In the respect of automobile history, the tendency to the development of automobiles for the latest 100 years has been leaded by technical performances. Especially, with the rapid growth of the newest electronic industry, the technical know-hows of automobiles improved in short terms have brought about outstanding results. The differences of the technical know-hows are little between some of the famous automobile manufacturing industries and the rising. So, now, the automobile design became a basis in selecting a car. The latest tendency to automobile style in accordance with the improvement of a universal life quality has been changed to a characteristic design meeting various needs of customers. RV, UV, MPV(and so forth ) meeting their needs made an appearance, or a characteristic model derived from them respectively appeared. We tried to study a new mini SUV-typed-concepcar design with a touch of the next concept. The whole design process from our researches to the end hard model was performed at the Design Center, Daewoo Automobile, based on the automobile design processes. Especially, We styled an automobile concept as inexpensive, characteristic, new one to have a car easily at the young and made an analysis of customers' responses for referring to this study in generating the next SUV-typed-automobile.
R&D into future technologies should be conducted in conjunction with technological innovation strategies that are linked to corporate survival within a framework of information and knowledge-based competitiveness. As such, future technology strategies should be ensured through open R&D organizations. The development of future technologies should not be conducted simply on the basis of future forecasts, but should take into account customer needs in advance and reflect them in the development of the future technologies or services. This research aims to select as segmentation variables the customers' attitude towards accepting future telecommunication technologies and their value orientation in their everyday life, as these factors wilt have the greatest effect on the demand for future telecommunication services and thus segment the future telecom service market. Likewise, such research seeks to segment the market from the stage of technology R&D activities and employ the results to formulate technology development strategies. Based on the customer attitude towards accepting new technologies, two groups were induced, and a hierarchical customer segmentation model was provided to conduct secondary segmentation of the two groups on the basis of their respective customer value orientation. A survey was conducted in June 2006 on 800 consumers aged 15 to 69, residing in Seoul and five other major South Korean cities, through one-on-one interviews. The samples were divided into two sub-groups according to their level of acceptance of new technology; a sub-group demonstrating a high level of technology acceptance (39.4%) and another sub-group with a comparatively lower level of technology acceptance (60.6%). These two sub-groups were further divided each into 5 smaller sub-groups (10 total smaller sub-groups) through two rounds of segmentation. The ten sub-groups were then analyzed in their detailed characteristics, including general demographic characteristics, usage patterns in existing telecom services such as mobile service, broadband internet and wireless internet and the status of ownership of a computing or information device and the desire or intention to purchase one. Through these steps, we were able to statistically prove that each of these 10 sub-groups responded to telecom services as independent markets. We found that each segmented group responds as an independent individual market. Through correspondence analysis, the target segmentation groups were positioned in such a way as to facilitate the entry of future telecommunication services into the market, as well as their diffusion and transferability.
Park, Jong-Kil;Jung, Woo-Sik;Kim, Eun-Byul;Park, Gil-Un
Journal of the Korean earth science society
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v.28
no.7
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pp.878-890
/
2007
This study aimed to provide a fundamental basis for the development and promotion of a Korea windchill temperature index model in the field of human biometeorology. For this, a sensitivity model currently being used by KMA (Korea Meteorological Administration) was analyzed. The results of the analysis showed that the Korean peninsula could be divided into the urban area, the coastal/island area, the inland area, and the mountain area. The average temperature was highest in the coastal/island area, while it was lowest in the mountain regions. The lowest temperature in the urban and coastal/island areas was 20 degrees below zero and that in the inland and mountain regions were 30 degrees below zero. As for wind speed, both average and maximum wind speed were highest in the coastal/island area. The distribution of temperature and wind speed in winter was similar to that of the entire period. The results of the JAG/Tl and Missenard model sensitivity showed that temperature tends to have more influence on sensitivity than any other factors. In sub-zero temperature, however, the influence of wind speed tends to increase.
