Podcasts about Management science

Telling people not to listen drove three times more podcast listeners than telling them why they should. That's behavioral science at work, and most marketers are barely scratching the surface of it.This week, Elena, Angela, and Rob are joined by Phill Agnew, host of "Nudge," the UK's number one marketing podcast. Phill breaks down the hidden psychology that shapes how consumers think and buy, from why visible effort makes your brand more valuable to how scarcity can be applied in ways that go far beyond a "limited time offer." You'll walk away with principles you can apply immediately... and a few that might change how you think about advertising altogether.Topics covered:•    [03:00] The labor illusion: why showing your work increases perceived value•    [05:00] What System 1 vs. System 2 thinking means for marketers•    [12:00] Costly signaling and why TV advertising commands trust•    [17:00] The mere exposure effect•    [24:00] Distinctiveness vs. differentiation and how to stand out•    [33:00] Scarcity done right: the KFC Australia example.•    [40:00] The Pratfall Effect and why admitting weakness builds brand likability.To learn more, visit marketingarchitects.com/podcast or subscribe to our newsletter at marketingarchitects.com/newsletter.Resources:Buell, R. W., & Norton, M. I. (2011). The labor illusion: How operational transparency increases perceived value. Management Science, 57(9), 1564–1579. https://doi.org/10.1287/mnsc.1110.1376 2018 The Choice Factory Book: https://www.richardshotton.com/the-choice-factory Behavioral Business Book by Richard Chataway: https://www.amazon.com/Behaviour-Business-behavioural-science-business/dp/0857197347 Phill Agnew's LinkedIn: https://www.linkedin.com/in/phill-agnew/Get more research-backed marketing strategies by subscribing to The Marketing Architects on Apple Podcasts, Spotify, or wherever you listen to podcasts.

“Friction for us has to do with obstacles,” says Hayagreeva “Huggy” Rao, a professor of organizational behavior at Stanford Graduate School of Business. “Obstacles can disable you. Obstacles can enable you.”Rao compares friction to cholesterol: Some is good, but some is bad. “Good friction actually slows you down, gets you to pause, and most of all, gets you to reflect,” he explains. “But there's also friction that overwhelms you, exhausts you, confuses you.” On this episode of If/Then, Rao explores how to cultivate the productive kind of friction, reduce the unhelpful kind, and manage your team's most precious resource. “Great leaders are people who think of themselves as trustees of other people's time,” he says. Do you have any favorite examples of good or bad friction? Share one with us at ifthenpod@stanford.edu.Related Content:Huggy Rao faculty profile The Friction ProjectHow to become a friction fixerChapters:00:00:00 Airport baggage claim, waiting, & good friction00:03:20 Introduction00:03:48 What friction means in organizations00:05:42 Where friction comes from00:07:52 Scaling through smart subtraction00:08:24 DropBox's approach to meetings00:10:45 The problem with meetings00:13:53 What good friction looks like00:16:56 Friction, trust, & institutional legitimacy00:19:31 Why Huggy Rao started studying friction00:22:20 ConclusionSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this special episode, created by one of our student podcast fellows, NYU student Avani Advani, interviews Joshua Lewis, an Assistant Professor of Marketing at the NYU Stern School of Business. Avani speaks to Joshua about the human side of decision-making, how “loss aversion” influences what we value, and why some people chase risk while others avoid it entirely.Professor Lewis researches consumer behavior, managerial decision-making, and global risk management. His research addresses wide-ranging themes such as when people will invest to improve outcomes they care about, how to optimally set targets, whether people neglect low probability risks, and much more. His work has been published in leading journals such as Journal of Consumer Research, Management Science, Psychological Science, Journal of Experimental Psychology: General, and Organizational Behavior and Human Decision Processes.In 2019, Professor Lewis received the Society for Judgment and Decision Making's Hillel Einhorn Award for the best paper by a new investigator, and in 2020, he received ACR's Best Paper award. He received his BS in Economics from the University of Warwick. He holds a PhD in Decision Processes from the University of Pennsylvania.For a full transcript of this episode, please email career.communications@nyu.edu. 

“I don't see things like anybody else,” says Jonathan Berk, a professor of finance at Stanford Graduate School of Business. “And so I can see things people don't see.” On this episode, Berk explores recent research that pushes against conventional wisdom, from questioning the utility of the debt-to-GDP ratio to asking whether regulation is actually in the best interests of the consumer. “If you disagree with me… You have to write down a convincing theoretical model and analyze [it].”Berk admits his unique lens doesn't always make life easy. But on the other hand, “it confers an enormous advantage” — and he believes that organizations which are able to harness the power of unconventional thinking can gain a competitive edge.“It's allowed me to solve problems that other people couldn't solve,” he says. Has seeing the world differently helped you resolve a conundrum? Tell us more at ifthenpod@stanford.edu.Related Content:Jonathan Berk faculty profile What If We're Looking at the National Debt All Wrong? Chapters:00:00:00 The Fosbury Flop, innovation, & unconventional thinking00:03:18 Introduction00:04:24 Questioning conventional wisdom00:04:57 Rethinking the debt-to-GDP ratio00:08:21 A finance perspective on national debt00:10:36 Why theory matters before alarm00:12:38 Regulation, charlatans, & consumer interests00:16:22 Licensing, certification, & competition00:19:51 The cost of pushing back00:21:16 Building organizations that welcome dissent00:24:59 ConclusionIf/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Dans le cadre du cours de MSDGN, les élèves de terminale STMG ont pris part à une séance de révision portant sur les notions clés du programme. Ils ont élaboré leurs textes avec l'appui de l'intelligence artificielle. Communique-t-on de la même manière avec tous les acteurs ? par Paloma, Meyla et Louane 02:07 – Les transformations […]

“When people come to view attitudes and opinions towards, say, political policies or issues as relevant to their identities, they become more extreme in their attitudes,” says Christian Wheeler, the StrataCom Professor of Management and Professor of Marketing at Stanford Graduate School of Business. “I become more positive or negative towards an issue the moment it becomes relevant to who I view myself as being.”Wheeler's research offers insight into our increasingly polarized politics. However, his work has also yielded ideas for bridging divisions — beginning with how we listen to each other and how we see the people we disagree with.The moment we see someone as an individual rather than a category, we become more likely to find common ground. “Instead of viewing you as a Democrat or a Republican, I can view you as an individual,” Wheeler recommends. “Anything that humanizes you and moves you away from this simple category will help me to view you as an individual and less as just an interchangeable member of a category.” How much do your opinions define who you are? Tell us more at ifthenpod@stanford.edu.Related Content:Christian Wheeler faculty profile In a Polarized World, an Open Mind Can Hurt Your ReputationYou May Not Be Who You Think You AreClass Takeaways — How to Build Connection Through Better ListeningChapters:00:00:02 Tattoos, identity, & personal evolution00:03:26 Introduction00:03:59 Why identity matters00:04:56 Identity relevance & its implications00:08:03 Why openness to the other side gets punished00:10:57 Identities vs. opinions00:13:53 The power of individuation00:15:53 How to break the cycle of polarization 00:19:41 Organizational applications00:23:26 ConclusionIf/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Aharon “Ronny” Ben-Tal is a Professor of OR and former head of the MINERVA Optimization Center at the Faculty of Industrial Engineering and Management at the Israel Institute of Technology (Technion). His interests lie in Continuous Optimization, particularly nonsmooth and large-scale problems, conic and robust optimization, as well as convex and nonsmooth analysis. He has published more than 130 papers in professional journals and co-authored three books. Ronny was Dean of the Faculty of Industrial Engineering and Management at the Technion and he also served as a council member of the Mathematical Programming Society. He was Area Editor Operations Research and Math. of OR, and member of the Editorial Board of SIAM J. Optimization, J. Convex Analysis, OR Letters, Mathematical Programming, Management Science, Math. Modeling and Numerical Analysis, EJOR, and Computational Management Science. He also served as Associate Editor for SIAM J. Optimization. He in an EURO Gold Medalist, an INFORMS and SIAM fellow, and a Distinguished Scientist by CWI in The Netherlands. Ronny is a recipient of the IBM Faculty Award, and was also awarded the Khachiyan Prize by the INFORMS Optimization Society for lifetime achievements in the area of Optimization. In addition, the OR Society of Israel awarded him the lifetime achievement Prize. As of April 2026, he has over 41,000 citations on Google Scholar.

With Wen Nottebohm—Managing Director, Wealth Advisor at Cresset Overview Wen Nottebohm of Cresset joins Mindy Diamond to share the next gen perspective: how advisors can design their own growth path, earn credibility among UHNW clients, the value of mentors, the influence of AI, and much more. Listen in… > Download a transcript of this episode… NOTE: The views and opinions expressed by the guests on this podcast are their own and do not necessarily reflect the views and opinions of Diamond Consultants. Neither Diamond Consultants nor the guests on this podcast are compensated in any way for their participation. Watch… https://youtu.be/jmtqqBQ9C80 About this episode… There's a fairly well-defined career path for most financial advisors. You spend the early years learning the business, supporting senior advisors, and gradually taking on more responsibility. When it comes to ultra-high net worth clients, that timeline tends to stretch even longer, given the complexity and expectations that come with those relationships. But the path isn't always linear. And in some cases, it moves faster than people expect—especially when the focus shifts from simply accumulating experience to developing real expertise and “a seat at the table” early on. That's part of what makes Wen Nottebohm's perspective so compelling. Wen is part of the Atlanta team at Cresset, a $230B+ multi-family office. The team manages roughly $7B in assets, and Wen herself is advising on $1.6B for UHNW families and entrepreneurs. What stands out is not just the scale, but how early in her career Wen stepped into that level of responsibility—and what it actually required to make that work. In this conversation with Mindy Diamond, Wen offers a very real look at the next gen perspective, including: The wirehouse environment—and what made it a successful training ground. The value of a mentor—and how working with Justin Berman helped her move to the next level. Building a book to over $1B—and how she did so in a much shorter timeline than many of her peers. Earning credibility—and what it really takes to build a business and client trust with less of a track record. Working with a sophisticated client base—and how to manage expectations and identify what they really value. The benefit of a firm like Cresset—and how the more personalized culture and boutique feel creates a foundation for growth. The influence of AI—and how it's both changing the dynamic and raising the level of the advisor-client conversation. This episode is a masterclass for next gen and seasoned advisors alike, identifying what it really takes to build a billion-dollar business in a rapidly changing environment and questioning whether the traditional timeline for building an advisory practice is being rewritten in real time. Want to learn more about where, why, and how advisors like you are moving? Click to contact us or call 908-879-1002. Related Resources Finding the Shortest Path to Excellence Can Be a Game Changer for AdvisorsDoing everything you can to deliver better service, drive growth, and achieve your goals faster can result in extraordinary benefits. The 4th Annual Advisor Transition ReportA data-driven look at where advisors are moving, why they're making changes, and what it means for your business in 2026. Life After Goldman Sachs: A Story of Extraordinary SuccessEx-Goldman Sachs advisor Justin Berman shares how he found the courage to leave the Goldman imprimatur, brave Garden Leave, and build the $3B Berman Capital Advisors. Wen NottebohmManaging Director and Wealth Advisor Wen Nottebohm is a Managing Director, Wealth Advisor at Cresset. She works with clients to help protect and grow their legacy in order to have a bigger impact on what is most important to them. Wen was named to the 2024 Barron's Top 100 Independent Advisors, 2025 Barron's Top Independent Financial Advisors, 2025 Barron's Top Financial Advisors By State, 2025 Barron's Top Women Financial Advisors, 2025 Forbes Top Women Wealth Advisors Best-In-State, 2025 Forbes Best-In-State Wealth Advisors, 2025 Forbes Top Next-Gen Wealth Advisors Best-In-State, and 2025 Forbes America's Top Next-Gen Wealth Advisors lists. Prior to Cresset, Wen worked as a Wealth Advisor for Berman Capital Advisors, and before that was with AQR Capital Management, where she was a Client Strategies and Portfolio Solutions Analyst. Wen started out her career in the Private Wealth Management division at Morgan Stanley Smith Barney, where she specialized in risk and discretionary account management for the firm's ultra-high-net-worth clients. Wen graduated from MIT with Bachelor of Science degrees in Economics and Management Science. She also holds an MBA from The Wharton School, University of Pennsylvania. She obtained the CERTIFIED FINANCIAL PLANNER® designation in 2019. Wen and her husband live in Atlanta with their son and daughter. She serves on the Board of the YWCA of Greater Atlanta and is involved with the Atlanta Regional Commission Global Advisory Panel, the MIT Alumni Association, the Wharton Club of Atlanta, and the Young Women Leadership Forum. Wen is also a member of the LEAD Atlanta Class of 2016.

