Identifying potential users of technology for technology transfer using patent citation analysis: a case analysis of a Korean research institute

The purpose of this study is to examine whether patent citation analysis can be used for making decisions of technology transfer. More precisely, the authors of this paper are interested in the matter of identifying potential users of technology by patent citation analysis. Previous research relied on patents’ keywords, and as a consequence it was difficult to implement in practice where organizations retain huge number of patents to transfer. In this study, we attempt to use IPCs instead of keywords. Our approach is to identify dominant IPC and sub-classes of an organization by applying co-classification analysis, and explore firms that cited the patents in the dominant IPC. Our view is that the organizations explored in this process can be potential users of technology. To verify our view, we examined the patents and technology transfer cases of two divisions in K Research Institute in Korea. The results show that our view was right only for a limited field. We suppose that the reasons may stem from technological characteristics and firm size effect. Therefore, we suggest that there should be further research considering technological characteristics and firm size.     

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.     

Structural decomposition of technological domain using patent co-classification and classification hierarchy

Scientometrics - This paper proposes a new method for decomposing a technological domain (TD). Specifically, the method identifies sub-TDs at the different levels of technological hierarchy within...     

Exploitation of patent information in R&D output analysis for policymaking

Scientometrics - This paper provides an insight into the growing importance and conditions of studying R&D output and impacts as well as the internationalisation of R&D. Focusing on...     

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.     

Mapping Korea’s national R&;D domain of robot technology by using the co-word analysis

In this paper, we show a “Strategic Diagram” of the robot technology by applying the co-word analysis to the metadata of Korean related national R&D projects in 2001. The strategic diagram shows the evolutionary trends of the specific R&D domain and relational patterns between subdomains. We may use this strategic diagram to support both the strategic planning and the R&D Program.     

Productivity of R&D institution: The case of Indonesia

This study analyzes the performance of Indonesian R&D institutions based on R&D productivity. By applying an institutional approach, the effects of collective determinants such as quality of researcher, R&D budgets, locations and ages of R&D institutions on productivity are considered. Our findings show that these performance variables had strong and significant effects on R&D productivity. A national innovation system should be developed in developing countries with different models from those used in developed countries. The non-economic dimension is essential in developing national innovation systems in developing countries such as Indonesia.     

The Role of Time in Assessing the Economic Effects of R&D

This study investigates the impacts of R&D on firm performance. It extends previous research by constructing alternative stocks of R&D‐Capital that take into account that time plays an important role in assessing the pay‐off of industrial research. The results show that even when we employed R&D‐Capitals that placed more emphasis on the industrial research that had been undertaken 7 years ago, the effects of R&D were very (statistically) significant and relatively high, thereby suggesting that the life of R&D (on average) tends to be long. The results however, vary across organizations depending on both firm size and the technological opportunities that a company faces. It appears that the depreciation rate of R&D investments is higher in the case of technologically sophisticated firms. In contrast, strategic investments in industrial research generate a relatively constant effect on the performance of other firms, supporting the notion that the corresponding returns for such firms decay slowly.     

Analyzing technology impact networks for R&D planning using patents: combined application of network approaches

Recently, national governments have tried to improve technology ecology, by formulating research and development (R&D) policies and investing in R&D programs. For strategically designed national R&D plans, analytic approaches that identify and assess the impact of each technology from short-term and long-term perspectives are necessary. Further, in methodological perspective, the approaches should be able to synthetically consider the most recent technological information, the direct and hidden impacts among technologies, and the relative impacts of the focal technology in globally-linked technological relationship from the overall perspective. However, most previous studies based patent citation networks are insufficient for these requirements. As a remedy, we present a combined approach for constructing a technology impact network and identifying the impact and intermediating capability of technology areas from the perspective of a national technology system. To construct and analyze the technology impact network, our method integrates three network techniques: patent co-classification (PCA), decision making trial and evaluation laboratory (DEMATEL), and social network analysis (SNA). The advantages of the proposed method are threefold. First, it identifies the directed technological knowledge flows from the most recent patents, by employing PCA. Second, the proposed network contains both the direct and indirect impacts among different technology areas, by applying the DEMATEL method. Third, using SNA, the method can analyze the characteristics of the technologies in terms of the comprehensive impacts and the potential brokerage capabilities. The method is illustrated using all of the recent Korean patents (58,279) in the United States patent database from 2008 to 2012. We expect that our method can be used to provide input to decision makers for effective R&D planning.     

