All posts by VPInstitute

Text mining to gain technical intelligence for acquired target selection: A case study for China’s computer numerical control machine tools industry

CTI, Data Type, Patents, Research Examples, Research Type

Technology strategy plays an increasingly important role in today’s Mergers and Acquisitions (M&A) activities. Informing that strategy with empirical intelligence offers great potential value to R&D managers and technology policy makers. This paper proposes a methodology, based on patent analysis, to extract technical intelligence to identify M&A target technologies and evaluate relevant target companies to facilitate M&A target selection. We apply the term clumping process and a trend analysis together with policy and market information to profile present R&D status and capture future development signals and trends in order to grasp a range of significant domain-based technologies. Furthermore, a comparison between a selected acquirer and leading players is used to identify significant technologies and sub-technologies for specific strategy-oriented technology M&A activities. Finally, aiming to recommend appropriate M&A target companies, we set up an index-based system to evaluate the acquired target candidates from both firms-side perspective and target firm-side perspective and differentially weigh for specific M&A situations. We provide an empirical study in the field of computer numerical control machine tools (CNCMT) in China to identify technology M&A targets for an emerging Chinese CNCMT company — Estun Automation under different M&A strategies.

http://www.sciencedirect.com/science/article/pii/S0040162516305364

Author(s): Tingting Ma, Yi Zhang, Lu Huang , Lining Shang, Kangrui Wang, Huizhu Yu, Donghua Zhu
Organization(s):  Beijing Wuzi University; Beijing Institute of Technology
Source: Technological Forecasting and Social Change
Year: 2016

A Mapping of Marine Biodiversity Research Trends and Collaboration in the East Asia Region from 1996–2015

Research Examples

Many countries define policies to manage oceans and coastal areas in order to utilize marine ecosystems strategically. When we reviewed the strategies and policies of various countries in relation to ocean sustainability, we found that biodiversity preservation is a key issue for policies related to sustainable marine development. We investigated the research trends and collaboration status of China, Japan and South Korea regarding marine biodiversity through the analysis of scientific articles using bibliometric analysis. The results showed that Japan collaborated the most with other countries compared to China and South Korea. All three countries collaborated with the Organization for Economic Cooperation and Development (OECD) and Association of Southeast Asian Nations (ASEAN) countries frequently. South Korea showed the strongest inter-collaboration amongst China, Japan and South Korea. Microorganism research is a common research topic in China, Japan and South Korea. Each country demonstrated its own prominent research area, such as local region research in China, deep-sea research in Japan and aquaculture research in South Korea.

http://www.mdpi.com/2071-1050/8/10/1075

Author(s): Jungjoon Kim, Sangpil Lee, We Shim, and Jongseok Kang
Organization(s): Korea Institute of Science and Technology Information, Korea University of Science and Technology
Source: Sustainability
Year: 2016

Climate Change and Our Future: Anticipating Trends and Challenges Using Media Data

Data Type, novel source, Research Examples

This paper proposes a multidisciplinary approach to understanding the future perspectives of climate change. First, it analyzes the possibilities of using the media as an information source for anticipating trends and challenges in this area through exploring the topics that have been actively discussed in the news in the recent 5 years. Second, qualitative and quantitative approaches are combined in this study in order to identify trends of different categories: social, technological, economic, environmental, political and values/culture. It allows integrating the results of trends monitoring obtained from qualitative and quantitative sources and create a complex map of trends. Qualitative approach is based on the literature review and consultations with the experts, while quantitative analysis includes collecting the news from Factiva database and processing it in Vantage Point software using bibliometric analysis, natural language processing, statistical analysis and principal component analysis. The results shown that 58% of trends were validated by the news and its contribution to the final trends list accounts for 25% on average, which means that the media can be considered as a useful additional data source for validating and updating trends. The results of this multidisciplinary study can be of interest to researchers, economists, business representatives and policy makers that are involved in the climate change related activities.

