Monitoring the organic structure of technology based on the patent development paths

As the strategic importance of understanding changes in technology for successful business of most firms increases, the ability to analyze and monitor the current stage and history of technology is reckoned as a critical asset both for gaining competitive advantage and identifying promising niches. Patent citation networks have been widely used for systematic and empirical analysis of technology development. Understanding of technology's detailed changes in large patent citation networks, however, is difficult to achieve because of these networks' large and complex structures. To overcome this problem, we suggest an algorithm that identifies patent development paths from a large patent citation network by evaluating the weight of citations between patents. We then apply this algorithm to flash memory patents in an empirical study. Our algorithm is a new methodology that can be used to analyze the dynamic and complex structure of individual technologies.     

Exploring technology diffusion and classification of business methods: Using the patent citation network

Among the many technology forecasting indicators, patents and patent citations are useful and important indicators. The more frequently a certain patent is cited by subsequent patents, the more the related technology can be said to be diffused, implying that the technology is more widely applied and thus more valuable. This paper analyzes the business methods technology which retrieves patents from the USPTO database. There are two purposes of this paper: 1. establish the indicators for finding basic patents and measure the relationship of these basic patents; 2. classify the basic patents and explain the groups of technology diffusion. Finally, this study identifies the two mainstreams in business method technology: one is focused on marketing technology, and the other one stresses on data security. Both are important for Internet data processes or e-commerce activities.     

Keeping abreast of technology-driven business model evolution: a dynamic patent analysis approach

All firms that depend on technology for their competitive positions recognise that keeping abreast of technology-driven business model evolution is of vital importance. However, previous studies cannot offer a concrete way of profiling trends owing to the lack of quantitative data and systematic processes. We propose a dynamic patent analysis that can identify complex relationships among business method patents and visualise trends in technology-driven business model evolution. At the heart of the suggested approach is morphological analysis (MA) for structuring different types of business models at a technological attribute level and modified formal concept analysis (FCA) for investigating technological changes in business models over time. A case study of business method patents concerning electronic shopping is presented to show the feasibility of the proposed approach. We believe our method can promote consensus-building on up-to-date trends in technology-driven business model evolution, serving as a starting point for a more general model.     

A semantic analysis approach for identifying patent infringement based on a product–patent map

Identifying patent infringement beforehand is highly important for reducing the risk of damages. However, as the approach to patents is changing from the technological and legal approaches of the past to the business approach, strategic patent infringement litigation and securement of patents can be important tools for companies. From various viewpoints, companies can consider an aggressive patent infringement litigation as well as evasion strategy of patent infringement litigation to keep competitors in check. Previous research on patent infringement identification only considered the possibility of infringement between patents. However, infringement cases between patent and product are prevalent. Thus, this research aims to suggest an automated method for identifying patent infringement between the patent and product in business. To this end, this paper proposes the subject–action–object (SAO) semantic technological similarity-based product–patent method for generating infringement maps. Several indices and subgrouping methods are suggested to interpret the map. As an exemplary case, data on technology and products related to the light emitting diode (LED) lamp are collected and exploited.     

Business planning based on technological capabilities: Patent analysis for technology-driven roadmapping

This research responds to the needs of technology-driven business by focusing on how firms can find new business opportunities based on their technological capabilities. It proposes a technology-driven roadmapping processes that starts from capability analysis for technology planning and ends with business opportunity analysis for market planning. We suggest the use of patent data as a proxy measure of technological capability for this purpose and develop four analysis modules — Monitoring, Collaboration, Diversification, and Benchmarking — to support decision-making during the process. Various analysis techniques such as text-mining, network analysis, citation analysis and index analysis are applied to discover meaningful implications from the patent data, which are summarized in four maps — Actor-similarity map, Actor-relations map, Technology-industry map, and Technology-affinity map. For the purpose of illustration, RFID-related patents are collected and the 18 firms with the most patents used, focusing especially on the third biggest. We believe using roadmapping and patent analysis together can play complementary roles for each other. Putting roadmapping techniques together with patent analysis can increase the objectivity and reliability of technology roadmap, while using patent analysis restricted to technological information together with roadmapping techniques can ensure that a more valuable breadth of strategic information is extracted from patents.     

