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.     

Anticipating technology-driven industry convergence: evidence from large-scale patent analysis

ABSTRACT

Industry convergence has been the subject of many prior studies, yet most have focused on certain domains based on ex post evaluation. This study presents a systematic approach to anticipating technology-driven industry convergence using large-scale patent analysis covering all technology fields. Our approach includes patent co-classification analysis with the concordance between patent classes and industrial sectors to measure technological relations between industries; centrality and brokerage analysis to identify the specific roles of technology fields in industry convergence; and finally link prediction analysis to anticipate technology-driven industry convergence. A case study with the patents issued by the United States Patent and Trademark Office from 1976 to 2014 confirms that our approach provides a holistic and forward-looking perspective on technology-driven industry convergence.     

A semantic analysis approach for identifying patent infringement based on a product–patent map

Identifying patent infringement beforehand is highly important for reducing the risk of damages. However, as the approach to patents is changing from the technological and legal approaches of the past to the business approach, strategic patent infringement litigation and securement of patents can be important tools for companies. From various viewpoints, companies can consider an aggressive patent infringement litigation as well as evasion strategy of patent infringement litigation to keep competitors in check. Previous research on patent infringement identification only considered the possibility of infringement between patents. However, infringement cases between patent and product are prevalent. Thus, this research aims to suggest an automated method for identifying patent infringement between the patent and product in business. To this end, this paper proposes the subject–action–object (SAO) semantic technological similarity-based product–patent method for generating infringement maps. Several indices and subgrouping methods are suggested to interpret the map. As an exemplary case, data on technology and products related to the light emitting diode (LED) lamp are collected and exploited.     

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.     

制造企业技术创新与商业模式创新协同演化:一个多案例研究

制造企业发展过程表明,技术创新和商业模式创新之间存在复杂的协同演化关系。结合多案例研究方法,分析制造企业演化过程中技术创新和商业模式创新的匹配模式、协同演化关系。结果发现：技术创新和商业模式创新动态演化存在3种模式：简单线性模式、反馈控制模式、复杂系统模式。基于此,构建技术创新和商业模式创新协同演化模型,指出协同演化呈现“创新-调整-适应”等复杂的螺旋化发展过程,并提出技术创新和商业模式创新协同演化的3种机制：互动机制、学习机制、选择与反馈机制。突破了关于技术创新和商业模式创新之间简单的线性关系和静态视角,从动态视角分析技术创新和商业模式创新协同演化,补充和修正了技术创新和商业模式创新关系的认识,丰富了现有创新演化理论。研究结论对中国制造企业实施创新战略的启示在于：单一创新虽然在一定程度上能为制造企业带来盈利,但是其作用和持续性均有限,技术创新和商业模式创新有效协同是制造企业竞争力持续提升的关键。     

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.     

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.     

Relating business model innovations and innovation cascades: the case of biotechnology

This article conceptualizes innovation as a process, where the scientific and industrial application of technological knowledge nurtures new routines and institutions, in order to relate changing business model innovations to innovation cascades. Innovation in science-based, high-tech sectors is changing its tempo, from the evolutionary pace of incremental novelties punctuated by occasional radical novelties, to innovation cascades. These cascades involve a long series of interlinked radical innovations, which can be traced through various scientific and technological indicators like patents and publications. Innovation cascades are relevant to industry, because they make the future less predictable. They are particularly interesting because these changes also enable the testing an abundance of new business models. Innovation cascades have a major impact on the number and sustainability of business models and on strategy. Business model innovations are visible not only in the existing organizations that undergo change, but also new organizational models appear. The case of biotechnology after the 1980s is used to illustrate our conceptualization.     

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。     

Better technology forecasting using systematic innovation methods

An evolved version of the Soviet-originated Theory of Inventive Problem Solving, TRIZ, contains a series of generically predictable technology and business evolution trends uncovered from the systematic analysis of over 2 million patents, academic journals and business texts. The current state of the art—recorded for the first time together in this paper—now bring the total number of generic technical trends to over 30, and the number of business trends to over 20. The paper describes some of the newly discovered trends, and their incorporation into a design method that allows individuals and businesses to first establish the relative maturity of their current systems, and then, more importantly, to identify areas where ‘evolutionary potential’ exists. The paper introduces this concept of evolutionary potential—defined as the difference between the relative maturity of the current system, and the point where it has reached the limits of each of the evolution trends—through a number of case study examples focused on the design and evolution of complex systems.     

Tracing the Evolution of Biomedical 3D Printing Technology Using Ontology-Based Patent Concept Analysis

Three-dimensional (3D) printing enables products to be custom-designed and produced using additive manufacturing processes. This research develops a patent analysis approach to explore biomedical 3D printing technology trends. First, the method searches for related patents. Second, frequently appearing key terms in patents are extracted as a means to identify key concepts of inventions. Third, in order to structure the domain knowledge, the ontology is created by referring to the relevant key terms and literature. The key terms create indexes used to measure similarities for clustering the patents and sub-technologies. Based on the patent context and dynamic patent concept analysis maps, the evolutionary trends of technology development are depicted. Biomedical 3D printing R&D projects are used as case examples to compare against co-occurring patent evolutions. The proposed patent concept analysis is generalisable for critical decision support of R&D planning and evaluation in any market sector.     

