Week 4b: Questions - How does experience and environment shape innovative activity? #11
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In recent studies, researchers examined the impact of team structures on scientific innovation. Smaller, flatter teams are shown to foster disruptive, novel ideas by exploring deeper and less popular knowledge, while larger, hierarchical teams tend to develop existing ideas, achieving immediate but short-lived impact. As the prevalence of large teams grows, concerns arise about the effects on early-career researchers' opportunities for leadership and creativity. Hierarchical teams may limit junior members' contributions to support roles, hindering their development and reducing the potential for groundbreaking innovation. Question: |
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The third article proposes that remote work merely executes, but on-site collaboration ideates as an explanation for why remote work tends to produce less disruptive research. In the post-pandemic world, corporates are trying reinstate in-person work as the norm once again to improve productivity. However, this paper illustrates that remote work is not necessarily less productive; in fact, remote work "permits more combinations of knowledge in principle", suggesting that certain work like technical processes could be naturally more suited for remote work. Thus, how can the corporate working environment be restructured such that ideation and execution each occur in the most optimal format? Can this be an argument for hybrid work's potential to maximize productivity over purely in-person settings? |
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Based on the article by Rembrand et al. on environment shaping innovative activity - a natural question is how might the underrepresentation of women and other marginalized groups in patenting not only limit innovation in areas relevant to their needs but also reinforce systemic inequalities in healthcare access and outcomes, and what structural changes could simultaneously diversify inventor representation and broaden the scope of invention to address historically neglected issues? However I am also curious if redefining the incentives or criteria for patent funding help ensure a more equitable distribution of inventions that address diverse health concerns? |
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From the reading “Who do we invent for? Patents by women focus more on women’s health, but few women get to invent,” we learn that women are underrepresented in commercial patenting, yet their biomedical inventions are significantly more likely to focus on women's health. This suggests that the gender gap in inventorship contributes to a lack of female-focused innovations and influences who benefit from scientific advancements. While the study highlights that women’s biomedical inventions are more likely than men’s to address women’s needs, I am curious about how products patented by women for women compare to those patented by men in terms of market performance. Does this underscore the importance of having diverse research teams, or are the impacts on product performance relatively minor? |
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The article “Who Do We Invent For? Patents by Women Focus More on Women’s Health, but Few Women Get to Invent” highlights that research teams led by women tend to prioritize innovations in women’s health more than those led by men. However, innovations led by women are less likely to be patented or commercialized. My hypothesis is that women innovators may face fewer funding opportunities, whether through grants or private capital like venture capital. What I’m curious about is whether the lack of funding is due to inherent biases against women innovators or their inventions among investors, or if it’s a result of market demand steering investors toward products that focus on men. And if it’s the former, what can be done to mitigate this bias? If it’s the latter, why do men-focused products seem to have higher market demand, even though women represent a significant portion of the consumer market? |
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Who gets to invent—and who benefits? The gender gap in patenting is more than a labor market disparity; it has profound implications for the kinds of innovations that reach the public. However, with women making up only 13% of U.S. patent inventors, this disparity has resulted in thousands of missing female-focused inventions since 1976, potentially limiting advancements in medical treatments and technologies that cater to women’s unique health needs. |
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In the graphs in the paper "Large teams develop and small teams disrupt science and technology" we observe that small teams consistently rank higher in disruption percentile than large teams, indicating a propensity to generate groundbreaking ideas. Meanwhile, larger teams tend to garner more citations, suggesting a focus on incremental progress or consolidation of existing knowledge. These patterns are apparent across a variety of fields and the disparity widens as team size increases. Given these findings, what underlying mechanisms might explain why smaller teams often produce more disruptive work, even when controlling for factors such as publication year, topic area, and author characteristics? Furthermore, how can institutions leverage these insights to encourage innovative thinking and balance the complementary strengths of both small and large teams in the broader ecosystem of scientific and technological research? |
