Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: the case of Korean national R&D

Rapid technological advancements and increasing research and development (R&D) costs are making it necessary for national R&D plans to identify the coreness and intermediarity of technologies in selecting projects and allocating budgets. Studies on the coreness or intermediarity of technology sectors have used patent citations, but there are limitations to dealing with patent data. The limitations arise from the most current patents and patents that do not require citations, e.g. Korean patents. Further, few or no studies have simultaneously considered both coreness and intermediarity. Therefore, we propose a patent co-classification based method to measure coreness and intermediarity of technology sectors by incorporating the analytic network process and the social network analysis. Using IPC co-classifications of patents as technological knowledge flows, this method constructs a network of directed knowledge flows among technology sectors and measures the long-term importance and the intermediating potential of each technology sector, despite the limitations of patent-based analyses. Considering both coreness and intermediarity, this method can provide more detailed and essential knowledge for decision making in planning national R&D. We demonstrated this method using Korean national R&D patents from 2008 to 2011. We expect that this method will help in planning national R&D in a rapidly evolving technological environment.     

What do university patent routes indicate at regional level?

Summary We estimate the determinants of university patents by route in Spain. National patents are an indicator of R&D efforts when we focus on the region, but not of how regions organize their university or joint research structure. International patents are a stronger indicator of R&D efforts, so they express confidence in the potential of the patent. Neither set is an indicator of proximity to the region's competencies in technologies other than for production-intensive sectors, so they will not always foster regional technology transfer. Since the driving forces of national and international patents differ, the use of both is recommended.     

Innovation and market regulation: evidence from the European electricity industry

This paper studies the effects of changes in the level of product market regulation on the industry-level innovation intensity in the EU electricity sector during years 1990–2009. In order to test the impact of deregulatory policies on the propensity to innovate in energy technologies, we match data on R&D budgets and European Patent Office patent applications from International Energy Agency and Eurostat Databases with the Organisation for Economic Co-operation and Development indexes of product market regulation. The analysis addresses innovations in the traditional electricity-related technologies, but keeping aside renewable energy technologies. Findings show an increase in patenting activities following market deregulation, measured along three factors: entry barriers, public ownership and vertical integration. In particular, econometric results suggest that policies aimed at reducing vertical integration – i.e. to unbundle networks from energy generation and supply – have a positive impact on innovation activity. Results are robust to the introduction of controls for country-level public R&D expenditures in the electricity field.     

Technology landscape and a short patentometric review for antibiofilm technologies

This study presents an overview and a short critical review of patented antibiofilm technologies. Patent information was used to determine scenarios that could be used by decision-makers or business intelligence. The study found that academia, mainly from the USA, has been applying for the most patents since 1997. Based on the S-curve analysis, the maturity of this technology sector is emerging. The technological specialization for the 10 most prominent patent applicants and state-of-the-art antibiofilm patents are presented.The high dispersion of patent applicants, the presence of universities among the most active patent applicants, and the content of the patents analyzed are good indicators to infer that developed technologies are close to the academic level. Moreover, many efforts are necessary to bring these technologies into the market.Polymers-N-based, amino acids and peptides, P and S compounds, chelating agents and organometallic complexes, nanoparticles, or composites are claimed to be active against biofilm formation. Such compounds are presented in this work, and in rare cases, they are described as compositions ready for use as marketable products.     

Are significant inventions more diversified?

This study aims at exploring whether significant inventions are more technologically diversified or have more diverse applications, investigating whether there are any innovation laws existing in R&D activities. Based on technology co-classification analysis, we select patent dataset meets the specific standard from the worldwide patent database named Derwent Innovations Index as sample dataset. Three indicators out of four verify the proposed hypotheses, i.e., significant inventions are more diversified in terms of individual invention. The fourth indicator implies that focusing on some core technology domains maybe better for creating significant inventions when R&D activities are considered as a whole. The results are of great theoretical significance by helping us identifying the diversified characteristic laws of significant inventions; moreover, they are of crucial practical meanings to R&D work and technology innovation activities etc.     

Patents as indicators for the evaluation of industrial research output

Patent indicators are used in the evaluation of industrial research at many different levels of aggregation. They are used in policy-level applications to look at industrial research capability from a national or regional viewpoint comparing, for example, EU regional technology with that of Japan and North America. They are used in strategic-level applications to look at industrial research from a company viewpoint. For example, CHI Research, Inc. has used them to compare auto company research output company-by-company and technology-by-technology. They are used in tactical-level applications, typically involving technology tracing—where the performance of research groups is measured against one another within the domain of a specific technology. At the tactical level these indicators can characterize industrial research in three planes or stages: The early Precursor Plane, the current Technology Plane and the future-oriented Successor Plane. Finally, at the most precise level of evaluation, patent indicator techniques are now beginning to be used in the United States in establishing the value of patent portfolios for cross-licensing purposes, and in patent infringement litigation, where citation techniques demonstrate the importance and utility of patented technology.     