“Masculinity is my new frontier,” says Ashley Martin, an associate professor of organizational behavior at Stanford Graduate School of Business. Martin, whose work examines why gender plays such a central role in how we perceive and make sense of others, has been looking at how traits associated with masculinity are simultaneously organizationally rewarded even as they're personally harmful to men. “We spend a lot of time talking about gender inequality through the lens of women's disadvantage,” she says. “I think that many of the problems that we're seeing today… are actually bound up in masculinity.” What impact do you think masculinity and femininity have on our work and our world? Tell us more at ifthenpod@stanford.edu.Related Content:Ashley Martin faculty profile Is that Self-Driving Car a Boy or a Girl? Why Taking Gender Out of the Equation Is So DifficultChapters:00:00 How movies shape our ideas about masculinity04:02 Introduction05:15 How Ashley Martin got into studying gender05:58 When gender is removed from hiring07:10 The “pet rock” study10:35 The universal use of gender13:02 Gendering objects15:12 How masculinity affects men18:13 The current implications of Martin's research20:41 What healthier models of masculinity might look like23:47 Ashley's next frontier: masculinity, material culture, and social problems25:07 ConclusionIf/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Learn why scaling AI is as much a human challenge as it is a technological one. Stefano Puntoni, Co-Director of Wharton Human-AI Research and Professor at The Wharton School, examines the limits of data-driven decision making in the age of AI and why insights so often fail to translate into action. He breaks down the psychology behind AI resistance and outlines the leadership and change management strategies needed to turn AI potential into real organizational impact. Key Moments: Why More Data Doesn't Lead to Better Decisions (02:26): Stefano challenges the assumption that smarter algorithms automatically produce smarter decisions. He argues that decision quality depends on rigorous conceptual thinking before turning to data. Without clearly defining objectives, alternatives, and success criteria, analytics efforts rarely translate into meaningful action. Conversational AI and the Lowering of the Cost of Action (07:26): Stefano explains how conversational AI brings decision makers closer to data by reducing friction. By lowering the cost of experimentation, AI enables managers to test hypotheses in real time instead of waiting days for analysis. This shift moves organizations from analysis paralysis to faster, more confident action. Rethinking Your Role in the Age of AI (17:16): For professionals navigating disruption, Stefano outlines two paths forward. One is becoming a complement to AI by upskilling and using the technology as a productivity multiplier. The other is pivoting toward skills AI is less likely to replace, such as strategy, orchestration, and human judgment. The AWARE Framework: Pairing Technical Rollout with Human Rollout (22:41): Stefano introduces the AWARE framework to help leaders anticipate and manage the human reactions to AI transformation. He argues that every technical implementation must be matched with structured communication, identity support, and organizational alignment. Without this dual-track approach, even well-designed AI systems can fail to gain traction. Change Management, AI Literacy, and the Gap in Organizational Readiness (31:11): Only a small percentage of organizations have formal AI change management programs. Stefano questions whether companies are truly prepared for large-scale AI transformation. He emphasizes that AI literacy, leadership accountability, and structured change management will determine whether AI investments translate into sustained performance. Key Quotes: “ The leaders need to know why we are doing AI. AI is not a strategy; AI is just a tool. So what is it that we're trying to achieve?” - Stefano Puntoni “ I think the problem is that technology is almost like taking all the oxygen from the room. There's so much attention and urgency around the tech itself that we often forget the people around it.” - Stefano Puntoni “You don't want to be the substitute to the technology because if that is what you do, then there's no future. But if you're a complement, the technology might be a multiplier of your productivity.” - Stefano Puntoni Mentions Decision-Driven Analytics: Leveraging Human Intelligence to Unlock the Power of Data The Wall Street Journal: The Boss Has a Message: Use AI or You're Fired 2025 Report Accountable Acceleration: Gen AI Fast-Tracks Into the Enterprise How AI Affects Our Sense of Self Why Gen AI Feels So Threatening to Workers Conversational AI: The Next Frontier of Digital Platform Monetization Guest Bio  Stefano Puntoni is the Sebastian S. Kresge Professor of Marketing at The Wharton School. Prior to joining Penn, Stefano was a professor of marketing and head of department at the Rotterdam School of Management, Erasmus University, in the Netherlands. He holds a PhD in marketing from London Business School and a degree in Statistics and Economics from the University of Padova, in his native Italy. His research has appeared in several leading journals, including Journal of Consumer Research, Journal of Marketing Research, Journal of Marketing, Nature Human Behavior, and Management Science. He also writes regularly for managerial outlets such as Harvard Business Review and MIT Sloan Management Review. Most of his ongoing research investigates how new technology is changing consumption and society, including how humans are adopting and evolving with AI. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Steven Callander has spent years building a mathematical framework to answer the question of how people learn from experience. “Here in Silicon Valley, the expression that you learn from failure is very widespread and very intuitive. But the question is… what do you learn? How do you optimally learn from that experience?”In this episode, Callander, the Herbert Hoover Professor of Public and Private Management and Professor of Political Economy at Stanford Graduate School of Business, explains the hidden, deceptively simple logic of correlated learning — and it may change how you think about finding the right job, the right market, or the right strategy. “It fascinates me and I can't stop thinking about it,” he says. Has theory made an impact on your life? Tell us more at ifthenpod@stanford.edu.Related Content:Steven Callander faculty profileHow to Turn Old Ideas Into Creative Solutions to Modern ProblemsWhat We're Still Learning from Silicon Valley's Bank CollapseChapters:00:00 Ann Miura-Ko on learning and the search for patterns in Venture capital02:51 Introduction05:23 What is correlated learning?06:40 Where does this research apply in the real world?09:28 Brownian Motion12:45 Steven Callander's Framework15:25 Examples of correlated learning when seeking expert advice20:53 Applying correlated learning23:57 Why correlated learning research?24:51 ConclusionIf/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Jorge Nocedal is a Professor in the Department of Industrial Engineering and Management Sciences at Northwestern University. He obtained his B.S. degree from UNAM, Mexico, and a PhD from Rice University. His research is in optimization, both deterministic and stochastic, and with emphasis on large-scale problems. He served as editor-in-chief of the SIAM Journal on Optimization, is a SIAM Fellow, and was awarded the 2012 George B. Dantzig Prize (MOS-SIAM), the 2017 Von Neumann Theory Prize (INFORMS), and the 2024 John Von Neumann Prize (SIAM) for contributions to theory and algorithms of nonlinear optimization. He is a member of the US National Academy of Engineering.

Shyam Sankar is Chief Technology Officer and Executive Vice President at Palantir Technologies, where he has served since 2006 as one of the company's earliest hires and key builders. A seasoned technologist with over two decades of experience, he has led the design and deployment of software platforms that support some of the world's most complex and high-stakes environments. from defense operations to enterprise systems. Sankar holds a B.S. in Electrical and Computer Engineering from Cornell University and an M.S. in Management Science and Engineering from Stanford University. His career reflects a commitment to advancing technology that strengthens national resilience and accelerates industrial and defense innovation. A vocal advocate for applying artificial intelligence to empower American workers and reindustrialize the United States, Sankar is deeply engaged in initiatives such as the American Tech Fellows program, which develops domestic AI talent. He regularly speaks on the role of AI in transforming national security and industry through practical adoption rather than speculation. Rejecting narratives of AI “doomerism,” Sankar emphasizes real-world deployment and measurable results—showing how Palantir's tools are redefining the speed of warfare, industrial output, and decision-making across the defense and commercial landscapes. His insights are frequently featured in conversations about the future of AI, national power, and America's technological edge. Shawn Ryan Show Sponsors: Join thousands of parents who trust Fabric to help protect their family—apply today in just minutes at https://meetfabric.com/SHAWN. Try Gusto today at https://gusto.com/SRS and get three months free when you run your first payroll. New customers can save 35% on your first month of Dose for Cholesterol by going to https://dosedaily.co/SRS or entering SRS at checkout. Shyam Sankar Links: X - https://x.com/ssankar Substack - https://www.shyamsankar.com LinkedIn - https://www.linkedin.com/in/shyamsankar On The Defense Reformation - https://18theses.com First Breakfast - https://www.firstbreakfast.com Book - https://www.amazon.com/Mobilize-Reboot-American-Industrial-World/dp/B0FQWGC94Z/ref=sr_1_1 Learn more about your ad choices. Visit podcastchoices.com/adchoices

What does it truly take to change what we do — for yourself and at scale, sustainably in the real world?In this episode, Angela sits down with Hengchen Dai, Associate Professor at UCLA Anderson and co-director of the UCLA Nudge Unit, to explore the science behind why people do what they do, and what it takes to shift it.Hengchen brings rigorous academic research published in Nature and other notable publications, and field experiments run inside hospitals, university health systems, and national pharmacy chains with millions of participants. What emerges is a practical toolkit for anyone trying to create lasting change — whether you're a leader, a clinician, a policymaker, or just someone trying to get better at your own habits.Key Takeaways  -  Behaviour change is not one-size-fits-all — someone who skipped their flu shot this year (but got it last year) has a completely different barrier (forgetting, procrastination) than someone who has never been vaccinated (belief, scepticism). Targeting interventions based on past behaviour dramatically improves results. 

