Category Archives: ST&I indicators

Emergence scoring to identify frontier R&D topics and key players

Indicators of technological emergence promise valuable intelligence to those determining R&D priorities. We present an implemented algorithm to calculate emergence scores for topical terms from abstract record sets. We offer a family of emergence indicators deriving from those scores. Primary emergence indicators identify “hot topic” terms. We then use those to generate secondary indicators that reflect organizations, countries, or authors especially active at frontiers in a target R&D domain. We also flag abstract records (papers or patents) rich in emergent technology content, and we score research fields on relative degree of emergence. This paper presents illustrative results for example topics – Nano-Enabled Drug Delivery, Non-Linear Programming, Dye Sensitized Solar Cells, and Big Data.

https://doi.org/10.1016/j.techfore.2018.04.016

Author(s): Alan L. Porter, Jon Garner, Stephen F. Carley, Nils C. Newman
Organization: Georgia Institute of Technology
Source: Technological Forecasting and Social Change
Year: 2018

Tracking the emergence of synthetic biology (full-text)

Synthetic biology is an emerging domain that combines biological and engineering concepts and which has seen rapid growth in research, innovation, and policy interest in recent years. This paper contributes to efforts to delineate this emerging domain by presenting a newly constructed bibliometric definition of synthetic biology. Our approach is dimensioned from a core set of papers in synthetic biology, using procedures to obtain benchmark synthetic biology publication records, extract keywords from these benchmark records, and refine the keywords, supplemented with articles published in dedicated synthetic biology journals. We compare our search strategy with other recent bibliometric approaches to define synthetic biology, using a common source of publication data for the period from 2000 to 2015. The paper details the rapid growth and international spread of research in synthetic biology in recent years, demonstrates that diverse research disciplines are contributing to the multidisciplinary development of synthetic biology research, and visualizes this by profiling synthetic biology research on the map of science. We further show the roles of a relatively concentrated set of research sponsors in funding the growth and trajectories of synthetic biology. In addition to discussing these analyses, the paper notes limitations and suggests lines for further work.

Full-text available at https://link.springer.com/article/10.1007/s11192-017-2452-5

Author(s): Philip Shapira, Seokbeom Kwon, Jan Youtie
Organization(s): University of Manchester, Georgia Institute of Technology
Source: Scientometrics
Year: 2017

An indicator of technical emergence

Developing useful intelligence on scientific and technological emergence challenges those who would manage R&D portfolios, assess research programs, or manage innovation. Recently, the U.S. Intelligence Advanced Research Projects Activity Foresight and Understanding from Scientific Exposition Program has explored means to detect emergence via text analyses. We have been involved in positing conceptual bases for emergence, framing candidate indicators, and devising implementations. We now present a software script to generate a family of Emergence Indicators for a topic of interest. This paper offers some background, then discusses the development of this script through iterative rounds of testing, and then offers example findings. Results point to promising and actionable intelligence for R&D decision-makers.

https://link.springer.com/article/10.1007/s11192-018-2654-5?wt_mc=Internal.Event.1.SEM.ArticleAuthorOnlineFirst

Author(s): Stephen F. Carley, Nils C. Newman, Alan L. Porter, Jon G. Garner
Organizations(s): Search Technology
Source:
Scientometrics
Year: 2018

A measure of staying power: Is the persistence of emergent concepts more significantly influenced by technical domain or scale? (full-text)

This study advances a four-part indicator for technical emergence. While doing so it focuses on a particular class of emergent concepts—those which display the ability to repeatedly maintain an emergent status over multiple time periods. The authors refer to this quality as staying power and argue that those concepts which maintain this ability are deserving of greater attention. The case study we consider consists of 15 subdatatsets within the dye-sensitized solar cell framework. In this study the authors consider the impact technical domain and scale have on the behavior of persistently emergent concepts and test which of these has a greater influence.

