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.     

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.     

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.     

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.     

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.     

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.     

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.     

International diffusion of embodied and disembodied technology: A network analysis approach

This study proposes a quantitative method for investigating the structure of international technology diffusion. By using network analysis, this study defines the structural configuration of each country within the international diffusion network by measuring its degree, closeness, and betweenness centralities. In addition, this study distinguishes between embodied technology diffusion, measured by multilateral trade, and disembodied technology diffusion, measured by patent citations, in individual countries. This study empirically tests a sample data set of international technology diffusion taken from 48 countries. The empirical results show that the structural configuration of countries exhibits similar patterns in both embodied and disembodied diffusion networks. Significant global stratification patterns exist in the capability of national international technology exportation and brokerage advantages. Moreover, this study distinguishes four blocks of countries that play different roles in international technology diffusion: the leading countries provide a source of technological knowledge; an intermediate group diffuses the knowledge acquired from the source; a third group is in the process of initiating the export of technological knowledge; and a final group of countries absorbs technological knowledge without reciprocal exportation. Finally, this study identifies two types of catch-up strategies that newly industrialized or developing countries can use to move up the international technology stratification.     

The typology of technology clusters and its evolution — Evidence from the hi-tech industries

Clustering is one of the key drivers for regional economic growth. Development of clusters is a dynamic process shaped by a variety of internal and external factors such as availability of skilled labor, presence of functioning networks and partnerships, technological changes, and market competition, etc. As a result, the patterns of cluster growth may differ from one another. Although each cluster is unique in some way, previous research has attempted to identify few simplified models of evolution of clusters. In this study, we briefly reviewed the literature on a variety of models of clusters. Based on these models, we investigated 15 hi-performing metropolitan-based clusters in the United States, covering communications equipment manufacturing, information technology, and biopharmaceutical industries, in order to find out the similarities and differences between real-world clusters. Specifically, by examining the composition of these high-tech clusters, we attempted to find out the following: 1) What are the typologies of these technology clusters? 2) Whether different industries tend to support different cluster typologies? and 3) How do clusters change their typologies over time? Our analysis results suggest that the real-world clusters rarely feature any single type of typology; a mixed type of typology is much more prevalent in reality.We also found that different industries tend to support different types of cluster typologies. In other words, an individual cluster's typology is to some extent shaped by the industry group it belongs to. In addition, we note that, as a cluster goes through different stages of its lifecycle, its typology may change significantly.     

美国专利实用性探析与启示

文章基于美国专利实用性相关案例资料,对美国专利实用性的内涵、功能进行了分析,报告了美国专利实用性含义的演变历程。通过采用案例分析、规范分析等方法,基于美国相关案例对有关专利实用性含义的解释进行了实证调查,指出了司法案例对于特定实用性、基本实用性、实际实用性、道德实用性的具体界定,同时解读了美国宪法和专利法对于专利实用性的相关规定,反映了专利实用性在化学物质、基因技术等领域的应用问题,认为专利实用性具有提高专利质量和进行利益权衡的功能,美国专利商标局和法院通过对实用性标准进行灵活掌握,有助于实现专利权人与社会公共之间的利益平衡,其运用专利法基本制度作为实现价值权衡工具的做法值得我国借鉴。     

A predictive filtering approach for clarifying bibliometric datasets: an example on the research articles related to industry 4.0

ABSTRACT

This study proposes a filtering approach based on text classification and a fuzzy multi-criteria decision-making technique to select the relevant bibliometric data for further analyses in the scope of bibliometrics, scientometrics, and related methodologies. The proposed approach is illustrated on Industry 4.0 and internet of things which are the concepts that currently draw utmost attention with a growing number of research and applications. Accordingly, various findings are presented revealing the characteristics of the selected bibliometric data with the help of text and network analytics. The potential contribution of this study is two-fold such that the study not only suggests a novel approach for clarifying the retrieved bibliometric data but also emphasises the mainstream research areas and directions of Industry 4.0 along with the concept of the internet of things. Thus, an analysis framework with computing techniques has been used to reveal the characteristics of literature in a field of technology.     

