Extracting the commercialization gap between science and technology — Case study of a solar cell

In this paper, we compared structures of the citation network of scientific publications with those of patents, and discussed the differences between them. A case study was performed in a solar cell to develop a method of detecting gaps between science and technology. Scientific research has tended to be more basic, especially in terms of cell design, whereas patents have focused on more applied technology used in solar cell modules. Of the major citation clusters of scientific publications, only two, namely silicon and compound solar cells, corresponded semantically with patent clusters. Conversely, there were no patent clusters corresponding to the other two scientific research fronts, namely dye-sensitized and polymer solar cells. These research areas could be regarded as opportunities for industrial commercialization because scientific activities exist but not technological applications. Our results could offer an intellectual basis for discovering potential opportunities for industrial commercialization.     

Types of patents and driving forces behind the patent growth in China

As a developing economy, China's unprecedented patenting surge is puzzling. We study China's patent surge and its driving forces using a novel and comprehensive merged dataset on patent applications filed by Chinese firms. We find that R&D investment, FDI, and patent subsidy have different effects on different types of patents. First, R&D investment has a positive and significant impact on patenting activities for all types of patents under different model specifications. Second, the stimulating effect of foreign direct investment on patent applications is only robust for utility model patents and design patents. Third, the patent subsidy only has a positive impact on design patents. The results imply that FDI and patent subsidy may disproportionately spur low-quality patents.     

Factor analysis and structural equation model for patent analysis: a case study of Apple’s technology

In this study, we analyse patent data for technology analysis (TA) because patents are rich in information on developed technology. The results of TA can be used to perform more efficient research and development (R&D) planning. Most companies are trying to develop new and innovative technologies to improve their competitive positions. Research involving TA has been introduced in a variety of fields. Most of the published research analysed original variables related to a target technology. However, it is necessary to analyse the latent variables as well as the original variables included in the technology to achieve a better TA model. Therefore, we propose a factor analysis and a structural equation model for patent analysis. In addition, we use Apple’s patents to determine the target technology. In our case study, we analyse Apple’s technologies by latent variables. Our case study shows how the proposed model is applied to Apple’s R&D planning.     

Strategic technology editing of the patent stage: lesson from a case of inkjet printer development

Patents are conventionally regarded as representing post-procurement of rights based on results of research and development (R&D). Patents can also be regarded as factors promoting R&D itself. In this study, the author examines the strategic meaning of patents in R&D through analyses of the R&D processes at Canon Inc., which is widely considered to submit patents strategically. The author identified characteristic behaviour related to patent acquisition in the R&D of inkjet printers. Canon constructed a strong patent group precisely by editing patents submitted earlier. Characteristic patent submissions were also identified: they elevated the obtained R&D results to higher concepts as milestones of R&D. These findings are discussed from the viewpoint of the meaning of patents for R&D and the possibility of effective R&D at the patent stage.     

A compared R&D-based and patent-based cross impact analysis for identifying relationships between technologies

The planning of technological research and development (R&D) is demanding in areas with many relationships between technologies. To support decision makers of a government organization with R&D planning in these areas, a methodology to make the technology impact more transparent is introduced. The method shows current technology impact and impact trends from the R&D of an organization's competitors and compares these to the technology impact and impact trends from the organization's own R&D. This way, relative strength, relative weakness, plus parity of the organization's R&D activities in technology pairs can be identified.A quantitative cross impact analysis (CIA) approach is used to estimate the impact across technologies. Our quantitative CIA approach contrasts to standard qualitative CIA approaches that estimate technology impact by means of literature surveys and expert interviews. In this paper, the impact is computed based on the R&D information regarding the respective organization on one hand, and based on patent data representative regarding R&D information of the organization's competitors on the other hand. As an illustration, the application field ‘defence’ is used, where many interrelations and interdependencies between defence-based technologies occur. Firstly, an R&D-based and patent-based Compared Cross Impact (CCI) among technologies is computed. Secondly, characteristics of the CCI are identified. Thirdly, the CCI data is presented as a network to show the overall structure and the complex relationships between the technologies. Finally, changes of the CCI are analyzed over time. The results show that the proposed methodology has the potential to generate useful insights for government organizations to help direct technology investments.     

