Duke Fuqua Insights

Professor Kimberly Wade-Benzoni explains how reflecting on long-term impact shapes motivation, behavior, and decision-makingMany people ask themselves, “does my work actually matter?” Concerns about engagement, burnout, and job satisfaction are common, and they relate to a basic need to feel that work has an impact not only today, but also in the future. In this episode of Fuqua Insights Podcast, Professor Kimberly Wade-Benzoni of Duke University’s Fuqua School of Business discusses her research on the psychology of legacy. She defines legacy as “an enduring impact attached to one’s identity that persists after one has left the context in which the lasting effect was created.” Her research examines how thinking about legacy influences decisions, especially those involving tradeoffs between present and future outcomes. One of the main findings of Wade-Benzoni’s research is that when people reflect on the legacy they want to leave, their work feels more meaningful. They are also more satisfied in their jobs and more likely to help others. These results come from studies showing that activating legacy motivation can produce positive outcomes in workplace settings. Legacy reflection changes how people think about their work. As Wade-Benzoni explains, “it’s a way that our actions can have impact that outlasts our individual lives.” This process allows people to think about how part of their identity can continue through others, which helps create meaning and shifts attention from immediate tasks to longer-term goals. The research also identifies practical applications. A structured reflection exercise—for example, asking individuals to write about how they want to be remembered and the impact they want to have—can activate legacy thinking. This approach can be used in leadership development, career planning, and other organizational contexts. It also encourages people to behave in a more future-oriented and other-oriented way, helping counter short-term, self-focused decision-making, and supporting more meaningful and lasting impact.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor John Graham explores how AI is affecting productivity, hiring, and firm strategy based on new CFO survey dataArtificial intelligence is everywhere—from automating routine tasks to generating insights in seconds. Yet despite the hype and anxiety, especially around job loss, the real impact of AI on companies may be more nuanced than headlines suggest.In this episode of Duke Fuqua Insights, Professor John Graham of Duke University’s Fuqua School of Business draws on data from The CFO Survey, which included responses from nearly 750 financial executives across industries. The survey, conducted in late 2025, asked how firms are currently using AI and what they expect in 2026. By focusing on CFOs—"leaders who know what the spending is on AI,” Graham said—the research offers a grounded perspective on how AI is affecting productivity, workforce composition, and investment decisions. The central finding: AI is expected to boost productivity without causing widespread job losses—at least in the near term. CFOs forecast productivity gains of up to 3% in 2026, “a significant increase,” Graham said, while overall employment remains largely stable.Instead of mass layoffs, firms anticipate modest declines in routine clerical roles, partially offset by hiring in technical positions.Interestingly, the AI-driven productivity gains aren’t fully reflected in increased revenue forecasts. Graham points to a modern “productivity paradox.” As he explains, “we’re hearing more about productivity than we’re seeing it in the revenue numbers,” suggesting a lag between implementation and financial results. Companies may improve output per worker first, but it takes time for those gains to translate into sales due to production cycles and human-driven sales processes.For business leaders and MBA students, the implications are that AI’s value today lies less in cost-cutting and more in enhancing quality, innovation, and customer satisfaction.To students, Graham suggests focusing on core strengths: “Do what you do really well, and improve it through AI.” Technical skills are increasingly valuable, but equally important are critical thinking, communication, and the ability to interpret AI-generated outputs. In a world where “anybody can produce numbers,” the real advantage lies in understanding and explaining them. Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor Jordan Etkin explains how “time-first budgeting” can help people improve performance and set smarter goalsIt’s a familiar pattern: You begin your morning with a lengthy to-do list and a plan to complete it, and somehow the day ends with unfinished tasks and a sense that time slipped away. Is there a better way?Professor Jordan Etkin, a consumer behavior scholar at Duke University’s Fuqua School of Business, explores why people consistently misjudge how much they can accomplish. Drawing on her research on motivation and performance, she proposes a simple shift: “time-first budgeting.” Instead of starting with goals and assuming the time will follow, she suggests beginning with a realistic assessment of how much time you have, then allocating it across tasks. Etkin finds that people routinely overestimate how much they can do because they ignore real time constraints. In experiments, participants’ estimates of how long tasks would take exceeded their available time by as much as 50%. When people instead budget their time first, they set more realistic goals and report greater progress. Etkin explains that people often fail to account for everything a task involves, from transitions to competing priorities. “If I'm thinking about a workout, I might not account for the getting to the gym piece, the washing my hands afterwards piece, needing a few minutes to clean up and move on with my day,” she said. Time-first budgeting works because it flips that process: “What if we start by thinking about what time I have available, and given that available time, how much time am I willing to spend on those different types of goals?”The approach applies broadly, from managing personal workloads to professional settings where colleagues depend on what you deliver. As Etkin puts it, “we can’t do things we don’t have time for,” making it critical to treat time as a finite resource when setting expectations.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Marketers are increasingly pessimistic about the economy, with sentiment reaching its lowest level since the pandemic in 2020. In response—and facing organizational pressures for returns—marketing activities are contracting, lowering spending and prioritizing existing customers over expansion opportunities.At the same time, companies are accelerating adoption of artificial intelligence, projecting that AI will account for more than half of all marketing activities within three years. Yet this rapid technological progress is outpacing organizational readiness, with no marketing technology activity currently delivering at its full potential. These are among the findings of the 35th edition of The CMO Survey, directed by Professor Christine Moorman of Duke University’s Fuqua School of Business and co-sponsored by Deloitte and the American Marketing Association.The survey was conducted from January 7 to January 29, 2026. It polled 308 marketing leaders at for-profit U.S. companies, 97% of whom are VP-level or higher.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor Christine Moorman on why keeping marketing secrets may cost more than letting them goCompanies spend billions safeguarding their marketing secrets—from customer insights to pricing algorithms—assuming these secrets are key to competitive advantage. The global data loss prevention market is valued at an estimated $1.5 to $2 billion annually and continues to grow. But does locking down knowledge undermine performance rather than protect it?In this episode of Duke Fuqua Insights, Professor Christine Moorman of Duke University’s Fuqua School of Business, a leading scholar of marketing strategy and the director of The CMO Survey, examines whether protecting marketing knowledge is worth the cost.Drawing from in-depth interviews with senior executives across industries, Moorman and her co-authors explore how firms manage three types of marketing knowledge: customer and competitor insights, marketing plans, and marketing know-how, such as pricing algorithms. Their research challenges the conventional wisdom that tighter control always leads to stronger advantage.The research found that efforts to prevent knowledge leakage often generate significant costs, while the external benefits may be overstated. Firms frequently rely on “leakage prevention strategies” that restrict who can access or share information. But Moorman finds these controls can create a set of “hidden costs” that can undermine decision quality, slow execution, and even weaken morale. Protection can also unintentionally block learning as well as leaks. “If you put up all of these barriers, those same barriers are going to also prevent information from coming to you,” she said. On the benefit side, Moorman points out that these benefits may be overestimated. The reason is that even when information escapes, competitors must first notice it, interpret it correctly, and have the resources to act on it before any real harm occurs. Moorman suggests that instead of obsessing over preventing leaks, companies should first weigh a careful assessment of these costs and benefits. Companies should also consider alternative knowledge protection strategies that do not have these costs. These include investing in harm prevention strategies, like refreshing their marketing knowledge faster than competitors can use it, and out-executing rivals even when information escapes. Competitive advantage may depend less on secrecy and more on speed.