Seemingly unrelated activities — like taking a soccer penalty kick or crafting an online dating profile — involve an embedded economics. “Understanding and applying economic logic can be valuable in pretty much any job or any other endeavor in your life,” says Paul Oyer, a professor of economics at Stanford Graduate School of Business. On this episode, Oyer digs into the shared economic logic of online dating and the labor market, explains why pro athletes and sports fans think like economists, and explores how AI has reduced the beneficial friction that was once a part of job searches. Got a question about the economics of dating, sports, or the job market? Ask us at ifthenpod@stanford.edu.Related Content:Paul Oyer faculty profileUtility Player: Paul Oyer Explains How Economics Can Make Sports More FunIf/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week on The GovNavigators Show, Robert and Adam welcome Wynn Coggins, former Acting Secretary of Commerce and now Chief Growth Officer at Management Science and Innovation, for a candid conversation on leadership forged through crisis, transition, and 35 years of federal service.Wynn shares the lessons she's carried from her early days as a patent examiner through navigating COVID at the Department of Commerce, serving as Acting Deputy Secretary, and landing in the private sector at Deloitte before her current role. The throughline: surround yourself with people who challenge you, park your ego at the door, and build a culture where failing fast is a feature, not a flaw.Robert and Adam also cover the week's big news: the introduction of the Federal Loan System Modernization Act of 2026, a bill that would finally bring a single platform to manage the government's sprawling loan portfolio, and the escalating standoff between the Department of Defense and Anthropic, which has now prompted the White House to direct agencies to cancel contracts with the AI company. Plus: Microsoft's major takedown of a global phishing operation responsible for 30 million fraudulent emails a month.Show Notes:Federal Loan System Modernization Act of 2026Check out the The Lending Brief Podcast's new homeWhat's on the GovNavigators' Radar:Mar 12, 2026AFCEA NOVA Naval IT DayMar 17, 2026AGA Technology and Transformation SummitApr 22, 2026ACT-IAC Emerging Tech Demo Day (rescheduled from March 18)

When should we leap instead of take the obvious next step? Why do we instinctively see gender everywhere? When do our opinions begin to feel less like ideas and more like our identity?If/Then, from Stanford Graduate School of Business, is back with a new season of sharp, surprising conversations that deepen our understanding of business and leadership.Each episode brings you into the room with a Stanford GSB faculty member as they discuss their research and how it challenges conventional wisdom, sharpens judgment, and reframes the way we approach complex decisions. Join us on Wednesdays for a new season of If/Then.What do you want to hear on If/Then? Email us at ifthenpod@stanford.edu.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Artigo publicado no Management Science conclui que, nas sociedades com maior pressão social, o valor das gorjetas vai aumentando com o tempo, como forma de respeitar uma suposta norma social

“You can create a virtual board of directors that will have different expertises and that will come up with ideas that a given person may not come up with.” – Felipe Csaszar About Felipe Csaszar Felipe Csaszar is the Alexander M. Nick Professor and chair of the Strategy Area at the University of Michigan’s Ross School of Business. He has published and held senior editorial roles in top academic journals including Strategy Science, Management Science, and Organization Science, and is co-editor of the upcoming Handbook of AI and Strategy. Webiste: papers.ssrn.com LinkedIn Profile: Felipe Csaszar University Profile: Felipe Csaszar What you will learn How AI transforms the three core cognitive operations in strategic decision making: search, representation, and aggregation. The powerful ways large language models (LLMs) can enhance and speed up strategic search beyond human capabilities. The concept and importance of different types of representations—internal, external, and distributed—in strategy formulation. How AI assists in both visualizing strategists' mental models and expanding the complexity of strategic frameworks. Experimental findings showing AI's ability to generate and evaluate business strategies, often matching or outperforming humans. Emerging best practices and challenges in human-AI collaboration for more effective strategy processes. The anticipated growth in framework complexity as AI removes traditional human memory constraints in strategic planning. Why explainability and prediction quality in AI-driven strategy will become central, shaping the future of strategic foresight and decision-making. Episode Resources Transcript Ross Dawson: Felipe, it’s a delight to have you on the show. Felipe Csaszar: Oh, the pleasure is mine, Ross. Thank you very much for inviting me. Ross Dawson: So many, many interesting things for us to dive into. But one of the themes that you’ve been doing a lot of research and work on recently is the role of AI in strategic decision making. Of course, humans have been traditionally the ones responsible for strategy, and presumably will continue to be for some time. However, AI can play a role. Perhaps set the scene a little bit first in how you see this evolving. Felipe Csaszar: Yeah, yeah. So, as you say, strategic decision making so far has always been a human task. People have been in charge of picking the strategy of a firm, of a startup, of anything, and AI opens a possibility that now you could have humans helped by AI, and maybe at some point, AI is designing the strategies of companies. One way of thinking about why this may be the case is to think about the cognitive operations that are involved in strategic decision making. Before AI, that was my research—how people came up with strategies. There are three main cognitive operations. One is to search: you try different things, you try different ideas, until you find one which is good enough—that is searching. The other is representing: you think about the world from a given perspective, and from that perspective, there’s a clear solution, at least for you. That’s another way of coming up with strategies. And then another one is aggregating: you have different opinions of different people, and you have to combine them. This can be done in different ways, but a typical one is to use the majority rule or unanimity rule sometimes. In reality, the way in which you combine ideas is much more complicated than that—you take parts of ideas, you pick and choose, and you combine something. So there are these three operations: search, representation, and aggregation. And it turns out that AI can change each one of those. Let’s go one by one. So, search: now AIs, the current LLMs, they know much more about any domain than most people. There’s no one who has read as much as an LLM, and they are quite fast, and you can have multiple LLMs doing things at the same time. So LLMs can search faster than humans and farther away, because you can only search things which you are familiar with, while an LLM is familiar with many, many things that we are not familiar with. So they can search faster and farther than humans—a big effect on search. Then, representation: a typical example before AI about the value of representations is the story of Merrill Lynch. The big idea of Merrill Lynch was how good a bank would look if it was like a supermarket. That’s a shift in representations. You know how a bank looks like, but now you’re thinking of the bank from the perspective of a supermarket, and that leads to a number of changes in how you organize the bank, and that was the big idea of Mr. Merrill Lynch, and the rest is history. That’s very difficult for a human—to change representations. People don’t like changing; it’s very difficult for them, while for an AI, it’s automatic, it’s free. You change their prompt, and immediately you will have a problem looked at from a different representation. And then the last one was aggregating. You can aggregate with AI virtual personas. For example, you can create a virtual board of directors that will have different expertises and that will come up with ideas that a given person may not come up with. And now you can aggregate those. Those are just examples, because there are different ways of changing search, representation, and aggregation, but it’s very clear that AI, at least the current version of AI, has the potential to change these three cognitive operations of strategy. Ross Dawson: That’s fantastic. It’s a novel framing—search, representation, aggregation. Many ways of framing strategy and the strategy process, and that is, I think, quite distinctive and very, very insightful, because it goes to the cognitive aspect of strategy. There’s a lot to dig into there, but I’d like to start with the representation. I think of it as the mental models, and you can have implicit mental models and explicit mental models, and also individual mental models and collective mental models, which goes to the aggregation piece. But when you talk about representation, to what degree—I mean, you mentioned a metaphor there, which, of course, is a form of representing a strategic space. There are, of course, classic two by twos. There are also the mental models which were classically used in investment strategy. So what are the ways in which we can think about representation from a human cognitive perspective, before we look at how AI can complement it? Felipe Csaszar: I think it’s important to distinguish—again, it’s three different things. There are three different types of representations. There are the internal representations: how people think in their minds about a given problem, and that usually people learn through experience, by doing things many times, by working at a given company—you start looking at the world from a given perspective. Part of the internal representations you can learn at school, also, like the typical frameworks. Then there are external representations—things that are outside our mind that help us make decisions. In strategy, essentially everything that we teach are external representations. The most famous one is called Porter’s Five Forces, and it’s a way of thinking about what affects the attractiveness of an industry in terms of five different things. This is useful to have as an external representation; it has many benefits, because you can write it down, you can externalize it, and once it’s outside of your mind, you free up space in your mind to think about other things, to consider other dimensions apart from those five. External representations help you to expand the memory, the working memory that you have to think about strategy. Visuals in general, in strategy, are typical external representations. They play a very important role also because strategy usually involves multiple people, so you want everybody to be on the same page. A great way of doing that is by having a visual so that we all see the same. So we have internal—what’s in your mind; external—what you can draw, essentially, in strategy. And then there are distributed representations, where multiple people—and now with AI, artifacts and software—among all of them, they share the whole representation, so they have parts of the representation. Then you need to aggregate those parts—partial representations; some of them can be internal, some of them are external, but they are aggregated in a given way. So representations are really core in strategic decision making. All strategic decisions come from a given set of representations. Ross Dawson: Yeah, that’s fantastic. So looking at—so again, so much to dive into—but thinking about the visual representations, again, this is a core interest of mine. Can you talk a little bit about how AI can assist? There’s an iterative process. Of course, visualization can be quite simple—a simple framework—or visuals can provide metaphors. There are wonderful strategy roadmaps which are laid out visually, and so on. So what are the ways in which you see AI being able to assist in that, both in the two-way process of the human being able to make their mental model explicit in a visualization, and the visualization being able to inform the internal representation of the strategist? Are there any particular ways you’ve seen AI be useful in that context? Felipe Csaszar: So I was very intrigued—as soon as LLMs became popular, were launched—yeah, ChatGPT, that was in November 2022—I started thinking, there are so many ways in which this could be used. So myself and two co-authors, Hyunjin Kim and Harsh Ketkar, we wrote a paper, one of the initial papers on how AI can be used in strategy. It’s published in Strategy Science, and in that paper, we explore many ways in which AI could be used in strategy. Of course, you can ask AI about coming up with answers to questions that you may have. You can also use AI to use any of these frameworks that have been developed in strategy. It was very clear to us that it was usable. Then the question was, how good are those uses? What’s the quality of current AI doing this type of task? So what we did is an experiment where we compared the performance of AI to the performance of humans. In strategy, there are two types of tasks: one is to generate alternatives, and the other is to select alternatives. You have a problem—the first thing you want to do is have possible solutions, and then you want to be able to pick the best out of those. So we had two experiments: one where we measured the ability of AI to generate alternatives, another to select. For generation, what we did is we got data from a business plan competition where people were applying with business plans that all had the same format. The important thing is that the first paragraph of that application had the problem—a problem that they thought was important. So we took all of those applications and removed everything except for the problem, and then we gave that problem to an AI and asked the AI, “Hey, complete the rest of the business plan.” So now we have business plans that are real, and the AI twins of those—business plans created by an AI that try to solve the same problem. Then we put both in a kind of business plan competition, where we had people with experience in investments ranking all of these business plans, and they didn’t know which ones were created by humans and which ones were created by AIs. We looked at their evaluations at the end of the day, and on average, the ones that were generated by the AI were ranked a little bit higher—7% higher—than the ones that were generated by humans. So at least in this very specific context of business plan competitions, there’s potential. We’re saying, hey, AI could generate things at a level that is comparable to the people applying to this type of business plan competition. That has a lot of potential. We could use it in different ways. The other part of this study was to measure the ability of AI to select strategies among strategies. There, what we did is use data from another business plan competition, where all of the business plans had been evaluated by venture capitalists according to 10 dimensions: how strong is the idea, how strong is the team, how strong is the technology, etc. Then we gave an AI the same rubric that the venture capitalists received and asked the AI to rank or grade each one of these startups according to these 10 dimensions. Then we compared how similar the evaluations of the LLM were to the evaluations of the venture capitalists, and we showed that they are quite similar—there’s a correlation of 52%. This, again, tells us that there is potential here. An AI could do things that are quite similar to an experienced human evaluating this type of startup. A very interesting result there is that the correlation between two venture capitalists is lower than that 52%. So if you want to predict what a venture capitalist is going to say about your business, you’re better off asking an LLM than asking another venture capitalist. Ross Dawson: Yes, which perhaps shows the broad distribution of VC opinions. So obviously, LLMs can play valuable roles in many aspects of the strategy process, but this brings us back to the humans plus AI role. There are many—again, a big topic—but rather than looking at them, comparing what humans and AI did, where do you see the primary opportunities for humans and AI to collaborate in the strategy process? Felipe Csaszar: Yeah, yeah. So I think that’s a fascinating question, and my guess is that the study of the strategy process will completely change in the next 10 to 20 years. So far, all of the strategy process has been to study what happens when you have multiple people making strategy decisions. In the past, we studied things like devil’s advocate, or we have studied the role of changing the size of the group of people making decisions, or the consensus level required. But in the future, there will be AIs in this process that will have completely different bounds or capacities than humans. So we will need to learn what’s the best way of collaborating with them and including them into the strategic decision making process. Today, we don’t know much about it. We are beginning to learn things, like the study I mentioned—hey, in this task, it seems to be better—but there’s so much that we need to learn. I am working on some things, but it’s still early. Ross Dawson: Going back to the distributed representation—this is something where, of course, distributed representation can be in multiple people. Arguably, it can include human and AI agents as each having different representations. But this goes, of course, to the aggregation piece, where the aggregation is—you have a board of directors, group of executives, potentially a participative strategy process bringing more people into the organization. What are the specific roles of AI in assisting or facilitating effective aggregation to form a cohesive strategy? Felipe Csaszar: Yeah, so the truth is, we yet don’t know. There’s not enough research. We’re starting to think about it. We can see many uses, and I think what people should be doing now is running experiments to see when those add value and when they don’t. It will be different for different companies in different industries, so probably there’s no one solution that’s the same for everybody. For example, one possible use in strategic decision making is predicting what your competitors would do. If I do this, what would be the most likely reaction of my competitor? That’s one. Another one is predicting consumers: if I launch this product with this set of characteristics, what would be the most likely response of my consumers? In strategy, something that has been very popular for the last 20 years is something called the Blue Ocean Strategy, which is a method to come up with new offerings, with new value propositions, but that requires a lot of creativity. With AI, you can automate part of that. At the end of the day, it’s a search process. You have to think about what would happen if I add this, or if I add this other thing, or if I increase this. Part of that can be automated—that would be another use. Or if you have different proposals—in this other study, we show, hey, AI is good at evaluating, so if you have the right rubric, this can automate the evaluation, or can automate the first part of that evaluation so that you only have to spend your time among the really complicated, more sophisticated decisions or alternatives. There are many, many things that can be done at this point. Ross Dawson: Which goes to, I think, one of the interesting points in your work—representational complexity. Some strategies are arguably simple; other strategies, you can call them more sophisticated, but they are more complex. The representation of complexity is greater. There are two things that are required for that. One is, of course, sophisticated thinking, but also, because strategy in any organization involves multiple people, it requires that there is an ability for a number of people together to hold a hopefully similar or very similar representation of a quite complex topic. What are ways in which AI can be used to enhance that development of more sophisticated or nuanced or complex representations that can support a better strategy? Felipe Csaszar: So that’s a great point. I have a paper from before this new round of AI called exactly that—representation complexity. There has been a long-standing discussion in strategy of when you want to use a simple representation, whether it’s better to use a complex representation, or something in between. We tried to clarify when each one of these applies. But then came this new round of AI, and I think it changes things a lot. I talk a little bit about this in a chapter I uploaded recently—it’s called “Unbounding Rationality.” The key thing there is that humans—we have our own computer here, it’s the brain, and the brain has some constraints. One very important for strategy is the capacity of our working memory. There’s this famous paper from the 1950s called “The Magical Number Seven,” that we can hold in our working memory seven plus or minus two items—so between five and nine things we can keep at the same time in our mind. That’s why, for example, I think all strategy frameworks are very simple. There’s the five forces—fits within our working memory—or these typical two by twos, they have four quadrants—fits within our working memory. But AIs don’t have that bound. They are not constrained by the same working memory constraint that we have. So I would expect that future frameworks will be much more complex, that representational complexity will increase because of AI. Of course, frameworks of the future won’t have a million things, because when you put too many things, you’re overfitting—it works well with things that happened in the past, but not in the future—but they will probably have more than five things. Also, another reason for not having a million things inside a framework is that at the end of the day, you will still need to communicate frameworks. You will need to convince the other people in the organization, the ones that are implementing the strategy, that this is the right strategy. You will need to convince them, so you don’t want to have something that’s extremely complex. But my guess would be that the complexity of frameworks and of strategies will increase with AI. Ross Dawson: So looking forward—you talked about 10 or 20 years. If we see the current pace of capability development of LLMs on a similar trajectory, where do you see the remaining role of humans as a complement to AI in shaping strategy? I think you mentioned this possibility of essentially AI forming strategy, but I think for a wide array of reasons, it will be human plus AI—humans will play a role as final decision maker or other things. So where do you see those fundamental human capabilities still being retained for the foreseeable future, as a complement to AI in strategy? Felipe Csaszar: So I think that for the next 10, 20, maybe 30 years, humans will be really busy coming up with how to use AI—all of these experiments that we mentioned, people will be running all of those things in all different industries, and that takes a while. That will require human ingenuity and trying things and really understanding strategy and understanding the capabilities of AI. So I don’t see AI replacing human strategists in the very short term. On the contrary, because of AI, strategists will be more busy finding what are the best ways of using AI in their businesses. I think 10, 20, or 30 years is very reasonable. If you think about the previous technological revolution, which I could say was the Internet—the technology for the Internet, we could say, existed since around ’94. The World Wide Web is from ’94, browsers are from ’94, bandwidth enough to send email. Essentially all of the technology that supports internet business today was mostly in place in the mid to late ’90s. But the businesses, or people, ended up using all of those things 10 or 20 years after that, because it takes a long time for people, for strategists, to come up with the idea—for someone to come up with the idea of, let’s say, Netflix or eBay or PayPal or Facebook—all of those things, they take time for people to understand this is doable. Then it takes time to implement. Then it takes time for users to say, “Hey, this is useful.” There’s a lot of adaptation, and then there will be regulation. So the whole process takes a long time. I don’t think that businesses will change from one day to the next. It will be a relatively slow process that will take decades. When we look back in 20 years from now, we will see, “Hey, everything changed,” but every year we will see just a little bit of change, like what happened with the Internet. So I imagine that people designing strategies, implementing strategies, they will be very busy in the next 20 years. Ross Dawson: So to round out, I won’t ask you to make predictions, but maybe some hypotheses. What do you think are some interesting hypotheses that will inform your research—not just next year, but in the years beyond? Where do you think are the interesting avenues that we should be not just exploring and researching, but where there is a valid and useful hypothesis? Felipe Csaszar: Yeah, so many things, but one very important—I think that strategy will be more about making the right predictions. The role of foresight. It turns out that when you want to train a machine learning algorithm, you need to have some signal that informs how you train the system. It’s called the gradient, or the objective function. So in strategy, we will need to make that more central, and then think, what are the best ways in which you can use AI to make the right predictions? That requires measuring the quality of predictions. So you change this in the business, and this ends up happening. We want an AI to be able to do that. So coming up with ways in which you can measure the quality of decisions will become more important, so that we can train those AIs. That’s one. And very related to that is, well, the thing that’s generating the predictions are representations, and then it’s coming up with those more complex representations that are better at making decisions or are better at discovering things that are hard for humans to discover. Those are the two main things. I think the future of strategy will be about finding ways of improving foresight and finding ways of improving the thing that creates that foresight, which are the representations. All of that will change what has been called the strategy process—how we make decisions in strategy. Ross Dawson: So I just need to pick up on that point around prediction. One of the challenges with external predictions is that, then, as a strategist, you have to say, either I will build my strategy based on that prediction, or I question that prediction. I think there are alternatives or attribute probabilities to it. So even if a prediction machine gets better, it’s still very challenging, particularly cognitively, in terms of accountability for the strategist to incorporate a prediction where you don’t necessarily have all of the logic behind the prediction as a machine learning model to incorporate. So how can a strategist incorporate what may be a relatively black box prediction into an effective strategy? Felipe Csaszar: Yeah, well, and here we are in the conjecture part of this interview. So my answer is in that spirit. I think there are two ways out of this. One is that we will ask for explainable predictions. There’s a whole area of AI called Explainable AI, which is exactly trying to do this—not just say what’s the best prediction, but why the AI is saying that’s the right prediction. So that could develop, and probably that will develop, because humans will question whatever the AI will predict. That’s one way. The other is, imagine that the AI becomes very, very, very good at making predictions. Then at some point, it doesn’t matter if it can explain it or not—it’s just making very good predictions. It’s like, imagine you want to win at chess and you have this machine that can play chess very well. This machine wins at chess. You don’t need to exactly understand how that machine is making each one of those decisions. But if the machine is very good at it, and it’s consistently good at it, people will use it. In a sense, the market will decide. If this works better than a machine that provides an explanation for each one of the steps, people will just go with the one that’s making the right prediction. Ross Dawson: I think there’s all sorts of other places we can go to from there, but that’s fascinating. So where can people go to find out more about your work? Felipe Csaszar: Well, I upload all of my stuff to SSRN. So if you Google my name and SSRN, you will find all of my papers. In the near future, like in the next three months or so, I’ll have two things coming out. One is a Handbook of AI, written also with my co-editor Nan Jia from USC, that will have 20 chapters that will explore different ways in which AI will be affecting strategies—the Handbook of AI and Strategy, published by Elgar. And then around that same time, there will be a special issue of the Strategy Science journal where I’m one of the co-editors, which will be exactly about the same—about AI and strategic decision making. We already have accepted several of the papers for that special issue. Those papers will be pushing the frontier of what we know about AI and strategic decision making. Ross Dawson: That’s fantastic. I will certainly be following your work—very highly aligned with the humans plus AI movement. And thank you for all of the wonderful research and work you’re doing. Felipe Csaszar: Thank you so much, Ross. It’s been a pleasure. The post Felipe Csaszar on AI in strategy, AI evaluations of startups, improving foresight, and distributed representations of strategy (AC Ep32) appeared first on Humans + AI.

