The Effects of Diversity and Network Ties on Innovations: The Emergence of a New Scientific Field (original) (raw)
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Being a Catalyst of Innovation: the role of knowledge diversity and network closure
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Whereas recent research on organizational innovation suggests that there is an ecology of roles supporting the innovative process, the majority of network research has concentrated on the role of inventors. In this paper, we contribute to research on organizational innovation by studying the social structural conditions conducive to individuals supporting, facilitating and promoting the innovativeness of their colleagues – a role we refer to as catalysts of innovation. We consider an individual’s network position and the type of knowledge available to them through their network as key enabling conditions. We argue that the unique configuration of having access to diverse knowledge through a closed network enables individuals to act as innovation catalysts. Based on a study of 276 researchers in the R&D division of a large multinational high-tech company we find strong support for our prediction and demonstrate that catalysts make important contributions to the innovative outputs of other researchers in terms of their colleagues’ patent applications.
INNOVATIONS ARE DISPROPORTIONATELY LIKELY IN THE PERIPHERY OF A SCIENTIFIC NETWORK
Theory in BioSciences
The origins of innovation in science are typically understood using historical narratives that tend to be focused on small sets of influential authors, an approach that is rigorous but limited in scope. Here, we develop a framework for rigorously identifying innovation across an entire scientific field through automated analysis of a corpus of over 6000 documents that includes every paper published in the field of evolutionary medicine. This comprehensive approach allows us to explore statistical properties of innovation, asking where innovative ideas tend to originate within a field's pre-existing conceptual framework. First, we develop a measure of innovation based on novelty and persistence, quantifying the collective acceptance of novel language and ideas. Second, we study the field's conceptual landscape through a bibliographic coupling network. We find that innovations are disproportionately more likely in the periphery of the bibliographic coupling network, suggesting that the relative freedom allowed by remaining unconnected with well-established lines of research could be beneficial to creating novel and lasting change. In this way, the emergence of collective computation in scientific disciplines may have robustness-adaptability tradeoffs that are similar to those found in other biosocial complex systems.
Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l'Administration, 2012
We examined the role of network position and knowledge diversity as related to new knowledge creation within a network of 239 academics from business administration departments at four universities. Analyses of their 1,827 publications involving 1,541 coauthors between 1986 and 2008 revealed an inverse U-shaped relationship between network centrality and knowledge creation. Moreover, knowledge diversity positively moderated the association between centrality and the quality of the knowledge created, but negatively moderated the centrality-knowledge quantity relationship.
Making gender diversity work for scientific discovery and innovation
Nature Human Behaviour, 2018
ender diversity is increasingly the norm in scientific work. Women and men already share laboratories, research facilities and work spaces in most disciplines, and universities and science policymakers see gender diversity as a key driver of excellence and innovation 1-6. Yet, gender diversity comes with both challenges and opportunities. Careful management is required to maximize the benefits of diversity for scientific discovery. This Perspective distinguishes three approaches to gender diversity: diversity in research teams, diversity in research methods and diversity in research questions (Fig. 1). Gender diversity is commonly understood to refer to the gender composition of research teams. However, fully realizing the potential of diversity for science and innovation also requires attention to diversity in research methods and in research questions. Importantly, gender diversity functions within larger research contexts. In the second half of this paper, we provide a framework to understand how the three approaches to gender diversity function across four interdependent domains: research teams, disciplines, research organizations and societies at large (Fig. 2). In each of the four domains, we evaluate potential drivers and barriers to gender diversity. Understanding the interplay between our three approaches to diversity and how they function within institutional frameworks will assist universities, funding agencies, industries and governments to harness the power of diversity for discovery and innovation. This Perspective integrates insights from multiple disciplines, including social psychology, management and social studies of science and innovation (search methods are specified in the Supplementary Notes and Supplementary Tables 1 and 2). Many organizations understand the importance of increasing women's participation in science and technology, and, increasingly, funding agencies are emphasizing the value of bringing diverse methods, such as integrating sex and gender analysis, into research design. Crucially important also is being attuned to the novel research questions newcomers to traditional disciplines might bring. This attention to diversity goes well beyond the dynamics of the research team itself and needs to be fostered by disciplines, research organizations and societies at large. Three approaches to gender diversity In this section, we distinguish three approaches to gender diversity: diversity in research teams, diversity in research methods and diversity in research questions. Diversity in research teams. The best-understood approach to gender diversity concerns the composition of research teams. Diversity refers here to the different ideas, beliefs and perspectives that women, men and gender-diverse people bring to the team. The possible benefits of gender diversity are linked to cognitive diversity, conceptualized here as the different ways in which "people represent problems and go about solving them in team work" 7. Research suggests that cognitive diversity can heighten creativity and encourage the search for novel solutions 8,9. Experiments indicate that teams comprised of diverse problem-solvers can outperform teams that prioritize best-performing individuals 7. Gender-diverse teams may, however, encounter higher levels of