This study aims at identifying potential industry-University-research institution collaborations partners (IURC) efficaciously and analyzes the conditions and dynamics in the IURC process, based on knowledge potential and the knowledge spillover theory. Furthermore, a new identification method is constructed that takes into account the law of scientific research cooperation and economic factors. The method utilizes multisource data, combining bibliometric and econometrics analyses to achieve the network core of the existing collaboration network, and institution competitiveness in the innovation chain. Empirical analysis of the genetic engineering vaccine field shows that throughout the distribution characteristics of creative technologies from different institutions, the analysis based on the innovation chain can identify more complementarities between institutions. Compared to previous studies, this study emulates the real conditions of IURC. The rule of technological innovation can be better revealed, potential partners of IURC can be more easily identified, and the conclusion has a higher value in consultation. In particular, diverse informative indices can assist researchers in deriving appropriate partners for research and development cooperation.
Author(s): Haiyun Xu, Kun Dong, Ling Wei, Chao Wang, Shu Fang
Organization(s): Chengdu Documentation and Information Center, CAS; University of Chinese Academy of Sciences
Source: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Business intelligence enables enterprises to make effective and good quality business decisions. In the knowledge economy, patents are seen as strategic assets for companies as they provide a competitive advantage and at the same time ensure the freedom to operate and form the basis for new alliances. Publication or disclosure of intellectual property (IP) strategy based on patent filings is rarely available in the public domain. Because of this, the only way to understand IP strategy is to look at patent filings, analyze them and, based on the trends, deduce strategy. This paper tries to uncover IP strategies of five US and Indian IT companies by analyzing their patent filings. Gathering business intelligence via means of patent analytics can be used to understand the strategies used by companies in advocating their patent portfolio and aligning their business needs with patenting activities. This study reveals that the Indian companies are far behind in protecting their IPs, although they are now on course correction and have started aggressively protecting their inventions. It is also observed that the rival companies in the study are not directly competing with each other in the same technological domain. Different patent filing strategies are used by firms to gain a competitive advantage. Companies make use of disclosure as strategy or try to cover many aspects of a technology in a single patent, thereby signaling their dominance in a technological area and at the same time as they add information.
Author(s): Shabib-Ahmed Shaikh, Tarun Kumar Singhal
Organization(s): Symbiosis International University (SIU), Symbiosis Centre for Management Studies
Source: Journal of Intelligence Studies in Business
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.
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
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
For about 5 years, production of automobiles equipped with head-up display (HUD) systems has continuously grown and this trend will remain for at least three years more from 2014 [7, 19]. Therefore, looking for clarifying how to orientate future efforts in developing these systems, a systematic analysis approach has been implemented for identifying best design practises, common characteristics, gaps, implementation trends and research topics on automotive HUD systems. The proposed approach is conducted on two areas, firstly exploring the current scientific literature to find the most relevant research topics and understanding how these are evolving. Secondly, a competitive intelligence analysis was conducted compiling patents related to automotive HUD systems. This analysis was specially oriented towards determining, currently and in the near future, basic product design implementation trends in automotive HUD systems. Finally, the results obtained from both scientific and technological points of view were compared and commented, looking for determining common, converging or diverging, evolution parameters in automotive HUD systems. In this way, the results exposed the distraction as an outstanding research topic for these systems, becoming even more crucial if they are mixed with augmented reality projections, advanced driver assistance systems (ADAS) or infotainment systems.
Author(s): J. Alejandro Betancur, Jesús Villa-Espinal, Gilberto Osorio-Gómez, Sergio Cuéllar, Daniel Suárez
Organization(s): Pontificia Universidad Javeriana, Universidad EAFIT
Source: International Journal on Interactive Design and Manufacturing (IJIDeM)
Patent landscape and the accompanying IP competitive intelligence involves understanding and anticipating the competitive environment within which a company operates. More specifically, IP competitive intelligence highlights emerging IP risks, provides patent portfolio benchmarking, monitors competitor technology development efforts, and predicts commercialization of technology.
This paper provides a framework for patent landscape and IP competitive intelligence as driven by strategic intent. This paper advocates the benefits of both “quantitative” statistical analysis and “qualitative” human intelligence for IP competitive intelligence. Moreover, this paper defines four Levels of IP analysis with pruned examples for effective competitive intelligence.