Determining patent filing targets based on patent cost retrieval from Patent Examination Data System

I have utilized Patent Examination Data System (PEDS) to propose a patent filing strategy decomposed by sub-divisions within a Research and Development (R&D) department of a large organization. The unique method relies on breaking the patent cost into fixed cost and variable cost. The variable cost is determined by automatically retrieving data from PEDS. The data includes historical average of number of interactions of a patent applicant with the patent office, grouped by technology domains. The variable cost may then be used in a linear programming model to obtain optimal filing targets for each sub-division within the R&D department. The proposed strategy will help an organization to take objective decisions for determining patent filing targets for its sub-divisions, which will eventually help with an efficient patent strategy for the organization.     

A structured approach to explore technological competencies through R&D portfolio of photovoltaic companies by patent statistics

When the technological development of an enterprise is path dependent, core technological competencies will develop. In addition, core technological competencies promote technological development. Consequently, enterprises should always examine the advantages of their core technological competencies. Under dynamic competition, enterprises should monitor their own performance as well as their competitors at all times and consequently adjust their technological strategies. This study used two patent indices, Patent Share and Revealed Technological Advantage, to measure the internal core technological competencies of manufacturers. It also integrated four other indices namely: (1) Technology Attractiveness (Relative Growth Rate), (2) growth potential of technologies (Relative Development of Technology Growth Rate), (3) Relative Patent Position, and (4) Revealed Patent Advantages. These were used to analyze the external strengths and weaknesses of the research and development (R&D) portfolios of companies. These two analytical methods can effectively identify the internal core technological competencies and the external advantages of R&D portfolios of leading companies in the solar photovoltaic (PV) industry. This study also discussed the relationship between R&D portfolios and core technological competencies of leading solar photovoltaic companies and compared those with two core technological competencies with those that have a single core technological competence. The study results show that the R&D portfolios of companies engaged in a single, specific technology field have advantages. This study helps improve the quality of technological planning and decision-making of manufacturers, proposes a method of using core technological competencies to analyze the advantages of R&D portfolios, and helps solar PV manufacturers monitor their own core technological competencies as well as their competitors and partner companies.     

Research on the impact of global innovation network on 3D printing industry performance

In this study, we attempted to fill a gap that literature has yet to investigate: the impact of global innovation network on industry performance. Based on 3D printing patent data, this paper builds a cooperative innovation network of 34 economies for six years. It represents the network characteristics of each economy through 204 network attribute indicators. The panel data model is used to study the relationship between global innovation network characteristics and the R&D efficiency and the income of the main business of the 3D printing industry. The input and output data for the R&D efficiency of the 3D printing industry is derived from the Wohlers Report. R&D efficiency indicator values are measured by the Malmquist Productivity Index model based on DEA. The research results show that the global innovation network centrality indicators, structural hole indicators and clustering coefficient indicators have significant correlation with industrial performance. The research conclusions will provide theoretical support for various economies to formulate global innovation strategies and policies of 3D printing industry.

     

Mapping the dynamics of knowledge base of innovations of R&;D in Bangladesh: triple helix perspective

Triple helix (TH) collaborations involving university, industry and government provide a networked infrastructure for shaping the dynamic fluxes of knowledge base of innovations locally and these fluxes remain emergent within the domains. This study maps these emergence dynamics of the knowledge base of innovations of Research & Development (R&D) by exploring the longitudinal trend of systemness within the networked research relations in Bangladesh on the TH model. The bibliometric data of publications collected from the Science Citation Index (SCI), the social sciences and the arts and humanities for analysis of science indicators and the patent data collected from the US Patent Office to analyze the patent success ratio as a measure of innovation within TH domains. The findings show that the network dynamics have varied considerably according to the R&D policies of the government. The collaboration patterns of co-authorship relations in the SCI publications prominently increased, with some variation, from 1996 to 2006. Nevertheless, inter-institutional collaboration negatively influenced by the national science and technology (S&T) research policies in the last 5 years due to their evaluation criteria. Finally, the findings reveal that the R&D system of Bangladesh is still undergoing a process of institutionalizing S&T and has failed to boost its research capacity for building the knowledge base of innovations by neglecting the network effects of TH dynamics.     