Using patent data to analyze trends and the technological strategies of the amorphous silicon thin-film solar cell industry

With the shortage of raw materials for the production of crystalline silicon solar cells, the next generation of solar cells has reached the perfect stage for development. While in the past, researchers have emphasized the development of crystalline silicon solar cells, the application of the next generation of crystalline silicon solar cells is different. Of the thin-film solar cells (TFSCs), the most widely recognized is the amorphous silicon (a-Si) TFSC. It has the greatest potential to be developed, and many manufacturers have already invested in its research and development (R&D). In this study, we employed a set of indicators to analyze the technological development of the a-Si TFSC, and found that the major technology field has reached the mature stage in the technology life cycle of this product; moreover, four patent strategic clusters were identified. The results regarding the company and technology levels of the clusters were integrated with profile data and developmental progress information to understand the patent performance, technologic capacity, and R&D background of the a-Si TFSC.     

基于因子分析法的地区专利发展水平比较研究

专利是一个国家或地区科技资产的核心,专利综合实力是衡量一个国家或地区综合实力以及区域创新能力的重要标志。通过对2008年我国发明、实用新型和外观设计三种专利申请总量排名前20位地区的分析,运用因子分析法评价了其专利发展状况,然后通过分析评价结果指出了各地区的优势与劣势。这对于提升各地区的专利综合实力具有重要的参考价值和借鉴意义,也为各相关部门的政策制定提供了理论决策依据。     

Patterns of technology life cycles: stochastic analysis based on patent citations

Patent analysis has been considered as an effective means of estimating phases of a technology life cycle. However, previous studies have not considered the dynamic and idiosyncratic aspects of a technology’s progression since they were based on deterministic methods, mainly fitting s- or double s-shaped curves to patent application counts. Moreover, previous methods cannot be executed at the individual patent level. We propose a stochastic technology life cycle analysis to trace the phases of a technology’s progression based on patent citations and identify the patterns of technology life cycles at the individual patent level. At the heart of the proposed approach are a hidden Markov model to estimate the probability of a system being at a certain hidden state from observation and cluster analysis to group a set of objects according to their similarities. A case study of patents about laser technology in lithography is presented.     

Utilizing patent analysis to explore the cooperative competition relationship of the two LED companies: Nichia and Osram

This study used patent analysis to explore the co-opetition behavior between the two light emitting diode (LED) manufactures, Nichia and Osram, from the two critical technological fields in the LED industry: LED components and phosphor. The results of patent analysis indicated that Nichia had advantages in the field of LED components, while Osram had advantages in the field of phosphor. Therefore, there existed cooperation opportunities for the two opponents in the LED industry, because their technological capabilities were partially complementary. Therefore, Nichia and Osram were willing to make a compromise to solve the patent litigations between them and further agreed to offer cross-licensing of patents for each other. Their strategic interaction was changed from full competition to co-opetition which is win-win for them. This study demonstrates that patent analysis is a useful tool for R&D management and technical analysis, and the results of this study can provide a valuable reference for managers in formulating patent portfolio.     

A patent-based cross impact analysis for quantitative estimation of technological impact: The case of information and communication technology

The increasing syntheses and interactions between various technologies increase the usefulness of cross impact analysis (CIA) as a method for forecasting and analyzing them. Conventional CIA depends on an expert's qualitative judgment or intuition and thus it is difficult to evaluate quantitatively the impact of one technology on another. In this study, we employ patent analysis in CIA to examine such impacts between technologies based on multiple patent classifications. Patent information is used for facilitating quantitative and systematic approach in CIA. The distinctive feature and main contribution of the proposed approach is the overcoming of the limitations of conventional CIA, by employing conditional probabilities based on the patent information. The classification of patents, particularly the multiple classifications, is used to evaluate the relationships between technologies. As an illustration, a patent-based CIA with information and communication technologies (ICTs) was conducted. Firstly, the patent-based cross impact among ICTs was calculated. Secondly, the technology pairs were classified based on the cross impact score between ICTs. Thirdly, a cross impact network was constructed to identify the complex relation among ICTs. Finally, the changes in cross impact scores between technologies over time were analyzed. The results of this research are expected to help practitioners to forecast future trends and to develop better R&D strategies.     