Usually, I feel like a Nincompoop. I am embarrassed. I feel like a failure. I can't do things right. Always. But, it means I try. As an Associate Professor of Strategy and Innovation at Florida State University, I study how firms innovate and learn from failure. I have (co)founded three ventures, one failed, two are doing okay. One is R3ciprocity.com, a platform for researchers to create "non-rejectable papers" through the power of community and AI. R3ciprocity aims to allow researchers to create nearly non-rejectable research papers and grants, and have fun too! Through R3ciprocity, I also engage with a global audience of researchers and practitioners, sharing insights and hope to millions of people on research, innovation, and strategy. I dabbled and failed to publish research in many contexts including editors, prospective entrepreneurs, medical technology, Formula 1 Racing, software development, content creators, and automobile recalls. Occasionally, it has gotten through. He has taught undergraduate, MBA, and doctoral courses on Strategy, Organizational Theory, Research Methods, and Innovation and Entrepreneurship. He is currently on the Editorial Board of Academy of Management Review, Organization Science, Strategic Organization, serves as the Secretary of the Strategy Division in the Academy of Management. He has published in such outlets as Harvard Business Review, Journal of Management, Journal of World Business, Management Science, Organization Science, and Strategic Management Journal. He has a PhD in Strategy from the Ivey School of Business (Western University), and degrees in Chemical Engineering, Management Science, and Sociology from the University of Waterloo. He held non-academic positions in scientific programming and public policy. He (co)founded the Ivey Medical Technology Innovation conference, CSOL, and R3ciprocity. The Carnegie School of Organizational Learning (CSOL) is the preeminent conference on decision-making and learning within and between organizations. Podcast: https://open.spotify.com/show/3886vB9hdqnmHkOZRFlyih?si=554c3eb0b6bd4a39 YouTube: https://youtube.com/c/r3ciprocityTeam Platform: https://www.r3ciprocity.com

This week, Iranian historian and returning guest Navid Zarrinnal calls in to the show from Tehran via telephone amid Iran's continued internet shutdown to elaborate on his recent dispatch for BreakThrough News, "Iran's Protests Explained: A Diary from Tehran." Navid is professor at the Lahore University of Management Sciences in the Islamic Republic of Pakistan, host of The Colony Archive, and working on his first monograph, "Secularisation, Mass Literacy and Education in Modern Iran." Navid gives us a timeline of events and shares his analysis, discussing key differences with previous waves of protest, the evidence and extent of foreign infiltration, the nature of the government's response, and what Iranians think about "regime change". Check out Navid's amazing work on The Colony Archive on YouTube. If you want to support the show and receive access to tons of bonus content, including the new and improved "Last Week in Lebanon" column and video blog by Roqayah and Lebanese war correspondent and our new third cohost Hadi Hoteit, you can subscribe on our Patreon for as little as $5 a month. Also, don't forget to subscribe, rate, and review the show on Apple Podcasts. We can't do this show without your support!!!

Episode: 2548 INFORMS and the mathematics of problem solving.  Today, strange bedfellows.

