Category Archives: Citation analysis

Qualitative Patents Evaluation Through the Analysis of Their Citations. Case of the Technological Sectors in the Basque Country

Patents are an output of the level of innovation of a company or region. Patent quantitative studies are performed by simply counting the number of these documents. For the qualitative evaluation, there is a certain consensus among the authors to consider the citations as the most adequate indicator. However, this indicator presents several problems regarding its correct interpretation. In the present study, in order to avoid the typical citation interpretation biases, a precise methodology is presented. As an illustrative example, we present a comparative study of the quality of patents in technological sectors of the Basque Country region over the period 1991–2011.

DOI
https://doi.org/10.1007/978-3-319-96005-0_28

Author(s): J. Gavilanes-Trapote, Ernesto Cilleruelo-Carrasco, I. Etxeberria-Agiriano, Gaizka Garechana, Alejandro Rodríguez Andara
Organization(s): University of the Basque Country
Source: Engineering Digital Transformation. Lecture Notes in Management and Industrial Engineering. Springer, Cham
Year: 2018

Research network emergence: societal issues in nanotechnology and the center for nanotechnology in society

This article looks at the creation of a network of researchers of social issues in nanotechnology and the role of the Center for Nanotechnology in Society at Arizona State University (CNS-ASU) in the creation of this network. The extent to which CNS-ASU is associated with the development of a research network around the study of social issues in nanotechnology is examined through geographic mapping of co-authors and citations of center publications, network analysis of co-authors of papers on social issues in nanotechnology, and a disciplinary analysis of these papers. The results indicate that there is an extensive network of co-authorships among researchers studying social issues in nanotechnology with CNS-ASU at the center of this network. In addition, papers written by center members and affiliates integrate a diverse range of disciplines. Qualitative data are used to interpret some of the ways that citation occurs.

https://doi.org/10.1093/scipol/scy043

Author(s): Jan Youtie, Philip Shapira, Michael Reinsborough, Erik Fisher
Organization(s): Georgia Institute of Technology, Arizona State University
Source: Science and Public Policy
Year: 2018

Innovation core, innovation semi-periphery and technology transfer: The case of wind energy patents

Some scholars have pointed to a rise of South-South technological transfer led by emerging economies such as China, India, Brazil and South Africa while other scholars highlight that emerging economies still need to catch up with developed countries. Drawing on world system’s theory, we argue that an adapted innovation framework of ‘core – semi-periphery – periphery’ could be an important analytical framework that may help us understand the process of innovation catch up. This may help specifically to better understand how an emerging economy can at least in theory have sectors that could be defined as innovation core and source for technology transfer. We will look at wind energy as North American, European, Indian and Chinese firms dominate the market. This study used citation network analysis and patent analysis to analyse knowledge flows between wind firms and to identify and compare the position and role of each firm in the knowledge network. We argue that there is still, despite catching up, a difference between innovation core countries (US, Germany, Denmark) and innovation semi-periphery (China, India) which will limit the opportunities of knowledge transfer within the sector of wind energy.

https://doi.org/10.1016/j.enpol.2018.04.048

Author(s): Johan Nordensvard, Yuan Zhou, Xiao Zhang
Organization(s): University of Southampton, Tsinghua University
Source: Energy Policy
Year: 2018

Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective

“Disruptive technology & disruptive innovation” have been of scholarly interest for years, but there is still a need to better understand the nature of disruptions and their relationship to emerging technology processes. This paper pursues these issues by analyzing the interplay of technological emergence, disruption, and innovation. Applying bibliometric methods, the paper explores the conceptual foundations, themes, and research communities within these research domains. Co-citation analyses point to three largely distinct communities on disruptive technology/innovation and emerging technology. The results highlight the multiple theoretical foundations of research around technological change processes, disruption, and emergence. These differences among the domains invite conceptual cross-fertilization and consideration of interdisciplinary approaches to technological (and commercial) emergence.

https://doi.org/10.1016/j.techfore.2017.09.032

Author(s): Munan Li, Alan L. Porter, Arho Suominen
Organisation(s): South China University of Technology, Georgia Institute of Technology, VTT Technical Research Centre of Finland
Source: Technological Forecasting & Social Change
Year: 2018

Big Data in the Social Sciences

Recent emerging technology policies seek to diminish negative impacts while equitably and responsibly accruing and distributing benefits.  Social scientists play a role in these policies, but relatively little quantitative research has been performed to study how social scientists inform the assessment of emerging technologies. This paper addresses this gap by examining social science research on “Big Data” – an emerging technology of wide interest. This paper analyzes a dataset of fields extracted from 488 social science and humanities papers written about Big Data. Our focus is on understanding the multi-dimensional nature of societal assessment by examining the references upon which these papers draw. We find that eight sub-literatures are important in framing social science research about Big Data. These results indicate that the field is evolving from general sociological considerations toward applications issues and privacy concerns. Implications for science policy and technology assessment of societal implications are discussed.