Assessing the Effectiveness of Quantitative and Qualitative Methods for R&D Project Proposal Evaluations

Abstract:

R&D project success and value is often difficult to predict at the proposal stage. Evaluation methods and their effectiveness vary considerably and are influenced by specific organizational cultures and managerial skill sets. A two-year field study examined the strength, challenges, and limitations of various R&D project evaluation and selection methods. The results suggest that for many project situations, the decision-making process must go beyond analytical methods. It should include both quantitative and qualitative measures and be linked with the internal and external support groups, as well as be strategically aligned with the enterprise. This article identifies specific managerial actions and organizational conditions for evaluating and selecting R&D proposals, aimed at optimizing future value and chances of success.     

Systemic aspects of R&D policy subsidies for R&D collaborations and their effects on private R&D

This paper analyses how context- and time-dependent factors determine the impact of R&D subsidies on firm behaviour with respect to private R&D expenditures. Based on German R&D survey data, we combine propensity score matching with a difference-in-difference estimator in order to measure the causal influence of public direct R&D project funding on firm behaviour. Our results indicate that (i) repeated participation in R&D projects on average leads to a higher increase in R&D expenditures than once-off funding; (ii) the aggregate effect of R&D funding on R&D expenditures of business firms is somewhat higher for business–business collaboration projects than for science–business collaboration projects; (iii) R&D expenditures of business firms that cooperate with science show a higher share of external R&D spending. Results of one particular cluster programme indicate that at least the short-term development of R&D does not so much depend on which programme direct R&D project funding is applied to.     

Patent analysis of wind energy technology using the patent alert system

Using publicly available information effectively is important to remain competitive in technology related industries. The main difficulty in this is determining how to use the information effectively and in a manner that will yield results that can be acted upon. Several different methodologies are being developed in the Technology Watch area of research including the Patent Alert System (PAS) by Dereli and Durmusoglu. By using two different variations of the Patent Alert System, this paper will analyze two different technologies based on wind energy. These variations include Linear Regression based PAS and Fuzzy Logic based PAS. Each approach uses a different methodology to evaluate the available data and generate a trend that will be used to predict future values of patent counts in the applied area of technology. The results of these different approaches are compared in order to determine if either method produces more reliable results which would then lead to better decisions by the organization. In order to connect the results with real-world events, trend changes will be evaluated against global events which should have an impact on technological development in this area.     

Digitalization and CO2 emissions: Dynamics under R&D and technology innovation regimes

New digital technologies help to curtail those that are carbon intensive but are accompanied by CO₂ emissions due to their own energy demand. Whether digitalization relates to increased or decreased carbon emissions may depend on the sophistication of an economy's research and development (R&D) output. This study explores the R&D-induced regime transition that governs the relationship between digitalization and CO₂ emissions. The study seeks evidence of the environmental Kuznets curve hypothesis and tests it with a panel smooth transition regression (PSTR). Employing this estimator with two R&D output regimes makes it possible to account for year- and country-varying effects of digitalization, human capital, and country income level on CO₂ emission. The research covers 55 high- and middle-income economies from 1996 to 2019. The paper finds that the transition process is driven by R&D output level – measured in technology patents per country inhabitants. The findings support the environmental Kuznets curve hypothesis and confirm that CO₂ emissions have an inverted U-shaped relationship with digitalization and income level. This nonlinear relationship transitions smoothly in the exogenous R&D output level. The digitalization indicator in the lower R&D regime has a significant point estimate of 0.07; in the higher regime, the estimate is −0.14. The R&D output threshold at which the transition function switches between the two regimes corresponds to a level of 39.9 technology patents per million inhabitants.     

