61,415 research outputs found
The evolution of networks of innovators within and across borders: Evidence from patent data
Recent studies on the geography of knowledge networks have documented a negative impact of physical distance and institutional borders upon research and development (R&D) collaborations. Though it is widely recognized that geographic constraints and national borders impede the diffusion of knowledge, less attention has been devoted to the temporal evolution of these constraints. In this study we use data on patents filed with the European Patent Office (EPO) for OECD countries to analyze the impact of physical distance and country borders on inter-regional links in four different networks over the period 1988-2009: (1) co-inventorship, (2) patent citations, (3) inventor mobility and (4) the location of R&D laboratories. We find the constraint imposed by country borders and distance decreased until mid-1990s then started to grow, particularly for distance. We further investigate the role of large innovation "hubs" as attractors of new collaboration opportunities and the impact of region size and locality on the evolution of cross-border patenting activities. The intensity of European cross-country
inventor collaborations increased at a higher pace than their non-European counterparts until 2004,
with no significant relative progress thereafter. Moreover, when analyzing networks of geographical mobility, multinational R&D activities and patent citations we cannot detect any substantial progress in European research integration above and beyond the common global trend
The relationship of policy induced R&D networks and inter-regional knowledge diffusion
Knowledge diffusion is argued to be strongly influenced by knowledge networks and spatial structures. However, empirical studies primarily apply an indirect approach in measuring their impact. Moreover, little is known about how policy can influence the spatial diffusion of knowledge. This paper seeks to fill this gap by testing empirically the effects of policy induced knowledge networks on the propensity of inter-regional patent citations. We use patent citation data for 141 labor market regions in Germany between 2000 to 2009, which is merged with information on subsidized joint R&D projects. Based on the latter, we construct a network of subsidized R&D collaboration. Its impact on inter-regional patent citations is evaluated with binomial and negative binomial regression models. Our findings do not indicate that inter-regional network links created by public R&D subsidies facilitate patent citations and, hence, inter-regional knowledge diffusion
Measuring research performance in international collaboration
Chinchilla-Rodríguez, Zaida; Miguel, Sandra; Perianes-Rodríguez, Antonio. (2016). Measuring research performance in international collaboration. 14th International Congress of Information, Info '2016. La Havana, Cuba, October 31- November 4, 2016.International collaboration in the creation of knowledge is responsible to change the structural stratification of science having profound implications for the governance of science. Analysis of collaboration in Latin American and Caribbean countries is of particular significance, because initiatives are often the result of “research-for-aid” arrangements, generally based on North–South asymmetries. However, collaboration for mutual benefit and excellence has gained increasing acceptance, with “partner” selection becoming a strategic priority to enhance one’s own production. The general aim of this study is to quantify the benefit rate in visibility and impact of scientific production in the field of nanoscience and nanotechnology (NST) bearing in mind the different types of output (total, in leadership, excellent, and excellent with leadership) of the six main producers of knowledge in NST in Latin America in the period 2003-2013. More specifically we aspire to visualize the networks of international collaboration in a given country (ego-network) to represent the difference between the citations received per type of output, and identify the associates with whom a country has greater potential and capacity to generate knowledge of high quality, as well as the differences existing in terms of visibility depending on the type of production analyzed. In short, we wish to determine the benefits of such collaborative efforts. In this way we could respond to questions such as: a) With which countries is collaboration established? and b) With which collaborating countries are the greatest volume of citations per document obtained, according to the type of output.This work was made possible through financing by the Project NANOMETRICS (Ref.
