Monitoring trends of technological changes based on the dynamic patent lattice: A modified formal concept analysis approach

The strategic importance of monitoring technological changes is highlighted given the ever faster pace and increasing complexity of technological innovation. In this respect, patent citation analysis has been the most frequently adopted tool among others. However, patent citation analysis is subject to certain drawbacks that stem from only consideration of citing-cited information and time lags between citing and cited patents. This study proposes a formal concept analysis (FCA)-based approach to developing a dynamic patent lattice that can analyze complex relations among patents and monitor trends of technological changes. The FCA is a mathematical tool for grouping objects with shared properties based on the lattice theory. The distinct strengths of FCA, vis-á-vis other methods, lie in structuring and displaying the relations among objects from a massive amount of data. For the purpose of technology monitoring, the FCA is modified to take into account time periods and changes of patent keywords. A patent context is first constructed with the aid of domain experts and text mining technique. Two types of dynamic patent lattices are then developed by executing the modified FCA algorithm. A case study of laser technology in lithography for semiconductor manufacturing shows that the suggested dynamic patent lattice has considerable advantages over conventional patent citation maps in terms of visualization and informative power.     

Trajectory patterns of technology fusion: Trend analysis and taxonomical grouping in nanobiotechnology

The potential of technology fusion has been advanced as a promising breakthrough function to create hybrid technologies. Despite its importance, however, the evolutionary path of technology fusion is yet unexplored. In this paper, by employing the case of nanobiotechnology, we attempt to deepen understanding of the development trajectories of technology fusion in three important aspects. The first aspect is the development of an index that measures the degree of fusion of cross-disciplinary technology at the meso level. The second aspect is to classify the trajectory patterns of technology fusion in terms of fusion degree. We analyze fusion mechanism by utilizing citation network analysis. The third aspect is to visualize the relationship between patents and their backward and forward patent citations, at the patent class level, with their direction on a citation map. This facilitates understanding of the overview as well as fusion patterns. The changes in fusion patterns are analyzed using time series comparisons. An empirical analysis in the nanobiotechnology field shows no positive relationship between the inflow and outflow degree of fusion. We also observe changes in the trajectory patterns of fusion over time. Analysis demonstrates that each fusion pattern has evolved in such a way that technologies focus more on their niche technologies, and that those technologies which cannot incorporate the technology fusion have been eliminated during the development process.     

Quantitative mapping of patented technology — The case of electrical conducting polymer nanocomposite

This study aims to obtain global technology evolution by constructing and analyzing patent citation network and patent citation map for the field of electrical conducting polymer nanocomposite. A total of 1421 patents are retrieved from USPTO patent database and patent citation network is established by combing both patent citation and social network analysis. Network properties, e.g. Degree Centrality, Betweenness Centrality, and Closeness Centrality, are calculated for representing several technology evolution mechanisms that first proposed in this study. Also, a distance-based patent citation map is constructed by calculating relative distances and positions of patents in the patent citation network. Quantitative ways of exploring technology evolution are investigated in this study to unveil important or emerging techniques as well as to demonstrate dynamics and visualization of technology evolutions.     

Enhanced co-citation analysis using frameworks

The valuation of intangible assets, such as patents, has recently been considered an important technique for R&D strategies. This paper proposes a citation analysis as a method of valuation on patent clusters having patent networks. A citation analysis is a method that examines the value of a patent on the basis of the number of citations of references. In particular, a co-citation analysis is used for coupling patents as the patent cluster and valuating the patent cluster. While the co-citation analysis is of great interest as a method of valuation, this analysis has not been fully examined and does not define any framework for a technology transition and patent strategy. Therefore, in this paper, the conventional co-citation analysis for evaluating the patent clusters is enhanced and frameworks for the technology transition and patent strategy are proposed by analysing citation routes in a co-citation analysis.     