The purpose of this study is to investigate the relationships among customer satisfaction, trust, and loyalty and examine the differences and similarities between specialized and general merchandise internet shopping malls concerning the relationships of these key success factors. The structural model is tested with each of the sub-samples(i.e., specialized and general merchandise shopping customers taken separately) and the data from entire data samples(i.e., specialized and general merchandise shopping customers pooled together). The same research model was used in analysing general merchandise, specialized, and integrated internet shopping mall to reveal and compare the casual path constructs. In the analysis of path coefficients composed of separated taken sample, all research hypothesis is accepted and the model's goodness of fit also shows all high. In the basis of the previous empirical test, multiple sample method was used. Properties of the causal paths, including standardized path coefficients, the significance of difference, latent correlations and variance explained for satisfaction, trust and loyalty in the hypothesized model, have similarities in general. This means that the proper structural management concerned with customer satisfaction, trust and loyalty is very crucial for the success of all kinds of internet shopping malls. Following the model test, I conduct a test of integrated model's path coefficients. Statistical results show that all the hypothesis concerned with internet shopping malls were accepted like the separated sample test. Click and mortar companies should clearly understand and articulate the key requirements of shopping mall satisfaction, trust and loyalty and encourage to establish linkage and interactive relationship among the research variables. In addition, internet marketers are required to customize the interaction considering and adapting the patterns of internet shopping malls. Other interesting results concerning the strategies in internet shopping malls strategy are also presented.
Park, Jinhyeon;Ryu, Hyeonsu;Heo, Jung;Cho, Mansu;Yang, Wonho
Journal of Environmental Health Sciences
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v.45
no.1
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pp.1-8
/
2019
Objectives: The purpose of this study was to estimate the ventilation rate of residential homes in Korea through tracer gas methods using indoor and outdoor concentrations of carbon dioxide ($CO_2$) and $CO_2$ generation rates from breathing. Methods: In this study, we calculated the number of occupants in a home by time through data on the average number of people per household from the Korean National Statistical Office and also measured the amount of $CO_2$ generation by breathing to estimate the indoor $CO_2$ generation rate. To estimate the ventilation rate, several factors such as the $CO_2$ generation rate and average volume of residential house provided by the Korean National Statistical Office, indoor $CO_2$ concentrations measured by sensors, and outdoor $CO_2$ concentrations provided by the Korea Meteorological Administration, were applied to a mass balance model for residential indoor environments. Results: The average number of people were 2.53 per household and Koreans spend 61.0% of their day at home. The $CO_2$ generation rate from breathing was $13.9{\pm}5.3L/h$ during sleep and $15.1{\pm}5.7L/h$ in a sedentary state. Indoor and outdoor $CO_2$ concentrations were 849 ppm and 407 ppm, respectively. The ventilation rate in Korean residential houses calculated by the mass balance model were $42.1m^3/h$ and 0.71 air change per hour. Conclusions: The estimated ventilation rate tended to increase with an increase in the number of occupants. Since sensor devices were used to collect data, sustainable data could be collected to estimate the ventilation rate of Korean residential homes, which enables further studies such as on changes in the ventilation rate by season resulting from the activities of occupants. The results of this study could be used as a basis for exposure and risk assessment modeling.
