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.     

Keeping abreast of technology-driven business model evolution: a dynamic patent analysis approach

All firms that depend on technology for their competitive positions recognise that keeping abreast of technology-driven business model evolution is of vital importance. However, previous studies cannot offer a concrete way of profiling trends owing to the lack of quantitative data and systematic processes. We propose a dynamic patent analysis that can identify complex relationships among business method patents and visualise trends in technology-driven business model evolution. At the heart of the suggested approach is morphological analysis (MA) for structuring different types of business models at a technological attribute level and modified formal concept analysis (FCA) for investigating technological changes in business models over time. A case study of business method patents concerning electronic shopping is presented to show the feasibility of the proposed approach. We believe our method can promote consensus-building on up-to-date trends in technology-driven business model evolution, serving as a starting point for a more general model.     

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.     

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.     

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.     

A New Comprehensive Patent Analysis Approach for New Product Design in Mechanical Engineering

This study proposes a five-phase procedure for a new product design process. Based on the concept of “focus first, then extend”, this study presents a new approach called the New Comprehensive Patent Analysis model (NCPA) which combines the patent family with patent citation analysis in a new product design process. The procedure includes the following features: (1) integrating the perspective of management-based and technology-based design for patent searching, (2) building a patent family based on industry basic patents, (3) filtering the patent family to obtain key patents, (4) utilizing patent citations to gain necessary technology information in product development design, and (5) combining TRIZ theory to construct patent technology performance maps, and to discover product niches. This NCPA model is empirically applied in a real case. The results show that the NCPA improves the overall efficiency of new product designs, but also involves higher cost than other approaches.     

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。     

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。     

The relationship between a firm's patent quality and its market value — The case of US pharmaceutical industry

This study examined the relationships between corporate market value and four patent quality indicators - relative patent position (RPP), revealed technology advantage (RTA), Herfindahl-Hirschman Index of patents (HHI of patents), and patent citations - in the US pharmaceutical industry. The results showed that RPP and patent citations were positively associated with corporate market value, but HHI of patents was negatively associated with it, while RTA was not significantly related to it. Thus, if pharmaceutical companies want to enhance their market value, they should increase their leading positions in their most important technological fields, cultivate more diversity of technological capabilities, and raise innovative value of their patents. In addition, this study found that market value of pharmaceutical companies with high patent counts was higher than that of pharmaceutical companies with low patent counts, and suggested that pharmaceutical companies with low patent counts should increase RPP in their most technological fields, decrease HHI of patents, or raise patent citations to further enhance their market value. Furthermore, this study developed a classification for the pharmaceutical companies to divide them into four types, and provided some suggestions to them.     

Health services research in heart failure patients treated with a remote monitoring device in Germany—a retrospective database analysis in evaluating resource use

Abstract

Objectives:

Heart failure is an increasing burden for all healthcare systems with prevalence reaching over 20 million patients worldwide and direct costs of disease requiring ～1% of healthcare budget expenditures. Beyond traditional pharmaceutical treatment, medical devices and remote monitoring tools were introduced to ensure a closely managed control of patients. In this context, a decision-maker needs to know whether the new technology provides clinical benefit towards patients and what resource use is attached to them.

Methods:

Health services research is a complementary approach to clinical trials providing results to the impact of the technology in real life settings. As an example this study reports of a secondary data analysis of one of the largest health insurance companies in Germany, comparing resource use of heart failure patients receiving a cardiac resynchronization therapy (CRT) device coupled with a fluid status monitoring and alert function with patients receiving conventional CRT, ICD (implantable cardioverter defibrillator), or no intervention.

Results:

Disease-associated expenses can be attributed to far more than 50% to heart failure. Although implementation of the CRT device with alert function was most expensive (31,794 Euros compared to 27,659 Euros in the conventional CRT group, 24,128 Euros in the ICD group, and 3735 Euros in the no intervention group) in the first year after implementation, the least costs have been caused in this group (7000 Euros compared to more than 11,000 Euros in all other groups).

Conclusion:

This article highlights potential health services research approaches focusing on the example of a CRT device coupled with a pulmonary diagnostic and alert function. Although this retrospective analysis holds a number of limitations (e.g., small number of patients in intervention group, cost calculations only from the payer perspective), and despite the need for randomized controlled trials, it was shown that secondary data research in this field is a valuable approach.     

EVEREST II high risk study based UK cost-effectiveness analysis of MitraClip® in patients with severe mitral regurgitation ineligible for conventional repair/replacement surgery

Abstract

Objectives:

To evaluate the cost-effectiveness of MitraClip, an interventional procedure for patients with chronic severe mitral regurgitation.

Methods:

A decision analytic model with a lifetime horizon was developed to assess the cost-effectiveness of MitraClip vs conventional medical management in patients with severe mitral regurgitation, ineligible for surgery. The analysis was performed from a UK NHS perspective and the estimates for mortality, adverse events, and cross-sectional NYHA class were obtained from the EVEREST II High Risk Study (HRS). Utility decrements were obtained from a heath technology assessment on Cardiac Resynchronization Therapy, while unit costs were obtained from national databases. The concept model was clinically validated. Costs (2011 £UK) and benefits were discounted at an annual rate of 3.5%.