Determinants of patent value: Insights from a simulation analysis

This paper contributes to understanding the determinants of patent value. By drawing on a real options approach, we develop a theoretical model of patent value, which explicitly considers the uncertainty about future value. On this basis, we rely on Monte Carlo simulations with data from a case study in a large chemical firm to estimate patent value according to our model. In the simulation analyses, we compare an R&D project with patent protection and the same project without patent protection. The difference of the values of the two projects is the surplus in profit that may be expected from having a patent covering the project. This surplus is regarded as the value that is directly attributable to the patent. The results of the simulation analyses indicate that the development costs and expected net cash flows of a patent-protected project are higher than of an unpatented project. The higher net cash flows outgrow the increased development costs, and patent value is positive. However, this value is smaller than the overall project value of the patent-protected R&D project.     

A note on the effect of patents in endogenous growth models

This note examines the effect of patent protection in an endogenous growth model with a generic innovation process. It indicates that increasing patent breadth stimulates innovation when R&D is less intermediates-intensive than production, whereas it has a non-monotonic effect on innovation when the former is more intermediates-intensive than the latter.     

A technology opportunities analysis model: applied to dye-sensitised solar cells for China

Technology opportunities analysis (TOA) can support policy-makers or managers in making strategic technical decisions so as to enhance their technological innovation capability and international competitiveness. This paper presents a multi-level framework to support and systematically identify technological opportunities. Patent data as a key component of technology innovation are used to enable TOA within the framework in the present research. At the research and development (R&D) level, we anticipate the directions of technology development based on technology morphology. Countries’ development emphases can also be investigated in order to help identify their R&D strengths and weaknesses and to seek promising development pathways. At the level of competition, we devise the assignee-technology analysis to obtain insight into competitive participants’ technical emphases and intents. It is also used to explore possible collaboration opportunities among them. At the market level, we apply patent family analysis to understand countries’ target markets and to assess prospects for the commercialisation of their technology. We pursue TOA to explore China's opportunities and challenges in dye-sensitised solar cells. The empirical case analysis supports the effectiveness of the TOA model. We believe it can be adapted well to fit other emerging technologies.     

Accounting for the recent surge in U.S. patenting: changes in R&D expenditures,patent yields,and the high tech sector

We decompose the recent patent increase into components representing (1) an increase in resources made available to research and development, (2) an across-the-board rise in the patent yield of an R&D dollar, and (3) changes in the patent yield in individual industries. Two high tech fields, computer hardware and pharmaceuticals, account for 22 percent of the patent increase. While these two industries had the fastest R&D growth among the industries we study, the pharmaceutical industry experienced a decline in its patent yield, limiting its patent growth. We show that increased R&D spending accounts for 70 percent of the patent increase. We discuss our results in the context of alternative hypotheses of the patent surge. We also compare our results to the anecdotal evidence of firm R&D performance at the industry level.     

Technology variation vs. R&D uncertainty: What matters most for energy patent success?

R&D is an uncertain activity with highly skewed outcomes. Nonetheless, most recent empirical studies and modeling estimates of the potential of technological change focus on the average returns to research and development (R&D) for a composite technology and contain little or no information about the distribution of returns to R&D – which could be important for capturing the range of costs associated with climate change mitigation policies – by individual technologies. Through an empirical study of patent citation data, this paper adds to the literature on the outcomes of energy R&D by focusing on the behavior of the most successful innovations for six energy technologies, allowing us to determine whether uncertainty or differences in technologies matter most for success. We highlight two key results. First, we compare the results from an aggregate analysis of six energy technologies to technology-by-technology results. Our results show that existing work that assumes diminishing returns but assumes one generic technology is too simplistic and misses important differences between more successful and less successful technologies. Second, we use quantile regression techniques to learn more about patents that have a high positive error term in our regressions – that is, patents that receive many more citations than predicted based on observable characteristics. We find that differences across technologies, rather than differences across quantiles within technologies, are more important. The value of successful technologies persists longer than those of less successful technologies, providing evidence that success is the culmination of several advances building upon one another, rather than resulting from one single breakthrough. Diminishing returns to research activities appear most problematic during rapid increases of research investment, such as experienced by solar energy in the 1970s.     