基于关键节点与关键路径的专利集群网络演进研究

专利作为技术和知识的重要载体,是研究技术演进和产业发展的重要信息源。目前缺乏针对专利集群网络中关键节点与关键路径中节点的比较分析和技术知识挖掘。构建基于关键节点和关键路径的专利集群网络演进模型,从两个层面综合分析技术演进特征。检索德温特数据库(Derwent Innovation Index)得到碳化硅肖特基势垒二极管（SiC-SBD）相关专利作为实证数据,时间跨度为1986-2017年。结果表明,SiC-SBD专利集群网络经历了萌芽期、成长期、成熟期和衰退期,其中,萌芽期专利主要涉及基础技术,成长期为器件结构,以完善器件结构、改进二极管性能为主要研究方向。近年来SiC-SBD专利年增长率下降,技术发展速度放缓,专利价值更多体现在其商业价值上。SiC-SBD专利集群网络关键节点与关键路径中节点重合度较高,核心专利识别可通过多视角分析得到。通过关键节点与关键路径分析专利集群网络演进过程,有助于更全面呈现技术演进过程,为决策者识别核心专利、预测技术发展提供参考。     

Measuring knowledge persistence: a genetic approach to patent citation networks

The aim of this paper is to propose a new empirical method for identifying technologically important patents within a patent citation network and to apply it to the telecommunication switching industry. The method proposed is labelled the genetic approach, as it is inspired by population genetics: as geneticists are interested in studying patterns of migration and therefore the common origins of people, in innovation studies we are interested in tracing the origin and the evolution of today knowledge. In the context of patent and citation networks, this is done by calculating the patent’s persistence index, i.e., decomposing patent’s knowledge applying the Mendelian law of gene inheritance. This draws on the idea that the more a patent is related (through citations) to “descendent” patents, the more it affects future technological development and therefore its contribution persists in the technology. Results show that the method proposed is successful in reducing the number of both nodes and links considered. Furthermore, our method is indeed successful in identifying technological discontinuities where previous knowledge is not relevant for current technological development.     

Extracting the commercialization gap between science and technology — Case study of a solar cell

In this paper, we compared structures of the citation network of scientific publications with those of patents, and discussed the differences between them. A case study was performed in a solar cell to develop a method of detecting gaps between science and technology. Scientific research has tended to be more basic, especially in terms of cell design, whereas patents have focused on more applied technology used in solar cell modules. Of the major citation clusters of scientific publications, only two, namely silicon and compound solar cells, corresponded semantically with patent clusters. Conversely, there were no patent clusters corresponding to the other two scientific research fronts, namely dye-sensitized and polymer solar cells. These research areas could be regarded as opportunities for industrial commercialization because scientific activities exist but not technological applications. Our results could offer an intellectual basis for discovering potential opportunities for industrial commercialization.     

Patent text mining and informetric-based patent technology morphological analysis: an empirical study

Patent technology morphological analysis utilises the advantages of both patent information analysis and morphological analysis to provide more detailed information on current and future patent technology. Current patent technology morphological analysis methods are largely reliant on manual expertise in the construction of morphological boxes with few approaches to the evaluation of future morphological configurations. We developed a patent text mining and informetric-based patent technology morphological analysis technique. We defined the basic parameters of the morphological box as the factors in factor analysis, with a patent keywords matrix, and the clusters in clustering analysis with factor scores. Patent citation, year of patent registration, keyword frequency, and contributing factors were used to evaluate future morphological configurations. We used an empirical study of liquid crystal display wide viewing angle patents to validate our method. The Thomson Reuters Derwent Innovation Index was used to collect patent text datasets. Our study indicates that this method is feasible for the implementation of patent technology morphological analysis. Our method provides advantages in terms of cost and time reductions during morphological box construction and more flexible methods for evaluating morphological configurations. We discuss problems and possible development of our method in the last section.     

