Misiek Piskorski

𝗔𝗱𝘃𝗮𝗻𝗰𝗶𝗻𝗴 𝗕𝗶𝗴 𝗜𝗱𝗲𝗮𝘀 𝘁𝗼 𝗘𝗹𝗲𝘃𝗮𝘁𝗲 𝗝𝗠’𝘀 𝗚𝗹𝗼𝗯𝗮𝗹 𝗦𝘁𝗮𝘁𝘂𝗿𝗲 𝗮𝗻𝗱 𝗜𝗺𝗽𝗮𝗰𝘁 In their first editorial, Jan-Benedict Steenkamp, Marc Fischer, Kelly Haws, Maura L. Scott, and Rebecca Slotegraaf outline their vision to shape JM’s future and expand its impact across academic, business, and societal domains. 𝗔𝗱𝘃𝗮𝗻𝗰𝗶𝗻𝗴 𝗕𝗶𝗴 𝗜𝗱𝗲𝗮𝘀 Paradigm-shifting knowledge that:  • stretches what we know and changes how we understand the world • opens new fields of inquiry • generates bold frameworks, many new questions and methods • endures over time  • appeals to a broad base of stakeholders  • provides new insights that change behavior 𝗧𝗵𝗿𝗲𝗲 𝗦𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗜𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀 (𝗮𝘀𝘀𝗼𝗰𝗶𝗮𝘁𝗲𝗱 𝘄𝗶𝘁𝗵 𝘁𝗵𝗿𝗲𝗲 𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗜𝘀𝘀𝘂𝗲𝘀) 𝟭) 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗶𝗻𝗴 𝗢𝗿𝗴𝗮𝗻𝗶𝗰 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗧𝗵𝗲𝗼𝗿𝗶𝗲𝘀 Research that develops marketing theory that is rooted in marketing phenomena and is not just borrowed from other fields 🔗Call for Papers: https://lnkd.in/gfm6JV9q 𝟮) 𝗦𝗽𝗲𝗮𝗸𝗶𝗻𝗴 𝘁𝗼 𝗮𝗻𝗱 𝗕𝗮𝗹𝗮𝗻𝗰𝗶𝗻𝗴 𝗠𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿𝘀 𝘁𝗼 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 𝗦𝗼𝗰𝗶𝗲𝘁𝘆'𝘀 𝗕𝗶𝗴 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀  Research that identifies and addresses tensions among stakeholders and studies their implications for consumers, companies, public policy, and society at large 🔗Call for Papers: https://lnkd.in/gTbJHse4 𝟯) 𝗧𝗮𝗸𝗶𝗻𝗴 𝗮𝗻 𝗘𝗺𝗽𝗶𝗿𝗶𝗰𝘀-𝗙𝗶𝗿𝘀𝘁 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝘁𝗼 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗖𝗿𝗲𝗮𝘁𝗶𝗼𝗻. Research that derives insights from real-world phenomena and observations, especially when theory is underdeveloped or conflicting 🔗Call for Papers: https://lnkd.in/dD_Jd-cd In sum, the editorial team’s vision is “to further cement and elevate the stature of the Journal of Marketing as the flagship journal in our discipline through Big Ideas and Robust and Rigorous Empirical Investigation.” #Marketing #Research #Science #MarketingResearch #Impact Marketing Scholars: Call for Papers, Research News and more

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Excited to share our new paper in Organization Science: "Designing Institutions for Applied Impact: Lessons from Engineering for Organizational Research" Huge thanks to Stephen Zhang and the editorial team for inviting us to contribute to this Crossroads collection on making organizational research more applied and impactful. It's been a privilege to be part of this important conversation alongside stellar colleagues. Grateful to Dr. Liz Gerber for being an amazing co-author on this journey—your interdisciplinary perspective spanning mechanical engineering, HCI, and organizational studies made this work possible. Yesterday, it was a pleasure to join Liz in person for a conversation about this piece in the Work, Technology and Organizations group alongside Bob Sutton and Pamela Hinds. Really great conversation about these important issues and how research is evolving, our moral obligations when doing field work, and how increasing scrutiny on the public value of research universities and the emerging use of AI is affecting all of this. Our core argument: The gap between research and practice isn't just about individual motivation—it's about institutional design. While organizational research privileges theoretical novelty, engineering fields have built structures that legitimize validated, usable contributions. We can learn from them. We identify three structural levers for change: Cognitive: Broaden what counts as knowledge to include validated solutions Normative: Value reproducibility and utility alongside theoretical elegance Regulative: Support diverse formats (implementation briefs, design notes, replication studies) The path forward isn't about lowering standards—it's about recognizing different forms of rigor and making applied work both feasible and legitimate. I encourage you to read the entire Crossroads collection—Zhang and Ertug's framing piece along with contributions from Croson and Croson, Berry, and Yoeli and Rand. Together, they offer a comprehensive vision for organizational research as an applied science. Special thanks to Daniel Armanios, Maria Yang, Warren Seering, and Kathleen Eisenhardt for invaluable feedback along the way, for inspiring us with your own work that it's possible to have both intellectual rigor and applied relevance, and to the editorial team for shepherding this project. Link: https://lnkd.in/gr7uDAsV Looking forward to the conversation about how we can redesign our institutions to serve both scholarly rigor and societal impact. #OrganizationalResearch #AcademicPublishing #AppliedScience