Technology variation vs. R&D uncertainty: What matters most for energy patent success?

R&D is an uncertain activity with highly skewed outcomes. Nonetheless, most recent empirical studies and modeling estimates of the potential of technological change focus on the average returns to research and development (R&D) for a composite technology and contain little or no information about the distribution of returns to R&D – which could be important for capturing the range of costs associated with climate change mitigation policies – by individual technologies. Through an empirical study of patent citation data, this paper adds to the literature on the outcomes of energy R&D by focusing on the behavior of the most successful innovations for six energy technologies, allowing us to determine whether uncertainty or differences in technologies matter most for success. We highlight two key results. First, we compare the results from an aggregate analysis of six energy technologies to technology-by-technology results. Our results show that existing work that assumes diminishing returns but assumes one generic technology is too simplistic and misses important differences between more successful and less successful technologies. Second, we use quantile regression techniques to learn more about patents that have a high positive error term in our regressions – that is, patents that receive many more citations than predicted based on observable characteristics. We find that differences across technologies, rather than differences across quantiles within technologies, are more important. The value of successful technologies persists longer than those of less successful technologies, providing evidence that success is the culmination of several advances building upon one another, rather than resulting from one single breakthrough. Diminishing returns to research activities appear most problematic during rapid increases of research investment, such as experienced by solar energy in the 1970s.     

Tracing the Evolution of Biomedical 3D Printing Technology Using Ontology-Based Patent Concept Analysis

Three-dimensional (3D) printing enables products to be custom-designed and produced using additive manufacturing processes. This research develops a patent analysis approach to explore biomedical 3D printing technology trends. First, the method searches for related patents. Second, frequently appearing key terms in patents are extracted as a means to identify key concepts of inventions. Third, in order to structure the domain knowledge, the ontology is created by referring to the relevant key terms and literature. The key terms create indexes used to measure similarities for clustering the patents and sub-technologies. Based on the patent context and dynamic patent concept analysis maps, the evolutionary trends of technology development are depicted. Biomedical 3D printing R&D projects are used as case examples to compare against co-occurring patent evolutions. The proposed patent concept analysis is generalisable for critical decision support of R&D planning and evaluation in any market sector.     

Patent portfolios and knowledge flow(s) of photovoltaic companies

The current trend towards green energy is encouraging manufacturers to invest in photovoltaic technologies. In order to guarantee R&D and optimal operational performance, operators should be able to identify the technological advantages of their competitors for the conduct R&D and to ensure adequate technological knowledge intake. Therefore, from the perspective of patent portfolios and knowledge flow(s) of photovoltaic companies, this study adopted two approaches namely, patent counts and patent citations, to discuss the technical capability of R&D portfolios and the technological knowledge flow. Three patent indices were utilised for the integration of R&D portfolios which include: technology attractiveness, relative patent position, and revealed patent advantage. Technological knowledge flow allows construction of a patent citation network through backward citation of patents. Sources and movement directions of technological knowledge are measured by calculating the relative citation propensity. R&D portfolios and knowledge flow are complementary perspectives of each photovoltaic company.     

Innovation strategy and the patenting behavior of firms

This paper investigates whether firms’ innovation strategies affect their patenting behavior, as measured by both the probability of having a patent portfolio and the number of active patents held. Three main dimensions of an innovation strategy are taken into account: the relative importance of basic research, applied research and development work in total R&D activities, the product or process orientation of innovation efforts, and the extent to which firms enter into collaborative R&D with other institutions. The major findings can be summarized as follows: (1) taking into account the various dimensions of an innovation strategy turns out to approximate the patenting behavior of firms better than the traditional Schumpeterian hypotheses related to firm size and market power; (2) there is a positive relationship between the patent portfolio of firms and an outward-oriented innovation strategy characterized by R&D partnerships with external organizations - scientific institutions and competitors in particular; (3) process-oriented innovators patent less than product-oriented innovators; (4) a stronger focus on basic and applied research is associated with a more active patenting behavior; (5) firms that perceive high barriers to innovation (internal, risk-related or external barriers) have smaller patent portfolios; (6) the perceived limitations of the patent system do not significantly influence the patenting behavior, suggesting that firms patent for other strategic reasons than merely protecting innovation rents.     