A study on the relationship between technology diffusion and new product diffusion

This study investigates the relationship between “technology diffusion” and “new product diffusion”. We define “technology diffusion” as a knowledge spillover process, which is represented by patent citation, and “new product diffusion” as the spread of a new product that has been developed by the application of patented technology. To investigate the relationship between the two types of diffusion, we use patent citation data of code division multiple access (CDMA) technology and market sales data of mobile phones in South Korea for the analysis. The results show that the diffusion of technology through patent citation could be successfully explained by empirical analysis, for which the Bass diffusion model was used. Moreover, we can find out if technology diffusion can be the leading indicator of a new product's diffusion before its launching; in other words, before the commercialization of the patent.     

专利特征对加入专利池的影响——基于MPEG LA的实证研究

什么特征的专利更容易加入专利池？以MPEGLA专利池内1073件专利与池外1073件控制专利为样本,实证研究专利技术范围、权利与地域范围、审批与维持时间、前向与后向引用对加入专利池的影响。结果表明,技术和地域覆盖范围越广,维持时间越长,专利引用与被引数次越多,越有可能加入专利池;专利审批时间越长,非专利文献引用越多,越难加入专利池;权利要求范围对专利能否入池无显著影响。研究结论对企业专利文件撰写、专利入池申请及专利池管理机构开展专利评估具有重要意义。     

专利家族视角下技术演化路径依赖研究——以光刻技术为例

以专利家族为研究视角，阐述技术路径动态演化过程中的路径依赖。专利家族自引会对技术主路径造成干扰，通过对主路径进行调整，提出一种修正技术主路径的新思路。研究发现：光刻技术在“投影对准和曝光系统—浸没式投影物镜—浸没式光刻材料—光刻胶”4个阶段经历了“路径消解—路径产生与路径依赖—路径消解与突破”的动态演化过程。在此过程中，以荷兰阿斯麦、德国蔡司和日本东京电子为代表的专利家族发挥重要作用。其中，以阿斯麦为核心的利益联盟垄断核心技术，强化光刻技术发展的路径依赖作用，占据市场领先地位。研究结论有助于深化对路径依赖理论的认知，通过揭示光刻技术路径演化过程及企业演化格局，为后发国家突破技术路径依赖提供实践启示。     

地理邻近与知识产权——基于中国1 331项新能源技术发明专利的实证研究

虽然远程交流技术快速发展，但现有研究表明专利发明在很大程度上仍依赖于信息的地理邻近。以中国1992-2009年的1 331个新能源发明专利为研究对象，运用Jung Wonn,Jaffe等的实验设计方法，研究了专利引证的地理邻近是否会随时间递进而增大。结果表明，个人、大学、公司及其它种类发明专利引证的地理邻近会随着时间变化而增大，而政府受到的影响较小。另外，由于区域城市分属不同省份，因此并不能证明区域专利引证的地理邻近也会随着时间变化而增大。     

专利间知识流动与技术融合趋势研究

通过专利引用关系研究技术交叉融合趋势，进而发掘主流技术领域和新兴领域具有现实意义。考虑到目前专利技术边界划分的片面性、技术融合过程缺乏对时间因素的考虑，提出一套结构化的技术融合分析方法。利用产业与专利的映射关系，构建不同技术领域间知识流动矩阵；从技术溢出、技术影响两个维度，构建技术融合趋势图，刻画出4种不同的技术融合类型，并通过时间序列分析技术融合的动态过程。以国家知识产权局新能源汽车专利数据为例，验证了方法的可行性，发现技术融合过程存在明显的技术邻近性，并且技术融合角色呈现动态变化。     

A stochastic patent citation analysis approach to assessing future technological impacts

The anticipation and forecast of technological changes are of vital importance, as technological advances become increasingly fast and complex. What is at the core is identification of the current technologies that will drive technological changes over the coming few years. In this respect, numerous approaches have been devised to assess future technological impacts based on patent citation information, but do not provide a fair reflection of dynamic and idiosyncratic aspects of technological impacts as they are deterministic methods based on simple citation counts. We propose a stochastic patent citation analysis that can assess future technological impacts in a time period of interest by employing the future citation count as a proxy. At the heart of the proposed approach is a Pareto/NBD (Negative Binomial Distribution) model for taking into account the dynamic and idiosyncratic aspects of technological impacts. A patent citation matrix is first constructed for each time unit with citation patterns of the past. The future technological impacts are then derived by Pareto/NBD sub-model and gamma–gamma sub-model. A case study of the display technology patents is presented to illustrate the proposed approach. We believe our method can be employed in various research fields, from narrow patent valuation, to broad technological analysis and planning.     

