• Journal of Digital Convergence
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• v.19 no.3
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• pp.65-79
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• 2021

The purpose of this study was to research how emotional factors affect decision-making on the maintenance and abandonment of a patent, and to present new criteria for patent policies. The types of Korean patent abandonment were analyzed according to the patent holding period, and a questionnaire survey was carried out to verify whether there are differences among patentees in terms of sunk cost bias, endowment effect, and coupling or not. Individuals and small and medium-sized enterprises showed relatively greater emotional bias toward sunk cost and endowment effect than large companies, and the sunk cost effect decreased as decision-making experience increased. In addition, the reduction in the payment cycle of the patent renewal fee has a positive effect on the increase in the willingness to use the patent right, and the individuals and small and medium-sized enterprises has a greater synergistic effect than the case of large companies, in particular. This study are expected to play a part in establishing policies to minimize wasteful factors of patent assets based on the propensity of the patentees.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.147-170
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• 2022

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.

• Knowledge Management Research
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• v.11 no.1
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• pp.65-81
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• 2010

This paper explores the determinants of the economic value of patents using a survival time analysis. The analysis is based on renewal information of about 250,000 patents filed from 1984 to 2005 in the Korea Intellectual Property Office. A patent right is valid only when its owner pays yearly maintenance fees. Failure to pay causes patent rights to be lapsed. We use the fact that more valued patents live longer and the lengths of their renewals can be closely related to their value. The value can be affected not only by its own technological aspects such as quality and breadth, but also by characteristics of its owners such as innovativeness and age. This paper presents patent-specific and firm-specific characteristics which influence patent value. The result of analysis implies that patent value depends on both the technological contents of the patent and general capabilities of a firm.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.1-8
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• 2020

The use of text data in big data analytics has been increased. So, much research on methods for text data analysis has been performed. In this paper, we study Bayesian learning based on conjugate prior for analyzing keyword data extracted from text big data. Bayesian statistics provides learning process for updating parameters when new data is added to existing data. This is an efficient process in big data environment, because a large amount of data is created and added over time in big data platform. In order to show the performance and applicability of proposed method, we carry out a case study by analyzing the keyword data from real patent document data.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.676-693
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• 2016

Although the methodology and models to assess the economic value of technology assets such as patents are being presented in various ways, there does not exist a structured assessment model which enables to objectively assess a database property's value, and thus there is a need to enhance the application feasibility of practical purposes such as licensing of DB assets, commercialization transfer, security, etc., through the establishment of the valuation model and the life-cycle decision logic. In this study, during the valuation process of DB assets, the size of customer demand group expected and the amount of demand, the size and importance of data sets, the approximate degree of database' contribution to the sales performance of a company, the life-cycle of database assets, etc. will be analyzed whether they are appropriate as input variables or not. As for most of DB assets, due to irregular updates there are hardly cases their life-cycle expires, and thus software package's persisting period, ie. 5 years, is often considered the standard. We herein propose the life-cycle estimation logic and valuation models of DB assets based on the concept of half life for DB usage frequency under the condition that DB assets' value decays and there occurs no data update over time.