Search results

Patent contains vast information on developed technologies because of the patent system. So, it is important to analyze patent data for understanding technologies. Most previous studies on patent analysis were focused on the technology itself. Their research results lacked the consideration of products. But the patent analysis based on products is crucial for company because a company grows by sales of competitive products. The purpose of this paper is to propose a novel methodology of patent analysis for product-based technology. This study contributes to the product development strategy of a company.

The primary goal for developing technology is to release a new product. So it is important to analyze the technology based on the product. In this study, the authors analyze Apple’s technologies based in iPod, iPhone, and iPad. In addition, the authors propose a new methodology to analyze product-based technology. The authors call this an integrated social network mining (ISNM). In the ISNM, the authors carry out a social network analysis (SNA) according to each product of Apple, and integrate all SNA results of iPod, iPhone, and iPad using the technological keywords.

In this case study, the authors analyze Apple’s technologies according to Apple’s innovative products, such as the iPod, iPhone, and iPad. From the ISNM results of Apple’s technology, the authors can find which technological detail is more important in overall structure of Apple’s technologies.

This study contributes to the management of technology including new product development, technological innovation, and research and development planning. To know the technological relationship between whole technologies based on products can be the source of intensification of technological competitiveness.

Most of studies on technology analysis were focused on patent technology itself. Though one of their research goals was to develop new product, they had their limits considering the products because they did not use the technology information in the technology analysis. The originality of this research is to use the product information in technology analysis using the proposed ISNM.

The convergence of industries exposes the involved firms to various challenges. In such a setting, a firm's response time becomes key to its future success. Hence, different approaches to anticipating convergence have been developed in the recent past. So far, especially IPC co-classification patent analyses have been successfully applied in different industry settings to anticipate convergence on a broader industry/technology level. Here, the aim is to develop a concept to anticipate convergence even in small samples, simultaneously providing more detailed information on its origin and direction.

The authors assigned 326 US-patents on phytosterols to four different technological fields and measured the semantic similarity of the patents from the different technological fields. Finally, they compared these results to those of an IPC co-classification analysis of the same patent sample.

An increasing semantic similarity of food and pharmaceutical patents and personal care and pharmaceutical patents over time could be regarded as an indicator of convergence. The IPC co-classification analyses proved to be unsuitable for finding evidence for convergence here.

Semantic analyses provide the opportunity to analyze convergence processes in greater detail, even if only limited data are available. However, IPC co-classification analyses are still relevant in analyzing large amounts of data. The appropriateness of the semantic similarity approach requires verification, e.g. by applying it to other convergence settings.

Under such circumstances, how to assign the highest priority for future products which will create the greatest value will be the key success factor for a product planning model. The purpose of this study is to construct an improved planning model for new products based on the theoretical structures of technology roadmaps and patent analysis.

This study takes the perspective of a product planning strategy, using technology roadmap developed by Institute of Manufacturing Technology of the University of Cambridge, combining with scenario planning and patent analysis. The main body of the proposed model is the technology roadmap of the product. Through patent analysis, the technology roadmap was integrated into the hierarchical execution of product planning to improve the disadvantages of the original technology roadmap and thereby clarify the content of the implemented procedure. With the planning of digital home products in a large household appliance manufacturer in China as a case study, the feasibility of the proposed model was verified.

The improved planning model for new products comprised five planning phases: market scenario planning, product feature analysis, technological development analysis, patent combination analysis, and resource allocation. A matrix corresponding to product planning was established. The case study is to find out the developing trends in next‐generation product features in six different scenarios of digital home for M, a home appliance manufacturer. There are five steps of the product planning model. The product planning model provides enterprises with integrated information from market demand, technology as well as patents. At the same time, it is easy to maintain and reproduce. The authors expect the model to make a contribution to practical product planning.

This model should become an essential prediction tool for enterprises developing new products and can assist in decision‐making and strategic implementation.

Using the large database of patent, the purpose of this paper is to structure a technology convergence network using various patent network analysis for integrating different results according to network characteristics.

The patent co-class analysis and the patent citation analysis are applied to discover core safety fields and technology, respectively. In specific, three types of network analysis, which are centrality analysis, association rule mining analysis and brokerage network analysis, are applied to measure the individual, synergy and group intensity.