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The paper by Lin, Frey, and Wu highlights the challenges remote teams face in producing breakthrough innovations. The study shows that while remote teams excel in executing technical tasks, they struggle with conceptual tasks due to reduced knowledge exchange and the lack of spontaneous interactions facilitated by in-person settings. This "remote work penalty" suggests that although remote collaboration can support incremental innovation, it hinders the disruptive discoveries essential for long-term growth. Given these findings, how might hybrid models or remote work approaches be designed to replicate the spontaneity of in-person collaboration? Should organizations prioritize investing in such solutions, or would a return to on-site work deliver greater long-term benefits for innovation? |
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I recently worked at a behavioural economics lab on campus that published a paper while I was there. The authors in the main line were the professors who managed how the paper was written. Only in the acknowledgements were the predocs, who seemed to have done most of the work and came up with many of the ideas in the papers themselves. There was little hierarchy among the authors listed, so Flat teams drive scientific innovation would likely have used this as a data point for a flat team – ironically, directly because the research team was so hierarchical. In the UK, co-authorships for papers are more readily given to junior researchers than in the US. Could we compare the results of this study for US-based papers to international papers to understand differences in research groups’ dynamics between countries, and how this influences quality of research? |
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Thinking about Remote collaboration fuses fewer breakthrough ideas as it relates to investing in startups. This conclusion would then suggest that it would be unwise to invest in remote companies, particularly early stage ones, because the knowledge that will lead to a breakthrough is tacit and difficult to communicate virtually. It seems like traditionally, the argument investors will make about working in-person versus remote is a positive statement more than a normative one, "vibes" or something along those lines. However, does this paper make the argument normative instead of positive? Is it giving more empiricism to a previously non-empirical argument? A few ways teams can be remote: WFH in the same geography, separate geographies entirely. Might be curious to see how the different arrangements might affect disruption, but I'll assume the effects to be minimal. |
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I found the article “Who do we invent for? Patents by women focus more on women’s health, but few women get to invent" to be really thought provoking. It reminded me of something I learned in a data science class about how AI models trained primarily on data from white men can be biased and inaccurate when applied to a broader population. |
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In “Large teams develop and small teams disrupt science and technology.”, the operations of a large vs small group were compared. I found it interesting that many of the primary motivations that larger groups had to operate in this manner were similar to the incumbents that we discussed in previous weeks. They're larger, have more that they have to lose should they fail, and there are many smaller groups trying to make breakthroughs. |
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The Ideal of Science and Technology: Where Are We Going? This Thursday’s readings are all meta-analyses of the innovation industry. To list a few: the first paper demonstrates that aging scientists preferentially cite earlier work, a practice associated with increased novelty but reduced disruption; the second paper shows that larger teams tend to focus on developing existing ideas and thus receive immediate attention, whereas smaller teams, viewing deeply into the past, prone to creation disruptions whose impact would appear in the future; and the fourth paper emphasizes how remote collaboration favors incremental innovation at the expense of disruptive discoveries. An important insight from these meta-analyses is the heterogeneity of innovation. That is, although the innovation industry can ensure its creativity and growth through patent-ing and paper-ing, the acquisition of a patent or the success of a paper can lead to various kinds of innovation. Critically, it is the specific types of innovation that determine the trajectory of innovation. The fifth paper gives a good example: women researchers were more likely to make scientific discoveries that might lead to women's health patents. Due to such heterogeneity and radical possibilities, it is important for us to understand where we want to strive toward before deciding which kinds of innovations we want to support. My question: before devising specific policies, how can we know what kinds of innovation/growth people want? What reasons might urge people to prefer disruptive innovation over incremental innovation, for example? Or if we value diversity/heterogeneity, on what spectrums on we talking about such diversity (race, gender, culture, income, discipline, and more?)? |