Results:

Compared to medical management, over 2- and 10-year periods MitraClip had incremental Quality Adjusted Life Year (QALY) gains of 0.48 and 2.04, respectively. The Incremental Cost-Effectiveness Ratios for MitraClip at 2 and 10 years are £52,947 and £14,800 per QALY gained. Overall, the model was most sensitive to the choice of time horizon, the discount rate applied to benefits, the starting age of cohort, the utility decrement associated with NYHA II, and cost of the MitraClip procedure. The model was insensitive to changes in all other parameters. MitraClip was also found to be cost-effective, regardless of the modelling approach, and insensitive to the key assumptions of the procedure cost.

Study limitations:

The primary limitation of the analysis is the reliance on aggregate data from a modestly sized non-randomized study with a short-term follow-up period. Aligned to this was the need to extrapolate survival well beyond the study period in order to generate meaningful results. The impact of both of these limitations was explored via extensive sensitivity analyses.

Conclusion:

Compared to medical management, MitraClip is a cost-effective interventional procedure at conventional threshold values.     

面向专利技术融合的3D打印产业化路径选择研究

3D打印在中国面临大规模产业化的起点,作为一项新兴的融合型技术,其产业化路径具有区别于传统技术的特异性。从专利情报和技术融合视角探究其产业化模式和路径选择,提炼技术融合对技术产业化的影响机理,依托迈克尔波特对零散型产业的界定,提出“3D打印+”产业化模式选择,探究其与制造业、互联网融合趋势及前景。应用产业技术融合测量方法,实证揭示中国3D打印专利在技术结构上的不均衡性和技术融合上的多样性,为中国3D打印技术及其产业化发展提出相关对策与建议。     

基于科学的产业创新主体专利合作伙伴识别研究

近年来,发展基于科学的产业已成为全球科技和产业竞争的焦点。基于科学的产业具有开放式创新特点,产业创新主体致力于寻找合作伙伴以充分利用外部资源。专利信息涵盖丰富的技术信息、法律信息及经济信息,是创新主体寻找合作伙伴并开展创新合作的重要资源,但鲜有学者运用专利信息研究基于科学的产业创新问题。构建基于科学的产业专利合作伙伴识别研究框架,以石墨烯这一典型的基于科学的产业为例,采用专利技术组合和社会网络分析方法,从行动者网络理论的4个行动者转译环节出发,全面展现我国石墨烯产业中最具潜力的国内和跨国专利合作伙伴识别过程,以挖掘专利合作机会并提高企业竞争优势。最后,从政府、高校、企业3个层面为我国石墨烯产业创新发展提供决策参考。     

Two-way relationship between innovation and market structure: evidence from Indian high and medium technology firms

ABSTRACT

This study analyses a two-way relationship between innovation and market structure in Indian high and medium technology firms. We perform an empirical analysis based on a simultaneous equation model on data for 991 high and medium technology firms during 2000–2015. Patent applications and patent grants capture innovation activity of the firms. We find that the market structure has an insignificant impact on innovation. A separate analysis of neck-and-neck firms also suggests that market structure has no impact on innovation. On the other hand, patenting has a positive and significant impact on market structure in both high and medium technology firms. The study concludes that in-house technology creation is a vital source of market dominance in Indian high and medium technology firms.     

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.     

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。     

技术融合对现代制造企业创新绩效的影响：知识基的中介效用

新兴产业普遍呈现出技术融合的趋势,融合创新已经成为把握产业未来发展先机的重要方式,提升响应技术融合的能力是现代制造业企业持续创新亟需考虑的问题。基于技术融合的专利网络特征归结出实践中的三类技术融合形式,应用负二项回归模型对我国汽车制造业上市公司财报和专利数据进行实证分析,探索技术融合对企业创新绩效的影响。研究发现,制造企业实施中介、接近、聚类三类技术融合均有助于提升创新绩效。同时,影响过程伴随着企业知识基的显著中介效用。特别是,中介效用中知识基的宽度对聚类技术融合的影响和知识基的深度对接近技术融合的影响更为强烈。为优化技术融合策略和提升创新绩效提供了企业管理层面的有益参考。     

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.     

Tracking the technological composition of industries with algorithmic patent concordances

ABSTRACT

Patents are a useful proxy for innovation, technological change, and diffusion. However, fully exploiting patent data for economic analyses requires linking patents to measures of economic activity, which has proven to be difficult. We construct probabilistic linkages between the U.S. Patent Classification (USPC) system and Cooperative Patent Classification (CPC) system and industry and product classifications including the North American Industrial Classification System (NAICS), International Standard Industrial Classification (ISIC), Harmonized System (HS) and Standard International Trade Classification (SITC). We use these concordances to evaluate the persistence of technology-industry relationships over time by generating linkages over different years of patent data. We find strong persistence in technology usage within industries and, until recently, relatively little change in the technology composition of industries over time. As the technology composition of industries becomes more stable, we find evidence of increased specialization. Finally, we show that industries that exhibit changing technology composition also show shifting occupational composition.     

An analysis of the intellectual structure of the cloud patents of SaaS

In this study, we reveal and analyse the hitherto implicit intellectual structure of cloud computing by using the methods of patent clustering and co-word clustering, respectively. In order to enhance the quality of patent clustering, we conduct the Taguchi method, which uses the E–I index as the quality characteristic, to investigate three influential factors to the quality, including the cut-off value for dichotomisation, the number of terms, and the sparsity. In co-word clustering analysis, this study demonstrates how the utilisation of the proposed modified co-word analysis method, factor analysis, multidimensional scaling analysis, and network analysis can efficiently explore the relation between R&D themes and competition between companies. This study reveals the knowledge networks in the area of Software as a Service (SaaS), thereby helping academia and practitioners to reach a richer understanding of the up-to-date studies.