技术路线图方法探索与实践应用研究

技术路线图作为一种预测和描绘新兴技术发展路径的工具,已被广泛应用于企业、产业、国家的技术发展规划中,以减少创新和规划过程中的不确定性。然而,目前技术路线图的研究和制定常以定性方法为主,过分依赖专家经验。在剖析技术路线图研究机理的基础上,将文献计量和专利分析引入技术路线图应用中,以减少技术路线图对专家经验的依赖。构建基于文献计量、专利分析和技术路线图的新兴技术产业未来发展分析框架,并以染料敏化太阳能光伏技术产业为例进行了实证研究,验证了该分析框架的可行性和有效性。     

Forecasting MBT technologies using DEA and LR

First, this paper explores Main Battle Tank (MBT) data set with different statistical methods in order to decide the most appropriate variables as reliable yardsticks in applying technology forecasting (TF) using data envelopment analysis (TFDEA) technique. It then applies TF using DEA method to forecast MBT technologies. This article attempts to predict technology development year of MBT commercialised from 1941 to 1994. This article presents the processes of TFDEA in detail and identifies some issues to search for appropriate input and output variables to forecast MBT technologies. The purpose of this study is to address some issues and identify an appropriate data to predict future trends of MBT technologies when using TFDEA and multiple linear regression tools. Finally, the study provides an understanding of the technological advances being sought in MBT technologies and information for use in making decisions regarding development strategy.     

The death knells of mature technologies

The oscillatory behavior in the mature phase of some technologies' diffusion-related S curves are investigated, specifically with regard to the influences that other technologies can have on the oscillations. The notion of mortality indicators is raised, that is, whether such behavior is a signal that the mature technology is under attack from an emerging technology. The case of structural panels in the wood products industry is considered as an example, and an updated forecast of the substitution of oriented strand board for plywood is made. It is concluded that factors such as macroeconomic business cycles are primarily responsible for the oscillations in plywood's S-curve, although it is argued that an emerging technology can also contribute to perturbations in a mature technology's S-curve. Two possible alternative explanations for the oscillatory behavior are also discussed, a previously proposed chaos formulation, and a mathematical model based on modified Lotka-Volterra equations. This model shows that the oscillatory behavior in mature technologies' S-curves can also result from symbiotic interaction between two technologies under certain circumstances.     

A comparative study of hype cycles among actors within the socio-technical system: With a focus on the case study of hybrid cars

Many forms of technology cycle models have been developed and utilized to identify emergent technologies and forecast social changes, and among these, the technology hype cycle introduced by Gartner has become established as an effective method widely utilized in the field. However, if the hype cycle indeed exists in the various dimensions that constitute the socio-technical system, those who seek to analyze innovative activities using bibliometrics will be confronted with the new problem of actors' choices and the need to analyze their hype cycles. In seeking to overcome such limitations of conventional studies, this paper analyzes the hype cycles of three actors that constitute the core of the socio-technical system through the case study of the successful market entry of hybrid cars. The hype cycle of the user, the first actor, is analyzed based on the search traffic generated by their web searches, and the hype cycle of the producer or researcher, the second actor, is measured based on the data regarding patent applications. Lastly, the hype cycle of the information distributor, namely individuals constituting the market network, is analyzed by examining the exposure in news reports. The outcomes of this research showed that among the three actors, the consumers and the information distributors exhibited hype cycle patterns (bell curves) that were distinct from the market trend, and that there was a difference in time interval of around five quarters. By contrast, it was found that the hype cycle of the producers reflected a logical response, exhibiting a pattern similar to the S-curve during the market's growth period unlike the pattern found in other actors. In conclusion, this study of the particular case of hybrid cars confirmed that the two components of the hype cycle can be respectively verified using consumer search traffic and the patent applications made by the producers. If in the future, such analyses of the hype cycles of producers and consumers are expanded in application to various other industries, it will be possible to obtain more generalizable research outcomes. This is expected to contribute to determining technological life cycles or hype cycles with greater objectivity and efficacy, and furthermore to facilitate the systematic identification of promising technologies.     

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。     

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.     