CSO2014-57770-R) supported by Ministerio de Economía y Competitividad of SpainPeer reviewe
Studying the Emerging Global Brain: Analyzing and Visualizing the Impact of Co-Authorship Teams
This paper introduces a suite of approaches and measures to study the impact
of co-authorship teams based on the number of publications and their citations
on a local and global scale. In particular, we present a novel weighted graph
representation that encodes coupled author-paper networks as a weighted
co-authorship graph. This weighted graph representation is applied to a dataset
that captures the emergence of a new field of science and comprises 614 papers
published by 1,036 unique authors between 1974 and 2004. In order to
characterize the properties and evolution of this field we first use four
different measures of centrality to identify the impact of authors. A global
statistical analysis is performed to characterize the distribution of paper
production and paper citations and its correlation with the co-authorship team
size. The size of co-authorship clusters over time is examined. Finally, a
novel local, author-centered measure based on entropy is applied to determine
the global evolution of the field and the identification of the contribution of
a single author's impact across all of its co-authorship relations. A
visualization of the growth of the weighted co-author network and the results
obtained from the statistical analysis indicate a drift towards a more
cooperative, global collaboration process as the main drive in the production
of scientific knowledge.Comment: 13 pages, 9 figure
Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)
Opinion mining and sentiment analysis has become ubiquitous in our society, with
applications in online searching, computer vision, image understanding, artificial intelligence and
marketing communications (MarCom). Within this context, opinion mining and sentiment analysis
in marketing communications (OMSAMC) has a strong role in the development of the field by
allowing us to understand whether people are satisfied or dissatisfied with our service or product
in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To
the best of our knowledge, there is no science mapping analysis covering the research about opinion
mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science
mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work
during the last two decades in this interdisciplinary area and to show trends that could be the basis
for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer
and InCites based on results from Web of Science (WoS). The results of this analysis show the
evolution of the field, by highlighting the most notable authors, institutions, keywords,
publications, countries, categories and journals.The research was funded by Programa Operativo FEDER Andalucía 2014‐2020, grant number “La
reputación de las organizaciones en una sociedad digital. Elaboración de una Plataforma Inteligente para la
Localización, Identificación y Clasificación de Influenciadores en los Medios Sociales Digitales (UMA18‐
FEDERJA‐148)” and The APC was funded by the same research gran
Cross‐campus Collaboration: A Scientometric and Network Case Study of Publication Activity Across Two Campuses of a Single Institution
Team science and collaboration have become crucial to addressing key research questions confronting society. Institutions that are spread across multiple geographic locations face additional challenges. To better understand the nature of cross‐campus collaboration within a single institution and the effects of institutional efforts to spark collaboration, we conducted a case study of collaboration at Cornell University using scientometric and network analyses. Results suggest that cross‐campus collaboration is increasingly common, but is accounted for primarily by a relatively small number of departments and individual researchers. Specific researchers involved in many collaborative projects are identified, and their unique characteristics are described. Institutional efforts, such as seed grants and topical retreats, have some effect for researchers who are central in the collaboration network, but were less clearly effective for others
Technological Innovation Performance Analysis Using Multilayer Networks: Evidence from the Printer Industry
Department of Management EngineeringThe importance of collaboration and technology boundary spanning has been emphasized in other inquiries into technological innovation. Therefore, this research project first tried to investigate the effect of collaboration on technology boundary spanning. Then, we investigated the effect of collaboration and technology boundary spanning on technological innovation within a firm by using a multilayer network to analyze patent data. The aim of this paper is to provide new insight into the process of analyzing patent data using multilayer networks. This empirical study is based on a sample of 408 firms within the printer industry from 1996 to 2005.
Starting with a theoretical discussion of R&D collaboration, technology boundary spanning and innovation performance, the importance of a firm???s collaboration and technology boundary spanning in its technology innovation performance was empirically analyzed using patent data. We followed changes in collaboration networks, technology class networks and the connection between them and tried to find the meaning of those changes in firms??? technology innovation performances. We used degree centrality within the collaboration network and the ratio of collaborated patents to the total number of patents in order to measure a firm???s collaboration and formulated technology boundary spanning represented by exploitation and exploration by using edges of the multilayer network. As dependent variables, we used the number of patents and the average number of citations received over three, five, and 10 years to measure the firm???s quantitative and qualitative innovation performance respectively.
The results of the analysis can be summarized as follows: a firm???s collaboration has positive effects on both exploitation and exploration. Firms with more collaborations show higher quantitative innovation performances while firms with more collaborations exhibit lower qualitative innovation performance. Exploitation has a positive impact on a firm???s quantitative innovation performance while exploration has negative effects on a firm???s quantitative innovation performance. The relationship between a firm???s exploration activities and a firm???s qualitative innovation performance manifests as an inverted U-shape. On the other hand, a firm???s exploitation activities have a U-shape relationship with the firm???s qualitative innovation performance.
The implication of this study is that multilayer networks can be used to analyze patent data. This study used multilayer networks to formulate the exploitation and exploration only. However, in further research it can be utilized to find the hub firms that fuse technologies.clos
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