Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.
Technological substitution is the process by which a radical technology replaces the dominant technology in an industry. The processes of diffusion and substitution have been modeled extensively (Technology & innovation, 2010). However, the formulation of classical quantitative models encompasses only part of the theoretical space. These models impose many simplified constraints to the achievement of analytical resolution. The interior design organization needs to establish a set of technical system requirements by describing the scope of the accessibility needs of the organization against current technology use. Because of complicated design resources and ongoing advances in design technologies, design systems face the challenge of prioritizing new technologies for supporting. The problem is small design organization administration often displays a lack of concern toward the evaluation of technology integration. In this paper, I will identify the influence of a design organization's technology, and predict how future technology will inform, support, and potentially hinder productivity, culture, and work satisfaction within a design organization in the industry. In addition, I will use current design organizational behavior and leadership models to support my predictions. Finally, I will examine a proven approach to assist designers with evaluating technology integration in interior design organization. The goal is to develop a high quality, professional development scorecards for the evaluation. I will conduct both the evaluation of technology integration and CRM performance evaluation is recommended to assess the effectiveness of technology integration. Therefore, the evaluation of integration technologies oriented design hold the promise of solving the organization application integration challenge. The evaluation of integration technology is a significant pattern for processing such a vision. The careful selection of an integration technology for this purpose is crucial in contributing toward the success of such an interior design organization endeavor.
IPTV(Internet Protocol Television) is an innovation technology to lead the new media age. Internet protocol television (IPTV) is a next generation television converged with the Internet which are delivered portal services such as information search, games, movies, home shopping and banking. Generally, service quality affects to adopt or use these technologies. Quality of experience (QoE) is more issue to be considered than service quality because of the technological restriction and limitation that IPTV is accessed by the Internet. The QoE is defined as the cognitive and experienced quality measured with users through an experiment and is conceptually related to service quality. The objective of this paper is to suggest a methodology to measure the QoE of IPTV using a user testing. We find significant factors affecting QoE of IPTV through an exploratory study and measure QoE scores. We found the nine factors of graphics, picture, accuracy, access method, quality of contents, usability, security, and performance important for QoE. The QoE scores of picture, graphics, and quality of contents gained over the average score, but the overall score for IPTV service providers was not high and the QoE needs to be improved.
Journal of Korea Society of Digital Industry and Information Management
/
v.17
no.1
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pp.57-73
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2021
The purpose of this study is to analyze the diffusion period and productivity of smartwork in an organization. Firms are increasingly interested in smartwork for non contact work and working from home because of the corona 19. The smartwork is a new technology that changes face-to-face work in an organization. It helps the work of individuals and organizations regardless of time and place. The theoretical background describes the complexity, system thinking, diffusion theory, smart work, organizational resistance, and productivity. This study analyzes the diffusion period and productivity of smart work through business simulation techniques. A simulation study progresses four stages. There are problem definition, hypothesis establishment and causal loop diagram, model construction and verification, and policy evaluation. The simulation models contain an individual's resistance variables organizational investment and leadership variables related to the operation of smartwork. The organizational investment variables include organizational culture, legal system, implement systems and technology investment. The individual resistance variables include cognitive, attitude, structure and technological resistance. The leadership includes leadership interest variables and performance linkage variables. The simulation executed the changes of a people number adopting smart work and the organizational productivity monthly. As a result of the simulation, many organization members have accepted the smart work innovation after 20 months. The organizational productivity through smart work showed very high value after 16 months. In scenario analysis, the individuals' awareness and attitude resistance showed very important variables to productivity and a personal change of smart work adoption. Meanwhile, The organizational investment showed that the high driving-force increased not productivity and the low driving-force showed decreased low productivity. Also, leadership variables showed a powerful driver for changing smart work productivity. The implication of the study has suggested extending complexity, diffusion theory and organization resistance theory based on simulation methods.