Author(s): Nadezhda Mikova
Organization(s): National Research University Higher School of Economics
Source: Higher School of Economics Research Paper No. WP BRP 65/STI/2016.
Year: 2016

Anticipating Future Pathways of Science, Technologies, and Innovations: (Map of Science)2 Approach

Research Examples

Anticipating future pathways of Science, Technologies, and Innovations is a complex task in any R&D field and is even more challenging for the complex landscape of promising R&D directions in multiple fields. As a solution, this study analyzes research papers in Scientometrics and Technology mining. It presents an approach and text mining tools for building maps of science of a special kind which is called the Map of Science Squared. Nodes of maps corresponding to R&D fields and locations (e.g., as centers of excellence) are created, weighted, and coupled whenever possible based on processing full texts or abstracts of research papers. The questions to answer with this are as follows: (1) Do Scientometrics and Technology mining cover the full range of topics both in terms of breadth and depth? (2) Do research papers appear “at the right time,” i.e., just or soon after emergence of a topic? (3) Do researchers link R&D fields in non-traditional ways through their studies? (4) What fields are locally bound? (5) What conclusions on future pathways of Science, Technologies, and Innovations can be drawn on the basis of the analysis of the Scientometrics and Technology mining agenda?

Author(s): Irina V. Efimenko , Vladimir F. Khoroshevsky, Ed. C. M. Noyons
Organization(s): Higher School of Economics, Dorodnitsyn Computing Center,  Leiden University
Source: Anticipating Future Innovation Pathways Through Large Data Analysis
pp 71-96
Year: 2016

Generating Competitive Technical Intelligence Using Topical Analysis, Patent Citation Analysis, and Term Clumping Analysis

Future-oriented technology analysis, Research Examples, Research Type

Because of the flexibility and complexity of Newly Emerging Science and Technologies (NESTs), traditional statistical analysis fails to capture technology evolution in detail. Tracking technology evolution pathways supports industrial, governmental, and academic decisions to guide future development trends. Patents are one of the most important NESTs data sources and are pertinent to developmental paths. This paper draws upon text analyses, augmented by expert knowledge, to identify key NESTs sub-domains and component technologies. We then complement those analyses with patent citation analysis to help track developmental progressions. We identify key sub-domain patents, associated with particular component technology trajectories, then extract pivotal patents via citation analysis. We compose evolutionary pathways by combining citation and topical intelligence obtained through term clumping. We demonstrate our approach with empirical analysis of dye-sensitized solar cells (DSSCs), as an example of a promising NESTs, contributing to the remarkable growth in the renewable energy industry. The systematic approach we proposed not only offers a macro-perspective covering technology development levels and future trends, but also makes R&D information accessible for micro-level probes as needed. We work to uncover developmental trends and to compile mentions of possible applications, and this study informs NESTs management by spotting prime opportunities for innovation.

Author(s): Ying Huang, Yi Zhang, Jing Ma, Alan L. Porter, Xuefeng Wang, Ying Guo
Organization(s): Beijing Institute of Technology, University of Technology Sydney
Source: Anticipating Future Innovation Pathways Through Large Data Analysis pp 153-172
Year: 2016

Building a View of the Future of Antibiotics Through the Analysis of Primary Patents

Data Type, Patents, Research Examples, Research profiling, Research Type

The primary patent application of a new drug is the application that claims the chemical structure of that new compound and is usually the first patent filled regarding that new drug. Therefore, the analysis of the recent primary patents in a therapeutic group reflects the results of the research toward finding new compounds and allows building a view of the future of that therapeutic class. The identification of the primary patents is challenging and requires data treatment, visualization, and analysis tools. In order to address this matter, this paper presents a method for gathering and analyzing the primary patent applications for new antibiotics using the VantagePoint software. This therapeutic class was chosen due to the continuous rise of resistant bacteria, the critical need for new antibiotics that, combined with the lack new drugs in the market, leads to an urgent need for public and private policies to improve research in the field. The method resulted in 1333 primary patent applications of new antibiotics that were analyzed regarding the discovery strategy, the chemical classes, and mechanisms of action and according to the bacteria for which they are active. This analysis was made using different VantagePoint resources and allowed view of the new compounds that might reach the market in the future.