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor Anna Cieslak explains how central bank communication shapes financial markets, even when rates stay the sameWhen the Federal Reserve meets, markets obsess over one question: Will interest rates go up or down? But sometimes, market moves happen even when rates don’t change at all. In uncertain times, a subtle shift in tone can ripple across global financial markets.In this episode of Duke Fuqua Insights Podcast, Professor Anna Cieslak of Duke University’s Fuqua School of Business explores how central bank communication shapes financial conditions beyond formal rate decisions. Her research examines how the Fed uses “policy tilts”—signals about future intentions—to influence investor expectations and long-term interest rates.Drawing on decades of data—including the late 1990s productivity boom and the post-COVID recovery—her research shows how policy tilts shift investor risk perceptions and long-term Treasury yields, with effects that can rival formal rate decisions.  She explains that the Fed follows a “risk management approach,” assessing not just the most likely forecast but also low-probability, high-cost scenarios. By signaling vigilance, policymakers reduce fears that they will fall behind inflation.The stakes of getting communication right are high. In 2021, the Fed's 'lower for longer' messaging diverged from rising inflation concerns, tightening financial conditions even as rates held steady. As former Fed Chair Ben Bernanke observed, monetary policy is '98% talk and 2% action'—which means parsing Fed language is as important as watching the rate decision itself.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor Elia Ferracuti explains how activist investors reshape corporate research, and why it matters for long-term innovation.Why would a company famous for breakthrough discoveries suddenly pull back from bold research in favor of safer bets? Research shows shareholder pressure plays a role. The tension between short-term financial pressure and long-term scientific progress is at the heart of many hedge-fund-led activist campaigns and may explain why companies retreat from basic research, with effects across the broader innovation ecosystem.In this episode, Professor Elia Ferracuti, an accounting scholar at Duke University’s Fuqua School of Business, discusses new research—co-authored by Fuqua’s Rahul Vashishtha and Kevin Standbridge of the University of Utah—on how hedge fund activism affects corporate science.Drawing on large-scale data linking activist investor campaigns to corporate research outputs, Ferracuti and his coauthors examine what happens inside firms after activists push for operational and governance changes. Their analysis spans multiple industries, with particularly rich evidence from pharmaceuticals, where innovation choices are easier to observe and compare. The research found that after firms are targeted by activist hedge funds, they produce significantly less scientific research. Measured through publications in academic journals, corporate science declines overall—and drops most sharply in top-tier journals. In pharmaceuticals, targeted firms also shift away from novel drugs toward more incremental “me-too” compounds that closely resemble existing treatments. “Activism pushes corporations away from risky activities with long gestation periods and large spillovers,” Ferracuti said.Why does this happen? Hedge fund activists typically acquire minority stakes but exert outsized influence, pressing managers to boost near-term returns. According to Ferracuti, this pressure changes internal priorities: “Foundational scientific research may be among the first activities to go.” Because basic research is uncertain, slow to pay off, and often benefits society more than any single firm, it becomes vulnerable when managers face intense scrutiny to deliver quick results.The effects don’t stop with targeted firms. Rival companies in the same industry also scale back research, likely because they fear becoming the next activist target. Shareholder activism can improve efficiency—but it also carries hidden costs for innovation, economic growth, and social welfare.Ferracuti cautions against “fiddling” with the functioning of capital markets, instead pointing to the growing importance of sustaining and incentivizing fundamental research, especially at universities, at a time when public support for science is under pressure. Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor Simon Gervais explains how active managers can grow the economy, even when they don’t beat the marketMany investors are told that active funds rarely outperform passive index funds after fees. So why bother paying for them? In this episode of Duke Fuqua Insights podcast, Professor Simon Gervais, a financial economist at Duke University’s Fuqua School of Business, challenges the narrow way we evaluate active money management. Drawing on his paper, “Money Management and Real Investment”, Gervais argues that focusing only on fund returns misses a critical role active managers play in the economy: improving how capital is allocated across firms and industries. Rather than acting as passive observers, active managers influence real corporate investment decisions through the information embedded in stock prices.  