Journal of the Korea Institute of Information and Communication Engineering
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v.26
no.1
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pp.64-69
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2022
Commercialization of public technology is the transfer of government-led scientific and technological innovation and R&D results to the private sector, and is recognized as a key achievement driving economic growth. Therefore, in order to activate technology transfer, various machine learning methods are being studied to identify success factors or to match public technology with high commercialization potential and demanding companies. However, public technology commercialization data is in the form of a table and has a problem that machine learning performance is not high because it is in an imbalanced state with a large difference in success-failure ratio. In this paper, we present a method of utilizing CTGAN to resolve imbalances in public technology data in tabular form. In addition, to verify the effectiveness of the proposed method, a comparative experiment with SMOTE, a statistical approach, was performed using actual public technology commercialization data. In many experimental cases, it was confirmed that CTGAN reliably predicts public technology commercialization success cases.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.6
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pp.197-206
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2021
There is growing interest in the function and role of public research institutes as "entrepreneurial actors" that can contribute to industrial development by commercializing excellent research outputs. On the other hand, their performance in the commercialization phase is insufficient because of the insufficient technological technology readiness level or repeatability. This study conducted probit model analysis to examine the effect of the technology readiness level and commercialization activities on the success of technology commercialization. The results showed that the possibility of success in technology commercialization increased with increasing TRL at the time of acquisition. In addition, the difference between the TRL at the time of acquisition and the current TRL (TRL Gap) does not affect technology commercialization on its own. It generates additional effects in conjunction with the TRL at the time of acquisition. Finally, the results show that technology commercialization is most likely to succeed if technology with a TRL 4-6 level is improved to TRL 9 level through a marginal effect estimation.
The Journal of the Convergence on Culture Technology
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v.6
no.2
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pp.437-447
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2020
The purpose of this study is to research the countermeasures and expected effects through the use of drones in the field of disaster prevention as a drone-based smart quarantine performance method. The environmental, market, and technological approaches to the review of the current quarantine performance task and its countermeasures are as follows. First, in terms of the environment, the effectiveness of the quarantine performance business using drone-based control is to broaden the utilization of forest, bird flu, livestock, facility areas, mosquito larvae, pests, and to simplify and provide various effective prevention systems such as AI and cholera. Second, in terms of market, the standardization of livestock and livestock quarantine laws and regulations according to the use of disinfection and quarantine missions using domestic standardized drones through the introduction of new technologies in the quarantine method, shared growth of related industries and discovery of new markets, and animal disease prevention It brings about the effect of annual budget savings. Third, the technical aspects are (1) on-site application of disinfection and prevention using multi-drone, a new form of animal disease prevention, (2) innovation in the drone industry software field, and (3) diversification of the industry with an integrated drone control / control system applicable to various markets. (4) Big data drone moving path 3D spatial information analysis precise drone traffic information ensures high flight safety, (5) Multiple drones can simultaneously auto-operate and fly, enabling low-cost, high-efficiency system deployment, (6) High precision that this was considered due to the increase in drone users by sector due to the necessity of airplane technology. This study was prepared based on literature surveys and expert opinions, and the future research field needs to prove its effectiveness based on empirical data on drone-based services. The expected effect of this study is to contribute to the active use of drones for disaster prevention work and to establish policies related to them.
As of April 2006, Korea had successfully invited twelve global IT R&D centers to help implement the u-IT839 strategy, but there have also been some worries about their research and collaboration performance in Korea. Although it is too early to judge the invitation outcome only after two years or less of their working, the Korean government is being advised to employ a more customized invitation strategy. In this paper, an analytic framework for the attraction of global R&D centers is developed based on the attractiveness-competitiveness matrix, and is applied empirically to the IT industry. Fourteen major IT technology categories and their sub-technological areas are classified into four strategic groups (priority group, wish group, consideration group, and hold group) along the framework via expert surveys and the Analytic Hierarchy Process (AHP) technique. This study is expected to help the government to implement the 'select and focus' strategy in inviting global R&D centers and creating synergy effects between them by providing basic data on global R&D partnership priorities. The implications and limitations of the research and future research directions are discussed at the final section.
This paper delineates dynamic capabilities, which can be measured by internal capability and external knowledge, and also, in the shape of dynamic capabilities, bases on that corporate actions are expatiated by fitness and rent of evolutionary perspective. To achieve the goal of this study, classifying types of Nano-technology enterprise and suggesting analytical pattern based on dynamic capabilities, this thesis substantially analyzes how to categorize a type of enterprise and gauge a result through a survey of 359 domestic companies producing goods concerned with Nano-technology. This paper analyzes whether or not the internal capability and external knowledge affect the outcome of a certain enterprise. Moreover, in according to the results of practical analysis, it deducts 2 new variables by applying principal component analysis on four previous variables showing the internal capability and external knowledge. By classifying four types of enterprises with criterion of these two factors based on a relative extent and comparing each typical financial result, this paper suggests that the companies with relatively higher level of the internal capability and external knowledge surpass the lower ones at the financial outcome. Not only this, but also the technology-level analysis shows the same result, the higher capability and knowledge the higher performance. However, the analysis based on the difference of the four types of financial outcomes reveals that technological and evolutionary fitness can determine financial achievement.
With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.
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