Technology clustering based on evolutionary patterns: The case of information and communications technologies

Technology trend analysis anticipates the direction and rate of technology changes, and thus supports strategic decision-making for innovation. As technological convergence and diversification are regarded as emerging trends, it is important to compare the growth patterns of various technologies in a particular industry to help understand the industry characteristics and analyse the technology innovation process. However, despite the potential value of this approach, conventional approaches have focused on individual technologies and paid little attention to synthesising and comparing multiple technologies. We therefore propose a new approach for clustering technologies based on their growth patterns. After technologies with similar patterns are identified, the underlying factors that lead to the patterns can be analysed. For that purpose, we analysed patent data using a Hidden Markov model, followed by clustering analysis, and tested the validity of the proposed approach by applying it to the ICT industry. Our approach provides insights into the basic nature of technologies in an industry, and facilitates the analysis and forecasting of their evolution.     

Identifying the structure of knowledge networks in the US mobile ecosystems: patent citation analysis

With the emergence of smartphones, the paradigm of the mobile ecosystem has changed rapidly. In particular, global mobile firms focus on technological competition when jostling for market position in recognition of the strategic need to secure a strong mobile platform. In this paper, we analyse the network structure of technological knowledge flows in mobile ecosystems using US patent citation information. We find that two subsectors, platform providers and application and software providers, are at the centre of knowledge exchange activity and play a brokerage role as the key knowledge mediator. Then, we categorise mobile firms into five different groups based on the patterns of their network centrality: knowledge keystone players, knowledge-distributing mediators, knowledge-absorbing mediators, catch-up players, and pure knowledge receivers. The categorisation of firms demonstrates that knowledge flows in the mobile industry converge towards a few leading firms, and such patterns are shaping the mobile ecosystem with respect to technological knowledge. The firms categorised as catch-up players have played a brokerage role within their group, while the firms categorised as knowledge keystone players play a brokerage role across different groups.     

Personal attitudes in the assessment of the future of science and technology: A factor analysis approach

In 1996, the second German Delphi study (“Delphi '98”) was started. The Delphi '98 is a two-round Delphi expert survey being conducted by the Fraunhofer Institute for Systems and Innovation Research (ISI) on behalf of the German Federal Ministry of Education, Research, Science, and Technology (BMBF). The study was published in February 1998, and is now getting into its implementation phase. Its inherent focus is on the development of science and technology in 12 thematic fields in the next 30 years. To arrive at a better understanding of the influence of personal attitudes towards general developments in natural environment and society, the respondents were asked in the first round of the Delphi survey for their personal opinion towards several megatrends concerning the natural environment, economic, sociological, and political developments. Over 2,300 answers led to a very solid database, which gives insights into the general attitudes of the German R&D experts. On some topics, there is a high consensus, whereas in others, opposite opinions coexist. These results may serve as the database for a factor analysis leading to the identification of five different expert types. This paper examines the crucial question of whether different patterns in assessing the future development in science and technology by expert types can be observed. In general, it turned out that differences in personal attitudes towards megatrends do not influence the estimation of developments in science and technology. However, differences exist in specific topics and the distribution of the five experts types among the respondents differs significantly in the 12 fields.     

International diffusion of embodied and disembodied technology: A network analysis approach

This study proposes a quantitative method for investigating the structure of international technology diffusion. By using network analysis, this study defines the structural configuration of each country within the international diffusion network by measuring its degree, closeness, and betweenness centralities. In addition, this study distinguishes between embodied technology diffusion, measured by multilateral trade, and disembodied technology diffusion, measured by patent citations, in individual countries. This study empirically tests a sample data set of international technology diffusion taken from 48 countries. The empirical results show that the structural configuration of countries exhibits similar patterns in both embodied and disembodied diffusion networks. Significant global stratification patterns exist in the capability of national international technology exportation and brokerage advantages. Moreover, this study distinguishes four blocks of countries that play different roles in international technology diffusion: the leading countries provide a source of technological knowledge; an intermediate group diffuses the knowledge acquired from the source; a third group is in the process of initiating the export of technological knowledge; and a final group of countries absorbs technological knowledge without reciprocal exportation. Finally, this study identifies two types of catch-up strategies that newly industrialized or developing countries can use to move up the international technology stratification.     