Author(s): Cristina d’Urso de Souza Mendes and Adelaide Maria de Souza Antunes
Organization(s): Federal University of Rio de Janeiro (UFRJ), Brazilian National Institute of Industrial Property (INPI)
Source: Anticipating Future Innovation Pathways Through Large Data Analysis pp 303-320
Year: 2016

Recent Trends in Technology Mining Approaches: Quantitative Analysis of GTM Conference Proceedings

Research Type, Tech mining

This paper performs a quantitative analysis of trends in technology mining (TM) approaches using 5 years (2011–2015) of Global TechMining (GTM) conference proceedings as a data source. These proceedings are processed with a help of Vantage Point software, providing an approach “tech mining for analyzing tech mining.” Through quantitative data processing (bibliometric analysis, natural language processing, statistical analysis, principal component analysis (PCA)), this study presents an overview, explores dynamics and potentials for existing and advanced TM methodologies in three layers: related methods, data sources, and software tools. The main groups and combinations of TM and related methods are identified. Key trends and weak signals concerning the use of existing (natural language processing (NLP), mapping, network analysis, etc.) and emerging methods (web scraping, ontology modeling, advanced bibliometrics, semantic the theory of inventive problem solving (TRIZ), sentiment analysis, etc.) are detected. The results are considered to be taken as a guide for researchers, practitioners, or policy makers involved in foresight activity.

Author(s): Nadezhda Mikova
Organization(s): Higher School of Economics
Source: Anticipating Future Innovation Pathways Through Large Data Analysis pp 59-69
Year: 2016

Combining Scientometrics with Patent-Metrics for CTI Service in R&D Decision-Making: Practices of National Science Library of CAS

CTI, Research Examples, Research Type

Scientometric analysis and text-mining have been applied to scientific and technological trend-tracking and related scientific performance evaluations for several years in China. Since 2012, NSL-CAS provides CTI (competitive technical intelligence) services based on metrics for supporting R&D decision-making. NSL helps technology-based firms improve their innovation capabilities via CTI, for technology novelty review, selection of innovation paths, product development evaluation, competitor monitoring, identification of potential R&D partners, and support for industrial technology and development strategizing. Scientometric methods have established many indicators for technology analysis that can be applied individually or in combinations. Composite indexes are another useful option. For CTI services, we choose or customize layer or level indexes schemas for different purposes. For supporting industrial technological strategy decision-making and innovation path identification, scientometric indicators can be used for R&D trend analysis. Specifically, in meso-technology analysis, bibliometrics and patent analysis indicators can be combined in accord with different subjects or stages of an emerging technology, whose characteristics can then be reflected by these mixed indicators. Scientometric indicators can profile the framework for research subjects, and patent metrics can describe the technology development trends. In micro-technology analysis, technology trends analysis is used for new technological product development in planning strategy for technology-based firms, and bibliometric indicators can identify directions of related scientific subjects and research directions. In fact, when a client expresses a CTI need, they request the meso- and micro-, and even macro-technology analysis. So when we execute a CTI service, we run an iteration and loop analysis through bibliometric and patent metrics. We focus theme tracing or subject analysis by tech-mining and co-wording. For macro analysis, such as competition from institutions or countries and regions, we pay close attention to the combination of scientometric and patent indicators and appropriate schemas for CTI services.

Author(s): X. Liu , Y. Sun, H. Xu, P. Jia, S. Wang, L. Dong, X. Chen
Organization(s): National Science Library, Chinese Academy of Sciences
Source: Anticipating Future Innovation Pathways Through Large Data Analysis pp 321-339
Year: 2016

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

Future-oriented technology analysis, Research Examples, Research profiling, ST&I indicators

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

A taxonomy of small firm technology commercialization

Research Examples, Research Type, ST&I indicators, ST&I policy, Strategic planning

This article proposes a taxonomy of business models used by small, highly innovative firms focused on technology commercialization. Such firms disproportionately contribute to technological change in the US economy. The firms operate across industries and use a variety of technology platforms. Exploratory factor analysis of keyword occurrence on firm websites generated a taxonomy comprising: research organization; development stage biosciences; highly specialized component supplier; specialized subcontractor; product solutions providers; and service solutions providers. This framework provides entrepreneurs and policy makers with an overview of new technology commercialization paths tailored to small, innovative firms.

http://icc.oxfordjournals.org/content/25/3/371.abstract?keytype=ref&ijkey=1U2ith4ApM9iH7y

Author(s): Dirk Libaers, Diana Hicks, and Alan L. Porter
Organization(s): University of Missouri, Georgia Institute of Technology
Source: Industrial and Corporate Change
Year: 2016