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The paper Flat teams drive scientific innovation distinguishes the effects on scientific innovative capacity between teams with more hierarchical structures and those teams which are “flatter” and have less hierarchy by sharing leadership opportunities among a larger percentage of the team. One of the supporting results drawn from the study specifically indicates that “lead authors are more productive in hierarchical teams with a lower L ratio, but support authors experience greater productivity on flatter teams” (Xu, Wu, and Evans 2). My question is, why is it that only leaders experience a productivity boost within highly hierarchical teams? What about the nature of highly hierarchical teams causes lower level members, such as those in more “supporting” roles, to not experience this productivity boost compared to their higher-ups? Why is the situation different for flatter teams? |
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The readings explore how different types of scientific work—whether disruptive or developmental—emerge from team size, collaboration structure, and cognitive biases such as nostalgia. Research shows that small teams tend to be more disruptive, while large teams favor development and refinement. Meanwhile, nostalgia in science may reinforce established paradigms, potentially slowing the adoption of novel approaches. How can institutions balance the benefits of large-scale collaboration (which promotes cumulative knowledge-building) with the need for disruptive breakthroughs? Should funding agencies prioritize small teams for high-risk, high-reward research, or is there a way to structure large collaborations to foster disruptive thinking? |
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The “Large teams develop and small teams disrupt science and technology” paper asserts that small teams disrupt technologies as they tend to focus on novel matters and are more likely to take risks. In addition to that, small teams tend to have more innovative approaches to problem solving as they are less susceptible to “groupthink.” The cruciality of small teams to innovation is evident and almost necessary. The paper also asserts that solo and small teams that are more likely to introduce disruptive technologies tend not be underfunded especially in comparison to larger teams that tend to focus more on developing technologies. From a policy perspective, this raises the question of how can funding agencies reform their funding mechanisms to better support small teams to ensure the prevalence and continuity of disruptive innovations? In addition to that, how can funding agencies better screen amongst smaller teams which ones are more likely to come up with innovative and disruptive technologies? |
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The paper "Large teams develop and small teams disrupt science and technology" we see that larger teams are better suited for developing existing science and technology, while smaller teams are more likely to disrupt by exploring new problems and opportunities. I began to think about this in the context of government size. The United States Government employs approximately 15% of the U.S. workforce according to recent data, what are the implications for innovation in public institutions? Governments, by design, are large and structured to focus on development rather than disruption. However, if a team or institution becomes too large, does it risk stagnation or even regression in innovation? What are the key signs of stagnation or reversal in such cases? Additionally, how can we determine the optimal team size for an institution like the government, which must balance disruptive and developmental forces to achieve long-term progress, particularly in the context of political philosophy and its emphasis on public good? |
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“The Nostalgia Effect in Science” by Cui, et al explores the connections between career age, scientific memory, and innovation. Figures 1 and 2 on pages 4 and 5 illustrate the "Nostalgia Effect" by showing that as scientists age in their careers, they increasingly cite older literature (Fig. 1). This is especially true for fields like math, which progresses more slowly, so older literature is relevant for longer. Also, there is a shift from disruptive to recombinant creativity (Fig. 2). While scientists become better at combining existing ideas in novel ways, their likelihood of publishing a field-changing paper decreases. What sorts of interventions could be used to counteract this sort of attachment to older ideas and sustain disruptive innovation later in a scientist’s career? Interdisciplinary collaboration or increased exposure to emerging research could help scientists with continued innovation throughout their career. |
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These readings centered the question of how team structure creates the environment, or "ecosystem," needed to produce more innovations. Similar to the discussion in Baslandze (2023) of the phenomenon where smaller firms are more likely to innovate than larger firms that deploy new technologies (often after acquiring those smaller firms), Wu et al (2019) find that disruptiveness tends to come from smaller teams, while larger scientific teams then tend to develop ideas. Like in an ecosystem, small and large teams fulfill different but necessary roles. For me, this raises the question of how to evaluate what the best mixture of small/big teams is, and also whether science in the US or globally tends too much towards one size level or the other. This mirrors similar debates in antitrust law about balancing the interests of smaller and larger firms. How can we "ecologically engineer" science to encourage more robust innovation? |