The central insight of Gervais’s research is that active money managers can create economic value even if their funds generate negative net returns after fees. By trading on information about industries, competition, and macroeconomic trends, active managers help direct capital toward more productive uses. The result is a “bigger economic pie,” even if investors receive a slightly smaller slice of it. Active managers trade on information that corporate executives may not fully have, pushing stock prices up or down. Firms then learn from these price movements and adjust investment decisions accordingly. As Gervais puts it, if a firm announces a merger and its stock went down, maybe that is the signal that the merger was a bad idea. For MBA students and business leaders, the takeaway is a broader view of value creation. Passive investors may benefit indirectly from better capital allocation, but unlike active managers, they don’t automatically adjust as the economy changes. The research calls into question how regulators, investors, and institutions evaluate asset managers. If active management improves productivity and risk allocation, then traditional performance metrics like alpha may be incomplete. As Gervais suggests, the real challenge is learning how to measure not just who captures value, but who creates it.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Artificial intelligence promises massive productivity gains, but not everyone can immediately jump in to reap its benefits. While some firms and countries race ahead with new tools, others deliberately stick with older technologies, a choice may be entirely rational.In this episode of the Fuqua Insights podcast, Professor John Coleman of Duke University’s Fuqua School of Business joins host Sarah Kern to discuss how economies and businesses choose technologies based on the skills of their workforce.  Drawing on his paper The World Technology Frontier, co-authored with Francesco Caselli of the London School of Economics, Coleman explores why countries with access to the same global technologies nonetheless adopt very different production methods and experience sharply different income levels.Coleman’s central finding is that technology adoption is often an optimal choice, not a failure. Coleman distinguishes between skilled and unskilled labor, economic terms based primarily on formal education levels rather than the actual difficulty or value of work. In this framework, "skilled" workers have training that allows them to adapt to and leverage new technologies, while "unskilled" refers to workers with less formal education who may be highly capable but less equipped to use tools like AI.Advanced economies tend to develop and use technologies that favor skilled labor, while less-developed economies rely on older, less skill-intensive tools because those technologies better match their labor force. As Coleman explains, a poorer country may “optimally choose to adopt what seems to an advanced economy to be a backward technology”, because using more advanced tools without the right skills can actually reduce productivity.While technologies developed a long time ago are most suitable for labor that is mostly unskilled, newer technologies are designed for highly educated workers, Coleman notes. This framework applies directly to AI: “AI was developed by advanced economies that have the skilled labor that would benefit most from AI,” he says. Without that skill base, adopting AI may not pay off.Business leaders should remember to align innovations with workforce capabilities. “Adopting AI without a well-developed plan to integrate it into your workforce would likely be a disaster,” Coleman warns. Globally, AI may widen gaps in the short run, but Coleman emphasizes that technology is not a zero-sum game. Over time, moving up the technology frontier can create opportunities for growth across economies.Editor's Note: This episode was recorded prior to the extradition of Nicolás Maduro on January 3, 2026.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor David Brown explains how simple strategies can guide better decisions even when information is incomplete New job postings appear daily. Real estate markets update constantly with fresh listings. In an environment where alternatives continuously multiply and options can seem endless, the hardest decision is knowing when to stop searching and commit.In this episode, David Brown, the Snow Family Business Professor of Decision Sciences at Duke University’s Fuqua School of Business, discusses how people and organizations can make better decisions when information is scarce or costly. Building on economist Martin Weitzman’s classic “Pandora’s Box Problem,” Brown and his co-author, Fuqua Ph.D. student Cagin Uru, found that straightforward search rules perform nearly as well as complex algorithms. Their research shows a surprisingly simple solution: commit upfront to search a specific number of alternatives based on search costs, then simply rank what you've seen and choose the best. What makes their approach practical and appealing is its simplicity: it requires only the ability to rank alternatives you've seen and the discipline to stop searching at the right point, not probability calculations or complex data analysis. This applies broadly, from navigating job searches to booking flights to hiring contractors.The conversation also explores when sophisticated algorithms are truly necessary. Their research shows that, across several search settings, their simple, transparent rules perform nearly as well as those based on more complex approaches (e.g., AI), raising questions about when algorithmic solutions are worth the investment.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

