• Korea Trade Review
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• v.48 no.1
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• pp.83-126
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• 2023

The revenue histogram of venture businesses is shifting from bell-shaped normal distribution to power-law distribution, which implies that the fitness landscape of the venture businesses ecosystem is changing to be more rugged terrain. We argue that the firm should adopt both exploitation (fast follower) and exploration (or first mover) strategies not to get stuck in local maxima in the rugged fitness landscape from the complex system perspective. By designing and performing agent-based modeling simulation experiments which consist of three types of agents (new technologies, entrepreneurs, and consumers), we demonstrated that the ambidexterity strategy showed the highest performance score in three of four different environment except 'Fast Widening' case where the exploitation strategy showed the highest performance score under low technology appropriation and fast disruptive technology development speed. By investigating the financial and other statistics of 617 top venture businesses who have earned 100B won or higher annual revenue, we concluded that 82% and 9% of firms are bent on the exploitation and exploration strategy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6B
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• pp.551-563
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• 2011

Water resource projects need an enormous national budget. Therefore, a reasonable and reliable decision making is required for the planning of water resource projects, but decision making has been mostly performed by economic analysis. The objective of this study is to develop a Multi-criteria Decision Making(MCDM) model which can assess the project in various aspects for the selection of preferable alternative and determination of investment priority in water resource projects. In this study, the criteria involves economic feasibility, policies, vulnerability, and sub-items which have weights obtained from the expert survey for the consistent evaluation. We also derived the utility function considering risk trend of each item based on the expert survey. Then, the total score was estimated by weights of each item and utility score of each attribute. The results show that vulnerability is a major contributor for the criteria. This study will contribute to the selection of proper water resource projects considering efficiency of project and fairness for vulnerable area.

• Journal of Korea Technology Innovation Society
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• v.15 no.3
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• pp.649-674
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• 2012

The purpose of this study is to investigate the effects of public R&D subsidies on private R&D. We have analyzed rationales for the public R&D subsidy from different perspectives. On the basis of literature review, a two step research model is constructed: participation phase (when firms benefit from public subsidies) and decision phase (when firms make decision on additional R&D investments). Using propensity score matching(PSM) method, we compare the potential outcome of the treated group to a matched controlled group of non-subsidized firms. The data used in this paper was collected from various sources. The Korean Innovation Survey 2008(manufacturing sector) is a main source of data. Financial data such as revenue, asset and capital stock, and number of employees were supplemented from the Nice Information Service KIS Value database. The R&D survey, conducted by MEST(Ministry of Education, Science and Technology) each year, was also used for the R&D expenditures of the manufacturing firms. This study comes up with the following empirical results. First, a firm's innovation capability, financial constraints, and sector appear to influence the selection of firms who were benefited from government's financial supports for R&D. Second, empirical results show that public R&D funding complements private investment on average and appear to have perpetual effects on the following year. Finally, sectoral difference in the effect of public subsidies on firms' R&D investment was confirmed. In addition, SMEs show more positive effects than large firms.

• Journal of Korea Technology Innovation Society
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• v.21 no.2
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• pp.767-787
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• 2018

Technology-driven innovation and job-creation has each been the subject of much scholarly attention, but have largely been considered separately rather than in conjunction with each other. While the previous literature on economics pinpointed the macro effects on industry-level, this study explores the micro-level comparisons on innovation sources over the employment and financial performances. The PSM (propensity-score matching) analysis presents that firms, involved in an inward technology, tend to have higher employees with dominant technology capabilities than in-house R&D firms. The in-house R&D firms, on the contrary, have superior financial performances, suggesting that external technology commercialized firms suffer from low transformative efficiency. The mediation test analysis corroborates that the external technology-driven innovation induces more human resources in internalizing the exogenous technology. The positive relationship between R&D innovation and employment allow verification of the government's intervention in the promotion of technology commercialization in public sector. On the other hand, it also signals that the policy needs to enhance the recipient firms' commercializing capacity rather than a 'one-hit' transaction.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.527-556
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• 2019

In Korea, nearly 100 billion won is spent annually under the name of energy voucher on 600,000 households for the last five years, and this is a unique case and hard to monitor worldwide. Therefore, no studies have been conducted to assess impacts of the energy voucher on energy consumption and cost burden alleviation for beneficiaries. This paper aims to demonstrate the effectiveness of energy vouchers in terms of energy expense. The propensity score matching was conducted on samples of low-income households based on the Korea Welfare Panel. Then, simple Difference-In-Differences and Fixed-Effect Difference-In-Differences models were applied to estimate the effect of energy vouchers. In results, the beneficiaries of energy vouchers would spend an additional 4,371~4,870 won per month on energy consumption. The ratio is equivalent to 51.9~57.7 percent of the aid, which is also the highest when compared with 23~56 percent of U.S. Food Stamp. In terms of energy welfare, voucher payment could become one of the best management practices. However, identifying the blind spots as non-reciprocal households and expanding the differential support mechanism that reflects the energy consumption environment should be solved in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.57-69
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• 2023

In a situation where digital transformation using artificial intelligence is active around the world, the growth of domestic AI companies or AI industrial ecosystems is slow. Where a large amount of government funds related to AI are being invested to overcome the difficult economic situation, systematic research on the effect is insufficient. So, this study aimed to examine the policy effectiveness of the government artificial intelligence solution voucher support project for small and medium-sized enterprises (SMEs) using Propensity Score Matching (PSM) and Difference-in-Differences (DID) on the financial performance of beneficiary companies. For empirical analysis, PSM-DID analysis was performed using sales performance since 2019 for 461 companies with a history of voucher support among the AI SMEs data released by the National IT Industry Promotion Agency. As a result of the analysis, the beneficiary companies' asset growth, salary, and R&D expenses increased overall after government support, and no significant contribution could be confirmed in terms of profits. This study suggests that the voucher policy business directly contributed to the company's growth in the short term, but it requires a certain period of time to generate profits.