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The Nostalgia Effect text stood out to me, arguing that disruptive creativity declines with academic age. I see how older academics are inclined to cite earlier work because they have greater familiarity with it, but I am not convinced on the argument that intellectual aging is not a biological phenomenon. I see how social structures can justify older scientists continuing to lead hierarchical teams, exerting disproportionate influence, where younger members follow their lead. However, the text mentions that older scientists cite older references because of memory reinforcement loops, suggesting there is cognitive resistance, which could be influenced by biological and cognitive processes. My question is, is memory reinforcement not inherently a biological process? If older academics rely on past knowledge due to cognitive attachment, does this not suggest a neurological basis for intellectual aging? To what extent is intellectual aging a product of social hierarchies versus an inevitable cognitive process? Could interventions like interdisciplinary collaboration, institutional mobility, or alternative leadership structures mitigate intellectual stagnation, or are we constrained by inherent biological tendencies? |
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The paper "Remote collaboration fuses fewer breakthrough ideas" suggests that remote teams struggle with disruptive innovation due to reduced spontaneous interactions, while the "Nostalgia Effect in Science" highlights how established researchers tend to reinforce existing paradigms rather than disrupt them. Given these findings, could the structural effects of remote work exacerbate the tendency of senior researchers to rely on familiar frameworks, thus further limiting disruptive innovation? How might institutions counteract this potential compounding effect—should they design hybrid collaboration models that specifically encourage disruptive thinking among senior researchers, or would a different approach be more effective? |
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Innovation isn’t just about creativity, it’s about economic optimization. If diverse teams generate innovations that tackle historically overlooked issues, is the economy losing out by not funding a broader range of inventors? The study on women’s patenting shows that female researchers are more likely to develop solutions for women’s health suggesting that who gets to invent shapes what gets invented. One concern would be, are market failures emerging because innovations that could serve overlooked communities never receive funding. Would policies like R&D incentives for diverse teams or tax credits for inclusive innovation improve efficiency, or would they distort market forces? If inventors largely come from similar backgrounds, then certain needs might be ignored, not because they aren’t profitable, but because no one with the right perspective is working on them. Then does the current system allocate resources efficiently, or does it reinforce blind spots that hold back progress. |
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“The Nostalgia Effect in Science” uncovers an empirical relationship where scientists cite older literature as they age. This effect contributes to the broader hypothesis that while familiarity with historical ideas aids recombinant innovation, it also creates attachment that prevents disruptive ideas from emerging. Meanwhile, in “Large teams develop and small teams disrupt science and technology,” the paper finds that solo authors and small teams build on older, less popular ideas. This process of “searching deeper” leads to more disruptive findings. It seems, therefore, that the age of papers cited can be correlated with disruption in either direction. Is there truly any causal relationship associated with the age of papers, or is this variable purely a function of other, more important factors? |
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In recent years there have been more and more large research teams with clear hierarchies, especially in projects backed by major funding entities. From this week's readings, Xu (2022) suggests that smaller, flatter teams (those with a higher ‘L ratio’) actually produce more groundbreaking and influential work over the long run. How does this finding challenge the common belief that larger, more hierarchical teams are the primary producers of scientific innovation? What could this mean for organizations like the NIH that tend to favor big, top-down collaborations instead of smaller, more egalitarian ones? |
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The readings for this Thursday highlight a few important characteristics that create innovative teams, for example, small, diverse teams with flat hierarchical structures are most likely to generate disruptive new ideas and particularly if these teams are younger in academic age. One study also emphasizes the importance of collaboration in physical spaces as opposed to virtual meeting rooms. However, many large incumbent firms allow remote work, support tenure-based hierarchies, and lack diverse opinions. Perhaps this model supports the development of existing ideas better than the generation of destructive ideas, but does this suggest that the current separation of firms focused on development and innovation is the most efficient corporate model? Maybe allowing large firms to focus on the development of existing ideas and acquire innovative new companies, effectively outsourcing the R&D process, is most efficient for incumbent firms and adequately compensates young inventors enough to incentivize innovation. Does this system work with efficient access to capital for promising young startups, or is there a clear benefit to implementing organizational structures geared towards innovation in large incumbent firms? |