The core safety fields derived from three types of network analysis used by different nature of data algorithms are compared with each other to understand distinctive meaning of cores of patent class such as medical safety, working safety and vehicle safety, differentiating network structure. Also, to be specific, the authors find the detailed technology contained in the core patent class using patent citation network analysis.

The results provide meaningful implications to various stakeholders in organization: safety management, safety engineering and safety policy. The multiple patent network enables safety manager to identify core safety convergence fields and safety engineers to develop new safety technology. Also, in the view of technology convergence, the strategy of safety policy can be expanded to collaboration and open innovation.

This is the initial study on applying various network analysis algorithms based on patent data (class and citation) for safety management. Through comparison among network analysis techniques, the different results are identified and the collective decision making on finding core of safety technology convergence is supported. The decision maker can obtain the various perspectives of tracing technology convergence.

The Supreme Court’s decision in Federal Trade Commission v. Actavis, Inc. is a challenge to conventional antitrust analysis. Conventional civil antitrust cases are decided by a preponderance of the evidence. This means that conduct challenged under the rule of reason is only condemned if the conduct resulted in more competitive harm in the actual world than a world without the alleged violation. Under conventional analysis, the intent of the parties also plays only a supporting role in determining whether the conduct was anticompetitive. A holder of a valid patent has a right to exclude others practicing the patented technology. And, the patent holder is not assumed to have market power because it expended resources in maintaining exclusionary rights. Actavis creates doubts about these propositions in circumstances beyond the “reverse” payment settlement of a patent suit that may have delayed an alleged infringer market entry. This chapter explores whether applying Actavis logic to antitrust litigation can result in condemnation of practices where there is little chance of an anticompetitive effect, where the patent holder likely has a valid and infringed patent, where there is little reason to believe that the patent holder has market power, and where only one party, or no parties, to an agreement have an anticompetitive intent. This chapter also investigates whether Actavis creates new problems with standing analysis, damages calculations, and the balancing of efficiencies against anticompetitive effects. Nevertheless, the lower courts have begun to extend the logic of Actavis. This is apparent in the condemnation of no-Authorized-generic settlements.

An increasing amount of attention is being paid to three-dimensional (3D) printing technology. The technology itself is based on diverse technologies such as laser beams and materials. Hence, 3D printing technology is a converging technology that produces 3D objects using a 3D printer. To become technologically competitive, many companies and nations are developing technologies for 3D printing. So to know its technological evolution is meaningful for developing 3D printing in the future. The paper aims to discuss these issues.

To get technological competitiveness of 3D printing, the authors should know the most important and essential technology for 3D printing. An understanding of the technological evolution of 3D printing is needed to forecast its future technologies and build the R & D planning needed for 3D printing. In this paper, the authors propose a methodology to analyze the technological evolution of 3D printing. The authors analyze entire patent documents related to 3D printing to construct a technological evolution model. The authors use the statistical methods such as time series regression, association analysis based on graph theory, and principal component analysis for patent analysis of 3D printing technology.

Using the proposed methodology, the authors show the technological analysis results of 3D printing and predict its future aspects. Though many and diverse technologies are developed and involved in 3D printing, the authors know only a few technologies take lead the technological evolution of 3D printing. In this paper, the authors find this evolution of technology management for 3D printing.

If not all, most people would agree that 3D printing technology is one of the leading technologies to improve the quality of life. So, many companies have developed a number of technologies if they were related to 3D printing. But, most of them have not been considered practical. These were not effective research and development for 3D printing technology. In the study, the authors serve a methodology to select the specific technologies for practical used of 3D printing.

Diverse predictions for 3D printing technology have been introduced in many academic and industrial fields. Most of them were made by subjective approaches depended on the knowledge and experience of the experts concerning 3D printing technology. So, they could be fluctuated according to the congregated expert groups, and be unstable for efficient R & D planning. To solve this problem, the authors study on more objective approach to predict the future state of 3D printing by analyzing the patent data of the developed results so far achieved. The contribution of this research is to take a new departure for understanding 3D printing technology using objective and quantitative methods.

The purpose of this paper is to analyze the wind energy technologies using the social network analysis based on patent information. Analysis of patent documents with social network analysis is used to identify the most influential and connected technologies in the field of wind energy.

In the literature, patent data are often used to evaluate technologies. Patents related to wind energy technologies are obtained from the United States Patent and Trademark Office database and the relationships among sub-technologies based on Corporate Patent Classification (CPC) codes are analyzed in this study. The results of two-phase algorithm for mining high average-utility itemsets algorithm, which is one of the utility mining algorithm in data mining, is used to find associations among wind energy technologies for social network analysis.