Global distribution of micro–nano technology and fabrication centers: A portfolio analysis approach

Micro and Nano Technologies (MNT) are potential economic engines that have the capability to become the basis for regional and national job and wealth creation. Some have even suggested that MNT along with information technology and media form the basis of a new Schumpeterian or Kondratief wave. Many governments recognizing MNT as enabling technologies with exceptional economic potential have embraced them as centerpieces of their technology policy. Many of these same countries and regions as an expression of their technology policy are creating national centers that embrace the promise of MNT. These international Micro and Nano Technology Centers (MNTC) have taken a variety of forms.Here we review the variety of forms and define the nature of many these major MNTCs from around the world by describing some of their similarities and differences. We provide an insight into many of these centers' demonstrated policy and tactics as they optimize their value to their constituents. Finally we provide a contribution to the literature by providing a categorization scheme for global MNTCs based on our exploration.     

An exploration to visualise the emerging trends of technology foresight based on an improved technique of co-word analysis and relevant literature data of WOS

To explore the possible research fronts and emerging trends of technology foresight, through integrating co-occurrence of keywords and burst terms detection into an improved technique of co-word analysis based on the relevant literature in Web of Science is proposed. Based on the new analytical technique, the links among hot keywords, burst terms are probed, and the core literature related to the emerging trend or interdisciplinary researches are identified. Obviously, the attempts of new bibliometric method in this paper could be a valuable supplement to the traditional co-word analysis; meanwhile, it maybe is much more helpful for those interdisciplinary researchers.     

专利诉讼的时空选择机理——一个基于动态竞争视角的理论框架

鉴于专利诉讼数量显著增加,并超越单纯的法律案件性质,专利诉讼已成为企业动态竞争中的重要武器,进而成为企业专利战略管理的关键环节。从动态竞争角度看,专利诉讼的时间和地点选择对诉讼结果以及竞争的影响尤为关键。通过总结专利诉讼研究文献和动态竞争理论,从动态竞争视角构建专利诉讼时空选择机理、效应的理论框架模型,有助于进一步开展实证研究,也有助于企业把握专利诉讼的本质,在动态竞争中积累优势。     

The effects of cash flow and size on the investment decisions of ICT firms: A dynamic approach

This paper examines one of the fastest growing industries in our world today, the ICT industry. We assess the sensitivity of a firm’s investment to a set of financial determinants, by developing a flexible adjustment dynamic model. In particular, we examine the degree to which a firm’s liquidity influences firm investment and whether firm size and firm specialization have any additional implications. Moreover, the effect of the dot-com burst is also considered. For a panel of ICT and non-ICT US companies listed on the NASDAQ stock exchange, the results reveal the following: (1) all firms are sensitive to the availability of internal funds; (2) investment intensity decreases with firm size; (3) and leverage negatively affects investment for ICT firms.     

A dynamic approach to analysing the effect of the global crisis on nonperforming loans: evidence from the Turkish banking sector

This article analyses the effect of the global crisis on the determinants of nonperforming loans (NPLs) in the Turkish banking sector by using dynamic panel estimation techniques. Empirical findings suggest that NPLs present persistence, which is more evident after the crisis, while other regressors have also persistent effects in the post-crisis period. Moreover, NPLs are mostly shaped by bank-specific variables before the crisis, whereas, after the crisis, NPLs are also driven by macroeconomic and policy-related variables. In particular, the post-crisis significance of GDP, policy rate and sovereign debt shows that robust economic activity, tight monetary policy and strong fiscal balances restrict NPLs, thereby enhancing financial stability. The significance of inflation in both sub-periods shows that commitment to price stability objective is indispensable for limiting NPLs and promoting financial stability. In the period ahead, the speed and the direction of normalization in global monetary policies may determine the course of financial conditions, which, therefore, have implications regarding NPL dynamics and financial stability.