Author: Yateen R. Pargaonkar
Organization: Chevron Energy Technology Company
Source: World Patent Information
Understanding the evolution and emergence of technology domains remains a challenge, particularly so for potentially breakthrough technologies. Though it is well recognized that emergence of new fields is complex and uncertain, to make decisions amidst such uncertainty, one needs to mobilize various sources of intelligence to identify known–knowns and known–unknowns to be able to choose appropriate strategies and policies. This competitive technical intelligence cannot rely on simple trend analyses because breakthrough technologies have little past to inform such trends, and positing the directions of evolution is challenging. Neither do qualitative tools, embracing the complexities, provide all the solutions, since transparent and repeatable techniques need to be employed to create best practices and evaluate the intelligence that comes from such exercises. In this paper, we present a hybrid roadmapping technique that draws on a number of approaches and integrates them into a multi-level approach (individual activities, industry evolutions and broader global changes) that can be applied to breakthrough technologies. We describe this approach in deeper detail through a case study on dye-sensitized solar cells. Our contribution to this special issue is to showcase the technique as part of a family of approaches that are emerging around the world to inform strategy and policy.d to inform strategy and policy.
Author(s): Yi Zhang, Douglas KR Robinson, Alan L Porter, Donghua Zhu, Guangquan Zhang, Jie Lu
Organization(s): Beijing Institute of Technology, Université de Paris-Est
Source: Technological Forecasting and Social Change
In this article, the methodology of curves in S is applied in series of data on articles in Biotechnology and Nanotechnology since 1956 obtained from the ISI Web of Science and of patents since 1962 (year of priority) and 1970 (year of publication). Belonging to controlled release, of the medical context, the data was obtained from a Tech Mining approach using the Vantage Point software tool. With the accumulated data, in time, nonlinear regression was achieved and the inflection point in the two series was calculated, taking into account the statistical parameters like Fitted R2, Value T, Value P, and Durbin Watson. The data of the articles and patents were analyzed under the following models: Weibull, Gompertz, Logistic and Sigmodial, among others, for a total of 13 models analyzed. The models with the best fit in the inflection point were selected. In the series of data from the articles, one of the models that had the best fit was the Sigmoidal model. The Sigmoidal model contained three parameters which generated a value of 33.4 for the inflection point for the year of the studied series. With the obtained values for the inflection points in the series of articles and patents, the uncertainty can be reduced in the making of decisions about the Technology Life Cycle (TLC), especially in the following aspects: the identification of the kind of technology (before and after of the inflection point), the determination of the suitable moment to apply technological rights and intellectual property, and the establishment of strategies for monitoring (when the technology is emerging) and investment.
Full-text available at http://www.revistaespacios.com/a16v37n07/16370719.html
Author(s): Jhon Wilder ZARTHA Sossa; Fernando PALOP Marro; Bibiana ARANGO Alzate; Fabián Mauricio VELEZ Salazar; and Andres Felipe AVALOS Patiño
Organization(s): Universidad Pontificia Bolivariana, Universidad Politécnica de Valencia
- Data-driven clustering approach to group topics with high accuracy
- Similarity measure approach to trace the interaction between topics in time series
- Analyzing changes of TFIDF values of related topics to predict future trends
- Technology Roadmapping to blend historical analysis and expert-based forecasting
The number and extent of current Science, Technology & Innovation topics are changing all the time, and their induced accumulative innovation, or even disruptive revolution, will heavily influence the whole of society in the near future. By addressing and predicting these changes, this paper proposes an analytic method to (1) cluster associated terms and phrases to constitute meaningful technological topics and their interactions, and (2) identify changing topical emphases. Our results are carried forward to present mechanisms that forecast prospective developments using Technology Roadmapping, combining qualitative and quantitative methodologies. An empirical case study of Awards data from the United States National Science Foundation, Division of Computer and Communication Foundation, is performed to demonstrate the proposed method. The resulting knowledge may hold interest for R&D management and science policy in practice.
Author(s): Yi Zhang, Guangquan Zhang, Hongshu Chen, Alan L. Porter, Donghua Zhu, Jie Lu
Organization(s): University of Technology Sydney, Georgia Institute of Technology, Beijing Institute of Technology
Source: Technological Forecasting and Social Change
The Gulf Coast is facing significant challenges in rebuilding after Hurricane Katrina. Post disaster perceptions of blight and crime have severely harmed the bread-and-butter industry of the area: tourism. As a result, the region must take inventory of its intellectual assets in order to determine new areas for economic development. This chapter first discusses the importance of absorptive capacity in economic development. It then presents from a technology mining study conducted on the intellectual assets (publications and patents) along what is known as the I-10 Corridor in Louisiana, Mississippi, and Alabama. These results reveal indicators of the economic development struggle of the region. More importantly, they reveal the technology areas, largely economically untapped, where the region exhibits strong research capabilities and educational focus, indicating high levels of absorptive capacity and thus, are areas prime for economic development. In addition, the paper demonstrates how technology mining can be used as a tool to aid in economic development decision-making.
Author(s): Cherie Courseault Trumbach, Sandra Hartman and Olof Lundberg
Organization(s): University of New Orleans
Source: Management of Technology Innovation and Value Creation: Selected Papers from the 16th International Conference on Management of Technology; World Scientific