Energy R&D: investment challenge

Despite dependence on foreign oil that keeps countries like the US embroiled in the Middle East, and amid fears of global warming, research and development (R&D) funding for energy technologies has declined significantly during the last two decades throughout the industrial world. Investments in energy technology R&D, and in associated human and institutional capacity, are fundamental to our ability to respond to changing economic, energy, and environmental needs.Although there has been a recent wave of interest in R&D policy in general, and energy R&D in particular, this has not been translated into the needed increases in funding. In most OECD (Organization for Economic Co-operation and Development) member countries, government energy technology R&D budgets have been declining significantly in real terms since the early 1980s. The trends are particularly troubling given the pressing need to develop and utilize the clean energy and low carbon fossil-fuel energy technologies that will be critical in meeting our future energy needs, while addressing the local and global environmental problems we are facing.     

Assessing the Effects of International Trade on Private R&D Expenditures in the Food Processing Sector

This study empirically investigates the effects of imports and exports on private research and development (R&D) expenditures in the food processing sector. An analytical framework discussing the various effects of international trade on R&D activities is presented. This is followed by an empirical analysis that uses a dynamic empirical specification for current R&D expenditures and for a cumulative measure of R&D stock. The empirical investigation is applied to a panel dataset covering Organization for Economic Cooperation and Development's countries. The empirical results show that increases in import intensity levels induce reductions in private R&D expenditures whereas increases in export intensity levels promote larger private R&D expenditures. These outcomes imply that the R&D-enhancing effects of exports are countered by the R&D-reducing effects of imports.     

The effects of R&D subsidies and network embeddedness on R&D output: evidence from the German biotech industry

Although policy makers subsidize firms’ R&D projects to increase innovational output in an industry, region, or country, it remains unclear whether such subsidization triggers additional R&D efforts or crowds out private investments. To address this question, we assess the effectiveness of subsidization for individual and collaborative research in the German biotech industry while also examining the relevance of network embeddedness for patent output. Our results indicate that subsidies do lead to increased patent output, with additional benefits from involvement in more than one project. However, the amount of money is only significant under certain circumstances. Also, it is higher degree centrality in the firm network that significantly increases R&D success.     

Firm size and compositions of R&D expenditures: evidence from a panel of R&D performing manufacturing firms

The effect of firm size on diverse compositions of R&D expenditures is analysed in detail using firm-level data on the Korean manufacturing sector. On the grounds that each type of R&D activity differs in terms of salability in disembodied form and growth potential due to innovation, a distinction between product vs. process, and new vs. incremental R&D is made. Empirical tests show that the firm size is significantly associated with both the new and incremental R&D. Moreover, firm size is found to be significantly associated with other types of R&D compositions such as the share of R&D devoted to incremental innovation and multidimensional combinations of product, process, new and incremental R&D. These findings support the idea that large firms possess innovative advantages over smaller firms and firm size is an important determinant for firms’ heterogeneous R&D activities. We also discuss the limitations and the implications of the findings.     

A fuzzy ANP-based approach to R&D project selection: A case study

Research and development (R&D) project selection is a complex decision-making process. It involves a search of the environment of opportunities, the generation of project options, and the evaluation by different stakeholders of multiple attributes, both qualitative and quantitative. Qualitative attributes are often accompanied by certain ambiguities and vagueness because of the dissimilar perceptions of organizational goals among pluralistic stakeholders, bureaucracy and the functional specialization of organizational members. Such differences in perceptions often hinder the attainment of consensus and coordination. Therefore, failures are frequent in R&D investment planning. To perceive the preferences of the various stakeholders and to map them into an analytical decision-making framework are challenging tasks. Further, risks and uncertainties are also associated with the investments and returns of R&D projects. This paper illustrates an application of fuzzy ANP (analytic network process) along with fuzzy cost analysis in selecting R&D projects. Fuzzy set theory is incorporated to overcome the vagueness in the preferences. The method adopted uses triangular fuzzy numbers for pair-wise comparison and applies extent analysis followed by defuzzification to determine the weights for various attributes.