A single decision improved by 1% might seem trivial. But make 300 small improvements over a year, and the compounding effect becomes transformative. A/B testing allows companies to systematically test different approaches and optimize performance, but research shows that the startups that could benefit most are the least likely to use it.In this episode, Professor Sharique Hasan of Duke University’s Fuqua School of Business discusses his paper “Experimentation and Start-up Performance: Evidence from A/B Testing,” which focuses on how startups use A/B testing to drive performance. Based on data from more than 35,000 startups, Hasan and his coauthors found those that adopt A/B testing experience significantly higher performance over time—sometimes doubling outcomes after a year. Hasan explains that while the impact is strongest for smaller and non–Silicon Valley startups, these firms often lack the resources to implement A/B testing effectively. For them, he introduces the concept of “experimental thinking” as a more accessible alternative: a mindset of comparing options rigorously, asking the right causal questions, and framing decisions with clear counterfactuals. Drawing from both large-scale quantitative analysis and rich qualitative insights from tech practitioners, Hasan describes how small, compound decisions can lead to transformative outcomes.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor Bill Mayew explores whether public companies have visibility into the macroeconomy to filter errors in GDP data—and what that means for economic forecastingEvery quarter, the U.S. Bureau of Economic Analysis releases its initial GDP estimate—a flagship measure of economic health that influences corporate boardrooms, Federal Reserve policy, and investor portfolios. But there’s a catch: these early numbers are often wrong.In this episode, Professor Bill Mayew of Duke University’s Fuqua School of Business discusses his research, published in the Journal of Accounting and Economics, on how corporations respond when government economic data contains errors. Mayew explains why concerns about a potential “macro data crisis” have gained traction and why errors in economic data are not necessarily signs of dysfunction.Initial GDP estimates rely on incomplete survey data—less than half from actual three-month surveys—with the rest from extrapolations. The Bureau of Economic Analysis refines these estimates at the one-year and five-year marks as more data arrives. Revisions are therefore expected and necessary.Mayew’s research examined whether large public companies with a unique pulse on the economy could see through the errors inherent in initial GDP estimates.  Analyzing firm-level behavior, he and his coauthors found firms tend to take preliminary GDP figures at face value, failing to filter out the inherent noise. When GDP data signals strength in one quarter, companies increase investment, production, and inventory the next — and the same pattern occurs whether the GDP signal reflects real economic change or statistical error.For policymakers, the findings underscore the need for caution when substituting government data with private sector sources like ADP payroll information. While private data may complement government releases in some cases, Mayew emphasizes government data from agencies like the Bureau of Economic Analysis and Bureau of Labor Statistics still has substantial value.Instead, he concludes, “we need to think of other ways to improve government data, which may be increasingly possible as new and creative ways of measuring economic activity occur.”Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor Tong Guo explains how mandated transparency didn't reduce pharmaceutical payments to physicians—instead, it taught companies to optimize them.When the federal government mandated that pharmaceutical companies publicly disclose every payment to physicians—from conference sponsorships to consulting fees—policymakers expected transparency to reduce potential conflicts of interest. Instead, the payments kept flowing, and companies learned to optimize them.In this episode, Professor Tong Guo, an associate professor of Marketing at Duke University’s Fuqua School of Business, discusses her study of the Sunshine Act—a federal law requiring pharmaceutical and medical device companies to publicly disclose payments to healthcare providers. Published in the Journal of Marketing Research (2021), Guo's research using advanced machine learning methods called causal forests analyzed $100 million in payments between 16 antidiabetic brands and 50,000 physicians. Her findings reveal a nuanced reality: while total payments did not decline significantly, they shifted toward physicians who prescribe more expensive drugs and generate higher ROI for firms.As Guo explains, most disclosed payments are legal, including sponsorships