This week on If/Then we're sharing an episode of GSB at 100, a limited audio series created especially for Stanford Graduate School of Business's Centennial. GSB at 100 presents a scrapbook of memories, ideas, and breakthroughs as Stanford GSB celebrates its first century and looks around the corner to what the next 100 years may hold. On this episode of GSB at 100, you'll experience Centennial Day, hear Dean Sarah A. Soule honor the past, celebrate the present, and look to what the future may hold. GSB at 100 depicts a school defined not only by its innovation and impact, but by its people: curious students, devoted faculty, and accomplished staff — a community of thinkers, dreamers, and doers.Learn more about the Stanford GSB CentennialSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

As usual in the final episode of the year, we hand out three awards for what we think are some of the finest pieces of information systems scholarship produced this year. Except that this time, we are live at the International Conference on Information Systems in Nashville, Tennessee, in a room packed with our listeners. While this means the quality of the audio of our recording is not so great, the quality of the papers we honor this year is. And with a room full of laughter celebrating great information systems scholarship, we end the year on a high note. Congratulations to Stefan, Christoph, and Jan for winning the Trailblazing Research Award, John and Prasanna for winning the Elegant Scholarship Award, and Yanzhen, Huaxia and Andrew for winning the Innovative Method Award 2025. References Lowry, M. R. L., Vance, A., & Vance, M. D. (2025). Inexpert Supervision: Field Evidence on Boards' Oversight of Cybersecurity. Management Science, https://doi.org/10.1287/mnsc.2023.04147. Porra, J., Hirschheim, R., Land, F., & Lyytinen, K. (2025). Seventy Years of Information Systems Development Methodologies from Early Business Computing to the Agile Era: A Two-part History. Part 1: From Pre to Early ISD Methodology Era: The Emergence of ISD Methodologies and Their Golden Era (1880–1980). Journal of Information Technology, 40(4), 441-469. Porra, J., Hirschheim, R., Land, F., & Lyytinen, K. (2025). Seventy Years of Information Systems Development Methodologies from Early Business Computing to the Agile Era: A Two-part History. Part 2: Later ISD to Early Post ISD Methodology Era: Adapting to Accelerated Context Expansion (1980–today). Journal of Information Technology, 40(4), 470-498. Abbasi, A., Somanchi, S., & Kelley, K. (2025). The Critical Challenge of using Large-scale Digital Experiment Platforms for Scientific Discovery. MIS Quarterly, 49(1), 1-28. Storey, V. C., Baskerville, R. L., & Kaul, M. (2025). Reliability in Design Science Research. Information Systems Journal, 35(3), 984-1014. Larsen, K. R., Lukyanenko, R., Mueller, R. M., Storey, V. C., Parsons, J., VanderMeer, D. E., & Hovorka, D. S. (2025). Validity in Design Science. MIS Quarterly, 49(4), 1267-1294. Vance, A., Eargle, D., Kirwan, C. B., Anderson, B. B., & Jenkins, J. L. (2025). The Fog of Warnings: How Non-Security-Related Notifications Diminish the Efficacy of Security Warnings. MIS Quarterly, 49(4), 1357–1384. Baiyere, A., Bauer, J. M., Constantiou, I., & Hardt, D. (2025). Fake News and True News Assessment: The Persuasive Effect of Discursive Evidence in Judging Veracity. MIS Quarterly, 49(3), 823-860. Seidel, S., Frick, C. J., & vom Brocke, J. (2025). Regulating Emerging Technologies: Prospective Sensemaking through Abstraction and Elaboration. MIS Quarterly, 49(1), 179-204. Burton-Jones, A., Boh, W., Oborn, E., & Padmanabhan, B. (2021). Advancing Research Transparency at MIS Quarterly: A Pluralistic Approach. MIS Quarterly, 45(2), iii-xviii. Horton, J. J., & Tambe, P. (2025). The Death of a Technical Skill. Information Systems Research, 36(3), 1799-1820. Chen, Y., Rui, H., & Whinston, A. B. (2025). Conversation Analytics: Can Machines Read Between the Lines in Real-Time Strategic Conversations? Information Systems Research, 36(1), 440-455. Grisold, T., Berente, N., & Seidel, S. (2025). Guardrails for Human-AI Ecologies: A Design Theory for Managing Norm-Based Coordination. MIS Quarterly, 49(4), 1239-1266. Clark, A. (2015). Surfing Uncertainty: Prediction, Action, and the Embodied Mind. Oxford University Press. Recker, J. (2021). Scientific Research in Information Systems: A Beginner's Guide (2nd ed.). Springer. Hirschheim, R., & Klein, H. K. (2012). A Glorious and Not-So-Short History of the Information Systems Field. Journal of the Association for Information Systems, 13(4), 188-235.

IN THIS EPISODE: In this episode, Denise Silber HBS MBA welcomes Professor Daniel Elfenbein,  a triple Harvard alumnus and entrepreneurship researcher at Olin Business School. Together, they explore the delicate balance entrepreneurs must strike between confidence and overconfidence, commitment and detachment, and the hard truth of knowing when to pivot—or when to quit. Dan shares insights drawn from his own entrepreneurial journey, research experiments, and global teaching experience. From biotech boardroom standoffs to mathematical models of founder behavior, he unpacks how emotions, attachment, and overconfidence affect decision-making in startups. You'll learn why "quitting" may just be the smartest pivot of all—and how founders can better calibrate their confidence to avoid costly mistakes. GUEST BIO: Daniel Elfenbein is Professor of Strategy at Washington University in St. Louis's Olin Business School. A triple Harvard alumnus, Dan earned his Ph.D. and M.A. in Business Economics from Harvard, and graduated summa cum laude with an A.B. in Chemistry. Dan is a leading scholar at the intersection of strategy, entrepreneurship, and organizational economics. His research delves into how trust, incentives, and behavioral biases shape outcomes in entrepreneurial ventures and strategic alliances. His work has been published in top-tier journals including the Academy of Management Review, Organization Science, Strategic Management Journal, Management Science, and The Review of Economic Studies. A central theme of Dan's research is understanding the nuanced role of overconfidence in entrepreneurial decision-making. His work—spanning computational modeling, experiments, and economic theory—has provided deep insights into how different forms of overconfidence (including overestimation and overprecision) influence venture formation, pivot strategies, and exit decisions. He has demonstrated that some forms of overconfidence can impede learning and decision-making, while others may be counterbalanced by well-designed experimentation programs. Dan served as Chair of the Strategy and Entrepreneurship Area at Olin from 2020 to 2024, where he championed a culture of scholarly excellence and cross-disciplinary collaboration. He served as Academic Director and then as Associate Dean for Olin's joint Executive MBA Program with Fudan School of Management in Shanghai. Prior to academia, Dan worked as a consultant at Monitor Company—a firm founded by Harvard Business School professors and graduates, including Michael E. Porter, with whom Dan had the great privilege to work. He also served as a staff economist with the President's Council of Economic Advisers in the Clinton Administration. He has held faculty appointments at Berkeley's Haas School of Business and has delivered invited talks at Harvard Business School, MIT Sloan, and London Business School, and more than 30 other universities around the globe.  

Send us a textOn this episode of The Get Ready Money Podcast, I spoke with Miguel Ferreira, creator of the Finance For All program, about why financial literacy is the foundation for making confident, informed decisions—and how it helps reduce stress, increase awareness, and improve long-term outcomes.

Learn how one of the world's biggest restaurant companies is turning data and AI into a recipe for global innovation. Cameron Davies, Chief Data Officer at Yum! Brands, shares how he's combining strategy, technology, and change management to drive gobal growth. He explains how Yum! is building AI literacy from the top down, reimagining operations with generative AI, and partnering with NVIDIA to scale innovation. Cameron reveals what true data leadership looks like, balancing bold ideas with business impact, and proving transformation starts with people, not technology.Key Moments:Start with the Business Problem, Not the Tech (04:27): Cameron recalls advice from a mentor, “start with the business problem down, not the technology up.” He emphasizes that innovation only matters when it solves real business challenges, reminding data leaders not to get enamored with the “cool” factor of technology at the expense of impact.Balancing Global Scale with Local Agility (07:45): Cameron unpacks the challenge of scaling analytics across 160 countries and four major brands, 98% of which are franchise-owned. He explains how Yum! balances centralization and autonomy, ensuring smaller markets have a voice while global teams leverage shared technology and insights.Building AI Literacy from the Top Down (13:44): Cameron describes Yum!'s investment in digital upskilling, from Harvard-led training for executives to hands-on AI workshops for employees. He outlines how the company is embedding AI tools, like Microsoft Copilot and ChatGPT, into daily workflows to build confidence and accelerate adoption.Digitizing the Restaurant: Byte By Yum! (17:18): Cameron introduces Byte By Yum!, a suite of proprietary software that simplifies restaurant operations. He explains how it unifies e-commerce, point-of-sale, voice AI, and kitchen systems to make running a restaurant easier and more efficient in an increasingly complex digital environment.Partnering with NVIDIA to Power the Future (25:12): Cameron shares how Yum!'s strategic partnership with NVIDIA is fueling next-generation restaurant innovation. He reveals how the collaboration gives Yum! early access to cutting-edge AI engineering and product strategy, extending his team's capabilities with some of the best minds in the field.Key Quotes:“Technology's actually a whole lot easier than people, and the more successful the people are, the harder it is to get them to change.” - Cameron DaviesThe business problem is the business problem. You never have as much data as you want, as fast as you want, as cleanly as you want. People are always people, but the opportunities are always the opportunities.” - Cameron Davies“I think sometimes we get so enamored with the technology… We forget it's all in the service of a business problem.” - Cameron DaviesMentionsByte By Yum!Yum! Brands to accelerate AI innovation in an industry-first collaboration with NVIDIA2025 AI & Data Leadership Executive Benchmark SurveyGuest Bio Cameron Davies currently serves as the Chief Data Officer at Yum! Brands since July 2020. Prior to this role, Cameron held the position of Senior Vice President of Corporate Decision Sciences at NBCUniversal, Inc. from September 2013 to July 2020, overseeing the Corporate Management Sciences and NBCU News Group Insights teams, focusing on advanced analytics and data strategies. Cameron's career at Walt Disney Co. spanned from October 1996 to September 2013, where responsibilities included leading the Walt Disney World Resort Forecast and Planning teams and managing global Yield Management. Cameron established and led the Corporate Center of Excellence in Management Science and Integration, collaborating with Disney executives on analytics initiatives. Earlier in the career, from May 1989 to June 1996, Cameron served as a Professor of Finance and Accounting at Pensacola Christian College, teaching various business courses. Cameron holds a Master of Business Administration (MBA) in Marketing Research and Operations Management from the UWF Lewis Bear Jr. College of Business and a Bachelor of Science in Business/Accounting from Pensacola Christian College. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Dr. Corey Pfaffe is a Certified Public Accountant and Principal of MinistryCPA. They advise individuals and organizations as they steward the financial resources entrusted to them. Prior to this organization, Corey served as the Dean of the School of Business at Maranatha Baptist University in Watertown, Wisconsin. He holds a PhD in Management Science. Proverbs 3:9 says: "Honour the Lord with thy substance, and with the first fruits of all thine increase." We do this as we put our check in the church offering regularly, yet is there anything else we should be considering? Yes, there's the tax issue. Jesus said: "Render unto Caesar the things that are Caesar's, and to God the things that are God's." However, we aren't entitled to give Caesar more than he's entitled to. So is there a way we can do that without compromising our integrity while increasing our stewardship? This is where Dr. Pfaffe comes in as he explained a number of stewardship opportunities that he referred to as tax smart strategies. They include: Donor Advised Fund Qualified Charitable Distribution Gifts of Appreciated Stock Charitable IRA Request Required Minimum Distribution Listeners brought their questions to the broadcast as well, so there's a lot to take in and learn from this edition of Crosstalk.