https://link.springer.com/article/10.1007/s11192-017-2342-x

Full-text avalaible via ResearchGate
https://www.researchgate.net/publication/315462977_A_measure_of_staying_power_Is_the_persistence_of_emergent_concepts_more_significantly_influenced_by_technical_domain_or_scale

Author(s): Stephen F. Carley, Nils C. Newman, Alan L. Porter, Jon G. Garner
Organization(s): Georgia Institute of Technology, Search Technology
Source: Scientometrics
Year: 2017

A hybrid similarity measure method for patent portfolio analysis

Similarity measures are fundamental tools for identifying relationships within or across patent portfolios. Many bibliometric indicators are used to determine similarity measures; for example, bibliographic coupling, citation and co-citation, and co-word distribution. This paper aims to construct a hybrid similarity measure method based on multiple indicators to analyze patent portfolios. Two models are proposed: categorical similarity and semantic similarity. The categorical similarity model emphasizes international patent classifications (IPCs), while the semantic similarity model emphasizes textual elements. We introduce fuzzy set routines to translate the rough technical (sub-) categories of IPCs into defined numeric values, and we calculate the categorical similarities between patent portfolios using membership grade vectors. In parallel, we identify and highlight core terms in a 3-level tree structure and compute the semantic similarities by comparing the tree-based structures. A weighting model is designed to consider: 1) the bias that exists between the categorical and semantic similarities, and 2) the weighting or integrating strategy for a hybrid method. A case study to measure the technological similarities between selected firms in China’s medical device industry is used to demonstrate the reliability our method, and the results indicate the practical meaning of our method in a broad range of informetric applications.

Highlights

  • An application that introduces fuzzy sets to transform IPCs to numeric values.
  • A 3-level tree structure that arranges terms hierarchically for similarity measure.
  • A study that applies similarity measure for technology mergers and acquisitions.

http://www.sciencedirect.com/science/article/pii/S1751157715302169

Author(s): Yi Zhang, Lining Shang, Lu Huang, Alan L. Porter, Guangquan Zhang, Jie Lu, Donghua Zhu
Organization(s): University of Technology Sydney, Beijing Institute of Technology, Georgia Institute of Technology
Source: Journal of Informetrics
Year: 2016

A measure of staying power: Is the persistence of emergent concepts more significantly influenced by technical domain or scale? (full-text)

This study advances a four-part indicator for technical emergence. While doing so it focuses on a particular class of emergent concepts—those which display the ability to repeatedly maintain an emergent status over multiple time periods. The authors refer to this quality as staying power and argue that those concepts which maintain this ability are deserving of greater attention. The case study we consider consists of 15 subdatatsets within the dye-sensitized solar cell framework. In this study the authors consider the impact technical domain and scale have on the behavior of persistently emergent concepts and test which of these has a greater influence.

https://link.springer.com/article/10.1007%2Fs11192-017-2342-x

For full-text view, http://rdcu.be/qfTB

Author(s): Stephen F. Carley, Nils C. Newman, Alan L. Porter, Jon G. Garner
Organization(s): Georgia Tech, Search Technology
Source: Scientometrics
Year: 2017

Patent information retrieval: approaching a method and analysing nanotechnology patent collaborations

Many challenges still remain in the processing of explicit technological knowledge documents such as patents. Given the limitations and drawbacks of the existing approaches, this research sets out to develop an improved method for searching patent databases and extracting patent information to increase the efficiency and reliability of nanotechnology patent information retrieval process and to empirically analyse patent collaboration. A tech-mining method was applied and the subsequent analysis was performed using Thomson data analyser software. The findings show that nations such as Korea and Japan are highly collaborative in sharing technological knowledge across academic and corporate organisations within their national boundaries, and China presents, in some cases, a great illustration of effective patent collaboration and co-inventorship. This study also analyses key patent strengths by country, organisation and technology.

