average on the Bohr-Edison scale.

The survey also finds that professors who report conducting more applied research also are more willing to take risks in their personal lives. “Personal risk-taking is one of the best predictors of doing more applied, Edison-like work,” the co-authors write. If universities would like to increase their faculty’s applied research output, an index such as the Bohr-Edison score “could prove useful in generating observable, ex-ante variation in researchers’ positions along the basic-applied spectrum.”

This study is intended to shed light on how universities can better allocate resources and set up reward systems to encourage their most productive researchers, Myer explains in Working Knowledge. “That means we need to take seriously how we’re measuring scientists’ inputs and outputs.” 

Research News

■ Partnership focuses on fintech for Arab countries. The Behavioral and Economic Decision-Making Lab (BEDMLab) at the American University of Cairo School of Business has partnered with Fintech Robos in Bahrain to provide training, insights, and innovations related to the financial services industry to practitioners and decision-makers in the Arab countries. In addition, the partners will use insights related to human behaviors to design and implement prototypes of financial products and services tailored to the needs of Arab consumers.

■ Center works to advance healthcare solutions. The Haas School of Business (Berkeley Haas) and the College of Computing, Data Science, and Society at the University of California Berkeley have jointly launched the new Center for Healthcare Marketplace Innovation (CHMI). The center will produce healthcare research that combines artificial intelligence (AI) and behavioral economics to improve patient outcomes and reduce medical costs. CHMI will be housed within the Institute for Business Innovation at Berkeley Haas.

Center scholars estimate that the use of AI technologies could help healthcare providers reduce administrative costs by 15 percent to 30 percent—an annual cost reduction of up to 250 billion USD. The center’s research will focus on three areas of healthcare: creating more effective incentives to advance scientific innovation; encouraging interdisciplinary collaboration; and partnering with healthcare providers, insurers, government agencies, and other entities to test and refine interventions.

As AI tools are increasingly used in healthcare, it will be important to ensure that they actually “enhance care delivery and help patients” and “are built in equitable, ethical ways,” says Jonathan Kolstad, associate professor of economic analysis and policy, Berkeley Haas’ Henry J. Kaiser Chair, and the center’s faculty director. “By understanding the technology, the systemic incentives, and the human abilities in the healthcare system, we have a tremendous opportunity to help shape those dynamics.”

■ Index compares biotech innovation hubs. In a new white paper, the Institute for Deep Tech Innovation (DEEP) at ESMT Berlin and the international consulting group BCG have introduced the Biotech Innovation Hub Index, a tool that academics and policymakers can use to assess and compare the effectiveness of biotechnology hubs in Europe and the United States. The paper’s co-authors are Maximilian Nisslein, Benedikt von Bronk, and Torsten Kurth, all of BCG; and Francis de Véricourt, professor, the Joachim Faber Chair in Business and Technology, and academic director of DEEP.

In the paper, the co-authors decry the decentralization of innovation hubs in Germany specifically.  They recommend greater collaboration among hubs to improve biotech innovation and strategically redirect government funding to more effective stages of the innovation process. “This white paper,” says de Véricourt, “is a call to action for German policymakers, scientists, and industry stakeholders to rethink and revitalize the nation’s approach to biotech innovation.”

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