19 research outputs found

    Collective Intelligence: An Emerging World in Open Innovation

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    Responding to the lack of empirical research on the effect of collective intelligence on open innovation in the fourth industrial revolution, we examined the relationship between collective intelligence and open innovation. Collective intelligence or crowd innovation not only produces creative ideas or inventions, but also moderates any firm to innovate inside-out, outside-in, or in a coupled manner. We asked the following research questions: Does collective intelligence (or crowd innovation) motivate open innovation? Is there any difference in the effect of collective intelligence on open innovation by industry? These research questions led to the following three hypotheses: (1) Collective intelligence increases the performance of a firm, (2) collective intelligence will moderate the effect of open innovation, and (3) differences exist between the automotive industry and the pharmaceutical industry in these two effects. To empirically examine these three hypotheses, we analyzed the registered patents of these two industries from 2000 to 2014 over a 15-year period. These automotive and pharmaceutical patents were registered in the B60 category and the A61K category of the Korea Patent office, respectively. Collective intelligence was measured by co-invention. We found differences in the effects of collective intelligence on open innovation between the two industries. In the automotive industry, collective intelligence not only directly increased the performance, but also indirectly moderated the open innovation effect. However, this was not the case for the pharmaceutical industry. © 2019 by the authors.1

    Open innovation of knowledge cities

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    Purpose: This research seeks to answer the basic question, "As a city evolves from an industrial city to a knowledge one, are its open innovation activities vitalized?" Design/methodology/approach: In this research, we compare the total number of patent applications, the number of joint applicants of each patent, and the ratio of patents jointly applied, in four Korean cities-Daegu, Kwangju, Cheonann total, top 10 % patent applicants group among total patent applicants, and the lower 70 % patent applicant group among total patent applicants. The research included 144,625 patents submitted to the Korea Patent Office from 1981 to 2010. Findings: As knowledge-based urbanization proceeds, the size of a knowledge city increases. The lowest 70 % of patent applicants (rather than the top 10 %) apply for more patents, and the breadth and depth of open innovation rises. Research limitations/implications (if applicable): This research is limited to mutual patent applications as a target of open innovation. In the future, additional research will need to be conducted on various open innovation channels such as patent citation, intellectual property right transfer, licensing, and M & A. Practical implications (if applicable): To maximize the beneficial characteristics of a knowledge city in a large city, the improvement of open innovation across the city is essential. Social implications (if applicable): If strengthening open innovation by SMEs or start-ups is set as a corporate strategy or a government policy, it will be a source of development of knowledge-based urbanization and continued economic development of a knowledge city, as well as of the total knowledge assets. © 2015 Yun et al.TRU

    Structural Relationship and Influence between Open Innovation Capacities and Performances

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    Previous studies related to open innovation have presented piecewise implications in relation to various knowledge management capacities. The study published by Lichtenthaler and Lichtenthaler in 2009 presented a model that combines the various open innovation capacities of firms in view of a mix of knowledge management, dynamic capability and absorptive capacity. Despite these efforts, there have been few empirical studies on the relationships among capacities, or between capacities and performance from an integrated perspective. Therefore, this study seeks to clarify the relationships among knowledge capacities and between knowledge capacities, technological innovation and financial performance at the firm level. Our findings are that the transformative, connective, inventive and absorptive capacities both directly and indirectly affects technological innovation performance; and innovative and desorptive capacities are the key factors connecting technological innovation to financial performance. This study provides managerial implications for the balanced development of the various knowledge capacities and the improvement of technological innovation and financial performance for firm knowledge managers

    Network Analysis of Open Innovation

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    The way people innovate and create new ideas and bring them to the market is undergoing a fundamental change from closed innovation to open innovation. Why and how do firms perform open innovation? Firms’ open innovation is measured through the levels of firms’ joint patent applications. Next, we analyze network structures and characters of firms’ joint patent applications such as betweenness and degree centrality, structure hole, and closure. From this research, we drew conclusions as follows. First, the structure of collaboration networks has both direct and indirect effects on firms’ innovative performance. Second, in the process of joint patent applications, there is a long tail phenomenon in networks of joint patent applications. Third, the number of patents and International Patent Classification (IPC) subclasses together constitute a meaningful measure of the innovation performance of firms