conflict than more homogeneous teams 10. Careful team management is therefore imperative to reap the possible benefits of diversity (we return to this in the discussion of the four interdependent domains for scientific discovery and innovation). The impact of gender diversity on team performance has been analysed extensively in laboratory studies and in corporate and public organizations, but not in science 11-13. The few existing studies focusing on gender diversity in scientific teams typically evaluate research outcomes based on citation rates, publication productivity and patents. Surveying research from 2006 to 2015, we found eleven studies on team performance in research and innovation. Six studies examined research in for-profit research and development (R&D) firms 14-19 (Table 1), and, of these, five found possible benefits of team gender diversity for innovation and technological performance (measured by patents). Five of the original eleven studies focused on academic science 20-24 , and two of these found possible benefits of gender diversity-one with respect to citation impact; another with respect to publication productivity. The remaining studies showed no notable effects of gender diversity. Yet, gender diversity in teams may influence research outcomes in important ways not captured using traditional, bibliometric
Diversity, networks, and innovation: A text analytic approach to measuring expertise diversity
Cambridge University Press, 2022
Despite the importance of diverse expertise in helping solve difficult interdisciplinary problems, measuring it is challenging and often relies on proxy measures and presumptive correlates of actual knowledge and experience. To address this challenge, we propose a text-based measure that uses researcher's prior work to estimate their substantive expertise. These expertise estimates are then used to measure team-level expertise diversity by determining similarity or dissimilarity in members' prior knowledge and skills. Using this measure on 2.8 million team invented patents granted by the US Patent Office, we show evidence of trends in expertise diversity over time and across team sizes, as well as its relationship with the quality and impact of a team's innovation output.
Diversity Breeds Innovation With Discounted Impact and Recognition
2019
Prior work poses a diversity paradox for science. Diversity breeds scientific innovation, and yet, diverse individuals have less successful scientific careers. But if diversity is good for innovation, why is science not rewarding diversity? We answer this question by utilizing a near-population of ~1.03 million US doctoral recipients from 1980-2015 and their careers into publishing and faculty roles. The article uses text analysis and machine learning techniques to answer a series of questions: How can we detect scientific innovation? Does diversity breed innovation? And are the innovations of diverse individuals adopted and rewarded? Our analyses show that underrepresented groups produce higher rates of scientific novelty. However, their novel contributions are discounted: e.g., innovations by gender minorities are taken up by other scholars at lower rates than innovations by gender majorities, and innovations by gender and racial minorities result in fewer academic positions. This suggests an unfair system in which diverse individuals innovate, but their innovations are disproportionately ignored and fail to convert into career success at the same rate as majority groups. In sum, there may be an unwarranted reproduction of stratification in academic careers that discounts diversity's role in innovation and partly explains the underrepresentation of some groups in academia.
Scientometrics
Understanding the nature and value of scientific collaboration is essential for sound management and proactive research policies. One component of collaboration is the composition and diversity of contributing authors. This study explores how ethnic diversity in scientific collaboration affects scientific impact, by presenting a conceptual model to connect ethnic diversity, based on author names, with scientific impact, assuming novelty and audience diversity as mediators. The model also controls for affiliated country diversity and affiliated country size. Using path modeling, we apply the model to the Web of Science subject categories Nanoscience & Nanotechnology, Ecology and Information Science & Library. For all three subject categories, and regardless of if control variables are considered or not, we find a weak positive relationship between ethnic diversity and scientific impact. The relationship is weaker, however, when control variables are included. For all three fields, th...
The Diversity-Innovation Paradox in Science
arXiv (Cornell University), 2019
By analyzing data from nearly all US PhD-recipients and their dissertations across three decades, this paper finds demographically underrepresented students innovate at higher rates than majority students, but their novel contributions are discounted and less likely to earn them academic positions. The discounting of minorities' innovations may partly explain their underrepresentation in influential positions of academia.
A BIBLIOMETRIC ANALYSIS OF THE RELATIONSHIP BETWEEN WORKFORCE DIVERSITY AND INNOVATION
The relationship between workforce diversity and innovation has recently come to the attention of researchers, numerous studies focusing on the causal relationship between the two terms, but none of them having investigated the specialized literature pertaining to this relationship from a bibliometric perspective. The aim of this paper is to use a bibliometric analysis in order to highlight the way the link between these two concepts evolves within the scientific field. In this sense, 366 Web of Science indexed publications on this topic were selected and analyzed with the help of two popular software-Biblioshiny and VOSviewer. The results highlighted the evolution of academic production on the link between workforce diversity and innovation, their territorial dissemination based on the most productive countries, the collaboration among three of the most influential channels (affiliations, authors, and sources), and the conceptual structure of the scientific production based on keyword co-occurrence analysis, as well as a longitudinal thematic analysis. This study can contribute to the literature through a map of the relationship between workforce diversity and innovation. Its conclusions have led to the idea that employee diversity (in terms of education, ethnicity, race, gender, equity, age) can create all the necessary premises (human capital, knowledge, productivity, cultural diversity, motivation, leadership) for an organization to be innovative and to achieve performance, thus leading to a competitive advantage.