Read the full transcript here. Are stock prices set by cash flows or crowd vibes? Why do bubbles last if “smart money” can short them? What should retail traders learn from GameStop and zero-commission options? When does momentum make sense - and when does it burn you? Why don't obvious mispricings get fixed - what actually stops arbitrage? Will AI help us think clearer, or supercharge manipulation and personalized pricing? Where should regulators draw the line on gamified trading and price discrimination? Do tariffs feel good because they keep others out—even if we pay more? What does the "winner's curse" mean for auctions, IPOs, and everyday deals? How much of what we want is copied from other people, and why does that matter for markets? Alex Imas is the Roger L. and Rachel M. Goetz Professor of Behavioral Science, Economics and Applied AI and a Vasilou Faculty Scholar at the University of Chicago Booth School of Business, where he has taught Negotiations and Behavioral Economics. Alex studies behavioral economics with a focus on cognition and mental representation in dynamic decision-making. His research explores topics related to choice under uncertainty, applied AI, discrimination, and how people learn from information. Professor Imas' work utilizes a variety of methods, including lab experiments, field experiments, analysis of observational data and theoretical modeling. His research has been published in the American Economic Review, Journal of Finance, Proceedings of the National Academy of Sciences, Quarterly Journal of Economics, and Management Science, among others. Links: The Winner's Curse Alex's personal website Alex's Twitter Staff Spencer Greenberg — Host + Director Ryan Kessler — Producer + Technical Lead WeAmplify — Transcriptionists Igor Scaldini — Marketing Consultant Music Broke for Free Josh Woodward Lee Rosevere Quiet Music for Tiny Robots wowamusic zapsplat.com Affiliates Clearer Thinking GuidedTrack Mind Ease Positly UpLift [Read more]

Dr. Corey Pfaffe is a Certified Public Accountant and Principal of MinistryCPA. They advise individuals and organizations as they steward the financial resources entrusted to them. Prior to this organization, Corey served as the Dean of the School of Business at Maranatha Baptist University in Watertown, Wisconsin. He holds a PhD in Management Science. Proverbs 3:9 says: "Honour the Lord with thy substance, and with the first fruits of all thine increase." We do this as we put our check in the church offering regularly, yet is there anything else we should be considering? Yes, there's the tax issue. Jesus said: "Render unto Caesar the things that are Caesar's, and to God the things that are God's." However, we aren't entitled to give Caesar more than he's entitled to. So is there a way we can do that without compromising our integrity while increasing our stewardship? This is where Dr. Pfaffe comes in as he explained a number of stewardship opportunities that he referred to as tax smart strategies. They include: Donor Advised Fund Qualified Charitable Distribution Gifts of Appreciated Stock Charitable IRA Request Required Minimum Distribution Listeners brought their questions to the broadcast as well, so there's a lot to take in and learn from this edition of Crosstalk.

This week on If/Then we're sharing an episode of GSB at 100, a limited audio series created especially for Stanford Graduate School of Business's Centennial. GSB at 100 presents a scrapbook of memories, ideas, and breakthroughs as Stanford GSB celebrates its first century and looks around the corner to what the next 100 years may hold.On this episode of GSB at 100, you'll step inside the classrooms where teaching sparks transformation.Learn more about the Stanford GSB CentennialSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Marian Wentworth, President & CEO, Management Sciences for Health (MSH), at age 13 started working in a local factory. Attended the famous Latin School in Chicago. Studied math at Harvard. Then joined Merck as it was "growing ferociously fast." Stayed 27 years, grew and led the vaccine business to $6 billion. Was the "quant jock." Spearheaded the launch of Gardasil, the HPV vaccine. Then pivoted to MSH. It was important "not having a pharmaceutical company on my business card." Now as she reflects on the stunning year of 2025, a series of radical pivots for MSH, is there space for MSH in the America First Global Health Strategy? Yes. Excited by the Accra Reset? Yes. Where does this leave MSH? "I believe this time is a crucible."

This week on [If/Then or View From The Top] we're sharing an episode of GSB at 100, a limited audio series created especially for Stanford Graduate School of Business's Centennial. GSB at 100 presents a scrapbook of memories, ideas, and breakthroughs as Stanford GSB celebrates its first century and looks around the corner to what the next 100 years may hold.On this episode of GSB at 100, you'll hear from the dedicated and accomplished staff members who work behind the scenes to make Stanford GSB a community unlike anywhere else in the world.Learn more about the Stanford GSB CentennialSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Dorit S. Hochbaum is a distinguished professor in Industrial Engineering and Operations Research (IEOR) at UC Berkeley. Professor Hochbaum holds a Ph.D from the Wharton school of Business at the University of Pennsylvania. Her research interests are in areas of discrete optimization, network flow techniques, data mining, image segmentation, supply chain management and efficient utilization of resources. Her work contributed to the analysis of heuristics and approximation algorithms in the worst case, and on average, to the complexity analysis of algorithms in general, and nonlinear optimization algorithms in particular. Her theoretical work focuses on particularly efficient techniques using network flow for data mining and image segmentation including parametric flow for the convex Markov Random Fields problem establishing it as polynomial; the PseudoFlow algorithm for the maximum flow problem and the parametric flow and cut algorithms. Her recent research is on problems relating to machine learning on recognizing bias in labeled data; reducing dependence in training data; using pairwise relationships to enhance clustering methods. Applications include improved yield prediction in semi-conductor manufacturing; devising balanced covariates for experimental design; the maximum diversity and dispersion problem and group rankings and aggregate decision problems.Professor Hochbaum is the author of over 190 papers that appeared in the Operations Research, Management Science and Theoretical Computer Science literature. She served as department editor for Management Science department of Optimization and Modeling, and on a number of editorial boardsProfessor Hochbaum was named in 2004 as honorary doctorate of Sciences of the University of Copenhagen, for her work on approximation algorithms. She was appointed the Pinhas Naor lecturer of the Technion for 2013, and a Research Excellence professor at the University of Vienna in 2007. She is the winner of the 2011 INFORMS Computing Society prize for her work on algorithms for image segmentation. Professor Hochbaum is a fellow of INFORMS and a fellow of SIAM (Society of Industrial and Applied Mathematics). In 2024, she was awarded the Khachiyan Prize by the INFORMS Optimization Society, recognizing her for her extensive contributions to optimization, including her work on the design and analysis of algorithms and their applications across various domains.

Have you ever felt like you're constantly putting out fires at work instead of making progress? Kevin welcomes Don Kieffer and Nelson Repenning to discuss why so many workplace processes feel frustrating and ineffective, and what leaders can do about it. Drawing on decades of experience in operations and organizational design, Don and Nelson reveal why quick-fix workarounds backfire, how firefighting becomes the default mode of operation, and the hidden costs of constantly reacting instead of leading. They introduce the concept of dynamic work design and explain why breaking down silos isn't just nice to have, it's essential. Along the way, they share practical tools leaders can use to move from chaos to sustainable success. Listen For 00:00 Introduction and the problem with roadblocks at work 03:33 How they met and started collaborating 06:07 The Harley-Davidson connection 08:32 The big idea behind the book 09:41 Why organizations assume the world is predictable 11:03 What dynamic work design means 12:21 The hidden cost of firefighting and workarounds 13:01 The firefighting trap explained 15:33 How firefighting becomes self-reinforcing 17:36 Why the dynamic appears in every organization 19:12 Leadership behaviors that unintentionally worsen it 21:12 Moving beyond blame to system thinking 21:56 The problem with silos in organizations 23:43 How work actually flows across silos 25:12 Visualizing knowledge work to expose inefficiency 26:04 Silos and identity in organizations 27:22 Why we must focus on system productivity 28:36 The matrix problem in modern organizations 29:12 Five elements of dynamic work design 29:48 Problem formation as an underrated leadership skill 30:24 Why framing the problem matters 31:23 Using conscious thinking to solve the right problems 32:36 Asking "what problem are we trying to solve" 33:20 What leaders can learn from this habit 33:48 Don and Nelson's hobbies outside of work 34:38 What they are reading now 35:35 Where to find their book and connect 37:19 Wrap up and invitation to subscribe Their Story: Nelson P. Repenning and Donald C. Kieffer are the authors of There's Got to Be a Better Way: How to Deliver Results and Get Rid of the Stuff That Gets in the Way of Real Work. Nelson is the School of Management Distinguished Professor at the MIT Sloan School of Management. He is currently the director of MIT's Leadership Center and was recently recognized by Poets & Quants as one of the world's top executive MBA instructors. His scholarly work has appeared in Management Science, Organization Science, Administrative Science Quarterly, the Academy of Management Review, Strategic Management Journal, and Research in Organizational Behavior. Donald C. Kieffer is a Senior Lecturer in Operations Management at MIT Sloan. He is a career operations executive and co-creator of Dynamic Work Design. Kieffer started running equipment in factories at age 17. He was VP of operational excellence at Harley-Davidson, where he worked for 15 years. Since 2007, he has been advising leaders in a variety of industries around the globe. His guidance was instrumental in transforming both the production and technical development areas of the Broad Institute, a Cambridge-based genomic sequencing organization, now an industry leader. He is the founder of ShiftGear Work Design, LLC, and teaches Operations Management at AVT in Copenhagen. This Episode is brought to you by... Flexible Leadership is every leader's guide to greater success in a world of increasing complexity and chaos.  Book Recommendations There's Got to Be a Better Way: How to Deliver Results and Get Rid of the Stuff That Gets in the Way of Real Work by Nelson P. Repenning and Donald C. Kieffer  The Mindful Body: Thinking Our Way to Chronic Health by Ellen J. Langer  Murder Mysteries by Lousie Penny Like this? Competing in the New World of Work with Keith Ferrazzi How to Achieve Breakthrough Execution and Accelerate Growth with Patrick Thean Leave a Review If you liked this conversation, we'd be thrilled if you'd let others know by leaving a review on Apple Podcasts. Here's a quick guide for posting a review. Review on Apple: https://remarkablepodcast.com/itunes    Join Our Community If you want to view our live podcast episodes, hear about new releases, or chat with others who enjoy this podcast join one of our communities below. Join the Facebook Group Join the LinkedIn Group   Podcast Better! Sign up with Libsyn and get up to 2 months free! Use promo code: RLP  

