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.     

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.     

Vacant technology forecasting using new Bayesian patent clustering

Vacant technology forecasting (VTF) is a technology forecasting approach to find technological needs for given industrial field in the future. It is important to know the future trend of developing technology for the R&D planning of a company and a country. In this paper, we propose a new Bayesian model for patent clustering. This is a VTF methodology based on patent data analysis. Our method is composed of Bayesian learning and ensemble method to construct the VTF model. To illustrate the practical way of the proposed methodology, we perform a case study of given technology domain using retrieved patent documents from patent databases in the world.     

Patent keyword network analysis for improving technology development efficiency

The methods of patent analysis are largely divided into network-based patent analysis and keyword-based morphological patent analysis. Both methods have their shortcomings: internal patent information composed of natural languages cannot be analyzed in the network-based patent analysis method, and the correlation between patents cannot be analyzed in the keyword-based morphological patent analysis method. In this research, we analyze the patents of Light Emitting Diode (LED) and wireless broadband fields via a method that incorporates both the network-based patent analysis and the keyword-based patent analysis methods. And by using network indices, we identify the characteristics of the patent keyword network, and also perform a trend analysis to discover how keywords play a significant role in network changes over time. The analysis results indicate that the patent keyword network is sporadic but clustered and shows a clear power law distribution. Further, the inflow keywords are highly likely to tie new connections with other keywords in the existing associated communities. Also, we confirm the fact that, as time passes, the top core keywords of a particular technology field continue to play an important role in the network and that also the rate of technological changes in wireless broadband field is faster than that of LED. Through the proposed analysis, researchers can easily grasp what technology keywords are important in the specific technology field and identify the relations between the essential technology elements; furthermore, this information can be utilized for developing new technologies by combining these technology elements extracted from community analysis.     

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.     

Capturing the real value of patent analysis for R&D strategies

Patent information can be used for strategic planning purposes. Conventional patent analysis has commonly focused on factual information and, in particular, on information extraction, visualisation and interpretation. Less scholarly attention has been devoted to the strategic role of an integrated system of patent intelligence in supporting decision-making in R&D investments. Our paper addresses this gap and explores how patent analysis may benefit those firms that intend capturing the beneficial effects of Open Innovation. We also critically discuss the intrinsic limits of both patent information and patent analysis, which should be taken into account by systems of patent intelligence.     

基于应用领域视角的技术发展态势分析内容和方法——以石墨烯传感器技术为例

从应用领域的视角,提出分析技术发展态势的内容和方法,即首先利用专利信息和语义分析方法识别技术应用领域,然后从专利分布、专利权人和知识产权风险3个方面分析技术在不同应用领域的发展态势。以石墨烯传感器技术为例,分析了该技术在中国9个领域的发展态势以及在结构材料和电极领域的知识产权风险情况。     

基于因子分析的我国34省市专利发展实证研究

专利的定量研究对于完善地区专利决策、提高地区专利发展水平具有重要意义。运用因子分析方法,对我国34个省、市、自治区、直辖市的专利发展情况进行实证研究。结果表明,地区专利发展水平与经济发展具有一定的关系,但是,这种关系是相对而非绝对的,不同地区具有不同的比较优势,整体水平相同的地区,其优势可能不同,而整体水平不同的地区,其优势却可能相同。     

东盟五国农特产品加工业技术创新能力研究——基于专利信息分析的视角

通过检索新加坡、印度尼西亚、菲律宾、泰国及越南这东盟五国在国际专利分类号为C13(糖类产品制备技术)、A23F(茶叶产品制备技术)、A22(畜禽产品制备技术)和A01G(果蔬等栽培及设施技术)这4个农特产品加工技术领域的专利数据,统计其专利申请总量、领域分布、国别申请情况及年度变化趋势。在此基础上,对五国农特产品加工业的技术创新能力进行研究和评价。最后提出我国农特产品加工业在对东盟贸易中的技术创新目标及相应的专利战略。     

Mapping of scientific patenting: toward the development of ‘J-GLOBAL foresight’

The Japan Science and Technology Agency (JST) is in the process of building knowledge infrastructure by means of linking accumulated information assets to a variety of databases. It does not aim to develop knowledge data infrastructure based on proprietary format, but on an international standard format. JST is also in the process of creating ‘J-GLOBAL foresight’ [http://foresight.jst.go.jp (accessed June 2012)] in order to match up a variety of data such as results and indices of bibliometric analysis as well as of patent analysis derived from the knowledge infrastructure with applications like Google Maps and facilitate the visualisation of business information. This will contribute to help companies and institutions formulate business strategy based on the information obtained in the future. The former aims to be the bibliographic information version of the Data.gov, which discloses government data from the USA, while the latter seeks to be the Data-gov wiki version, which provides a demonstration by matching up governmental data with applications such as Google Maps.     