OPEN ACCESS article. For Full-text, go to https://link.springer.com/article/10.1007/s11192-017-2325-y

Author(s): Sercan Ozcan, Nazrul Islam
Organization(s): University of Portsmouth, University of Exeter
Source: Scientometrics
Year: 2017

Science-technology-industry correlative indicators for policy targeting on emerging technologies: exploring the core competencies and promising industries of aspirant economies

This paper seeks to contemplate a sequence of steps in connecting the fields of science, technology and industrial products. A method for linking different classifications (WoS–IPC–ISIC concordance) is proposed. The ensuing concordance tables inherit the roots of Grupp’s perspective on science, technology, product and market. The study contextualized the linking process as it can be instrumental for policy planning and technology targeting. The presented method allows us to postulate the potential development of technology in science and industrial products. The proposed method and organized concordance tables are intended as a guiding tool for policy makers to study the prospects of a technology or industry of interest. Two perceived high potential technologies—traditional medicine and ICT—that were sought by two aspirant economies—Hong Kong and Malaysia—are considered as case studies for the proposed method. The selected cases provide us the context of what technological research is being pursued for both fundamental knowledge and new industries. They enable us to understand the context of policy planning and targeting for sectoral and regional innovation systems. While we note the constraints of using joint-publishing and joint-patenting data to study the core competencies of developing economies and their potential for development, we realize that the proposed method enables us to highlight the gaps between science and technology and the core competencies of the selected economies, as well as their prospects in terms of technology and product development. The findings provide useful policy implications for further development of the respective cases.

https://link.springer.com/article/10.1007/s11192-017-2319-9

Author(s): Chan-Yuan Wong, Hon-Ngen Fung
Organization(s): University of Malaya
Source: Scientometrics
Year: 2017

The Diffusion of Military Technology

The impact of national defense research and development spending on overall innovation depends on the extent to which the knowledge and technologies generated by defense funding diffuse. This article uses an original data-set of patents assigned to defense-servicing organizations to investigate the diffusion of military technologies. Contrary to the predictions of the prevailing scholarship, I find no difference in the rate of diffusion between civilian and military technologies. Neither do military technologies assigned to government agencies diffuse at different rates than those assigned to firms. The overall technological experience of the patent assignee is found to be a positive predictor of the diffusion of military technologies. The effect of the prevailing intellectual property rights regime is ambivalent: when US patents are included in the sample, the effect of patent protection is positive, when the US is excluded, the effect is either non-significant or negative depending on the model specification that is utilized.

http://dx.doi.org/10.1080/10242694.2017.1292203

Author(s): Jon Schmid
Organization: Georgia Institute of Technology
Source: Defence and Peace Economics
Year: 2017

Nano-enabled Drug Delivery in Cancer Therapy: Literature Analysis Using the MeSH System

Biomedical literature provides abundant knowledge on R&D development and emerging themes and techniques to researchers and to enhance clinical treatment. Tracing research topic activity and researcher connections, and understanding evolving research landscapes, supports identification of research domain potential and informs R&D portfolio management. Methods: We offer a systematic approach to summarize biomedical research information compiled from the MEDLINE database. Selected MeSH qualifiers are applied as properties for clustering terms. Linkages among clusters are measured based on an object–attribute–value, relative research concentration. By arraying selected technical dimensions against each other, we enable identification and evaluation of latent connections. Results: 10354 MEDLINE records from 2000 to 2013 on nano-enabled drug delivery (NEDD) for cancer treatment are retrieved and analyzed. Seven topical clusters are generated with relatively clear boundaries. Elements with high relative research concentration but low number of records show emerging trends. And the concentrations’ decline indicates the universalization of drugs and nano components in cancer treatment. Conclusions: This systematic topical analysis process helps explore particular technological trends and potentials in biomedical areas. It combines an algorithm to reveal latent connections hidden in literature text content with expert judgement. From the standpoint of technology assessment, it provides researchers and administrators the ability to capture biomedical research dynamics.

http://www.eurekaselect.com/144824/article

Author(s): Tejraj M Aminabhavi, Jing Ma and Alan L Porter
Organization(s): Shree Dhanvantary Pharmacy College
Source: Pharmaceutical Nanotechnology
Year: 2016