This week on If/Then, we're sharing an episode of What's Your Problem?, a show from Pushkin Industries where entrepreneurs, engineers, and scientists talk about the future they're trying to build—and the problems they must solve to get there. Hosted by former Planet Money co-host Jacob Goldstein, each conversation explores the challenges and breakthroughs shaping the next wave of innovation.In this episode, Goldstein speaks with Fei-Fei Li, Stanford computer scientist, former Chief Scientist of AI and Machine Learning at Google, and one of the most influential figures in the field of computer vision. Li reflects on her pioneering work developing ImageNet, the massive dataset that helped spark the modern AI revolution, and the “north star” questions that have guided her research from neuroscience to machine learning.Together, they trace how a single insight about how humans see the world led to a paradigm shift in artificial intelligence—and how Li's vision continues to shape the way we teach machines to see, learn, and collaborate with us.More Resources: • Fei Fei Li • Stanford Institute for Human-Centered Artificial Intelligence (HAI) • ImageNet • What's Your Problem?If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society.Chapters: (00:00:00) Introducing “What's Your Problem?” Kevin Cool introduces the Pushkin Industries podcast hosted by Jacob Goldstein.00:00:45 — What Is Computer Vision? Jacob Goldstein and Fei-Fei Li explain how machines learn to see and interpret images.00:03:18 — Real-World Uses of AI Vision Li shares examples from healthcare, robotics, and environmental science.00:05:06 — Discovering the Science of SeeingHow human vision research inspired Li's lifelong “north star” in AI.00:09:56 — Creating ImageNet Li builds a massive image database that transforms computer vision research.00:13:29 — Defining 30,000 Visual Concepts How cognitive science helped shape ImageNet's massive scale.00:16:41 — Building the Dataset by HandLi's team uses global crowdsourcing to label millions of images.00:19:38 — The 2012 Breakthrough Jeff Hinton's neural network shatters records and sparks the deep learning era.00:22:19 — Data Meets Hardware Li reflects on how big data and GPUs converged to power modern AI.00:24:55 — Lightning Round with Fei-Fei Li Quick insights on resilience, mentorship, and the future of human-AI collaboration.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Earlier this month, the Trump administration announced a stunning $100,000 fee on new H-1B visas—the main channel through which U.S. employers hire foreign professionals in technology, engineering, and research.The move has sent shockwaves through America's innovation ecosystem, prompting fears that companies will either look abroad—or scale back their ambitions at home.Few countries will be as impacted by this change as India, whose citizens account for nearly three-quarters of annual H-1B visa petitions. So, what happens when the world's largest economy makes it harder for global talent to come in?To answer this question, Milan is joined on the show this by Britta Glennon. Britta is an assistant professor of management at the Wharton School of the University of Pennsylvania and a faculty research fellow at the National Bureau of Economic Research. Her research focuses on immigration and cross-border innovation. Much of her work dispels long-held myths about immigrants and how they influence the U.S. economy.Milan and Britta discuss the pluses and minuses of America's “demand-driven” skilled immigration system, the impact on Indians of the Trump administration's massive new fee on H-1B visas, and how the availability of skilled worker visas impact offshoring decisions. Plus, the two discuss how America's competitors are poaching U.S. talent, the complex connection between immigration and innovation, and the economic costs of the green card backlog.To watch this episode, click here.Episode notes:1. Britta Glennon, “Skilled Immigrants, Firms, and the Global Geography of Innovation,” Journal of Economic Perspectives 38, no. 1 (Winter 2024): 3-26.2. Britta Glennon, “How Do Restrictions on High-Skilled Immigration Affect Offshoring? Evidence from the H-1B Program​,” Management Science 70, no. 2 (February 2024): 907-930.3. Saerom (Ronnie) Lee and Britta Glennon, “The Effect of Immigration Policy on Founding Location Choice: Evidence from Canada's Start-up Visa Program,” NBER Working Paper 31634 (August 2023).4. Robert Flynn, Britta Glennon, Raviv Murciano-Goroff, and Jiusi Xiao, “Building a Wall Around Science: The Effect of U.S.-China Tensions on International Scientific Research,” NBER Working Paper 32622 (May 2025).5. Vox, “$100,000 for a visa,” Today, Explained (podcast), September 25, 2025.

On this episode of Deans Counsel, hosts Ken Kring and Jim Ellis speak with Oliver Yao, Dean of the University of Delaware's Lerner College of Business and Economics, a role he took on in August 2023.Oliver Yao's research interests are in the inter-disciplinary fields of information systems and supply chain management, including business value of IT-enabled supply chains, economics of electronic and mobile commerce, bullwhip effect and VMI, CPFR and CRM. His publications have appeared in Management Science, Information Systems Research, MIS Quarterly, Marketing Science, Operations Research, Journal of Operations Management, Production and Operations Management, among others.In an interview that moves almost as quickly as Oliver does, he shares with our hosts his thoughts and experiences regarding:- the overwhelm and challenges he faced early on in his role at Lerner- his approach to setting priorities - especially in the face of financial constraints- how Oliver's background in information systems influences his strategic planning- philanthropy and how he learned to embrace it - quicklyLearn more about Oliver YaoComments/criticism/suggestions/feedback? We'd love to hear it. Drop us a note!Thanks for listening.-Produced by Joel Davis at Analog Digital Arts--DEANS COUNSEL: A podcast for deans and academic leadership.James Ellis | Moderator | Dean of the Marshall School of Business at the University of Southern California (2007-2019)David Ikenberry | Moderator | Dean of the Leeds School of Business at the University of Colorado-Boulder (2011-2016)Ken Kring | Moderator | Co-Managing Director, Global Education Practice and Senior Client Partner at Korn FerryDeansCounsel.com

How do we further blend Shariah principles with ethical and equitable financial solutions to provide positive financial, social, and environmental outcomes? How can the impact of these initiatives be effectively measured? What's on offer from Waqf, Zakat, Sadaqah and Qard Hasan and how can we maximise the potential of new products such as social impact Sukuk? We ask an expert panel.Moderator:Elias Moubarak, Partner, Trowers & HamlinsPanelists:Dr Hamim Syahrum Ahmad Mokhtar, Lead Specialist, Capacity Development, Islamic Financial Services BoardDr Jane Chang, Director, Social Value MalaysiaDr Mohamed Damak, Managing Director and Global Head of Islamic Finance, S&P Global RatingsProfessor Dr Nurdianawati Irwani Abdullah, Department of Finance, Kuliyyah of Economics and Management Sciences, International Islamic University MalaysiaDr Rusni Hassan, Professor and Dean, IIUM Institute of Islamic Banking and Finance

This week on If/Then, we're sharing an episode of GSB at 100, a limited audio series created especially for Stanford Graduate School of Business's Centennial. GSB at 100 presents a scrapbook of memories, ideas, and breakthroughs, as the GSB celebrates its first century and looks around the corner to what the next hundred years may hold.The first episode of the series begins where the GSB begins: in 1925, Herbert Hoover, a Stanford alum and future U.S. president, had an idea. “A graduate School of Business Administration is urgently needed upon the Pacific Coast,” he wrote. One hundred years later, what has Stanford Graduate School of Business accomplished, and what might its future hold? Listen in as professors reflect on founding principles, frontier technologies, and the magic that makes the GSB the place it is — and shapes what it aspires to be.If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society. Each episode features an interview with a Stanford GSB faculty member.Learn more about the Stanford GSB CentennialSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The author of "Sustainable Qatar: Social, Political and Environmental Perspectives" delves into the multifaceted meaning of sustainability, especially within the context of the Arabian Peninsula. Our guest unpacks the region's unique environmental challenges, including sea level rise, extreme weather events, and biodiversity loss, and explores the innovative strategies being implemented to build a more resilient future. An Associate Professor at the College of Public Policy at Hamad bin Khalifa University, Logan Cochrane, also critically examines the concept of "greenwashing," the complexities of global sustainability metrics, and the challenges of policy making.  0:00:00 The Nuance of Sustainability0:03:05 Environmental Challenges in the GCC0:06:08 Time Scale of Environmental Issues0:09:42 Food Security in the Arabian Peninsula0:17:40 Water Sources and Challenges in Qatar0:20:25 Future Challenges and Adaptation in Arid Environments0:22:53 Skepticism Towards Energy Transitions0:24:50 Defining Greenwashing0:31:11 The Politics of Sustainability Metrics0:38:10 Global Leaders in Sustainability0:41:09 The Environmental Impact of Electric Vehicles0:48:10 The "Game of Telephone" in Policy Making0:51:30 Non-Governmental Efforts in Sustainability Logan Cochrane is an Associate Professor at the College of Public Policy at Hamad bin Khalifa University (HBKU). His research includes diverse geographic and disciplinary foci, covering broad thematic areas of food security, climate change, social justice and governance. For the last 15 years, he has worked in non-governmental organizations internationally, including in Afghanistan, Benin, Burundi, the Democratic Republic of the Congo, Egypt, Ethiopia, Qatar, Saudi Arabia, South Africa, South Sudan, Tanzania and Uganda. Logan has served as a director for two non-governmental organizations, and worked as a consultant with clients such as Global Affairs Canada, International Development Research Centre, Save the Children, Management Sciences for Health, the Liaison Office, UNICEF and UNAIDS. Connect with Logan Cochrane

In the latest episode of Making Cents of Money, learn about the habits that can impact your financial decisions and how stress plays a role in spending. Show Notes: American Psychological Association. (2015, February 4). American Psychological Association survey shows money stress weighing on Americans' health nationwide. Retrieved from https://www.apa.org/news/press/releases/2015/02/money-stress American Psychological Association. (2023). Stress in America 2023: A nation recovering from collective trauma. Retrieved from https://www.apa.org/news/press/releases/2023/03/stress-in-america Falconier, M. K., & Epstein, N. B. (2011). Couples experiencing financial strain: What we know and what we can do. Family Relations, 60(3), 303–317. Gelman, A., & Kliger, D. (2021). Effect of time-induced stress on financial decision making in real markets. PloS One, 16(11), e0123740. Heo, W., Cho, S. H., & Lee, P. (2020). APR Financial Stress Scale: Development and validation of a multidimensional measurement. Journal of Financial Therapy, 11(1), 2. https://newprairiepress.org/jft/vol11/iss1/2/ Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer Publishing Company. Narayan, A. (2024). The impact of financial stress on workplace harassment and discrimination. Management Science, 70(4), 2447–2458. Ong, A. D., Sturgeon, J. A., Arewasikporn, A., Okun, M. A., Davis, M. C., & Zautra, A. J. (2015). The psychosocial context of financial stress: Implications for inflammation and psychological health. Psychosomatic Medicine, 77(2), 187–194. Porcelli, A. J., & Delgado, M. R. (2009). Acute stress modulates risk taking in financial decision making. Psychological Science, 20(3), 278–285. Shafir, E., Mullainathan, S., & Shafir, E. (2013). Scarcity: Why having too little means so much. Times Books. Van Boven, L., & Gilovich, T. (2003). To do or to have? That is the question. Journal of Personality and Social Psychology, 85(6), 1193–1202. Wilke, J., & Boden, J. M. (2021). Financial scarcity and financial avoidance: A prospective study. Journal of Economic Psychology, 87, 102408. Mental Health Crisis Resources: Illinois Department of Central Management Services' Crisis Resources: https://cms.illinois.gov/benefits/stateemployee/bewell/mental-health/crisis.html Relevant Podcast Episodes: • Money in Relationships: https://soundcloud.com/idfpr/money-and-relationships • Financial Socialization: https://soundcloud.com/idfpr/episode-99-financial-socialization • Investing: https://soundcloud.com/idfpr/episode-57-investing-to-reach-financial-goals • Budgeting: https://soundcloud.com/idfpr/mcom-ep20-budgeting-final • Probably Inflation: https://soundcloud.com/idfpr/episode-30-inflation

Michael is a recognized corporate leader who built two successful financial technology companies, which collectively report on more than $6 trillion of assets. Michael's previous ventures have helped millions of Americans meet their financial goals and asset protection needs. Michael is a financial thought leader who holds two patents for his innovations in financial technology. Both of these inventions help financial institutions and advisors better understand and manage client portfolios. Michael is a graduate of Stanford University, where he combined his love of finance and technology to earn an undergraduate degree in Economics and a Master's degree in Management Science and Engineering. While at Stanford, Michael helped manage the Charles R. Blyth Fund, a student-run investment portfolio that invests a portion of Stanford University's nearly $37 billion endowment. Michael has deep expertise in alternative investments, including experience as a Partner at Andreessen-Horowitz, a leading Venture Capital firm that manages more than $42 billion, and a General Partner at ACG, a real estate firm responsible for more than $2 billion of developed properties.   Let's Talk Now    In this episode, Karen and Michael discuss: Success Story of Michael  Commit to Get Leads Spend at least 20-25% of your budget on different things to see what works. Consult to Sell Sophisticated portfolios will be tailored to the person while maintaining many sources of diversification. Connect to Build and Grow Check your metrics regularly, every day if you can. Quarterly or even monthly doesn't allow you to pivot when needed in the moment.  Success Thinking, Activities, and Vision Block out the noise and focus on what matters most. Sweet Spot of Success   "This is a phenomenal time to be investing in real estate and take some contrarian positions."- Michael Paulus   Connect with Michael Paulus: Website: https://encoreinvestment.com/   LinkedIn: https://www.linkedin.com/company/pcm-encore/   About the Podcast Join host Karen Briscoe each month to learn how you can achieve success at a higher level by investing just 5 minutes a day! Tune in to hear powerful, inspirational success stories and expert insights from entrepreneurs, business owners, industry leaders, and real estate agents that will transform your business and life. Karen shares a-ha moments that have shaped her career and discusses key concepts from her book Real Estate Success in 5 Minutes a Day: Secrets of a Top Agent Revealed. Here's to your success in business and in life!   Connect with Karen Briscoe: Facebook: 5MinuteSuccess Website: 5MinuteSuccess.com Email: Karen@5MinuteSuccess.com   5 Minute Success Links  Learn more about Karen's book, Real Estate Success in 5 Minutes a Day Karen also recommends Moira Lethbridge's book "Savvy Woman in 5 Minutes a Day" Subscribe to the 5 Minute Success Podcast   Spread the love and share the secrets of 5 Minute Success with your friends and colleagues!   Audio production by Turnkey Podcast Productions. You're the expert. Your podcast will prove it.