The ADVIAN classification — A new classification approach for the rating of impact factors

A new classification scheme for the impact analysis based on an impact matrix is presented. In contrast to the state-of-the-art methods the impact factors of a social system are not grouped into 4 or 5 groups but ranked according to different criteria. The criteria include for instance the driving impact factors as keys for improvements to the system and the driven impact factors that may be indicators for the improvement success. The ranking for each criterion is on a scale from 0 to 100, independent of the number of impact factors.     

The state of research on technological uncertainties, social uncertainties and emerging markets: A multidisciplinary literature review

The objective of this research work is to study the progress of research on technological uncertainties, social uncertainties and emerging markets and outline and identify the key disciplines, journals, articles and authors. For this the author studied the existing literature from the various fields in which technological uncertainties, social uncertainties and emerging markets research work have been published using ISI Web of Knowledge database. The paper finds that there is increasing research work on technological uncertainties, social uncertainties and emerging markets and the bibliographical search resulted in ninety-one documents written by one-hundred-sixty-one authors in eighty-four journals in seventy-two disciplines. The five major disciplines and their underlying journals are business and economics, agriculture, psychology, public administration, and environmental sciences and ecology accounting for majority of publications. In journals the most prolific, measured by number of articles published are Harvard Business Review, Social Science and Medicine, World Development, and Higher Education; and most influential, measured by the global citation received, are Harvard Business Review, Social Science and Medicine and Sociological Review. The top 10% of the journals are responsible for 23% of all publications but 85% of all global citations received. This highlights that despite the high, diverse and increasing number of journals; only few are dominating and shaping the research arena of technological uncertainties, social uncertainties and emerging markets. Further, in the ten most cited articles, no author appears more than once.     

A compared R&D-based and patent-based cross impact analysis for identifying relationships between technologies

The planning of technological research and development (R&D) is demanding in areas with many relationships between technologies. To support decision makers of a government organization with R&D planning in these areas, a methodology to make the technology impact more transparent is introduced. The method shows current technology impact and impact trends from the R&D of an organization's competitors and compares these to the technology impact and impact trends from the organization's own R&D. This way, relative strength, relative weakness, plus parity of the organization's R&D activities in technology pairs can be identified.A quantitative cross impact analysis (CIA) approach is used to estimate the impact across technologies. Our quantitative CIA approach contrasts to standard qualitative CIA approaches that estimate technology impact by means of literature surveys and expert interviews. In this paper, the impact is computed based on the R&D information regarding the respective organization on one hand, and based on patent data representative regarding R&D information of the organization's competitors on the other hand. As an illustration, the application field ‘defence’ is used, where many interrelations and interdependencies between defence-based technologies occur. Firstly, an R&D-based and patent-based Compared Cross Impact (CCI) among technologies is computed. Secondly, characteristics of the CCI are identified. Thirdly, the CCI data is presented as a network to show the overall structure and the complex relationships between the technologies. Finally, changes of the CCI are analyzed over time. The results show that the proposed methodology has the potential to generate useful insights for government organizations to help direct technology investments.     

Environmental jolts, entrepreneurial actions and value creation: A case study of Trend Micro

This paper draws on a single longitudinal case study of Trend Micro, a leading anti-virus company, to examine its entrepreneurial, value-creating trajectory. Applying and extending an entrepreneurship perspective, the paper manifests positive effect, rather than negative effect, of environmental jolt on entrepreneurial actions including opportunity identification and opportunity exploitation. We find that environmental jolt is likely to shift customers' cognition, which is an important source of opportunity and, in turn, catalyzes opportunity exploitation through innovations for value creation. The paper concludes with a model of the value-creating trajectory of Trend Micro. Implications for research and practices are discussed.     

A dynamic approach for outpatient scheduling

Aims: Patient no-show is a recurrent problem in medical centers and, in conjunction with cancellation of appointments, often results in loss of productivity and excessive patient time to appointment. The purpose of this study was to develop a dynamic procedure for scheduling patients within an outpatient clinic where patients are expected to have multiple appointments, such as physical therapy, occupational therapy, primary care, and dentistry.