Preprint available at http://works.bepress.com/jan_youtie/80/

Author(s): Jan Youtie and Alan Porter
Organizations: Georgia Institute of Technology
Source: Science and Public Policy
Year: 2016

Nano/micro-electro mechanical systems: a patent view

Combining both bibliometrics and citation network analysis, this research evaluates the global development of micro-electro mechanical systems (MEMS) research based on the Derwent Innovations Index database. We found that worldwide, the growth trajectory of MEMS patents demonstrates an approximate S shape, with United States, Japan, China, and Korea leading the global MEMS race. Evidenced by Derwent class codes, the technology structure of global MEMS patents remains steady over time. Yet there does exist a national competitiveness component among the top country players. The latecomer China has become the second most prolific country filing MEMS patents, but its patent quality still lags behind the global average.

http://link.springer.com/article/10.1007/s11051-015-3273-1

Author(s): Guangyuan Hu and Weishu Liu
Organization(s): Shanghai University of Finance and Economics,Shanghai Jiao Tong University
Source: Journal of Nanoparticle Research
Year: 2015

Scientometric cognitive and evaluation on smart city related construction and building journals data

In this paper, scientometrics cognitive and knowledge visualization technology were used to evaluate global scientific production and development trends in construction and building technology research of smart cities. All the data was collected from the Science Citation Index-Expanded (SCIE) database and Journal Citation Reports (JCR). The published papers from the subject of construction and building technology and their journals, authors, countries and keywords spanning over several aspects of research topics, proved that architecture/building research grew rapidly over the past 30 years, and the trend still continues in recent smart cities era. The purposed of this study were to identify the journals in the field of construction and building technology in smart city, make a comparative report on related researches, as well as propose a quality evaluation of those journals. Based on JCR and SCI paper data, the journals related to construction and building technology in smart city were assessed using ten metrics: languages, active degree, references, citation trends, main countries, leading institutes, cooperation trends, productive authors, author keywords and keywords plus. The results indicate that all the factors have great significance and are related to the impact of a journal. It also provides guidance to both evaluators and the study groups which assess journals during the process of judging or selecting research outlets, and future perspective on how to improve the impact of a paper or a journal.

Author(s): Liang-xing Su, Peng-hui Lyu , Zheng Yang, Shuai Ding, Kai-le Zhou
Organization(s): Wuhan University; Hefei University of Technology
Source: Scientometrics http://link.springer.com/article/10.1007/s11192-015-1697-0
Year: 2015

A systematic method to create search strategies for emerging technologies based on the Web of Science: illustrated for ‘Big Data’

Bibliometric and “tech mining” studies depend on a crucial foundation—the search strategy used to retrieve relevant research publication records. Database searches for emerging technologies can be problematic in many respects, for example the rapid evolution of terminology, the use of common phraseology, or the extent of “legacy technology” terminology. Searching on such legacy terms may or may not pick up R&D pertaining to the emerging technology of interest. A challenge is to assess the relevance of legacy terminology in building an effective search model. Common-usage phraseology additionally confounds certain domains in which broader managerial, public interest, or other considerations are prominent. In contrast, searching for highly technical topics is relatively straightforward. In setting forth to analyze “Big Data,” we confront all three challenges—emerging terminology, common usage phrasing, and intersecting legacy technologies. In response, we have devised a systematic methodology to help identify research relating to Big Data. This methodology uses complementary search approaches, starting with a Boolean search model and subsequently employs contingency term sets to further refine the selection. The four search approaches considered are: (1) core lexical query, (2) expanded lexical query, (3) specialized journal search, and (4) cited reference analysis. Of special note here is the use of a “Hit-Ratio” that helps distinguish Big Data elements from less relevant legacy technology terms. We believe that such a systematic search development positions us to do meaningful analyses of Big Data research patterns, connections, and trajectories. Moreover, we suggest that such a systematic search approach can help formulate more replaceable searches with high recall and satisfactory precision for other emerging technology studies.

http://link.springer.com/article/10.1007/s11192-015-1638-y

Author(s): Ying Huang, Jannik Schuehle, Alan L. Porter, and Jan Youtie
Organization(s): Beijing Institute of Technology and Georgia Institute of Technology
Source: Scientometrics
Year: 2015

Social science contributions compared in synthetic biology and nanotechnology

With growing attention to societal issues and implications of synthetic biology, we investigate sources of social science publication knowledge in synthetic biology and probe what might be learned by comparison with earlier rounds of social science research in nanotechnology. “Social science” research is broadly defined to include publications in conventional social science as well as humanities, law, ethics, business, and policy fields. We examine the knowledge clusters underpinning social science publications in nanotechnology and synthetic biology using a methodology based on the analysis of cited references. Our analysis finds that social science research in synthetic biology already has traction and direction, rooted in an ethical, legal, and social implications framework. However, compared with nanotechnology, social science research in synthetic biology could further explore opportunities and openings for engagement, anticipatory, and downstream application perspectives that will help to build a wider platform for insights into current and future societal impacts.

For full-text see:
http://www.tandfonline.com/doi/full/10.1080/23299460.2014.1002123#.VPTit5Y5B1s

Author(s): Philip Shapira, Jan Youtie, and Yin Li
Organization(s): University of Manchester and Georgia Institute of Technology
Source: Journal of Responsible Innovation
Year: 2015

Visualizing the intellectual structure and evolution of innovation systems research: a bibliometric analysis

Despite increasing awareness of the need to trace the trajectory of innovation system research, so far little attention has been given to quantitative depiction of the evolution of this fast-moving research field. This paper uses CiteSpace to demonstrate visually intellectual structures and developments. The study uses citation analysis to detect and visualize disciplinary distributions, keyword co-word networks and journal cocitation networks, highly cited references, as well as highly cited authors to identify intellectual turning points, pivotal points and emerging trends, in innovation systems system research from 1975 to 2012. As with other science mapping software tools (eg, Bibexcel and VantagePoint), CiteSpace can be used to produce and analyze co-occurrence network of key words and subject categories (co-word analysis), and co-citation networks of authors, documents and journals.

Author(s): Zhigao Liu, Yimei Yin, Weidong Liu, and Michael Dunford
Organization(s): Chinese Academy of Sciences, Beijing Union University, University of Sussex
Source: Scientometrics
Year: 2015