This week on If/Then, we're sharing an episode of View From The Top: The Podcast, an audio series featuring leaders from around the world in conversation with MBA students. Recorded live at the CEMEX Auditorium at Stanford Graduate School of Business, episodes feature insights on effective leadership, the values that guide it, and lessons learned along the way.Lisa Su, the chair and CEO of Advanced Micro Devices (AMD), leads one of the world's most influential technology companies, a pioneer in high-performance computing and designer of chips that power everything from cellphones to supercomputers.Su joins Michael Liu, MBA '25, to talk about what it takes to stay on the cutting edge of technology, the tremendous potential of artificial intelligence, and why her superpower may be her commitment to learning.“Careers are very much by chance,” Su says. “The nice thing about my early career is I was lucky enough to have bosses who asked me all the time, ‘What do you want to be when you grow up?' And I was like, ‘I don't know. Let me think about [it]...what I like to believe is the ability to learn at each step was what really helped me in my career.”This conversation was recorded on February 24, 2025. More Resources: • Lisa Su • GSB Insights • View From The Top If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society.Chapters: (00:00:00) Introduction Kevin Cool introduces a summer spotlight on other podcasts, featuring View from the Top.(00:00:59) Meet Lisa Su Michael Liu introduces Lisa Su, AMD CEO, and highlights her career transformation.(00:04:13) Growing Up & MIT Years Lisa reflects on her immigrant upbringing and her journey through three degrees at MIT.(00:05:43) Discovering Semiconductors A part-time lab job at MIT ignites Lisa's passion for chip technology.(00:07:21) From Engineer to Leader Lisa describes her transition from technical work to managing people and projects.(00:11:19) Tackling Hard Problems How curiosity and teamwork help Lisa embrace high-stakes technical challenges.(00:13:40) Betting on Talent Lisa recounts moments when she was given a chance—and how she now pays that forward.(00:17:03) Becoming CEO at AMDWhat brought Lisa to AMD and the unexpected call to lead the company.(00:21:51) Strategy in a TurnaroundHow AMD focused on high-performance computing and long-term bets.(00:25:41) Cultural Shift at AMD Lisa outlines how AMD's culture became collaborative, ambitious, and learning-driven.(00:27:19) AI & Global Tech PoliticsThe complex intersection of AI innovation and geopolitical regulation.(00:32:37) Open vs. Closed AI PlatformsAMD's open-source AI approach with NVIDIA's more vertical model.(00:38:54) Future Vision & Final ReflectionsLisa offers advice to MBAs and shares what she wants her legacy at AMD to be. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

As we celebrate the conclusion of the second season of the If/Then podcast, we present a bonus episode featuring Deborah H. Gruenfeld, the Joseph McDonald Professor and Professor of Organizational Behavior and a Senior Associate Dean for Academic Affairs at Stanford Graduate School of Business. Gruenfeld, who appeared on the first season of If/Then in an award-winning episode about hierarchies and the nature of power, returned to the studio to share her thoughts on the value of academic research and its impact on individuals and organizations. “The nice thing about research is that it provides tools and methods and an approach to learn about what's true in the world, taking into account that what we learn from firsthand experience is not reliable,” she says. “Research helps us build a body of knowledge about what's actually true that we can trust.”This episode was recorded on July 16, 2025.Related Content:Deborah H. Gruenfeld, faculty profileWhy Research MattersWhy I Research: Findings Fueled by the Head and the HeartIf/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society. Each episode features an interview with a Stanford GSB faculty member.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Keren speaks with Tayyab Safdar and Hasan H. Karrar about the China Pakistan Economic Corridor (CPEC), a 3,000 km Chinese infrastructure network project currently under construction in Pakistan and a flagship project of the Belt and Road Initiative. CPEC spans energy, highways, railways, and ports, aiming to connect China's western regions to the Arabian Sea through Pakistan. For China, CPEC offers shorter routes for energy imports and trade; for Pakistan, it offers economic growth, industrialization, and greater regional connectivity. Tayyab Safdar is the Global Security & Justice Track Director; Assistant Professor of Global Studies & Engagements, A&S at the University of Virginia. His research explores the evolving dynamics of South-South Development Cooperation, with the rise of emerging powers in the developing world like China and India. His research also looks at the implications of increasing Chinese investment in developing countries that are a part of the Belt & Road Initiative (BRI), like Pakistan.Hasan H. Karrar is Associate Professor in the Mushtaq Ahmad Gurmani School of Humanities and Social Sciences at the Lahore University of. Management Sciences. He researches transnational connections and geopolitical alignments between China, Central Asia and north Pakistan, as well as development, governance and securitization on state peripheries, and in the deployment and representation of Chinese economic and strategic power.Recommendations:Hasan:Study, think about, and pay attention to what is happening in PakistanVisit Pakistan!Tayyab:Pay attention to the local context (beyond nation-state-oriented views to more community-oriented views) when thinking about big projects like CPECAlso recommends visiting Pakistan Keren:Seeing China's Belt and Road, eds. Edward Schatz, Rachel Silvey (Oxford University Press, 2024)Thanks for listening! Follow us on BlueSky @beltandroadpod.blsk.social

It's not controversial to say that we are living in times of deep division, where there are so many forces keeping us apart, politics being a big part of that.  But did you know that there's a link between how satisfied you think you are with your life, how much you trust others, and how you vote? It's a mind-blowing, less-discussed topic, despite being a chapter in the latest World Happiness Report. Importantly, to make a difference, we wonder this - how do we actually build trust with people who hold different viewpoints, especially if our first impulse is to block them, disregard their comments, or ignore them entirely? We're so glad today to have one of the co-authors of the World Happiness Report here to talk with us about how we can use our understanding of wellbeing and trust to build stronger communities, reconnect with each other, and also bridge the politics of division.    What to listen for: What the World Happiness Report is Despite our focus on class struggle or traditional ideologies as the explanation for why people vote a certain way, it's actually more about life satisfaction and trust.  The wallet study The truth - that unhappy people are attracted by the extremes of the political spectrum. Low-trust people are found more often on the far right, whereas high-trust people are more inclined to vote for the far left. How we can rebuild trust in community, one meal at a time About our guest:  Jan-Emmanuel De Neve is Professor of Economics and Behavioural Science at the University of Oxford, where he also directs the Wellbeing Research Centre. He is best known for his research on the economics of wellbeing which has led to new insights into the relationship between happiness and income, productivity, firm performance, and economic growth. His pioneering research is published in the leading academic journals across multiple disciplines, including Science, Nature, The Review of Economics and Statistics, Psychological Science,world we Management Science, Journal of Political Economy, and the British Medical Journal. His research was recognized among "The Management Ideas That Mattered Most" by Harvard Business Review and he currently guides the world's largest study on workplace wellbeing in partnership with Indeed. De Neve co-authored the main textbook on wellbeing science with Richard Layard, is an editor of the World Happiness Report, and co-founder of the World Wellbeing Movement. Additionally, he serves as a member of the UN Expert Group on Wellbeing Measurement. De Neve frequently consults for governments and major corporations, and his insights on wellbeing and policy are sought by leading global media. Two of his books include Wellbeing: Science and Policy, and Why Workplace Wellbeing Matters.   

Super Mario Bros is 40 years old. It's an incredibly simple game (it takes up the same memory as a smartphone wallpaper), yet it's incredibly popular. Over 40 million people have played it. Why? Because it's packed with psychological tips that hook players in and keep them playing. Today, Ramli John explains the subtle behavioural science tricks Super Mario games use to keep us playing. ---  Ramli's book EUREKA: https://www.delightpath.com/book/eureka Ramli's website: https://www.delightpath.com/ Subscribe to the (free) Nudge Newsletter: https://nudge.ck.page/profile Connect on LinkedIn: https://www.linkedin.com/in/phill-agnew/ Watch Nudge on YouTube: https://www.youtube.com/@nudgepodcast/ Visit the new website: https://www.nudgepodcast.com/ ---  Sources:  Alter, A. L. (2023). Anatomy of a breakthrough: How to get unstuck when it matters most. Simon & Schuster. Allen, E. J., Dechow, P. M., Pope, D. G., & Wu, G. (2017). Reference-dependent preferences: Evidence from marathon runners. Management Science, 63(6), 1657–1672. Fishbach, A. (2022). Get It Done: Surprising lessons from the science of motivation. Little, Brown Spark. Graves, P. (2010). Consumer.ology: The truth about consumers and the psychology of shopping. Nicholas Brealey Publishing. Kivetz, R., Urminsky, O., & Zheng, Y. (2006). The goal‑gradient hypothesis resurrected: Purchase acceleration, illusionary goal progress, and customer retention. Journal of Marketing Research, 43(1), 39–58. Music by Koji Kondo, © 1985 Nintendo

This is just a teaser for today's episode, which is available for Patreon subscribers only!   We can't do the show without your support, so help us keep the lights on over here and access tons of bonus content, including Roqayah's new weekly column “Last Week in Lebanon,” by subscribing on our Patreon for as little as $5 a month. While you're at it, we also love it when you subscribe, rate, and review us on Apple Podcasts.  This week, Roqayah and Kumars are joined by returning guests Sina Rahmani, historian and creator of The East is a Podcast, and Navid Zarrinnal, professor at the Lahore University of Management Sciences and host of The Colony Archive to discuss the latest from the US-Israeli assault on Iran, the effectiveness of Iranian retaliation, the politics of the Iranian diaspora, and the stakes of the Iranian government's survival for a decolonized Middle East. For more of Sina and Navid, check out The Colony Archive and The East is a Podcast on YouTube. 

This week, Roqayah and Kumars are joined by an all-star panel of new and old friends of the show to discuss the growing threat of war against Iran and the challenges of renewed nuclear negotiations as well as the Islamic Republic's commitment to Palestinian liberation and anticolonial solidarity. Assal Rad is an Iranian American historian, a fellow at DAWN and the author of State of Resistance: Politics, Culture and Identity in Modern Iran.  Sina Toossi is an Iranian American policy analyst and fellow at the Center for International Policy.  Sina Rahmani is an Iranian-Canadian historian as well as the creator and host of The East is a Podcast. Navid Zarrinnal is an Iranian historian, assistant professor at the Lahore University of Management Sciences, and host of The Colony Archive on YouTube.  Follow Assal on Twitter @AssalRad, Sina Toossi at @SinaToossi, Sina Rahmani at @UrOrientalist and The Colony Archive @ColonyArchive. If you want to support the show and receive access to tons of bonus content, including Roqayah's new weekly column “Last Week in Lebanon,” you can subscribe on our Patreon for as little as $5 a month. Also, don't forget to subscribe, rate, and review the show on Apple Podcasts. We can't do this show without your support!!!