• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.508-517
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• 2020

Servitization presents an innovative model to create business value in the automotive industries. This study set out to introduce a servitization model based on the rental business of the tire industry and identify determinants to affect the renewal of contracts around the service types of servitization and the characteristics of customers. Independent variables include the service types, demographics and regions, and inflow channels in 163,742 contracts by case companies in the nation in 2016~2019 with the renewal of contracts as a dependent variable. Correlations between variables were analyzed through cross-tabulation and binary logistic regression analysis. The findings show that the contract renewal rate had positive(+) relations with customized service and negative(-) ones with vehicle maintenance service. There were differences in the contract renewal rate according to such customer characteristics as gender and region, but no clear correlations were found in the age group and vehicle type(domestic/foreign). Of the inflow channels, offline channels tended to have a higher renewal rate than online channels. At open malls, contract renewal increased by 8.4 times due to contract switches at offline channels. Based on these findings, the study discussed directions for practical strategies with regard to the development of new service, implementation of customer-centric servitization, and management of sales channels according to the servitization of manufacturers.

• Korean Journal of Social Welfare Studies
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• v.48 no.4
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• pp.59-89
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• 2017

Changes in the public welfare attitudes are very important to the welfare politics and policy. Considering that variability of public welfare attitudes has been ignored in previous studies, we analyzed welfare attitudes changes at individual level in Korea. Using the longitudinal data from the Additional Survey of 2010/2013/2016 Korea Welfare Panel Survey, we analyzed the changes in public welfare attitudes during 2010th-2016th years. Major findings are as follows. First, one of the findings from analysis is that the public welfare attitudes are very active and dynamic in Korea. This finding is contradiction to the results of the previous researches that are point to the stability or inertia of the public welfare attitudes in western welfare states and also in Korea. Second, occurrences of the welfare attitudes change are related with various individual characteristics; income status, occupation status, age, region, sex, political ideology, etc. These results from this study on the welfare attitudes change suggest that dynamics of the Korea welfare politics in recent years reflected the dynamic changes in public welfare attitudes. And, they suggest that Korea welfare politics are transformed from the traditional classes welfare politics to the new welfare politics which are influenced by various interests of the socio-demographic groups.

• Tunnel and Underground Space
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• v.33 no.5
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• pp.399-413
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• 2023

The present study conducted a numerical modeling of CO₂ injection at the Janggi Basin using the TOUGH-FLAC simulator, and examined the hydro-mechanical stability of the aquifer and the fault. Based on the site investigations and a 3D geological model of the target area, we simulated the injection of 32,850 tons of CO₂ over a 3-year period. The analysis of CO₂ plume with different values of the aquifer permeability revealed that assuming a permeability of 10^-14 m² the CO₂ plume exhibited a radial flow and reached the fault after 2 years and 9 months. Conversely, a higher permeability of 10^-13 m² resulted in predominant westward flow along the reservoir, with negligible impact on the fault. The pressure changes around the injection well remained below 0.6 MPa over the period, and the influence on the hydro-mechanical stability of the reservoir and fault was found to be insignificant.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.109-121
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• 2024

This paper adopts a resource-based approach to analyze why some universities have a greater number of faculty startups, and how this impacts on performance, in terms of indictors such as the number of employees and revenue sales. More specifically, we propose 9 hypotheses which link institutional resources to faculty startups and their performance, and compare 5 different groups of university resources for cross-college variation, using data from 134 South Korean four-year universities from 2017 to 2020. We find that the institutional factors impacting on performance of faculty startups differ from other categories of startups. The results show that it is important for universities to provide a more favorable environment, incorporating more flexible personnel policies and accompanying startup support infrastructure, for faculty startups, whilest it is more effective to have more financial resources and intellectual property for other categories of startups. Our findings also indicate that university technology-holding company and technology transfer programs are crucial to increase the number of faculty startups and their performance. Our analysis results have implications for both university and government policy-makers, endeavoring to facilitate higher particaption of professors in startup formation and ultimate commercialization of associated teachnologies.

• 한국노년학
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• v.40 no.4
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• pp.707-727
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• 2020

This study aims to empirically analyze the role that perception of the probability of lonely death among the elderly people living alone plays in the relationship between perceived social support and preference for institutional care based on Andersen's expanded Behavioral Model (2002). The subjects (n=676) of this study were the elderly people living alone, extracted from the "2018 Seoul Aging Survey." With "perceived social support" as an independent variable, "preference for institutional care" as a dependent variable, and "perception of the probability of lonely death" as a mediator variable, we conducted a Binary Logistic Regression to follow the three steps of analyzing mediation effect, as suggested by Baron and Kenny (1986). The results showed that perceived social support has a negative effect on the preference for institutional care and perception of the probability of lonely death among the elderly people living alone; at the same time, perception of the probability of lonely death was found to have a positive effect on their preference for institutional care. Lastly, perception of the probability of lonely death was found to partially mediate the effect of perceived social support among the elderly people living alone in terms of their preference for institutional care. Based on these findings, the practical implications of this study can be summarized as follows. First, various programs and support should be provided to the elderly people living alone in order to enhance the level of perceived social support, a factor that has been confirmed to increase preference for institutional care among the elderly people living alone. Second, as the perception of the probability of lonely death was confirmed to be a psychosocial factor of the preference for institutional care, we need to promote education and support for older people living alone to prepare them for lonely death. These efforts are expected to form a foundations for implementing a community-based integrated care system, "Aging in Place," which is the policy direction required for older people care.

• Parasites, Hosts and Diseases
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• v.23 no.1
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• pp.87-94
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• 1985

The seasonal variations of the rate and intensity of metacercarial infection of C. sinensis in P. parva were observed. The fish were collected at Sun-Am River which located in Kim-Hae City, Kyong-Sang Nam Do (=Province), Korea, from March 1983, to February 1984 every month. A total of 788 fish was examined. The number of metacercariae in each fish was individually counted after the individual digestion by artificial gastric juice. The results were as follows: 1. During one year, 513 (65.1%) out of 788 fish were infected with metacercariae. In May, June, July and September, the infection rates ranged from 82.0% to 98.6% whereas the rates was relatively low in March, April, November and February ranging from 11.4% to 64.7%. 2. The intensity of infection was similar with those of infection rates. The mean intensity per infected fish was 103.0 and standard deviation was 118.9 throughout one year. The highest mean intensity was in June (294.8) and the lowest in November (11.1). 3. The observed frequency of fish with certain intensities of metacercariae were fitted to theoretical equations derived from negative binomial distribution in March, April, November and February (p>0.05). Meanwhile, the equation of lognormal distribution were fitted with the observed frequencies in May, June, July and September (p>0.05, p>O. 75). The variance/mean ratio varied by month. The value was the highest in July (814.3) and the lowest in November (158.8). Unlike our hypothesis, the metacercarial density of Clonorchis sinensis in its the most favorable fish host, Pseudorasbora parva showed considerable seasonal variations in the hyperendemic area. The possible factors were discussed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.