Methods: This retrospective study involved the year 2014 de-identified patient records from an outpatient clinic affiliated with a large university hospital. A number of patient characteristics, appointment data, and historical attendance records were examined to determine whether they significantly impacted patients who missed scheduled appointments (no-shows). Patient attendance behaviors over multiple appointments were examined to determine whether their no-show and cancellation patterns differed from one appointment to the next. Decision tree analysis was applied to those predictors that significantly correlated with patient attendance behavior to assess the likelihood of a patient no-show. A sample dynamic appointment scheduling procedure that utilized different overbooking strategies for different appointment numbers was then developed. Computer simulation was used to assess the effectiveness of the dynamic procedure versus two other methods consisting of randomly assigned and uniformly assigned appointments.

Results: The dynamic scheduling procedure resulted in increased scheduling efficiency through overbooking but with less than 5% risk of appointment conflicts (i.e. two patients showing at the same time), equating to approximately 0.16 conflicts per clinician per day. It also increased clinic utilization by about 6.7%. It consistently outperformed the other two methods with respect to the percentage of appointment conflicts.

Limitations: The study is limited with respect to potential clinician cost increase resulting from possible appointment conflicts. A second limitation is that patients experiencing appointment conflicts might not wait for treatment, resulting in potential loss of revenue. A third limitation is that the model does not take into account patient satisfaction, nor the ethics of overbooking patients.

Conclusions: A dynamic appointment scheduling procedure was developed using actual patient characteristics. The procedure resulted in creation of more efficient appointment schedules thereby increasing the clinic utilization.     

Defining key inventors: A comparison of fuel cell and nanotechnology industries

This paper defines the notion of key inventors — those whose patenting is simultaneously highly productive and also widely cited. By implication, key inventors should be the leaders in any developing new field and we investigate the validity of the notion through an exploration of two emerging technological fields: fuel cell and nanotechnology. The nature of the two groups is compared to discuss the differences between the technological groups.     

The Czech economy as an integrated periphery: The case of dependency on Germany

The Czech Republic (CZ) is a small open economy that has been integrated into the European economy predominantly through its ties to Germany. Traditional analysis has focused on the positive aspects of this process and pointed out the favorable indicators of the Czech economy, strongly influenced by a modernist perspective (model of economic development) and neoliberalism (applied economic policies). The aim of this article is a more critical reflection on some important features of the Czech economic model. The application of some currently emerging analytic instruments of international economic relations allows us to point out many problematic features of the Czech economy—in particular its dependence on foreign capital combined with a weak ability to retain it and the low added value created within the CZ. There are indicators suggesting a dependent growth within a rigid pattern of an international division of labor and wealth distribution. We argue that shortcomings of the neoliberal model of development (even) in the case of a well prepared and governed economy are a good reason to bring the insights of dependency theory back into the discussion.     

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.     

A systematic quantitative backcasting on low-carbon society policy in case of Kyoto city

In order to realize a low-carbon society (LCS), it is necessary to formulate a comprehensive policy consisting of a large number of “options” (i.e., policies as well as technical and behavioral measures). Based on the concept of backcasting, this paper proposes a methodology and a model, called the backcasting model (BCM), that organizes a system of various LCS options and projects their detailed schedule toward a given target year. The methodology and model mainly focus on describing a complex system of LCS options and the consistency of their schedule. Other aspects such as the costs of LCS measures, stock dynamics of technologies, and effects of economic instruments are not explicitly considered. To permit quantitative treatment of various types of options, they are classified into several categories. The BCM calculates the schedule of the options under given quantitative information on the options and relationships between them. The methodology and model were applied to Kyoto City as an example. First, a quantitative snapshot of socioeconomic status and greenhouse gas (GHG) emissions was described. In the snapshot, a 45% reduction of GHG emissions compared with 1990 was achieved with moderate economic growth. The BCM was applied to about 130 options shown in an action plan of the Kyoto Municipal Government, and a schedule of the options was calculated. This methodology treats wide-ranging and complex low-carbon options in a quantitative and consistent manner and supports the policymaking process toward the realization of a low-carbon society.