Juhwan Kim, Sunghae Jun, Dong-Sik Jang and Sangsung Park
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
Details
Keywords
The keywords from patent documents contain a lot of information of technology. If we analyze the time series of keywords, we will be able to understand even more about…
Abstract
Purpose
The keywords from patent documents contain a lot of information of technology. If we analyze the time series of keywords, we will be able to understand even more about technological evolution. The previous researches of time series processes in patent analysis were based on time series regression or the Box-Jenkins methodology. The methods dealt with continuous time series data. But the keyword time series data in patent analysis are not continuous, they are frequency integer values. So we need a new methodology for integer-valued time series model. The purpose of this paper is to propose modeling of integer-valued time series for patent analysis.
Design/methodology/approach
For modeling frequency data of keywords, the authors used integer-valued generalized autoregressive conditional heteroskedasticity model with Poisson and negative binomial distributions. Using the proposed models, the authors forecast the future trends of target keywords of Apple in order to know the future technology of Apple.
Findings
The authors carry out a case study to illustrate how the methodology can be applied to real problem. In this paper, the authors collect the patent documents issued by Apple, and analyze them to find the technological trend of Apple company. From the results of Apple case study, the authors can find which technological keywords are more important or critical in the entire structure of Apple’s technologies.
Practical implications
This paper contributes to the research and development planning for producing new products. The authors can develop and launch the innovative products to improve the technological competition of a company through complete understanding of the technological keyword trends.
Originality/value
The retrieved patent documents from the patent databases are not suitable for statistical analysis. So, the authors have to transform the documents into structured data suitable for statistics. In general, the structured data are a matrix consisting of patent (row) and keyword (column), and its element is an occurred frequency of a keyword in each patent. The data type is not continuous but discrete. However, in most researches, they were analyzed by statistical methods for continuous data. In this paper, the authors build a statistical model based on discrete data.
Details
Keywords
Sangsung Park, Juhwan Kim, Hongchul Lee, Dongsik Jang and Sunghae Jun
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
Details
Keywords
Sunghae Jun and Sang Sung Park
Apple is a representative company of technological innovation (TI) and management. It has launched new and innovative products since 1977, and many companies and business schools…
Abstract
Purpose
Apple is a representative company of technological innovation (TI) and management. It has launched new and innovative products since 1977, and many companies and business schools around the world have attempted to learn about the success story of Apple's innovation. However, most previous research works on Apple's innovation have been based on qualitative approaches such as experts' opinions. Such studies offer a subjective point of view. By contrast, in this paper the authors aim to study the TI and forecasting of Apple by analyzing its patent applications, which is an objective approach to examining the innovation of Apple from a technological perspective.
Design/methodology/approach
TI is an important issue concerning technology management for companies and governments. To examine Apple's TI, the authors analyze all applied patents and construct analytical models according to three approaches. First, they build statistical models using the time series regression and multiple linear regression methods to create a technology map. Second, they cluster all Apple's patents to find its vacant technology domain. Lastly, they use social network analysis to search for technologies central to Apple's future.
Findings
The authors' study shows the technological trends and relations between Apple's technologies. This research finds vacant technology areas and central technologies for Apple's TI.
Practical implications
Using statistical and machine learning methods, the authors analyze all Apple's patents in order to predict the firm's future technologies. This research contributes to examining the TI of Apple. Therefore, the results of the patent analysis can highlight the technological opportunities for Apple's TI.
Originality/value
Traditional TI models have been based on qualitative methods. Previous investigations of Apple's TI have also relied on traditional analytical approaches. In this paper, however, the authors develop a quantitative and objective approach for examining Apple's TI.
Details
Keywords
Sunghae Jun, Sang Sung Park and Dong Sik Jang
The purpose of this paper is to propose an objective method for technology forecasting (TF). For the construction of the proposed model, the paper aims to consider new approaches…
Abstract
Purpose
The purpose of this paper is to propose an objective method for technology forecasting (TF). For the construction of the proposed model, the paper aims to consider new approaches to patent mapping and clustering. In addition, the paper aims to introduce a matrix map and K‐medoids clustering based on support vector clustering (KM‐SVC) for vacant TF.
Design/methodology/approach
TF is an important research and development (R&D) policy issue for both companies and government. Vacant TF is one of the key technological planning methods for improving the competitive power of firms and governments. In general, a forecasting process is facilitated subjectively based on the researcher's knowledge, resulting in unstable TF performance. In this paper, the authors forecast the vacant technology areas in a given technology field by analyzing patent documents and employing the proposed matrix map and KM‐SVC to forecast vacant technology areas in the management of technology (MOT).
Findings
The paper examines the vacant technology areas for MOT patent documents from the USA, Europe, and China by comparing these countries in terms of technology trends in MOT and identifying the vacant technology areas by country. The matrix map provides broad vacant technology areas, whereas KM‐SVC provides more specific vacant technology areas. Thus, the paper identifies the vacant technology areas of a given technology field by using the results for both the matrix map and KM‐SVC.
Practical implications
The authors use patent documents as objective data to develop a model for vacant TF. The paper attempts to objectively forecast the vacant technology areas in a given technology field. To verify the performance of the matrix map and KM‐SVC, the authors conduct an experiment using patent documents related to MOT (the given technology field in this paper). The results suggest that the proposed forecasting model can be applied to diverse technology fields, including R&D management, technology marketing, and intellectual property management.
Originality/value
Most TF models are based on qualitative and subjective methods such as Delphi. That is, there are few objective models. In this regard, this paper proposes a quantitative and objective TF model that employs patent documents as objective data and a matrix map and KM‐SVC as quantitative methods.