ABSTRACT
In 2020, the Government of Japan declared "2050 carbon neutral" and launched a long-term strategy to create a "virtuous cycle of economy and environment". Japanese firms possess many technologies that contribute to decarbonization, which is important to expand investment for Green Technology (environmental technology) development. As automobiles are major contributors to greenhouse gas emissions [1], the technological shift towards vehicle powertrain systems is an attempt to lower problems like emissions of carbon dioxide, nitrogen oxides [2]. On the other hand, patent data are the most reliable business performance for applied research and development activities when investigating the knowledge domains or the technology evolution (Wand, 1997). Our paper describes a Japanese patents dataset of the vehicle powertrain systems for hybrid electric vehicle (HEV), battery electric vehicle (BEV) and fuel cell electric vehicles (FCEV). In this paper we create a method of bombinating international patent classification (IPC) and keywords to define "green" patents in vehicle powertrains field, using patent data which were applied to Japan Patent Office recorded on EPO's PATSTAT database during 2010â¼2019 year. When analyze patents, it is necessary to consider the social situation of each country including language background, we collect patents description documents (abstracts and titles) not only written in English but also in Japanese. Finally, we build a database includes 6025 green patents' description documents and 266 patents' holding firms. With which we then identify 3756 HEV patents, 1716 BEV patents, and 553 FCEV patents. Data about patent holding firms is also appended. The full dataset may be useful to researchers who would like to do further search like natural language processing and machine learning on patent description documents, statistical data analysis for empirical economics.
ABSTRACT
Patent bibliometrics data are the most reliable business performance metric for applied research and development activities when investigating the knowledge domains or the technological evolution of vehicle powertrain technologies in the automotive industry. Our paper describes a global patents dataset for the internal combustion engine vehicles (ICEV), hybrid electric vehicles (HEV) and battery electric vehicles (BEV) over 1985-2016. We extracted the patents granted in each powertrain field from Thomson Reuters' Derwent Innovations Index (DII). We applied a combined search strategy of international patent classifications (IPCs) and keywords as well as 'patent families' and 'priority dates' to construct our global patents dataset. This strategy returned a total of 78,732 patents, within which we identified 49,154 ICEV patents; 10,888 HEV patents; and 18,690 BEV patents. Our database includes numerous descriptive features of each patent such as title, abstract, claim, priority, application and publication dates, IPCs, assignees/applicants, inventors, and cited references. These data are associated with the research article 'The evolution of dynamic interactions between the knowledge development of powertrain systems' [1]. The full dataset, which is attached to this article, may be useful to both researchers and practitioners interested in investigating, modelling or forecasting the complexity and evolution of the technical and knowledge domains of the vehicle powertrains, across a variety of instruments such as social network analysis and regression models.
ABSTRACT
The emergence of networks is a crucial channel for automotive organisations to build and diffuse the required environmental innovations in the transportation sector and accelerate the transition to the green mobility economy. This article contains the dataset regarding the global patents networks shaped both within and between the three vehicle powertrains of internal combustion engine vehicle (ICEV), hybrid electric vehicle (HEV) and battery electric vehicle (BEV) for the period of 1985-2016. The data was acquired from Thomson Reuters' Derwent Innovations Index (DII) platform using the elements of 'patent families' and 'priority dates'. We describe the dataset for the three major automotive periods of 'towards sustainable mobility' (1985-1996), 'towards hybridisation' (1997-2007), and 'towards mass commercialisation' (2008-2016). The dataset bears on two levels, individual and mutual, and we used a separate combined search strategy of keywords and IPCs codes (international patent classification) for each level. At individual level, we explored the internal network features of each powertrain individually (i.e. ICEV, HEV, and BEV). Monitoring a total of 78,732 patents in the three individual powertrain networks, we discovered a total of 1856 unique parent organisations connecting vis-à-vis 5849 bilateral relationships and operating around 4450 joint patents. At mutual level, we explored the mutually common network features of the powertrains (i.e. ICEV-HEV, HEV-BEV, and BEV-ICEV). Monitoring a total of 4702 patents in the three mutual powertrain networks, we discovered a total of 102 unique parent organisations connecting vis-à-vis 384 bilateral relationships and operating around 303 joint patents. These organisations were found specialised around 435 unique subgroup-level IPC codes, of which 134 codes were related to environmentally friendly innovations. The dataset presented in this article is used in [1] and allows researchers not only to map and model the network dynamics and structures within and between the powertrains at global level, but also to analyse and forecast their knowledge flows, technical domains and environmental innovations aspect, using a wide range of models such as social network analysis or regression.
ABSTRACT
OBJECTIVE:To study the characteristics of patent behaviors of Chinese pharmaceutical demonstration enterprises for intellectual property,and to provide reference for the improvement of patent behaviors in Chinese pharmaceutial enterprises. METHODS:After retrieving the applicants(patentees)from China Intellectual Property Right Net on the basis of taking 7 pharma-ceutical demonstration enterprises chosen through appraisal by State Intellectual Property Office of the P.R.C in 2013 as the study samples,empirical study was conducted on their patent behaviors during 1985 and 2013,including the number and type of the pat-ents for which applications were made,international patent classification and legal status. RESULTS:The number of patent applica-tions of the 7 pharmaceutical demonstration enterprises demonstrated a growing trend(an annual increase up to 79.0%). The appli-cations were dominated by the inventive patent(84.9%). Many patents were in an authorized legal status(46.7%). All of these en-terprises paid more attention to the maintenance of the authorized patent. The technology patent applications were mainly about chemical compound,composition,and preparation methods,including the technical proposal containing the active ingredients and properties of the pharmaceutical preparation (A61K),particularly the application of the technical proposal related to the treatment with the preparation (A61P). CONCLUSIONS:All the 7 pharmaceutical demonstration enterprises were aware of patent competi-tion and protection and characterized by a higher proportion of the application for the inventive patent,perfect patent information management institution and high-quality patent applications. Chinese pharmaceutical enterprises can enhance their competitiveness and creativity through adjusting patent behaviors and increasing their awareness of patent competition.
ABSTRACT
Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.
ABSTRACT
Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.
