1,721,076 research outputs found
Use of exclusive data for corporate research on machine learning and artificial intelligence: Implications for innovation and competition policy
No full textCorporate research has been a primary driver of recent advances in Machine Learning and Artificial Intelligence (ML/AI). The present study contends that firms' prominent role in advancing the ML/AI research field is partly attributed to their use of exclusive data for ML/AI research. Using data on nearly 8000 preprints of ML/AI research papers archived in arXiv and the performance of their proposed algorithms, we found multifaceted evidence that corporate ML/AI research has exhibited a particularly significant citation impact compared to noncorporate research. Importantly, we showed that the significance of corporate research is more pronounced when it originates from the use of exclusive data. We argue that firms' use of exclusive data has been instrumental in not only encouraging their research on ML/AI, but also enhancing the research impact, which we call the "dual role" of the data in corporate research on ML/AI. In light of the policy concern regarding the potential anticompetitive implications of firms' utilization of data exclusivity in the evolving landscape of ML/AI, our conclusion calls for a comprehensive policy discourse on the consequences of firms' exclusive use of data for their ML/AI research within broader dimensions of societal welfare, including innovation and competition.
Interdisciplinary knowledge combinations and emerging technological topics: Implications for reducing uncertainties in research evaluation
No full textThis article puts forth a new indicator of emerging technological topics as a tool for addressing challenges inherent in the evaluation of interdisciplinary research. We present this indicator and test its relationship with interdisciplinary and atypical research combinations. We perform this test by using metadata of scientific publications in three domains with different interdisciplinarity challenges: Nano-Enabled Drug Delivery, Synthetic Biology, and Autonomous Vehicles. Our analysis supports the connection between technological emergence and interdisciplinarity and atypicality in knowledge combinations. We further find that the contributions of interdisciplinary and atypical knowledge combinations to addressing emerging technological topics increase or stay constant over time. Implications for policymakers and contributions to the literature on interdisciplinarity and evaluation are provided.
Research addressing emerging technological ideas has greater scientific impact
No full textThis study empirically examines the association between the extent of emerging technological ideas in a scientific publication and its future scientific impact measured by number of citations. We analyze metadata of scientific publications in three scientific domains: Nano-Enabled Drug Delivery, Synthetic Biology, and Autonomous Vehicles. By employing a bibliometric indicator for identifying and quantifying emerging technological ideas - as derived terms from the titles and abstracts - we measure the extent to which the publication contains emerging technological ideas in each domain. Then, we statistically estimate the size and statistical significance of the relationship between the publication-level technological emergence score and the normalized number of citations accruing to the publication.,Our analysis shows that the degree to which a paper contains technologically emerging ideas is positively and strongly associated with its future citation impact in each of the three domains. An additional analysis demonstrates that this relationship holds for citations from other publications, both in the same field as, and in different fields from, the scientific domain of the focal publication. A series of tests for validation further support our argument that the greater the extent to which scientific knowledge (a paper) contains emerging ideas, the bigger its scientific impact. Implications for academic researchers, research policymakers, and firms are discussed.,
How does regulatory uncertainty shape the innovation process? Evidence from the case of nanomedicine
No full textThis study investigates the effect of regulatory uncertainty on the translation of scientific discovery on emerging research topics to technical applications in science-driven industry. Our empirical analysis using the case of the US Federal Drug and Food Administration's release of the report on the regulatory approach to nanomedicine in 2007 shows that; (1) the regulatory uncertainty decelerated the translation of nanomedicine research to technical applications, (2) this effect was particular for the nanomedicine research on emerging topics in the field. Our further analysis suggests that the effect of the regulatory uncertainty originated from the suppressed business activities in the field where the regulatory uncertainty presents. Our study elaborates on how regulatory authority actions shape the innovation process by shedding light on the impact of regulatory uncertainty on the development of technical applications of an emerging scientific area.
Navigating the innovation trajectories of technology by combining specialization score analyses for publications and patents: graphene and nano-enabled drug delivery
No full textIn this study, we combine the specialization scores for publications and patents (the latter is a new indicator of cross-disciplinary engagement) to achieve more comprehensive navigation of the innovation trajectory of a technology. The patent specialization score draws upon counterpart research publication indicator concepts to measure patent diversity. Two nano-based technologies-Nano-enabled drug delivery (NEDD) and Graphene-provide contrasting explorations of the behavior of this indicator, alongside research publication indicators. Results show distinctive patterns of the two technologies and for the respective publication and patent indicators. NEDD research, as evidenced by publication and citation patterns, engages highly diverse research fields. In contrast, NEDD development, as reflected in patent International Patent Classifications (IPCs), concentrates on relatively closely associated fields. Graphene presents the opposite picture, with closely linked disciplines contributing to research, but much more diverse fields of application for its patents. We suggest that analyzing the field diversity of research publications and patents together, employing both specialization scores, can offer fruitful insights into innovation trajectories. Such information can contribute to technology and innovation management and policy for such emerging technologies.
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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