Events

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How novel ideas are adopted and recognized is crucial to scientific progress, but not all ideas from all groups are equally recognized. This paper studies whether and how increasing gender diversity at universities may lead to greater inclusion and recognition of research traditionally associated with women. Leveraging the transitions to coeducation of 76 all-male universities and novel text-based measures of research content, we show that coeducation led to overall modest shifts toward female-associated research. This aggregate effect masks substantial heterogeneity across fields: in disciplines with higher early female representation, we observe a pronounced increase in female-associated research driven by both existing faculty and new entrants. Male-dominated fields, by contrast, exhibit little change or even declines in female-associated research, primarily due to changes in hiring practices. These findings highlight that while diversity can foster innovation, its effects may only be concentrated in areas already receptive to the new perspectives. (joint work with Drew Hendrickson and Ashley Wong)

Contact person:  Marina Chugunova

Subscription to the invitation mailing list and more information on theseminar page.

On 15/16 December 2025, the Max Planck Institute for Innovation and Competition will host the 8^th Research on Innovation, Science and Entrepreneurship Workshop (RISE8), an annual workshop for Ph.D. students and Junior Postdocs in Economics and Management. 

The goal of the RISE8 Workshop is to stimulate an in-depth discussion of a select number of empirical research papers. It offers Ph.D. students and Junior Postdocs an opportunity to present their work and to receive feedback.

Keynote speaker of the RISE8 Workshop is Matt Marx (Cornell University)

Program RISE8 2025

For more information see RISE Workshop.

How does big data change the search for innovation? Data-driven predictions can identify promising opportunities even when their underlying mechanisms are not understood. This has raised concerns that decoupling innovation from theoretical understanding weakens incentives to develop new theory and yields findings whose consequences are poorly understood. In this paper, I argue that big data can instead catalyze the generation of new theory. Data-driven search broadens the space of combinations explored and increases the variability in outcomes relative to the filtering provided by existing theory. As a result, this search strategy uncovers more empirical anomalies that stimulate, rather than substitute, new theorizing. I test these ideas in the domain of human genetics, where genome-wide association studies (GWAS) operate as a data-driven search for the genetic roots of disease. Compared with traditional theory-based approaches, GWAS introduce gene–disease combinations that span a wider portion of the genetic landscape, more frequently fall at both extremes of scientific quality, and often defy expectations drawn from prior knowledge. Rather than crowding out theory generation, GWAS findings are followed by a surge of research aimed at clarifying their causal mechanisms. Together, the results reveal a complementarity between theory and data in search, suggesting that big data can fuel virtuous cycles of theorizing by accelerating the identification of anomalies.

Contact person: Daehyun Kim

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Most innovation occurs inside firms, yet little is known about the organizational forces that shape it. We provide new evidence on how private information affects within-firm innovation using unique data from a global manufacturing firm tracking more than 200,000 workers’ ideas from invention to commercialization. Workers face incentives to inflate idea quantity at year-end to improve evaluations and pay, but these incentives generate substantially lower-quality ideas, consistent with moral hazard. Using quasi-random rotations in direct supervisors, we show that managers with invention experience increase both the quantity and quality of their new teams’ innovative output, indicating that such managers help firms screen ideas when workers hold private information. Complementary evidence from a survey of 1,659 firms suggests these patterns are widespread: firms with greater information asymmetry report more moral hazard and rely more heavily on managers for screening. Together, the results highlight private information as a key constraint on incentives for innovation.

Contact person:  Marina Chugunova

Subscription to the invitation mailing list and more information on theseminar page.

Dr. Georg Werner (Presiding Judge at Munich Regional Court I) and Prof. Dr. Peter Picht, LL.M. (Yale) (University of Zurich)

Herzog-Max-Str. 4, 80333 Munich

Joint event organized by the Max Planck Institute for Innovation and Competition and the Association of Friends and Former Employees of the Max Planck Institute for Innovation and Competition e.V.

Registration: alumni@ip.mpg.de

This paper studies the teaching of frontier knowledge in higher education and its impact on students. Using text analysis on 2 million course syllabi and 20 million academic articles, we develop a measure called “frontier knowledge proximity,” capturing how closely course content aligns with current scholarly research. We document significant variation in frontier knowledge proximity across courses, even within the same institution, and demonstrate that these differences substantially affect student outcomes. Linking syllabi to individual student records from Texas and leveraging unexpected syllabus updates, we show that increases in proximity improves both educational outcomes (graduation, major retention, and graduate school enrollment) and earnings. Educational gains are notably larger among median-ability and lowerincome students, whereas earnings benefits disproportionately accrue to higher-ability and higherincome students. These findings indicate that frontier knowledge exposure can narrow socioeconomic disparities in education but remains complementary to students’ existing resources. We conclude by showing that instructors, particularly research-active faculty, are the main drivers of differences in frontier knowledge proximity.

Contact person: Anastasiia Lutsenko

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The EU’s regulatory framework for data has expanded into a dense architecture of related pieces of legislation. Legislative instruments such as the General Data Protection Regulation (GDPR), the Digital Markets Act (DMA), the Data Act, and the Data Governance Act (DGA) seek to balance privacy, innovation, competition, and the free flow of data within the Digital Single Market. Yet their overlapping scopes and differing rationales raise the question of whether the EU has created a meaningful regime to regulate data or a legislative labyrinth that creates complicated challenges for compliance and enforcement.

This lecture explores the evolving logic of EU data governance —its normative foundations, institutional dynamics, and practical tensions. By examining how these instruments converge and conflict, it invites reflection on whether the EU’s data regime represents fragmentation or a carefully constructed mosaic of complementary rules.

We examine how repeated exposure influences the preference for highly novel ideas. We argue that the mere exposure effect fails to extend to such ideas. Instead, repeated exposure reduces preference by triggering a construal level misfit: evaluators seek concrete details, yet novel ideas offer primarily abstract information. This mismatch magnifies evaluators’ sense of unfamiliarity with each exposure. In a field study, we show that the usual mere-exposure-to-liking pathway reverses for highly novel ideas. In a subsequent quasi-experiment, we demonstrate that familiarity mediates this reversal: rather than growing more familiar with highly novel ideas, evaluators grow less familiar, which reduces their preference. These findings identify a critical boundary condition of the mere exposure effect precisely where innovation needs it most: highly novel ideas.

Contact person: Michael Rose

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How does a domain-spanning innovation achieve high impact and fulfill its transformative potential? To address this, recent research has wisely moved beyond studying the level of impact to examining the disruptive nature of impact: the degree to which an innovation departs from foundational work and undermines the status quo. This research reveals that the drivers of the two dimensions of impact are distinct, at least on the producer side. But fully addressing this question requires us to consider the audience side as well. We contend that how domain-spanning affects the level and disruptiveness of impact is contingent upon one feature of audiences: the degree to which they are partitioned into disconnected subsets. To test this, we focus on the realm of science and its prototypical form of domain-spanning: interdisciplinary research. Using data on thousands of scientists and over half a million scientific papers from the Web of Science, we find that spanning disciplines enhances both dimensions of impact. Importantly, when interdisciplinary research reaches a partitioned audience, the level of the research impact is stifled, but the disruptiveness is enhanced. We discuss how and why a more partitioned audience allows the ground-breaking potential of domain-spanning innovation to be realized.

Contact person: Marina Chugunova

Subscription to the invitation mailing list and more information on the seminar page.