for events, conference travel, and educational presentations. "Much of these expenditures are considered legal," she notes, "so it's natural that it doesn't come with much pressure to cut it down.""For firms, the number one rule for them to run their business is always to think about their ROI model," she explains. The transparency regulation gave firms information about which competitors were reaching out to which physicians and when, allowing them to optimize their existing relationships for maximum return. When transparency gives all competitors access to the same information, firms don't retreat—they optimize. For MBA students and professionals, Guo's findings offer critical lessons extending beyond healthcare. Transparency doesn't always lead to restraint. Understanding who benefits from newly available information—and how—is essential across industries, from healthcare to digital marketing. As Guo points out, similar disclosure regulations now apply across industries —from TikTok influencers required to disclose brand sponsorships to financial services and beyond. "Transparency regulations would not necessarily lead to drastic changes of how people practice their business," she says. Different parties have different capabilities to leverage disclosed information, potentially creating new competitive advantages rather than leveling the playing field. Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Professor Ali Makhdoumi reveals why your friend's social media activity might be compromising your privacy, even when you share nothing at all  Every time your colleague shares their location data or a friend posts their workout routine, they're inadvertently exposing details about you–even if you've never agreed to share your data. This hidden web of data spillovers means companies can predict your preferences, behaviors, and personal information simply by analyzing the digital footprints of people in your network.In this episode, Professor Ali Makhdoumi of Duke University's Fuqua School of Business discusses his research on personal data markets, based on his paper "Too Much Data: Prices and Inefficiencies in Data Markets," co-authored with 2024 Nobel Prize winner Daron Acemoglu. He explains that what we think of as personal, private data is actually more like a public good. Platforms can infer your information indirectly through your connections, creating what economists call "data externalities."  Makhdoumi explores why current data markets are so structurally inefficient. When your data can be predicted from others' sharing decisions, you lose bargaining power and companies acquire personal information at depressed prices. This creates market dynamics where users share more data than is socially optimal, often receiving compensation that doesn't reflect the full social costs.  The implications extend beyond individual privacy concerns. Makhdoumi's research shows that under certain conditions, shutting down data markets entirely would improve societal welfare. For business leaders, this challenges conventional thinking about data as a valuable corporate asset and raises questions about sustainable data strategies.Makhdoumi proposes innovative solutions, including "decorrelation" techniques that could allow beneficial data sharing while protecting privacy. He also outlines policy approaches that could help realign market incentives with social benefits. The research offers a framework for companies thinking more strategically about data acquisition, user trust, and the long-term sustainability of data-driven business models.  Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Ronnie Chatterji, Professor at Duke University's Fuqua School ofBusiness and Chief Economist at OpenAI, joins Jenny Laurence, MBA '26 to discuss his recent research paper analyzing over a million ChatGPT conversations to uncover patterns in where artificial intelligence is making impacts in our homes, our work, and our lives.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Trump's push to end quarterly reporting could reshape American business. Professor Rahul Vashishtha explains what research shows about the trade-offs. When companies report earnings more frequently, they make different investment choices, often abandoning profitable long-term projects that don't pay off quickly. This behavioral shift sits at the heart of President Trump's renewed call to end quarterly reporting requirements in favor of six-month reporting cycles.In this episode, Professor Rahul Vashishtha discusses his research examining what happened during the historical shift from annual to semi-annual to quarterly reporting between 1950 and 1970.Vashishtha found that when companies were required to report more often, they significantly reduced their investments in long-term projects. More concerning, this investment decline was accompanied by lower productivity, reduced sales growth, and weaker financial performance. This suggests companies weren't just eliminating waste, but abandoning profitable opportunities.This "managerial myopia" was most pronounced in industries where investments take years to pay off, precisely where quarterly earnings reports are least effective at capturing true value creation. As Vashishtha explains, "When you start increasing the frequency of your performance measures, what you do really is create a premature evaluation of decisions which are best considered over a much longer horizon."The episode explores both sides of the reporting frequency debate, examining the trade-offs between transparency and long-term value creation. Vashishtha also offers practical advice for corporate leaders and investors on encouraging long-term thinking, including cultivating patient capital, strategic communications, and thoughtful incentive design.  Record date: September 16, 2025Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