A hybrid selection model for emerging technology

Technology selection, which influences the advantages of an enterprise or a country, is a multi-criteria decision issue that can be improved by integrating different methods. In addition, it is more and more difficult to identify the right technologies because the technologies are increasing in number and complexity. This study proposes a technology selection process integrating fuzzy Delphi method, analytic hierarchy process (AHP), and patent co-citation approach (PCA) for technology selection. The former effectively gathers experts' judgments toward technology selection criteria and conducts the fuzziness existing in their responses. The analytic hierarchy process has the strength of identifying criteria and obtaining their relationship and their weights. The patent co-citation approach identifies the major R&D fields of a specific technology from patent data. Through this proposed process, the key technology fields can be identified in the end. The organic light emitting diode (OLED) technology in Taiwan is used to be an example to illustrate the proposed technology selection process.     

Marketing and r&d strategies for biotechnology firms in the usa

This pape reports on a survey of 64 biotechnology firms in the USA about their R&D strategy, marketing focud and sources of technology. The survey explored the interrelationships among the strategic issues and how they were related with the means of appropriating R&D results. Three stralegic clusters for technology acquisitin emerged from the data: (i) internal developer, (ii) joint developer, and (iii) cooperative financed. Three marketing clusters were: (i) market penetartor, (ii) innovative marketer, and (iii) market developer. The R&D clusters were: (i) defensive strategy, (ii) aggressive strategy, and (iii) research-intensive strategy. External sources of technology appeared to be predominant among thje various firms and apparently marketing strategy and source of technology had no significant relationship. Most of the firms were involved with commercial innovation in their R&D strategy and few were research specialists. Innovative firms were inclined to depend on external sources sources of technology. Issues related to appropriability of R&D results for the different groups have been examined for their implications for public policy.     

Multistage R&D competition and patent policy

In this paper a model of multistage R&D patent policy is investigated. We study the impact of the duration of patent protection for intermediate products on R&D races when the discovery of the final product requires the accomplishment of an intermediate step. Using a multistage model where firms choose their levels of research investment at each stage, we find all subgame-perfect equilibria of the game. We also determine how competition affects a firm's level of research investment at different stages of the R&D competition.     

Identifying R&D partners for dye-sensitized solar cells: a multi-level patent portfolio-based approach

There is a great and urgent necessity for appropriate data and methods to help organisations select appropriate R&D (Research and Development) partners. In response, this study presents a structured framework for identifying and selecting the R&D partners with the greatest potential to meet a given technological need. The formal methods in the framework include systematic information collection, patent portfolio analysis, technological similarity screening, and semantic evaluation that views subject-action-object (SAO) sentence structures as problem-solution patterns. The results of an empirical evaluation, with dye-sensitive solar cells as the case, demonstrate that using this framework can reveal more appropriate R&D partners for technological needs (TNS) in less time and with less cost than methods based solely on one criterion.     

International talent inflow and R&D investment: Firm-level evidence from China

Using firm-level R&D data with regional international talent data, we find that international talent increases the R&D investment of Chinese manufacturing firms, a result that is further confirmed with patent data and under a number of robustness checks. These findings stem from two mechanisms: international talent boosts human capital accumulation and provides a diversified labor force. Further, the R&D promoting effect is stronger if firms are located in eastern China rather than in other regions, of small and medium-sized rather than large-sized, of domestic ownership rather than foreign ownership. The policy implication is, the introduction of international talent can be a new way to promoting R&D investment, especially for skilled-labor constrained countries.     

The impact of public R&D investments on patenting activity: technology transfer at the U.S. Environmental Protection Agency

ABSTRACT

This paper presents estimates of the impact of public R&D on patenting activity at the U.S. Environmental Protection Agency (EPA). Using a time series of public sector agency data, we estimate the per-capita R&D elasticity of new patent applications using a knowledge production function framework model that is an expanded version of what other scholars have used with private sector data. New patent applications are an important step in the technology transfer activities of a federal agency. We estimate this elasticity to be about 2.0. This elasticity value represents an initial estimate of the impact of EPA’s R&D investments on its technology transfer activity.