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。     

A fuzzy-based roadmapping model for enhancing high-tech small firms’ technological entrepreneurship capabilities: cases of Iran

ABSTRACT

Technology-based firms need to survive via technological changes. Technological entrepreneurship is concentrated on identifying and exploiting the tech-opportunities for creating product innovation. This paper introduces a fuzzy-based tool to promote innovation throughout firms in order to enhance technological entrepreneurship capabilities (TEC). The effort involves identifying components of TEC to develop the inference system, specifying the fuzzy relationship among these components, assessing the TEC in firms, and designing a TEC roadmap after a fuzzy-based gap analysis. Designed roadmaps introduce technological change priorities as a growth path to firms to move up along the ladder of competitiveness. Based on the results, a method for categorizing firms into four distinct levels that involve passive, reactive, proactive and innovative is introduced. Hence, firms have an action plan to enhance TEC from passive to innovative level in a time-based transition pathway.     

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.     

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。     

Technology roadmapping in review: A tool for making sustainable new product development decisions

Typically, firms decide whether or not to develop a new product based on their resources, capabilities and the return on investment that the product is estimated to generate. We propose that firms adopt a broader heuristic for making new product development choices. Our heuristic approach requires moving beyond traditional finance-based thinking, and suggests that firms concentrate on technological trajectories by combining technology roadmapping, information technology (IT) and supply chain management to make more sustainable new product development decisions. Using the proposed holistic heuristic methods, versus relying on traditional finance-based decision-making tools (e.g., emphasizing net present value or internal rate of return projections), enables firms to plan beyond the short-term and immediate set of technologies at hand. Our proposed heuristic approach enables firms to forecast technologies and markets, and hence, new product priorities in the longer term. Investments in new products should, as a result, generate returns over a longer period than traditionally expected, giving firms more sustainable investments. New products are costly and need to have a durable presence in the market. Transaction costs and resources will be saved, as firms make new product development decisions less frequently.     

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.     

浙江省ICT产业产学研合作创新网络动态演化分析

推进ICT产业创新发展是浙江省实施数字经济"一号工程"的重要举措之一。运用社会网络分析方法,从不同阶段和不同行业领域两方面定量分析产学研合作创新网络特征及其对创新绩效的影响。研究表明:浙江省ICT产业产学研合作创新网络呈核心-边缘化结构,具有二步式螺旋式上升的演化特征;网络密度对创新绩效存在促进作用,网络中心性对创新绩效存在抑制作用;产学研合作创新网络对浙江省ICT产业的发展有推动作用。     

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。     

高校专利合作能力评价指标研究

专利合作能力是高校科技创新能力的重要组成部分,也是高校竞争力的关键因素。通过广度合作和深度合作评价高校专利合作能力,其中广度合作能力由合作专利数和合作企业数进行评价,深度合作能力由合作率、合作强度和活动年期进行评价,并利用熵值法确定指标权重,以广东省16所代表性高校的合作专利数据进行分析。结果发现,广东省同一类型或同一层次高校专利合作能力差异较大,专利合作能力与高校层次、地域不相关,专利合作缺乏长期性。结论对于高校加强专利合作与提升科技创新能力具有较高的参考价值,能为政府健全专利合作保障和激励机制提供决策依据。     

军民科技创新合作网络结构与演化——基于专利合作与社会网络实证分析

推进军民科技协同创新是攻克制约我国国防与经济发展科技难题的重要举措。为探索军民科技协同创新发展路径,采用北京市装备制造业2000-2019年军队单位、军工单位与民口单位联合专利申请数据,运用社会网络分析法和ArcGIS空间分析法,对北京市装备制造业军民科技创新合作网络结构和演化特征进行研究。结果发现,北京市装备制造业军民科技创新合作网络经历军民分离阶段、军民融合初步发展阶段,现正处于军民融合深度发展阶段初期。从结构特性看,创新合作网络规模不断扩大、密度逐步降低,网络结构呈现“多核心”特征、网络具有无标度特性;从空间分布看,北京与华东、中南地区合作频繁,逐渐形成以北京—陕西、北京—江苏、北京—河南为主的多条军民科技协同创新连接渠道;从核心节点看,军工高校与军队院校仍是军民科技研究主力,对军民科技协同创新发展起重要带动和引领作用。     

基于专利信息的中美区块链技术竞争态势分析

当前区块链技术仍处于快速发展期,对中美整体竞争格局影响至关重要。专利是关键技术的代表、产业发展的基石,从专利信息出发,可以把握技术竞争态势,进而管窥中美区块链产业发展差异,为我国区块链产业发展提供政策建议。基于德温特专利数据,采取专利分析法和社会网络分析法对其进行深度挖掘,结合“新钻石模型,研究发现,在政府、机会、需求条件、知识吸收层面上,中国区块链技术及产业具有优势地位;而在生产要素、产业支持、企业战略结构与创新能力方面,美国优势更为明显。从政府、行业、企业层面分别提出建议：①政府层面,继续保持在政府管理与公共服务领域的优势;②行业层面,注重提高区块链专利质量;③企业层面,提高国际合作能力,加强区块链服务于实体经济。     

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.     