太阳能技术的合作专利分析及对策

低碳经济已经成为国际经济发展的新要求,因此,低碳技术开发日益受到世界各国的重视。太阳能技术是一种典型的低碳技术,我国经过10几年的发展,在太阳能领域取得了举世瞩目的成就,但因缺乏核心技术,目前面临着严峻的挑战。由于专利分析能客观地评价技术创新与合作水平,因此,为更好地促进我国太阳能技术的发展,基于专利分析法,对我国太阳能合作专利数据进行了分析。结果表明:我国太阳能技术的跨机构技术联系较少,"产学研"创新体系尚不成熟;政策扶持对于太阳能这种新兴低碳技术有较大的影响力;国内太阳能专利授权的技术领域主要集中在太阳能热利用,而在光伏领域的合作较少;太阳能合作专利存在较大的区域差异,应该进一步加强区域之间的技术合作和技术转移:应该加强国际技术合作。     

萌芽期颠覆性技术识别研究

从颠覆性技术成长周期入手，根据萌芽期颠覆性技术特点，采用基于创新性、独创性与功能分析的识别方法，在技术创新没有造成市场显著变化时实现预警决策。首先进行技术生命周期分析，随后利用创新性和独创性特点衡量技术颠覆性，排除渐进性技术干扰，最后运用功能分析方法研究技术新功能对未来市场的影响。以工业机器人专利技术领域进行实证，验证了方法的可行性和有效性。     

基于K-means与技术生命周期的技术预见方法研究——以水体净化技术为例

预见水体净化技术发展趋势有助于实现“美丽中国”建设目标。已有技术预见方法缺乏定量客观依据,相关评判指标也不够全面。从Innography数据库检索2008-2019年发布的3552个污水处理技术专利,运用多维标度分析和K均值聚类法,基于专利静态指标分析专利技术发展潜力,采用技术生命周期分析法从动态视角判断每类技术的发展前景。研究发现：①污水与污染物双重回收可持续性技术在多个静态评价指标方面均优于其它技术,且处于从引入期到发展期的过渡阶段,具有较大的发展空间;②以去除特定污染物为目标的功能单一技术已被淘汰,市场开始应用污水处理原理不同的多种技术联合处理方式。据此,提出企业应选择污染物回收率高、二次污染物排放少、整体“净效益”为正的污水处理技术,并采取新旧技术联合处理方式降低企业采用新技术的转换成本。     

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.     

The George Washington University Forecast of Emerging Technologies: A Continuous Assessment of the Technology Revolution

A method is presented for the continuous assessment of major technological advances—the George Washington University (GWU) forecast of emerging technologies. Environmental scanning and trend analysis are used to identify emerging technologies (ETs), and a Delphi-type survey then asks a panel of authorities to estimate the year each advance will occur, its associated probability, the potential size of its market, and the nation that will lead each ET. Eighty-five prominent ETs have been identified and grouped into 12 fields: energy, environment, farming and food, computer hardware, computer software, communications, information services, manufacturing and robotics, materials, medicine, space, and transportation. Results are presented from four survey rounds covering the past 8 years, and they are compared longitudinally to estimate the range of variance. The data are also divided into three successive decades to provide scenarios portraying the unfolding waves of innovation that comprise the coming technology revolution.     

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.     

Factor analysis and structural equation model for patent analysis: a case study of Apple’s technology

In this study, we analyse patent data for technology analysis (TA) because patents are rich in information on developed technology. The results of TA can be used to perform more efficient research and development (R&D) planning. Most companies are trying to develop new and innovative technologies to improve their competitive positions. Research involving TA has been introduced in a variety of fields. Most of the published research analysed original variables related to a target technology. However, it is necessary to analyse the latent variables as well as the original variables included in the technology to achieve a better TA model. Therefore, we propose a factor analysis and a structural equation model for patent analysis. In addition, we use Apple’s patents to determine the target technology. In our case study, we analyse Apple’s technologies by latent variables. Our case study shows how the proposed model is applied to Apple’s R&D planning.     

基于专利文本挖掘的科技文化产业技术发展趋势研究

基于Citespace文献计量软件，运用可视化分析技术，以音乐科技产业技术为例、Derwent专利数据库为检索范围，利用CiteSpace、Matlab等软件全面挖掘1960-2016年音乐科技产业专利数据，结果发现，音乐科技专利申请量呈现稳定高速增长态势，主要集中在乐器声学、音视频录制与系统等产业技术领域，比较发达的产业代表为YAMAHA、CAWAI、CASIO等机构。解析出音乐科技产业专利申请生命周期分为4个阶段，分别是1960-1972的停滞期、1972-1992的萌芽期、1993-2005的发展期和2006至今的成熟期。研究发现，音乐科技行业已经形成并将持续快速发展，数字音乐是未来音乐产业发展主流;我国正处于音乐科技产业发展期，建议科技文化领域应关注重点发展方向、加强校企合作、不断完善知识产权保护体系。研究结论对发展我国科技文化产业技术、提升民族文化自信、建设文化强国具有重要意义。     