基于专利引证的数据生存周期安全技术竞争态势研究

以Patentics数据库获取的33229项有效专利文献为数据来源，采用专利引证分析法进行分析发现：美国、日本和中国是全球拥有数据生存周期安全技术TOP100专利申请人数量最多的前3个国家，其中国际商业机器、微软和日立为开拓者，国际商业机器、微软和惠普为领导者，苹果、阿里巴巴、亚马逊科技为新兴竞争者。我国有3所高校、14家企业进入全球数据生存周期安全技术专利数量TOP100申请人行列；华为作为全球数据生存周期安全技术专利TOP10的中国企业，其优势技术领域为H04L029、H04L009、H04L012，但目前研发团队个体创新能力不足。因此，应从国家层面转变政策思维，注重政策导向，推进政策落地；从行业层面推进协同研发，推动专利开放许可，推广技术国产化替代方案；从企业层面重视自主研发，寻求外部合作，引入发明人。     

Lovely but dangerous: The impact of patent citations on patent renewal

What is the impact of patent citations on patent renewal behaviour? Patent citations are commonly used as an indicator of technology spillovers. For cited patents, therefore, patent citations have a potentially ambiguous impact. On the one hand, patent citations may indicate a scientific breakthrough, a high value of the cited patent and therefore a long survival period. On the other hand, patent citations may indicate competing innovations that render the cited patent obsolete. By discriminating patents by technology field, it is demonstrated that patents that receive citations across technology fields survive longer than other patents. Patents that receive citations within the same technology field lapse earlier.     

Exploring the effect of structural patent indicators in forward patent citation networks on patent price from firm market value

This paper introduces structural patent indicators in the forward patent citation networks (FPCNs). Using the estimates of their relationship with firm market value, it explores the effect of the structural patent indicators on patent price. When applied to US smartphone industry and US drug and biotechnology industry, the common finding is that a firm's registered patent gets higher price if influenced faster by the previously registered patents of the same firm through self-citations. The empirical results imply that merely counting forward citations, shown related to patent price by the previous works, is insufficient; the structural properties in FPCNs are essential for the more accurate estimation of patent price. They also show that the relationships between structural patent indicators in the FPCNs and patent price are different between industries. It urges the necessity of selecting structural patent indicators, well fitted to each industry, for the better patent valuation using forward citations.     

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.     

Unveiling the core technology structure for companies through patent information

Patent information provides an objective and public source to understand core technologies of companies. In this paper, a method is proposed for identifying core technology capabilities for a company in the semiconductor industry. The method is built on the patent similarity and K-means clustering algorithm. The indirect relations among the patents in the complex industry are considered in the method. In addition, the age of the patent is taken into account to avoid identifying aged core patents. The method is demonstrated by exploring the core technology capabilities that support the platform technology portfolio of the Taiwan Semiconductor Manufacturing Company (TSMC).     

基于指数随机图模型的专利技术扩散机制实证研究

网络嵌入视角下专利技术扩散路径间存在相关性，但这种网络内生性影响并未在已有研究中得到足够重视。将扩散因素归纳为：专利价值、专利保护、多维同配、结构嵌入，从扩散网络内生、外生因素两个方面构建分析模型，并以石墨烯领域为例，采用指数随机图模型，开展实证研究。实证结果说明：专利价值、技术、地理、组织层面同配性、闭合三角结构嵌入均正向促进专利技术扩散，而专利保护强度反向抑制技术扩散。值得注意的是，专利技术扩散存在强烈的结构嵌入倾向，融合网络内、外生因素的模型能够更好地捕捉专利技术扩散机制。