Using patent analysis to establish technological position: Two different strategic approaches

Discussions on business strategy formation in the past 50 years can be separated into two categories: the inside-out and the outside-in approach. Technology is a critical factor when manager formulate their business strategy, and patents have served as an important indicator of technology. A patent portfolio can be used to understand the capabilities of a firm, as an inside resource pattern; and the patent citation of firms can be used to find the relationship of a firm, as an outside dependency. This study uses patent information to establish an effective model for the technological position of business methods. The 5 by 6 matrix was generated and four situations between firms were induced. Researchers and managers can use that matrix and situations to recognize the real competitors or cooperators, and formulate the technological strategies which include competition, cooperation, or complementary cooperation.     

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.     

Identifying digital traces for business marketing through topic probabilistic model

With the exponential growth of data from social media, new opportunities for businesses to supplement marketing have been created. However, finding potential interest of consumers from a social media platform is a crucial but challenging task. Analysing the actual textual content of social media platform can help business managers to better understand the consumers’ interest for marketing. In this article, an approach was proposed to discover and quantify the business marketing topics, repost interest points on consumers and trends over time from company's micro-blog posts, furthermore gaining insights into the business marketing on social media platform. The case study results on real world data from Sina weibo show that it is useful for companies to better understand the digital traces of interaction with its consumers. The approach offers a systematic method for dealing with a large number of textual data on social media platform for business intelligence.     

The boundaries of firms in the new economy: M&As as a strategic tool toward corporate technological diversification

Following the dynamic capabilities approach, we understand the recent wave of M&As as a corporate strategy mainly stimulated by the increasingly complex and uncertain techno-socio-economic environment in which firms operate. In this new situation, the boundaries of firms are in greater flux since firms are unable to develop individually all the competencies required to keep pace with the continual redefinition of business lines being driven by corporate competition. Using US patents granted to the world's largest firms, this paper analyses the dynamics of the sectoral specialisation of corporate technological profiles following large shocks that require some M&A deal. The findings of the analysis enable us to evaluate the adoption of M&As as a strategic tool to reshape corporate technological boundaries. On these grounds, we are able to identify patterns of technological diversification into strategic fields according to different models of industrial technological development.     

Schumpeter,Schumacher and the Greening of Technology

We propose a semantic patent claim analysis that can examine patents for possible infringements and identify which needs to be manually perused. So far, numerous approaches have been devised to systemise this burden, but have not been useful in practice because of a lack of consideration of semi-structure of patent claim data and claim element-based procedure of adjudicating patent infringement. At the heart of our method is a hierarchical keyword vector for representing the dependency relationships among claim elements (as well as unstructured textual information) and a tree matching algorithm for comparing claim elements of patents. A case study of the patents about DNA chip technology shows our method has considerable advantages in terms of accuracy and significance. We believe the suggested method could be employed in various research areas and serve as a starting point for developing more general models.     

龙头企业商业模式对技术创新的影响研究——以厦门汽车—工程机械产业龙头企业为例

龙头企业商业模式对技术创新具有重要影响,但既往文献中甚少提及,且未深入研究。以厦门汽车—工程机械产业龙头企业为例,从商业模式的构成要素与技术创新的影响因素间的交叉部分入手,分析龙头企业商业模式对于技术创新的影响。研究发现:在龙头企业商业模式中,价值定位决定技术创新起点,价值实现影响技术创新成果,价值保持促进技术创新实现。因此,从企业发展的全局出发,突破现有商业模式,重视企业技术创新,确定龙头企业创新主体地位,营造良好集群创新氛围,应成为产业集群乃至区域经济发展的重要战略选择。     

R&D EFFICIENCY AND THE NATIONAL INNOVATION SYSTEM: AN INTERNATIONAL COMPARISON USING THE DISTANCE FUNCTION APPROACH

This paper applies the distance function approach for stochastic frontier analysis (SFA) to compare research and development (R&D) efficiency across 24 nations during 1998–2005. In this multiple input–output framework, R&D expenditure stock and R&D manpower were inputs, while patents, scientific journal articles, and royalties and licensing fees (RLF) were outputs. Intellectual property rights protection, technological cooperation among business sectors, knowledge transfer between business sectors and higher education institutions, agglomeration of R&D facilities, and involvement of the government sector in R&D activities significantly improve national R&D efficiency.     

Capacity constraints, asymmetries, and the business cycle

We study how an occasionally binding capacity constraint affects the properties of business cycles. A real business cycle model is constructed where production takes place at individual plants and the number of plants operated varies over the cycle. The capacity constraint binds in states where all plants are operated. We derive the aggregate production function for this economy, which turns out to differ from the standard Cobb–Douglas function while retaining its desirable properties. The business cycle features of this one-sector growth model are similar to those of a standard real business cycle model in most respects. Our model does, however, display some properties of actual economies that standard models do not. In particular, business cycles in our model are asymmetric—troughs are deeper on average than peaks are tall. Also, labor's share of income is counter-cyclical, as it is in US data.