• Cartoon and Animation Studies
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• s.39
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• pp.393-412
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• 2015

See and feel the emotion recognition is the image of a person variously changed according to the environment, personal disposition. Thus, the image recognition has been focused on the emotional sensibilities computer you want to control the number studies. However, existing emotional computing model is numbered and the objective is clearly insufficient measurement conditions. Thus, through quantifiable image Emotion Recognition and emotion computing, is a study of the situation requires an objective assessment scheme. In this paper, the sensitivity was represented by numbered sizes quantified according to the image recognition calculation emotion. So apply the principal attributes of the color image emotion recognition as a configuration parameter. In addition, in calculating the color sensitivity by applying a digital computing focused research. Image color emotion computing research approach is the color of emotion attribute, brightness, and saturation reflects the weighted according to importance to the emotional scores. And free-degree by applying the sensitivity point to the image sensitivity formula (X), the tone (Y-axis) is calculated as a number system. There pleasure degree (X-axis), the tension and position the position of the image point that the sensitivity of the emotional coordinate crossing (Y-axis). Image color coordinates by applying the core emotional effect of Russell (Core Affect) is based on the 16 main representatives emotion. Thus, the image recognition sensitivity and compares the number size. Depending on the magnitude of the sensitivity scores demonstrate this sensitivity must change. Compare the way the images are divided up the top five of emotion recognition emotion emotions associated with 16 representatives, and representatives analyzed the concentrated emotion sizes. Future studies are needed emotional computing method of calculation to be more similar sensibility and human emotion recognition.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.485-499
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• 2022

Controlling the total survey error including sampling error and non-sampling error is very important in sampling design. Non-sampling error caused by non-response accounts for a large proportion of the total survey error. Many studies have been conducted to handle non-response properly. Recently, a lot of non-response imputation methods using machine learning technique and traditional statistical methods have been studied and practically used. Most imputation methods assume MCAR(missing completely at random) or MAR(missing at random) and few studies have been conducted focusing on MNAR (missing not at random) or NN(non-ignorable non-response) which cause bias and reduce the accuracy of imputation. In this study, we propose a non-response imputation method that can be applied to non-ignorable non-response. That is, we propose an imputation method to improve the accuracy of estimation by removing the bias caused by NN. In addition, the superiority of the proposed method is confirmed through small simulation studies.

• Korean Journal of Psychosomatic Medicine
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• v.21 no.1
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• pp.18-26
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• 2013

Objectives : Type D personality was originally introduced to study the role of personality in predicting outcomes of heart disease. However, researches showed that other medical conditions are also affected by this personality. The purpose of this study was to evaluate the relationship between type D personality and somatic symptom complaints in depressive patients. Methods : Eighty-two individuals diagnosed with depressive disorder were included. Type D personality was measured with DS14. Patient Health Questionnaire(PHQ) 9 and 15 were used to measure depression severity and somatization tendencies. For alexithymia, TAS-20 was used. Student T-test and linear regression analysis were performed. The best regression model was determined by stepwise variable selection. Results : More than half of the subjects(56%) complained at least medium degree somatic symptoms according to PHQ-15 criteria. Two-thirds of the subjects were classified as Type D personality(63.4%). The mean PHQ-15 score of the Type D individuals was significantly higher than the remaining subjects(PHQ-15 mean=12.7, $p=8.2{\times}10^{-7}$). The best regression model included age, PHQ-9 score and NA subscale score as predictor variables. Among these, only the coefficients of age($p=1.5{\times}10^{-3}$) and NA score($p=1.5{\times}10^{-7}$) were found to be statistically significant. Conclusions : The result showed that Type D personality was one of the strong predictors of somatic complaints among depressive individuals. The finding that negative affectivity rather than social inhibition was more closely associated with somatization tendencies does not fully agree with the traditional explanation that inability to express negative emotion predispose the individuals to somatic symptoms. The finding that alexithymia was not shown to be a significant predictors also substantiated this discrepancy. However, it might be possible that the high correlation between NA and SI subscore(r=0.65) and between NA and TAS-20 score(r=0.44) hid the additional effects of social inhibition and alexithymia. Further research with a larger sample would be needed to investigate the effects of the latter two components over and above the effect of negative affectivity on the somatic complaints in depressive patients.

• Korean Journal of Social Welfare Studies
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• v.45 no.2
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• pp.5-30
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• 2014

This study sought to identify developmental trajectories of bullying victimization from late elementary school through early high school, and to examine internalizing and externalizing problem outcomes associated with the trajectory group membership. Data from Seoul Panel Study of Children were collected annually over a 7-year period from 5th grade of elementary school through 2nd grade of high school (2005~2011). Latent class growth analysis yield three trajectory classes corresponding to stable low (81.2%), stable high (3.5%), and declining bullying victimization (15.6%). Findings from analysis of covariance indicated that students in both stable high and declining trajectory groups reported significantly higher means in internalizing behavior (withdrawal, depression/anxiety, and suicide ideation), compared to those in the stable low group. For externalizing behavior such as aggression and juvenile status offense, students in the stable high group showed higher means, compared to those in the stable low and declining trajectory groups. Developmental pattern of bullying victimization over multiple development stages and associated internalizing and externalizing outcomes are discussed as are the implications for the bullying prevention.