绿色创新绩效国际研究热点和发展趋势分析

绿色创新绩效体现企业与环境、资源相协调发展的创新成果，近年来引起了越来越多国内外学者的关注。运用文献计量法，对SSCI（Social Science Citation Index）社会科学引文索引数据库中以“绿色创新绩效”为主题的学术论文进行聚类图分析和战略图分析，剖析国际学术界绿色创新绩效的研究热点和发展趋势，以期为国内绿色创新绩效研究提供参考。目前国际上关于绿色创新绩效的研究数量呈现稳步上升趋势，企业资源、战略能力、研发活动、合作网络与绿色创新绩效之间的关系研究成为热点议题，未来具有高潜力的研究主要包括网络、信息技术、环境不确定性、创业导向、知识管理等主题。     

美国风力涡轮机技术监测与分析

运用专利计量学方法和VOSviewer信息可视化软件工具,对USPTO专利数据库中的风力涡轮机技术专利进行计量分析,从而实现对美国风力涡轮机领域的技术进行监测。结果显示:美国风力涡轮机技术专利授权量在2005年后快速增加,涡轮机技术发展前景较好;美国、丹麦和日本在该领域具有较强的技术优势,其中丹麦对风力涡轮机技术最为重视;美国通用电气公司、维斯塔斯风力系统公司和日本三菱公司是美国风电产业中的领导者;风力涡轮机自身结构等、风电控制系统与方法、垂直涡轮机是该领域的技术热点;IEEE的会议论文是美国风力涡轮机技术发展的重要科学基础,太阳能光伏发电与风力发电"融合"现象初现端倪,具有较大的发展潜力。     

基于专利的中美石墨烯技术创新比较研究

石墨烯作为一种新型纳米材料已成为物理学、材料科学和化学领域的研究热点,相关专利的申请数量增长迅速。通过对中国知识产权局(SIPO)和美国专利商标局(USPTO)公布的石墨烯相关发明专利数据进行深度标引,对比分析了中国和美国石墨烯相关技术的研发热点及发展态势。比较结果显示:中美两国石墨烯技术创新发展趋势基本相似,中国石墨烯技术专利申请量已经超过美国,但两国石墨烯专利技术分布领域及申请人类型差别较大。中国受理的石墨烯专利技术主要分布在电池、电极,申请人多为国内高校和科研机构;美国受理的石墨烯专利技术主要分布在半导体固体器件,申请人主要为企业且国外申请人占重要地位。这一分析结果从一个侧面反映了中美两国在石墨烯研究领域的异同,期望能为我国石墨烯相关领域的技术创新和决策提供参考。     

Understanding the intellectual structure and evolution of Competitive Intelligence: a bibliometric analysis from 1984 to 2017

ABSTRACT

Competitive Intelligence (CI) is a relatively novel discipline that is generating a growing interest in the field of strategic management. Its novelty, approach and origin have meant that the definition of the CI entails different interpretations and utilities depending on the audience. This research develops a conceptual analysis of CI in literature by quantifying the bibliometric performance indicators, identifying the main authors, countries, journals and research areas and evaluating the intellectual structure and evolution of the discipline using SciMAT as bibliometric analysis software. The bibliometric performance analysis is focused on the citation-based impact of the scientific output, while the science mapping illustrates the evolution of the research themes that build the discipline through the use of bibliometric network analysis techniques. To this purpose, the publications related to CI from 1984 to 2017 available at Scopus have been retrieved (5,275 publications). Finally, it offers a framework to support future researches.     

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.     

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.     

Multivariate multiple regression modelling for technology analysis

Technology analysis is important for technology management areas such as research and development strategy and new product development. So many studies on technology analysis have been used across a diverse array of fields. Most of these were based on patent analysis, which analyses patent documents using text mining and statistics. The studies on conventional patent analyses constructed models consisting of various independent variables (technologies) and one dependent variable. But in reality, we have to consider a model that includes several dependent variables at the same time, because most technologies influence each other. In this paper, we propose a methodology for patent analysis that reflects the various response technologies simultaneously. We perform multivariate multiple regression modelling in order to efficiently conduct our technology analysis. To show how our modelling can be applied to realistic context, we carry out a case study using the patent documents related to three-dimensional printing technology.     

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.     

专利运营基金:域外实践与本土探索

开放式创新加速了价值链的专业化分工,专利价值的实现方式也呈现多元化趋势,各种新兴的专利基金不断塑造出崭新的商业模式。对国外典型专利基金类型进行了系统分析,梳理了中国政府近年来在促进专利基金运营方面的政策努力,选取深圳中彩联科技有限公司、天津滨海国际知识产权交易所和睿创专利运营基金为样本,探讨了本土专利基金的实践探索与运营瓶颈。在《专利法》第四次修改的背景下,具体从专利运营的政策优化、专利诉讼的法律因应、专利投资的风险管控以及专利滥用的反垄断规制4个层面,提出了专利运营基金的完善路径。     

网上技术交易趋势预测模型及应用研究

网上技术交易平台开展交易趋势预测和交易潜力识别，可提高平台技术信息管理水平和网上技术市场运作效率。从网上技术市场和专利情报分析理论出发，提出网上技术交易趋势预测分析指标，设计构建预测模型和相关流程方法，并以广州知识产权交易中心的网上挂牌专利数据为例，进行定量测度和评价分析，从而提出发展网上交易服务能力的建议。结果表明，提出的技术交易趋势预测模型与流程具有适用性和可操作性，可针对网上平台技术资源确定差异化预测类型及其关键影响指标，建立基于技术领域分类的平台分析体系。研究结论可为网上平台设计基于自身特点的技术信息管理策略，提高信息服务专业化能力提供参考。