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.     

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。     

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.     

专利视角下人工智能与车联网技术融合演化研究

通过对人工智能与车联网技术融合特征进行研究,能够精准识别车联网产业技术机会,为人工智能与车联网产业创新融合发展提供方向指引。选取2000-2019年相关专利数据,对人工智能与车联网领域技术融合进行识别与测度,采用Word2vec文本挖掘算法和社会网络分析法,揭示融合领域技术发展态势、技术主题关联模式、技术共现网络整体结构和节点功能演变情况。研究发现,融合过程呈现明显的阶段性特征,图像识别等相关算法是车联网领域最基础的人工智能算法,卷积神经网络等相关算法是最具潜力和发展前景的人工智能算法;智能交通平台是融合领域的重点发展方向;数据识别与数据表示技术在融合演变过程中的控制能力较强,无线通信网络技术发展受到相关人工智能技术发展水平的制约。基于研究结论,从研发方向、学科建设、平台搭建等方面提出启示和建议。     

Mapping technological development using patent citation trees: an analysis of bogie technology

We create a generational patent citation tree to reveal the development of bogie technology in the high-speed rail industry. We cull the information in patent citations to reveal the generational development of bogie technology by analysing patent titles, patent publication dates and patent-granting regions. We then measure the development of bogie technology by calculating its technological development on-orbit rate and by mapping the stages of technological development and its regional diffusion. The results show that bogie technologies are in a period of sustained growth and this period of sustained growth will remain. Technological development is accelerating and this acceleration will persist, although the global dispersion of technology lags behind in scope and speed.     

Patent portfolios and knowledge flow(s) of photovoltaic companies

The current trend towards green energy is encouraging manufacturers to invest in photovoltaic technologies. In order to guarantee R&D and optimal operational performance, operators should be able to identify the technological advantages of their competitors for the conduct R&D and to ensure adequate technological knowledge intake. Therefore, from the perspective of patent portfolios and knowledge flow(s) of photovoltaic companies, this study adopted two approaches namely, patent counts and patent citations, to discuss the technical capability of R&D portfolios and the technological knowledge flow. Three patent indices were utilised for the integration of R&D portfolios which include: technology attractiveness, relative patent position, and revealed patent advantage. Technological knowledge flow allows construction of a patent citation network through backward citation of patents. Sources and movement directions of technological knowledge are measured by calculating the relative citation propensity. R&D portfolios and knowledge flow are complementary perspectives of each photovoltaic company.     

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。     

考虑关键核心技术发展的我国集成电路产业政策效力研究

基于专利数据识别集成电路产业关键核心技术，构建技术发展水平评价指标体系并评估关键核心技术发展水平。进一步基于13项关键核心技术对产业政策进行分解匹配，测度各技术环节政策措施间协调度，并实证分析政策措施及其协调度对关键核心技术发展水平的影响。结果表明，我国集成电路产业各关键核心技术差距明显，技术发展水平相对较低；规划引导措施对关键核心技术发展存在显著正向影响，监管认证、税收优惠、规划引导与技术支持措施间协调情况对关键核心技术发展具有显著负向影响，现有金融支持、技术支持措施与其它措施间协调情况较差，不利于关键核心技术发展水平提升。未来政策应鼓励创新主体加大研发投入力度，及时更新监管认证措施并加强对金融支持等措施的监督，为关键核心技术发展提供更强有力的政策保障。     

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.     

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.     

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.     

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.     

Lock-in and break-out from technological trajectories: Modeling and policy implications

The prevailing models explaining how technologies develop along a specific trajectory largely focus on the circumstances that lead to technological lock-in. We contribute substantially to this area of research by investigating the circumstances under which technological development may break-out of a trajectory. We argue that for this to happen, a third selection mechanism—beyond those of the market and of technology—needs to upset the lock-in. We model the interaction, or mutual shaping among three selection mechanisms, and thus this paper also allows for a better understanding of when a technology will lock-in into a trajectory, when a technology may break-out of a lock-in, and when competing technologies may co-exist in a balance. As a system is conceptualized to gain a (third) degree of freedom, the possibility of bifurcation is introduced into the model. The equations, in which interactions between competition and selection mechanisms can be modeled, allow one to specify conditions for lock-in, competitive balance, and break-out.     