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Across these readings, we see how team size, structure, demographic makeup, and even physical location can each uniquely shape innovation—small and flat teams drive disruption, large hierarchical teams refine existing ideas, women inventors highlight underrepresented needs, and remote setups excel in execution but sometimes struggle with ideation. How can we craft research environments or institutional policies that synthesize the strengths of different approaches—mixing the bold creativity of smaller teams with the resource power of larger ones, ensuring inclusive inventorship so neglected problems become opportunities, and balancing remote efficiency with the serendipity of in-person collaboration? Ultimately, is there an optimal “recipe” for fostering breakthroughs, or must we continually adapt our organizational structures, funding practices, and collaborative norms to reflect the changing landscape of knowledge production and societal priorities? |
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These readings collectively examine the structural and environmental factors that shape scientific and technological innovation. "Who Do We Invent For? Patents by Women Focus More on Women’s Health, But Few Women Get to Invent" highlights how the demographics of inventors influence what gets invented, particularly in the realm of biomedical patents. The study shows that women are significantly more likely to produce patents related to women’s health, yet they remain deeply underrepresented in the innovation space, resulting in a lack of biomedical advancements tailored to female patients. Meanwhile, "Remote Collaboration Fuses Fewer Breakthrough Ideas" explores how remote collaboration, while broadening networks, tends to generate fewer disruptive ideas compared to in-person research. The study suggests that remote teams focus more on technical execution rather than groundbreaking conceptual work, which may slow the pace of transformative innovation. In addition to team location, team structure plays a critical role in innovation outcomes. "Flat Teams Drive Scientific Innovation" finds that research teams with flatter hierarchies—where junior researchers have more leadership opportunities—are more likely to produce novel and disruptive ideas. By contrast, hierarchical teams, while efficient at refining established concepts, tend to discourage risk-taking and originality. Similarly, "Large Teams Develop and Small Teams Disrupt Science and Technology" distinguishes between the functions of large and small teams, showing that while large teams are better at building on existing knowledge, small teams are critical for producing radical breakthroughs. Given these findings, how can institutions balance the trade-offs between inclusivity, collaboration structures, and team size to maximize disruptive innovation? Would policies aimed at increasing diversity in patenting (such as grants for female inventors) yield better results if paired with initiatives that promote flat team structures or encourage in-person collaboration? Furthermore, as remote work continues to rise, how can research institutions ensure that geographic dispersion does not stifle the next generation of scientific breakthroughs? |
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Today, the widespread adoption of remote workflows and digital collaboration technologies has enabled more new firms to emerge, as operating without a physical workspace significantly reduces costs. However, in the article "Remote Collaboration Fuses Fewer Breakthrough Ideas," the authors highlight that face-to-face interaction is crucial for brainstorming, refining vague ideas, and integrating diverse expertise. While remote work is well-suited for late-stage, technical execution, it is less effective for conceptual development and early-stage innovation. Given this, would incumbent firms—which already have established systems, structured workflows, and clearly defined goals—be better positioned for remote work compared to newer firms, which are still in the process of developing ideas and refining their business models? What are the trade-offs between having a remote team that saves costs and offers flexibility versus the challenges of innovation and conceptual development in a remote environment, particularly for new entry firms? |
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“Who do we invent for?” examines the gender gap in patenting activity within the context of biomedical research, finding that “a lack of representation among inventors translates into a lack of breadth in inventions.” How can we craft effective policy solutions to increase the likelihood that underrepresented people can become inventors? Would a policy analogous to affirmative action — which seeks to level the educational playing field by actively correcting for systemic inequalities — be effective in the context of broadening inventor demographics? |
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