Purpose - In recent years, management scholars have expressed growing interest in the concept of person-Job fit because of having many benefits for employees' attitudes and behaviors. The related research is needed to determine what specific types of fit are related to each other, and to get important individual outcomes. Person-job fit of employees in service organization plays an important role in company as well as person in service industry. Person-job fit, representing the consistency between person (service provider) and job (service provided to the customers), gives significant and positive effects on the attitude and behavior of service provider. On the basis of the study background, the purpose of this study is as follows. First, we would like to examine the effects of person-job fit of service provider on their emotional intelligence. Emotional intelligence is divided into four sub-factors such as self-understanding, understanding others, emotional utilization, and emotional regulation. Second, we would like to identify the relationships between job satisfaction and sub-factors such as self-understanding, understanding others, emotional utilization, and emotional regulation. Research design, data, and methodology - We performed structural equation model using Spss 18.0 and Amos 20.0 in order to verify the hypotheses. Subjects were golf service assistants who were high-touching service with high degree in interaction and long contact time with customers. 178 out of the total 200 surveys were used in evaluation from helpers of golf service working as full-time service provider after selecting two locations of golf course located near Busan. From the evaluation of reliability and validity with variables used in this research, they satisfied and confirmed certain standard. Results - The results are as follows. First, as the results of identifying the relationships between person-job fit and emotional intelligence of service provider, person-job fit did not have positive and significant effect on self-understanding. On the other hand, it affected positively and significantly other factors in emotional intelligence such as emotion to others, emotional utilization, and emotional regulation. Second, as the results of identifying the relationship between emotional intelligence and job satisfaction, sub-factors in emotional intelligence such as emotion to others, emotional utilization, and emotional regulation except self-emotion affected significantly and positively job satisfaction. However, self-emotion did not have significant and positive effects on job satisfaction. Conclusion - These results will be valuable and used for service providers. In addition, many service providers will recognize that person-job fit is very important to get a job. This research has a purpose on the assumption that appropriateness between individual and task in service industry shall act as major influence in emotional intelligence of service provider. Recognitive ability of service provider is also very important per characteristics of service, but emotional intelligence that interacts and connected directly with most customers can be a very meaningful factor as well. Emotional intelligence allows people to recognize, understand, and empathize the emotion of customers shall be a positive reinforcement for customers to evaluate the service ultimately.
Asset management is a complex and difficult field that requires insight into numerous variables and even human psychology. Thus, it has traditionally been the domain of professionals, and these services have been expensive to obtain. Changes are taking place in these markets, and the driving force is the digital revolution, so-called the fourth industrial revolution. Among them, the Robo-Advisor service using artificial intelligence technology is the highlight. The reason is that it is possible to popularize investment advisory services with convenient accessibility and low cost. This study aims to clarify what factors are critically important when selecting robo-advisors for service users and providers in Korea, and what perception differences exist in the selection factors between user and provider groups. The framework of the study was based on the marketing mix 4C model, and the design and analysis of the model used Delphi survey and AHP. Through the study design, 4 main criteria and 15 sub-criteria were derived, and the findings of the study are as follows. First, the importance of the four main criteria was in the order of customer needs > customer convenience > customer cost > customer communication for both groups. Second, looking at the 15 sub-criteria, it was found that investment purpose coverage, investment propensity coverage, fee level and accessibility factors were the most important. Third, when comparing between groups, the user group found that the fee level and accessibility factors were the most important, and the provider group recognized the investment purpose coverage and investment propensity coverage factors as important. This study derived useful implications in practice. First, when designing for the spread of the robo-advisor service, the basis for constructing a user-oriented system was prepared by considering the priority of importance according to the weight difference between the four main criteria and the 15 sub-criteria. In addition, the difference in priority of each sub-criteria shown in the group comparison and the cause of the sub-criteria with large weight differences were identified. In addition, it was suggested that it is very important to form a consensus to resolve the difference in perception of factors between those in charge of strategy and marketing and system development within the provider group. Academically, it is meaningful in that it is an early study that presented various perspectives and perspectives by deriving a number of robo-advisor selection factors. Through the findings of this study, it is expected that a successful user-oriented robo-advisor system can be built and spread in Korea to help users.
Kim, C.H.;Na, J.G.;Park, C.J.;Park, J.H.;Im, C.S.;Yoon, E.;Kim, M.S.;Park, C.H.;Kim, Y.J.