Patent market dynamics: In view of the business model of non-practicing entities

The emergence of Non-Practicing Entities (“NPEs”) influences patent market dynamics. Based on a database of NPE activities from 1996 to 2010, this paper attempts to investigate these influences in view of NPEs' heterogeneity. We found NPEs with prominent R&D involvements can integrate knowledge from the innovation and patent markets, and might therefore generate valuable patents and facilitate effective technology transfer. Hence, when compared with NPEs without any R&D involvement, R&D-performing NPEs appeared able to monetize their patents without resorting to excessive litigation. Thus, different NPEs could exert different influences and drive patent market dynamics in their own respective ways.     

Induced technological change and the timing of public R&D investment in the Japanese electricity sector considering a two-factor learning curve

The UNFCCC has stated that energy policies and measures to address climate change should be cost-effective to ensure global benefits at the lowest possible cost. To mitigate the bulk of carbon emission from the electricity sector, a large market penetration of renewable energy technologies with as low cost as possible is a key research topic. The energy-related R&D policy in Japan aims to achieve a green economy. In our study, based on this context, we demonstrated how to optimize the timing of public R&D investment within the framework of a bottom-up partial equilibrium model. The developed optimization model represents the Japanese electricity sector and minimizes the total system cost subject to an accumulated carbon emission constraint. Our main research focus is the role of R&D activity, especially in the innovation stage of renewable technologies. We employ a two-factor learning curve and quantify the impact of the learning effect on the dynamic diffusion of major renewable technologies. The study shows a dynamic technology transition in the Japanese electricity sector and the optimized R&D investment schedule for each renewable technology. With the first-best energy policy, an R&D budget of more than 2000 million USD would be allocated to PV in 2050, which corresponds to 45% of the energy-related Japanese R&D budget in 2050. Because some have criticized the uncertainty problems with dynamic simulations and learning models, supplemental sensitivity analyses are included.     

An experimental provision of patent and non-patent documents to research and developmental projects in a scientific research council in Zambia: a comparative evaluation of the value of patent information in scientific and technological research and development

The value of patent information in the transfer of technology to developing countries and its relevance in R&D is assessed by the provision of patent and non-patent documents to R&D projects. The documents were then evaluated by researchers on the basis of: relevance, novelty, extent of disclosure and on ease of adaption of the technologies disclosed. Tabular and statistical data of the evaluation is given.     

Measuring defence R&D: A note on problems and shortcomings

Defence R&D continues to account for a very substantial share of many countries' research effort, often retaining or even increasing its role within the national innovation systems. Yet the quantitative analysis of defence research efforts and their impact is impaired by difficulties in defining defence R&D. The article studies these difficulties and focuses on the issue of identifying what constitutes, does not constitute, defence R&D. It finds that the OECD approach of defining defence R&D on the basis of the primary goals of the research is inadequate, particularly in the present context of the growing emphasis on dual-use technologies and research. It then analyses alternative approaches that could provide a more solid grounding for any systematic effort to collect international defence R&D data     

Effective R&D investment planning based on technology spillovers: the case of Korea

This study was performed to discuss an R&D investment planning method based on the technology spillover among R&D fields, from the point of view of technology convergence. The empirical analysis focused on a particular R&D group, such as university departments and specialized research institutes, since local technology combinations are more effective than distant combinations to create a new technology, according to previous research. In addition, worldwide technology competition is increasing, and with the recent convergence of various technologies and industries, strategies for R&D selection and resources allocation of particular R&D groups are becoming increasingly important. The empirical analysis uses a modified Decision Making Trial and Evaluation Laboratory method combined with information on patent citations to resolve the latent problems of the existing model, using as an empirical example the case of the Korea Institute of Geoscience and Mineral Resources (KIGAM), specialized in the geology and resources development R&D area. Through the empirical analysis, the KIGAM’s current R&D investment status is considered, and a reasonable R&D investment planning is suggested from the perspective of technology spillover. By using this framework, the magnitude of technology spillover from the R&D investment planning within a particular R&D group can be measured based on objective quantitative data, and the current R&D investment can be compared with recent global trends.     

Twenty years of US nanopatenting: Maintenance renewal scoring as an indicator of patent value

This paper introduces a new measure of patent value – Maintenance Renewal Score (MRSc) – reflecting assignee valuing the patent by paying successive renewal fees. We generate MRSc's for nanotechnology patents issued by the US Patent Office from 1999 through 2009, with US assignees and US inventors. Patenting increases over this period, coincident with increased US funding of nanotechnology R&D. We compare maintenance rates over the period, and against a comparison set of all 1999 USPTO grants to US inventors/assignees. We find differences in propensity to maintain the nanopatents by institution type, technological sector, and patent complexity.     