    Patent value and survival of patents

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    This study investigated the effect of patent value on the renewal (survival) of patents. The private value of patents can be one of the main pillars sustaining a firm's value, and the estimation of the value may contribute to the strategic management of firms. The current study aimed to confirm the recent research findings with survival analysis, focusing on the more homogeneous patent data samples. In this study, a dataset is constructed from a cohort of 6646 patents from the 1996 and 1997 application years, using patent data from the European Patent Office (EPO). We found that the family size and non-patent backward citations exhibited profound impacts on patent survival. This result is in line with numerous studies, indicating the positive impact of science linkages in the biotechnology and pharmaceutical fields. It was also found that the effect of the ex-post indicator is not as strong as the ex-ante indicators, like traditional family size and backward citations. In short, the family size matters most for the survival of patents, according to the current research

    The Effect of Open Innovation on Technology Value and Technology Transfer: A Comparative Analysis of the Automotive, Robotics, and Aviation Industries of Korea

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    With the advent of the Fourth Industrial Revolution, the Korean industrial environment has been rapidly changing. As a result, several industries are facing different innovation conditions, including: the automotive industry, which is a traditional manufacturing industry in Korea; the aerospace industry, which has been vertically integrated, and has been led by a single large company—Korea Aerospace Industries—since Korea went through an economic crisis in the 1990s; and the robotics industry, which is currently emerging. This study used parameters related to patents originating from the automobile, robotics, and aerospace fields. The patents subjected to analysis were those registered in Korea from 2001 to 2014, and included those that were applied for, jointly applied for, or registered by Korean companies. This study analyzed the differences caused by the effect of open innovation in the three industries. According to our results, first, the three industries experienced different effects of open innovation. Second, when large companies controlled a given industry, open innovation either worked a little or did not work at all. According to this research result, the Korean robotics industry, which has a weak dominance of large companies, experienced a strong effect of open innovation, in that joint patent applications led to economic gains from the patents and an increase in technology transfer and technology value. The aerospace industry of Korea, which has the highest dominance of large companies, experienced a slight effect of open innovation, as the effect of joint patent application only improved the technology value. Finally, the automotive industry of Korea had an intermediate level of open innovation, between the aerospace and robotics sectors

    Effect of Distance on Open Innovation: Differences among Institutions According to Patent Citation and Reference

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    The main topic of this paper is the effects of distance between technology and the market, on open innovation. For this, we set up two research questions, as follows: Is there any relation between the distance between technology and the market, and open innovation? If there is, what differences are there in the relation among Fortune 500 companies, non-Fortune 500 companies, laboratories, universities, and start-ups? First, this study measured the distance between technology and the market of a patent by the size of its list of references and citations. Second, the OI network among patent application subjects was described based on patent similarity. Third and most importantly, regression analyses were used to answer the research questions. The first result was that there were differences in the distance and OI among Fortune 500 firms, Fortune non-500 firms, laboratories, universities, and start-ups. Thus, there are relations between the distance between technology and the market, and open innovation. The second result was that the distance between technology and the market was found to moderate the open innovation effect in Fortune 500 companies and laboratories

    Measuring patent value indicators with patent renewal information

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    This paper attempts to fill a research gap of literature by constructing the dynamic model into which both ex ante and ex post patent value indicators are incorporated. A patent renewal model is tested using a large set of Pharmaceutical patents granted by the European Patent Office between 1996 and 2009. We test five ex ante indicators and single ex post indicator including family size, patent backward citations, backward references to non-patent literature, number of claims, number of inventors, renewal fee, patent age, application year, and the ex post indicator forward citations. Empirical findings show that three citation related indicators, family size, and the number of claims are positively associated with patent values, while the number of inventors, renewal fee, patent age, and application year are negatively correlated. In addition, forward citations seem to have persistent learning effects on patent values

    Dismantling of the inverted U-curve of open innovation

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    The purpose of this study is to address the following research question: What is the relationship between open innovation and firm performance? The study built up a research framework with three factors—i.e., open innovation strategy, time scope, and industry condition—to find out the concrete open innovation effects on firm performance. This study adopted four different research methods. Firstly, we applied the aforementioned factors to a game of life simulation in order to identify the concrete differences of open innovation effects on firm performance. Secondly, the study examined the real dynamics of open innovation effects on firm performance in the aircraft industry—one of the oldest modern industries—through a quantitative patent analysis. It then looked into the effects of major factors that impact open innovation effects. Thirdly, this study developed a mathematical model and tried to open the black box of open innovation effects on firm performance. Lastly, the study logically compiled research on open innovation effects on firm performance through the presentation of a causal loop model and derived the possible implications
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