Patent indicators for monitoring convergence - examples from NFF and ICT

The blurring of boundaries between hitherto distinct scientific disciplines, technologies or markets is a common and powerful phenomenon. Concentrating on monitoring convergence through patent indicators, we discuss convergence with examples from the area of Nutraceuticals and Functional Foods (NFF)/Cosmeceuticals as well as information technologies, consumer electronics, and telecommunications (ICT). We analyze 7455 scientific and patent references on phytosterols with the aid of SciFinder Scholar and 3836 documents employing STN AnaVist. Furthermore, we test an IPC co-classification based approach on 859,469 ICT-related and 341,846 NFF-related patents. Our results show clear indications for convergence and a proof of principle for our monitoring concept. Academics may better evaluate environmental parameters, like cases of convergence, influencing companies' actions. Implications for practitioners are based on a more reliable assessment prior to the forming of strategic alliances or mergers and acquisitions. This could help avoid costly adventures such as the mergers and acquisitions seen in ICT.     

关键共性技术合作网络演化机制研究——以医药产业为例

构建高效的技术合作网络是突破关键共性技术研发难题的关键,揭示技术合作网络演化机制对网络发展具有重要意义。以社会网络理论与随机统计理论为基础,将技术合作网络演化驱动因素归纳为属性驱动、同质驱动及结构驱动,基于医药产业关键共性技术合作专利数据构建技术合作网络,分析技术合作网络演化特征,同时采用指数随机图模型探究网络演化驱动机制。结果显示：网络演化过程中,仅有少数研发主体展开广泛而频繁的合作;研发主体研发能力与结构洞属性对技术合作网络演化无显著作用,但度中心性对网络演化的促进作用显著;网络演化具有显著的地理与组织同质效应;网络更倾向于形成星型结构与闭合三角结构,不倾向于形成开放三角结构。     

A visual scanning of potential disruptive signals for technology roadmapping: investigating keyword cluster,intensity, and relationship in futuristic data

Technology roadmapping of today’s era is necessarily based on comprehensive scanning of various signals with the disruptive potential in future paths of market, product, and technology. Previous attempts of data-driven technology roadmaps have mainly focused on data from such sources as patents and literatures. However, as these sources catalogue posteriori trends of evolution, roadmaps based on these data cannot be counted on to predict disruptions. In this regard, futuristic data in technology foresight websites may provide a better source. The objective of this research, in response, is to develop a support system for technology roadmapping that uses futuristic data. To this end, we suggest keyword-based visual scanning approach involving three keyword maps, used in succession: keyword cluster map, keyword intensity map, and keyword relationship map. Particularly, keyword intensity map is designed using weak signal theory which can help identify the visibility, diffusion, and interpretation of signals.     

论基础专利之改进技术保护路径的完善 ——以确立反向等同原则为视角

我国基础专利之改进技术的实施面临诸多障碍,阻碍了改进技术的推广应用,美国司法实践中由法官创设的反向等同原则对于我国解决这一困境具有借鉴意义。对反向等同原则的制度功能与理论基础进行规范分析,并辅以比较法视角,研究发现：反向等同原则不仅可以限制专利字面侵权,平衡专利权人与改进者之间的利益,还可以作为专利政策杠杆,对专利法保护的不同行业技术进行微观调控。确立反向等同原则符合专利契约理论对公平的要求,亦与知识产权工具论的主张相契合。最后,提出建议：以反向等同原则的确立为切入点,使落入专利权利要求字面含义范围内、与专利技术不相等同的全新改进技术免于专利侵权,同时严格把握反向等同原则的适用条件,兼顾基础专利保护与全新改进技术激励。     

Business cycle turning points based on DEA-discriminant analysis

Recently, the turning points of business cycle are decided with wide viewpoints after passing a couple of years from the points. This study tries to develop a model for judging the turning points in real-time by using a non-parametric approach, DEA-discriminant analysis, because we have sometimes faced sudden changes of economy and non-parametric approaches are useful for covering these movements. The constructed model succeeds to separate periods in Japanese economic expanding and recession terms, and the model would be helpful for the real-time judgments of the turning points of business cycle.     

A systematic approach for identifying technology opportunities: Keyword-based morphology analysis

Morphology analysis (MA), a representative qualitative technique in technology forecasting (TF), has been utilized to identify technology opportunities. However, conventional MA is subject to limitations in that there is no scientific or systematic way in establishing the morphology of technology, and it is difficult to prioritize the alternatives. As a remedy, we propose a keyword-based MA that is supported by a systematic procedure and quantitative data for concluding the morphology of technology. To this end, a technology dictionary is developed by factor analysis for keywords that are extracted from patent documents through text mining. Then, the morphology of patents is identified based on the technology dictionary. By listing the occupied configurations of collected patents, the unoccupied territory of configurations are suggested as technology opportunities. Moreover, the priority of alternatives is concluded, and similar and substitutive technologies can be analyzed for the purpose of extending morphology structure. Technical and managerial strategy for in-house R&D or cross-licensing can also be supported by examining the morphology portfolio of technologies. A thin film transistor-liquid crystal display (TFT-LCD) case is exemplified to illustrate the detailed procedure of this brand-new MA.