Identifying technological competition trends for R&D planning using dynamic patent maps: SAO-based content analysis

Patent maps showing competition trends in technological development can provide valuable input for decision support on research and development (R&D) strategies. By introducing semantic patent analysis with advantages in representing technological objectives and structures, this paper constructs dynamic patent maps to show technological competition trends and describes the strategic functions of the dynamic maps. The proposed maps are based on subject-action-object (SAO) structures that are syntactically ordered sentences extracted using the natural language processing of the patent text; the structures of a patent encode the key findings of the invention and expertise of its inventors. Therefore, this paper introduces a method of constructing dynamic patent maps using SAO-based content analysis of patents and presents several types of dynamic patent maps by combining patent bibliographic information and patent mapping and clustering techniques. Building on the maps, this paper provides further analyses to identify technological areas in which patents have not been granted (“patent vacuums”), areas in which many patents have actively appeared (“technological hot spots”), R&D overlap of technological competitors, and characteristics of patent clusters. The proposed analyses of dynamic patent maps are illustrated using patents related to the synthesis of carbon nanotubes. We expect that the proposed method will aid experts in understanding technological competition trends in the process of formulating R&D strategies.     

Patent data mining in fisheries sector: An analysis using Questel-Orbit and Espacenet

The advent of an enormous amount of patent data in various patent databases and patinformatics tools to analyze this data have led to an easy access to information for studying the technological trends and R&D activities in a sector. The fisheries sector is driven by the demand and profit generated and there are some unforeseen trends exhibited at different phases of development in specialized areas related to fisheries. In this study we have retrieved patent data of seven technology domains in fisheries, such as Fish, Fish Culture (FC), Fishing Technology (FT), Fish Processing and Products (FPP), Fish Health and Nutrition (FHN), Fish Genetics (FG) and Fish Rearing (FR) during 2000–2015. The legal status of patents, top priority countries and top assignees in different fields of the fisheries sector were analyzed. The results were compared with various developmental trends, indicating a clear relation to industrial ups and downs, the emergence of more patent portfolios in countries coping with latest technology trends and the improper litigation of legal status of the patents filed in the fisheries sector. Patent analysis in a specialized sector could be used as a potential tool in global policy debates, where fish as a natural resource is over-exploited without realizing its real potential.     

Identifying rapidly evolving technological trends for R&;D planning using SAO-based semantic patent networks

Patents constitute an up-to-date source of competitive intelligence in technological development; thus, patent analysis has been a vital tool for identifying technological trends. Patent citation analysis is easy to use, but fundamentally has two main limitations: (1) new patents tend to be less cited than old ones and may miss citations to contemporary patents; (2) citation-based analysis cannot be used for patents in databases which do not require citations. Naturally, citation-based analysis tends to underestimate the importance of new patents and may not work in rapidly-evolving industries in which technology life-cycles are shortening and new inventions are increasingly patented world-wide. As a remedy, this paper proposes a patent network based on semantic patent analysis using subject-action-object (SAO) structures. SAO structures represent the explicit relationships among components used in a patent, and are considered to represent key concepts of the patent or the expertise of the inventor. Based on the internal similarities between patents, the patent network provides the up-to-date status of a given technology. Furthermore, this paper suggests new indices to identify the technological importance of patents, the characteristics of patent clusters, and the technological capabilities of competitors. The proposed method is illustrated using patents related to synthesis of carbon nanotubes. We expect that the proposed procedure and analysis will be incorporated into technology planning processes to assist experts such as researchers and R&D policy makers in rapidly-evolving industries.     

The more you spend, the more you get? The effects of R&D and capital expenditures on the patenting activities of biotechnology firms

This paper provides evidence on the mechanisms influencing the patent output of a sample of small and large, entrepreneurial and established biotechnology firms from the input of indirect knowledge acquired from capital expenditures and direct knowledge from in-house R&D. Statistical models of counts are used to analyse the relationship between patent applications and R&D investment and capital expenditures. It focuses on biotechnology in the period 2002–2007 and is based on a unique data set drawn from various sources including the EU Industrial R&D Investment Scoreboard, the European Patent Office (EPO), the US Patent and Trademark Office, and the World Intellectual Property Organisation. The statistical models employed in the paper are Poisson distribution generalisations with the actual distribution of patent counts fitting the negative binomial distribution and gamma distribution very well. Findings support the idea that capital expenditures—taken as equivalent to technical change embodied in new machinery and capital equipment—may also play a crucial role in the development of new patentable items from scientific companies. For EPO patents, this role appears even more important than that played by R&D investment. The overall picture emerging from our analysis of the determinants of patenting in biotechnology is that the innovation process involves a well balanced combination of inputs from both R&D and new machinery and capital equipment.