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What drives AI adoption? ➡️ “Feelings,” is the quick answer. In our recent research, that Moritz Remund, Florence Bernays, PhD, and I presented at the Academy of Management Conference, we found that people’s emotional preferences -- how they want to feel during and after their work -- play a major role in whether they choose to use AI. 💡 If someone enjoys a task and wants to feel engaged or creative 𝘸𝘩𝘪𝘭𝘦 doing it, they tend to avoid using AI. If they care more about feeling proud or relieved 𝘢𝘧𝘵𝘦𝘳 the work is done, they’re more likely to use AI -- especially for tasks they don’t enjoy much. 💡 These patterns suggest that AI adoption isn't just about efficiency or output. It's also about how we want our work to feel. 📝 Organizations hoping to integrate AI effectively need to pay closer attention to the emotional side of work -- not just the technical one. Thanks to our fellow presenters in the session: Jeewon Gwak & Ashley Fulmer – Georgia State University Dejun "Tony" Kong – University of Colorado Boulder Liz Hood – University of Southern California Bess Rouse – Boston College Sandor Talas, Andre Pekerti, Neal M. Ashkanasy, Alexandra Kriz – The University of Queensland Mithira Siva, Mayank Varshney, Balagopal Gopalakrishnan – Indian Institute of Management Ahmedabad #AIAdoption #FutureOfWork #WorkplacePsychology #EmotionsAtWork #OrganizationalBehavior #GenerativeAI #HumanTechnologyInteraction #HRValley #LeadTheFuture UZH Center for Leadership in the Future of Work

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🏫 One of the peculiar insights of the Discounted Cash Flow approach* is that your skills are your most valuable asset and that education is the best investment. Or as the 19th century German philosopher Max Stirner put it, "Was du vermagst, ist dein Vermögen." 🎓 Think of education as an investment: Tuition, time, and lost income (opportunity cost) must be weighted against future benefits such as higher income, better job opportunities, lower unemployment risk, and greater mobility. 💸 The beautiful part about education is that the time horizon for payback is decades, many skills (like long-lived assets) retain value forever, and education creates career optionality which is like holding a valuable option. ➕ Plus, for sure, there can be numerous non-monetary benefits to education as well. * Discounted Cash Flow (DCF) is a valuation method that estimates the present value of future cash flows by discounting them. Picture from OpenAI

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🚀 The August issue of the Credible Management Research Newsletter is out! AOM is over, teaching has not started yet, the right time for some credibility! This month’s edition is mine—co-curated with Fabiola H. Gerpott and Jost Sieweke. Each month, new insights about #credibility in #science from the three of us. Teaser highlights • 🤖🧪 LLMs as “participants”? Tempting for speed and cost—but prompt sensitivity is real. Openness (share prompts, model specs, materials) is non-negotiable. Featuring work by Sarah Schröder and colleagues. • 📈🔋 Do we have enough power? Evidence from adjacent fields says “mostly not.” A fix: fewer, bigger, multi-lab studies across countries. Shout-out to Vincent Arel-Bundock and colleagues. • 🎧🍻 What to hear: Paul Bloom interviews Yoel Inbar—candid, funny, and brutally honest about theories and findings they no longer trust (and Sydney Sweeney) • 📝🔍 RR Watch: Thomas Rhys Evans et al. (unethical behavior at work), Lewend Mayiwar et al. (status → overconfidence), Michael P. Grosz et al. (narcissism & status). If you care about credible, transparent research, 🔔 subscribe & share so more colleagues run high-power, open studies that can make causal inferences. 👇 Thoughts on “synthetic” LLM participants, statistical power, or credibility events, news, or thoughts in general? Drop them in the comments. 💬 #OpenScience #ManagementResearch #Replication #RegisteredReports #AI #LLM #Metascience Bonus-Content: Pictures of us doing weird gestures at Academy of Management Conference in Copenhagen during the Credibility PDW

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✨ Research Update ✨ Joint work with Thomas Reutterer and Martin Reisenbichler on applying #genAI to search advertising has been accepted at INFORMS Marketing Science. While #llms will continue to improve, in "Applying Large Language Models to Sponsored Search Advertising," we show that: 1️⃣ Bigger doesn't mean better: A bespoke model based on GPT-2 outperforms approaches using state of the art models. As environmental concerns still loom, application-specific models may offer the desired performance with less environmental impact 🌲 2️⃣ AI-generated ads can help stretch the advertising budget 💸 AI-generated ads run on a tighter budget perform nearly as well as human-generated ads on a larger budget 3️⃣ Budget, competition, and web content quality all mitigate the gains associated with using AI-generated ads Many thanks to Olivier Toubia, the AE and reviewers for pushing us to focus on the key takeaways that will likely stand up even as AI models improve.

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