When a CEO speaks during an earnings call, investors typically focus on the numbers being reported. But studies suggest they should also be listening to how those numbers are delivered. The emotional undertones, vocal pitch, and subtle inflections that executives unconsciously broadcast may reveal as much about a company's future as the financial data itself.In this episode, Professor Bill Mayew of Duke's Fuqua School of Business reflects on his research analyzing CEO voices and how vocal cues can predict market reactions and executive success. His paper, The Power of Voice: Managerial Affective States and Future Firm Performance, published in the Journal of Finance, shows that layered voice analysis can detect emotional cues in CEO communication during earnings calls. These subtle vocal signals—particularly expressions of positive or negative emotion—predict both immediate market reactions and longer-term firm performance.Mayew's second study, Voice Pitch and the Labor Market Success of Male CEOs, analyzed the voices of nearly 800 male corporate executives and found that deeper-voiced CEOs consistently manage larger firms, earn higher compensation, and enjoy longer tenures. This correlation raises complex questions about leadership perception: Do deeper voices signal better leadership capabilities, or do early-life biases create advantages that compound over decades?  As Mayew explains, it’s difficult to disentangle perception from reality. If those with deeper voices are perceived as more authoritative beginning in childhood, they may receive more opportunities to develop actual leadership skills, making initial perceptions self-fulfilling over time.Today, academic findings about vocal cues are driving company decision making. Some hedge funds now deploy algorithms that analyze vocal patterns in real-time during earnings calls, executing trades based on emotional cues that human listeners might miss. Recent advances in AI voice analysis are pushing this technology even further, with platforms now capable of detecting "emotional peaks" to enhance portfolio performance. Meanwhile, the same voice analysis technology originally developed for police interrogations is being repurposed to help managers craft more confident communication.The conversation spans finance, psychology, linguistics and leadership — and will change the way you think about the most human element of communication: your voice.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

A casual conversation about a coworker's side business could be the spark that launches your own entrepreneurial journey. But whether that inspiration leads to action depends on factors you might not expect—including your race, gender, and workplace environment.In this episode, Professor Melanie Wallskog shares insights from her research into how workplace exposure to entrepreneurial coworkers affects an individual’s likelihood of launching a new venture. Her work sheds light on how “entrepreneurial spillovers” occur—when simply working with someone who has previously started a business can increase your own chance of doing so.Yet, this inspiration isn’t evenly distributed. Wallskog finds that white and Asian men are far more likely to benefit from these spillovers than women or Black workers. Women tend to be positively influenced only when the entrepreneurial coworker is also a woman. Black employees face compounded disadvantages: they’re less likely to work in entrepreneur-rich environments and less likely to be influenced even when they do.Her findings are especially relevant for “everyday entrepreneurship”—small businesses like local stores or services, not venture-backed tech startups. These enterprises make up a large share of the U.S. economy and are often launched with personal savings. Wallskog argues that understanding the social dynamics behind who starts these businesses can help policymakers build a more inclusive entrepreneurial economy.Companies also have a role to play. Rather than suppress entrepreneurial drive to retain talent, Wallskog suggests supporting internal innovation through flexible time, collaboration, and space to explore ideas. For aspiring entrepreneurs, the key takeaway is: learn from your peers but remember their experiences may not be your own.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Our brains are wired to seek order when we feel out of control. A framed logo, an organized grocery store, and a well-designed website all provide unconscious signals of stability to consumers navigating uncertainty.  