Journal of Korean Society for Atmospheric Environment
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v.19
no.5
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pp.595-610
/
2003
The statistical indexes such as RMSE (Root Mean Square Error), Mean Bias error, and IOA (Index of agreement) are used to evaluate 3 Dimensional wind and temperature fields predicted by operational meteorological model RAMS (Regional Atmospheric Meteorological System) implemented in CARIS (Chemical Accident Response Information System) for the dispersion forecast of hazardous chemicals in case of the chemical accidents in Korea. The operational atmospheric model, RAMS in CARIS are designed to use GDAPS, GTS, and AWS meteorological data obtained from KMA (Korean Meteorological Administration) for the generation of 3-dimensional initial meteorological fields. The predicted meteorological variables such as wind speed, wind direction, temperature, and precipitation amount, during 19 ∼ 23, August 2002, are extracted at the nearest grid point to the meteorological monitoring sites, and validated against the observations located over the Korean peninsula. The results show that Mean bias and Root Mean Square Error are 0.9 (m/s), 1.85 (m/s) for wind speed at 10 m above the ground, respectively, and 1.45 ($^{\circ}C$), 2.82 ($^{\circ}C$) for surface temperature. Of particular interest is the distribution of forecasting error predicted by RAMS with respect to the altitude; relatively smaller error is found in the near-surface atmosphere for wind and temperature fields, while it grows larger as the altitude increases. Overall, some of the overpredictions in comparisons with the observations are detected for wind and temperature fields, whereas relatively small errors are found in the near-surface atmosphere. This discrepancies are partly attributed to the oversimplified spacing of soil, soil contents and initial temperature fields, suggesting some improvement could probably be gained if the sub-grid scale nature of moisture and temperature fields was taken into account. However, IOA values for the wind field (0.62) as well as temperature field (0.78) is greater than the 'good' value criteria (> 0.5) implied by other studies. The good value of IOA along with relatively small wind field error in the near surface atmosphere implies that, on the basis of current meteorological data for initial fields, RAMS has good potentials to be used as a operational meteorological model in predicting the urban or local scale 3-dimensional wind fields for the dispersion forecast in association with hazardous chemical releases in Korea.
The land cover map is a very important data that is used as a basis for decision-making for land policy and environmental policy. The land cover map is mapped using remote sensing data, and the classification results may vary depending on the acquisition time of the data used even for the same area. In this study, to overcome the classification accuracy limit of single-period data, multi-series satellite images were used to learn the difference in the spectral reflectance characteristics of the land surface according to seasons on a U-Net model, one of the deep learning algorithms, to improve classification accuracy. In addition, the degree of improvement in classification accuracy is compared by comparing the accuracy of single-period data. Seoul, which consists of various land covers including 30% of green space and the Han River within the area, was set as the research target and quarterly Sentinel-2 satellite images for 2020 were aquired. The U-Net model was trained using the sub-class land cover map mapped by the Korean Ministry of Environment. As a result of learning and classifying the model into single-period, double-series, triple-series, and quadruple-series through the learned U-Net model, it showed an accuracy of 81%, 82% and 79%, which exceeds the standard for securing land cover classification accuracy of 75%, except for a single-period. Through this, it was confirmed that classification accuracy can be improved through multi-series classification.
In this study, on the basis of an analytic hierarchy process (AHP) method and through a questionnaire on subjective preference and importance, various power supply systems were comprehensively compared with multiple decision criteria such as environmental, social, healthy, and economic viewpoints and then overall priority was assessed. When a decision-making problem is modelled by a hierarchy structure, the AHP method is regarded as a useful tool for extracting subjective opinions via the aforementioned questionnaire. Here, the overall preferences were obtained by linearly aggregating weighting vector and preference matrix. The energy systems such as nuclear, coal, and LNG power plants were selected because they took share over 90% of domestic electricity supply in Korea. Furthermore, wind power and photovoltaic solar systems were included as representative renewable energy systems in Korea. According to the results of this demonstration study, the following comprehensive comparison indicators were yielded: 1) weighting factors for 4 types of main criteria as well as for 11 types of sub-criteria; 2) preference valuation for 7 types of energy systems under consideration; 3) overall score for each energy systems.
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