The results of this study show that it is very important to focus on wind motors and technologies related to energy conversion or management systems reducing greenhouse gas emissions. The results of this study imply that Y02E, F03D and F05B CPC codes are the most influential CPC codes based on social network analysis.

Analysis of patent documents with social network analysis for technology evaluation is extremely limited in the literature. There is no research related to the analysis of patent documents with social network analysis, in particular CPC codes, for wind energy technology. This paper fills this gap in the literature. This study explores technologies related to wind energy technologies and identifies the most influential wind energy technologies in practice. This study also extracts useful information and knowledge to identify core corporate patent class (es) in the field of wind energy technology.

The purpose of this paper is to discuss the issue of relevance in full‐text patent document searches from the viewpoint of end‐users in science and technology. It aims to present three cases of patent document analysis for relevance, with an additional case of improved search profile with increased relevance, and to summarise the findings in the form of instructions for users.

Two methodological approaches were used for the analysis of patent documents: value‐added processing of the bibliographic part of patent documents for the identification of trends; and structuring of data into systems for the determination of patent relevance. Overall, four sets of full‐text patent documents were analysed, covering the topics of: microencapsulated phase change materials; digital photography and image sensors; patent document processing; and patent analysis.

Value‐added analysis of the bibliographic parts of patent documents is a quick and useful option for the recognition of research trends. However, where non‐relevant patent documents are present in a data set, automatic bibliographic analysis may lead to conclusions that are mathematically and statistically correct, but that are not reliable or may even be incorrect for the user's research. Non‐adequate terminology is one of the main obstacles to relevant patent searches, especially if well‐defined keywords are non‐existent, as with cases of newly emerging and fast developing scientific and technological fields.

Based on the bibliographic and content analyses of patent documents, the paper provides instructions for users in the form of ten general rules for increasing the relevance of full‐text patent document searches.

This study aims to propose a methodology by integrating three approaches, namely, internal core technology, external knowledge flow and industrial technology development to help companies improve their decision-making quality for technology planning and enhance their research and development (R&D) portfolio efficiency.

The primary focus of this study is thin-film solar technology and patent data is retrieved from the United States Patent and Trademark Office (USPTO) database. This study presents a methodology based on the proposed integrated analysis method, constructed with patent indicators, centrality analysis of social networks and main path analysis.

The results of this study can be itemized as – the core technological competency: companies involved in two specific technology fields have lower strength in R&D portfolio than leading companies with single-core technology. Knowledge flow: most companies in a network are knowledge producers/absorbers and technological development: diverse source and sink nodes were identified in the global main path during 1997-2003, 2004-2010 and 2011-2017.

Latecomer companies can emulate leaders’ innovation and enhance their technological competence to seek niche technology. Using the global main path, companies monitor outdated technologies that can be replaced by new technologies and aid to plan R&D strategy and implement appropriate strategic decisions avoiding path dependency.

The knowledge accumulation process helps in identifying the change of position and the role of companies; understanding the trend of industrial technology knowledge helps companies to develop new technology and direct strategic decisions. The novelty of this research lies in the integrated approach of three methods aiding industries to find their internal core technical competencies and identify the external position in the competitive market.

The evolution of technology has become the mainstream of the current technological innovation era. Technological change is organized in its unique pattern and a new approach that takes place in a systematic and selective manner. Such change is generally molded with the amalgamation of various factors, namely, economic, social or scientific and technological. This paper aims to focus on identifying technological trajectories in a technological ecosystem with the case of m-payment technology.

This study constructs a patent citation network for mobile payment service technology through patent citation data and identifies the main evolution process using the main path analysis of the network. The scope of this study focuses on key innovation using social network analysis and patent citation network, validated using the case of a mobile payment system and analyzing its technological trajectory.

Analyzing technology evolution provides a greater insight of the overall technology landscape to the researcher and practitioner. Analyzing the m-payment technology landscape gives three main categories of m-payment systems: the mobile financial transaction system), the payee mobile device payment selection system and e-wallet services.

The novelty of this research lies in the process of identifying technological evolution using social network and patent citation network analysis. The case of m-payment technology ecosystem is studied quantitatively which is not explored by previous researchers. This research provides a way to develop the main path technology of innovative products or services to identify technology evolution using the case of m-payment landscape.