中国三种类型专利密度分布时空差异研究

对我国不同类型专利进行时空差异分析,有利于了解我国发明创新的特征、对经济发展的贡献点,以及专利发展程度的差异,突破专利促进经济发展的瓶颈,为不同地区经济发展提供针对性建议,寻求专利发展的新着力点。通过对我国省域专利类型密度时空差异的分析发现：从时间上看,我国三种专利类型发展程度不同,密度指数水平均有所提高,发明专利密度指数水平提升较快,且单位从业人员、产值和技术市场成交额与发明专利拥有量所占比例较均衡;实用新型专利密度指数发展一般,但均衡性较好;外观设计专利密度指数发展水平呈现波动性,均衡性降低;从空间上看,我国东部地区整体专利密度指数水平显著高于西部和中部地区,伴随发展的整个过程,因而不同专利类型和不同地区应区别对待。     

基于专利挖掘的感知人工智能技术融合趋势分析

对于新兴产业而言,把握产业技术融合现状对于引导产业发展、加强技术创新具有非常重要的意义。人工智能技术与其它技术融合是促进产业创新发展的主要内在动力,因此对技术融合趋势进行分析有利于提前、准确把握该产业技术发展方向。聚焦感知人工智能领域,率先采用专利分析方法对10 685项专利数据进行挖掘,结合ISI技术分类体系,基于技术共现次数及关联度识别感知人工智能融合核心技术,并从核心技术融合的分散度及专利增长量等方面考察感知人工智能技术融合情况。研究发现,目前感知人工智能技术融合正处在成长期向成熟期过渡的阶段,并很快进入技术融合衰退期,建议政府及投资者积极布局现有感知人工智能主导技术,以期在即将到来的技术融合成熟期掌握主动权。同时,应大力推广“感知人工智能+”模式,提升该领域技术融合动力,延缓融合衰退期的到来。     

How well do patent citations measure flows of technology? Evidence from French innovation surveys

Patent citation data are used in a growing body of economics and business research on technological diffusion. Until now, there exists little evidence on whether patent citations are a good measure of knowledge flows. Our paper assesses the legitimacy of using European patent citations as a measure of technology flows. It uses information from the Community Innovation Survey collected by the French Service des Statistiques Industrielles (SESSI), which contain firms’ responses to questions about their innovative activity. We show that patent citations are indeed related to firms’ statements about their acquisition and dispersion of new technology, but that the strength and statistical significance of this relationship varies across geographical regions and across channels of knowledge diffusion.     

A hybrid selection model for emerging technology

Technology selection, which influences the advantages of an enterprise or a country, is a multi-criteria decision issue that can be improved by integrating different methods. In addition, it is more and more difficult to identify the right technologies because the technologies are increasing in number and complexity. This study proposes a technology selection process integrating fuzzy Delphi method, analytic hierarchy process (AHP), and patent co-citation approach (PCA) for technology selection. The former effectively gathers experts' judgments toward technology selection criteria and conducts the fuzziness existing in their responses. The analytic hierarchy process has the strength of identifying criteria and obtaining their relationship and their weights. The patent co-citation approach identifies the major R&D fields of a specific technology from patent data. Through this proposed process, the key technology fields can be identified in the end. The organic light emitting diode (OLED) technology in Taiwan is used to be an example to illustrate the proposed technology selection process.     

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。     

人工智能技术对碳排放的影响

随着新一轮科技革命和产业变革的深入推进,人工智能技术在应对气候变化方面扮演重要角色,并赋能“碳达峰、碳中和”目标的实现。利用2006—2019年中国内地省级面板数据,考察人工智能技术对碳排放的影响。研究发现：人工智能技术与碳排放之间呈倒U型关系,即当人工智能技术达到一定阈值后,其碳减排效应逐渐凸显;人工智能技术主要通过提高能源利用效率实现碳减排;在东部和西部地区,人工智能技术与碳排放之间存在显著倒U型关系,而在中部地区,人工智能技术对碳排放发挥持续促进作用。因此,在推进“双碳”目标过程中,需要以绿色低碳发展为目标开发人工智能技术,正确引导人工智能在碳减排领域的研发应用,针对不同区域实际制定差异化发展政策。