In this episode, Professor Keisha Cutright of Duke University’s Fuqua School of Business discusses her research on how consumers respond to instability. In her widely cited paper, The Beauty of Boundaries: When and Why We Seek Structure in Consumption (Journal of Consumer Research), Cutright reveals that when people feel like they cannot control the outcomes in their lives, even subtle design cues become psychologically reassuring.  Cutright traces her insights back to her days at Procter & Gamble, where she first observed consumer segments deeply focused on orderly living. Her subsequent academic research revealed that this wasn’t just a preference, it was a psychological response to feeling powerless. When people believe things happen randomly in their environment, subtle cues that reflect intentionality can be comforting. These findings have proven consistent across major disruptions, from post-9/11 shopping behaviors to the surge in structured activities like baking during COVID-19.  The conversation covers practical applications for business leaders, from packaging to retail layouts and digital interfaces. Cutright explains how structured environments can serve as substitutes for community support, particularly for vulnerable populations, and why brands that understand this dynamic appeal to customers.  More than a decade after its publication, Cutright's research remains strikingly relevant as consumers navigate an increasingly uncertain world. Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

The next breakthrough drug or industry-disrupting innovation may come from a university lab funded by a federal grant. But a policy shift around how the government supports overhead costs could change which projects are pursued, and which institutions can afford to compete.When the federal government funds scientific research, universities negotiate overhead rates of 50 to 70% over the direct costs of research to cover expenses like lab space and utilities. In reality, they receive far less due to complex accounting rules. For more than 60 years, this complicated system of "indirect cost recovery” has funded America’s research infrastructure.Now that system faces a major disruption. Professor Daniel P. Gross of Duke's Fuqua School of Business analyzed data from 350 U.S. research institutions over 60 years and found that while negotiated rates keep rising, the actual overhead rates paid to research institutions have in practice have been flat for decades. Recent policy proposals to cap indirect cost recovery rates at 15% would have major impacts on research operations. Focusing on NIH funding alone, Gross's analysis shows these changes would reduce universities’ NIH research funding by 15 to 20% annually, with some institutions losing over $100 million a year. Strikingly, the hardest-hit institutions would be those whose work most frequently leads to private sector patents and FDA-approved drugs.In the interview, Gross walks through how seemingly technical policy changes could reshape American innovation and explores potential reforms that could address concerns about the current system. Drawing on historical examples from antibiotics to AI, Gross grounds these changes in a broader context, revealing how funding mechanisms shape what kinds of research gets done–and what’s at stake for the future of scientific discovery.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.

Before you mention that AI tool that's been helping you at work, consider how your colleagues might respond. In this podcast, Professors Richard Larrick and Jack Soll, along with PhD candidate Jessica Reif from Duke University’s Fuqua School of Business, discuss their research into how artificial intelligence tools are reshaping workplace dynamics. Their findings highlight a key paradox: while generative AI can boost performance, using it often makes workers appear less competent, less diligent, and even lazier in the eyes of others.Drawing on a series of experiments, the researchers show that people who use AI for work are judged more harshly than those who seek help from a colleague or even use other software tools. This “social evaluation penalty” can lead to lower hiring prospects, negative perceptions of job fit, and cause employees to hide their AI use altogether.But the penalty isn’t universal. The bias disappears when evaluators are frequent AI users. And when a task clearly benefits from AI (e.g., writing or coding), users face fewer reputational risks. The research also reveals that this judgment bias persists across gender, age, and job types — suggesting its effects are widespread.The research offers insights for both managers and MBA students: creating a culture that normalizes and openly discusses AI use may be critical to unlocking its benefits. Managers must lead by example, openly using generative AI tools to signal that their organization is a safe space for AI innovation and experimentation.Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.For more from Duke Fuqua, visit us on LinkedIn, Instagram, Facebook, Bluesky, and the Duke Fuqua Insights newsletter.