专利转化特征精准识别与预测——以人工智能芯片为例

探讨前沿科技领域专利转化特征并对其进行精准识别与预测，对于我国破解“卡脖子”技术难题及实现科技自立自强具有重要意义。选取人工智能芯片专利领域，采用机器学习算法测度最优转化预测方案，分析全球范围内主要国家或地区专利成功转化影响因素，从企业/高校、国内/国际等不同层面总结专利成功转化的主要特征。结果发现：随机森林算法预测效果较好，人工智能芯片领域专利转化概率服从对数曲线分布，影响高校/企业、国内/国外专利转化特征的因素有所不同。最后，提出高校/科研机构应注重高价值专利维持和团队合作、企业应提升专利技术质量和撰写质量等政策建议。     

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。     

A study of the method using search traffic to analyze new technology adoption

Various types of indices have been developed and applied for the purpose of identifying emergent technologies and forecasting their adoption. Recently, researchers have proposed search traffic analysis as a new method for tracking changes among consumers and utilizing this information to conduct further market research. Now with the onset of big data era, various attempts are being made to analyze the immense body of information made available by hidden traces left behind by consumers. In the same vein, our present study seeks to draw attention to the analytical advantages of utilizing search traffic. In this study, we use search traffic to analyze the adoption process of a new technology, in this case the technology of hybrid cars, for the purpose of verifying the potential value of conducting adoption analysis based on search traffic and we also propose a more refined method of analysis. First, we undertook to examine the keyword unit used in the searches, in order to refine our analysis of search traffic and thereby obtain greater practical utility. This was accomplished by comparing technology searches that specified the technology name with searches that specified the brand name. For each respective case, we also performed comparative analyses examining instances in which consumers simultaneously included the representative attributes of a product in their search.Our research found that the traffic of searches that specify a product's brand name was significant for explaining sales. Therefore, in the conclusion of this paper we argue that if the unit of search is properly refined, search traffic can indeed serve as an extremely useful method for analyzing or forecasting sales volume. Notably, brand-focused search traffic exhibited a superior ability to forecast sales volume compared to macro-indicators such as GDP growth or WTI prices that had been used to forecast car demand in preceding studies. Forecasting based on search traffic was even superior to forecasts using other bibliometric indices such as patent applications or news coverage.     

专利诉讼中外研究现状与发展趋势

以2000—2020年WebofScience核心数据库（SSCI）和CNKI核心数据库（CSSCI）收录的669篇文献为研究样本，采取文献计量法等方法并利用R语言编程等工具对国内外专利诉讼整体脉络、研究热点演进、研究前沿等进行系统分析。结果表明，专利诉讼研究已经成为重要交叉学科研究领域，美国是专利诉讼研究的领先国家，国内外发文数量差距较大且呈加剧之势，国内已有稳定期刊群，国内各机构关注的具体议题不同；国内外研究热点演进可以分为3个阶段，现阶段国外研究表现出研究范围广、对象多元、方法前沿、程度加深等特点，而国内特征为将国外研究框架、理论方法与我国具体国情实践相结合；国内外共同研究前沿为专利蟑螂和创新，其余方面则有一定差异。基于研究结论，给出加强交叉学科研究、紧跟国际趋势、加大国情视角分析等针对性建议。     

Breaking the Fence: Can Patent Rights Deter Biomedical Innovation in 'Technology Followers'?

The impact of patent protection on biomedical innovation has been a controversial issue. Although a 'medical anti-commons' has been predicted as a result of a proliferation of patents on upstream technologies, evidence to test these concerns is only now emerging. However, most industrial surveys that shed light on this issue are mainly from developed countries, making it very difficult to predict the impact of patenting on biomedical innovation in developing and least developed countries. This paper develops a framework of analysis for the impact of patent rights on biomedical innovation in 'technology follower' developing countries. Based on the framework developed in the paper, empirical data collected in an industry-level survey of the Indian pharmaceutical industry between November 2004 and January 2005 is used to analyze the impact of patent rights as recognized under the Agreement on Trade Related Aspects of Intellectual Property Rights (TRIPS Agreement) on biomedical innovation in technology followers.     

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.