• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Journal of Distribution Science
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• v.11 no.10
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• pp.93-105
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• 2013

Purpose - This empirical analysis determines the structured causal relations between perceived value, customer satisfaction, and repurchase intention among users of traditional markets. The results of this analysis would help merchants and market operators indevisingan appropriate strategy to successfully manage traditional markets. Research design, data, methodology - The perceived value model of traditional markets includes functional value (price), functional value (quality), emotional value, and social value. In this study, the perceived value of traditional markets is considered as an independent variable, while customer satisfaction and repurchase intention are shown as the dependent variables, where customer satisfaction is also considered as the mediating variable. The study aims to ascertain the extent of influence of the perceived value of traditional markets on customer satisfaction and repurchase intention. We use regression analysis to verify the effects. The measurement items were already deemed as reliable and valid in the previous study, but for this purpose, we made some modifications. We distributed questionnaires to 300 consumers on a national scale, and finally used 241 consumer responses among these as a sample. We analyzed the data using the SPSS 21.0 statistical program. Results - We obtained the following results. First, the order of perceived value dimensions of traditional markets that positively impact customer satisfaction is functional value (price), social value, emotional value, and functional value (quality). Second, the perceived value sometimes directly affects repurchase intention; its effect is typically strong with customer satisfaction as a parameter. The order of perceived value dimensions that positively impact repurchase intention is social value, functional value (price), emotional value, and functional value (quality). Third, the perceived value significantly influences repurchase intention, with customer satisfaction as the mediating variable. Conclusions - We should recognize the importance of perceived value in retail distribution markets, such as traditional markets. Moreover, we need to develop strategies to improve the perceived value. The practical implications of the study are as follows. First, with regards to functional value (quality; price) dimensions, we should have an appropriate assortment of high quality products that are reasonably priced. In addition, customers are satisfied with the friendly service, discounts, and other benefits provided by the merchants. Second, in terms of emotional value dimension, we need to develop differentiated events that provide fun and emotional experience to the customers. Third, in the context of social values dimension, we should strive to positively influence society to enhance social image through activities such as social services and contribution to community development. On the basis of these results, we present the implications, limitations, and future directions for the research. One of the policy implications of the study is that merchants of traditional markets must actively select customers and develop customer value. However, this study is limited in the fact that the population used for data collection is not fully representative, as the survey only covered some specific areas. Moreover, future studies could also benefit with additional research using moderating variables.

• The Journal of Engineering Geology
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• v.26 no.2
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• pp.197-205
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• 2016

Rainfall-induced landslide disaster case histories are typically required to establish critical lines based on the decrease coefficient for judging the likelihood of slope collapse or failure; however, reliably setting critical lines is difficult because the number of nationwide disaster case histories is insufficient and not well distributed across the region. In this study, we propose a method for setting the critical area to judge the risk of slope collapse without disaster case history information. Past 10 years rainfall data based on decrease coefficient are plotted as points, and a reference line is established by connecting the outermost points. When realtime working rainfall cross the reference line, warning system is operating and this system can be utilized nationwide through setting of reference line for each AWS (Automatic Weather Station). Warnings were effectively predicted at 10 of the sites, and warnings could have been issued 30 min prior to the landslide movement at eight of the sites. These results indicate a reliability of about 67%. To more fully utilize this model, it is necessary to establish nationwide rainfall databases and conduct further studies to develop regional critical areas for landslide disaster prevention.

• Nuclear Engineering and Technology
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• v.40 no.6
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• pp.451-458
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• 2008

After more than 10 years construction, KSTAR (Korea Superconducting Tokamak Advanced Research) had finally completed its assembly in June 2007, and then achieved the goal of first-plasma in July 2008 through the four month's commissioning. KSTAR was constructed with fully superconducting magnets with material of $Nb_3Sn$ and NbTi, and their operation temperatures are maintained below 4.5K by the help of Helium Refrigerator System. During the first-plasma operation, plasmas of maximum current of 133kA and maximum pulse width of 865ms were obtained. The KSTAR Integrated Control System (KICS) has successfully fulfilled its missions of surveillance, device operation, machine protection interlock, and data acquisition and management. These and more were all KSTAR commissioning requirements. For reliable and safe operation of KSTAR, 17 local control systems were developed. Those systems must be integrated into the logically single control system, and operate regardless of their platforms and location installed. In order to meet these requirements, KICS was developed as a network-based distributed system and adopted a new framework, named as EPICS (Experimental Physics and Industrial Control System). Also, KICS has some features in KSTAR operation. It performs not only 24 hour continuous plant operation, but the shot-based real-time feedback control by exchanging the initiatives of operation between a central controller and a plasma control system in accordance with the operation sequence. For the diagnosis and analysis of plasma, 11 types of diagnostic system were implemented in KSTAR, and the acquired data from them were archived using MDSpius (Model Driven System), which is widely used in data management of fusion control systems. This paper will cover the design and implementation of the KSTAR integrated control system and the data management and visualization systems. Commissioning results will be introduced in brief.

• The Korean Journal of Franchise Management
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• v.9 no.2
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• pp.7-16
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• 2018

Purpose - Turnover Intention in the franchise industry is becoming a very important issue. This study examines the structural relationships between organizational justice, emotion, job satisfaction, and turnover intention in the franchise industry. In this model, emotion was classified into two sub-dimensions such as positive and negative emotion. Research design, data, methodology - The sample of this study collected from employees of a food-service franchise company is representative. Copies of the questionnaire along with a cover letter were delivered by a research assistant to the human resources manager or the general manager of the selected food-service franchise firms after they agreed to participate in the study. In order to increase the response rate of the respondents, a small gift was provided to the respondents who completed the questionnaire. A total of 300 questionnaires were distributed and 285 returned responses, 9 responses were not usable due to missing information. Thus, a total of 276 responses were used using structural equation modeling with Smartpls 3.0. Results - The results showed that organizational justice had positive significant effects on positive emotion and job satisfaction. Job satisfaction had negative a significant effect on turnover intention. And negative emotion had positive significant effect on turnover intention. Conclusions - The results of this study provide some implications. If employees feel that the franchise headquarters is fair about the methods and procedures of decision making, resource allocation, information sharing, etc., it means that employees feel better. If the franchise's decision-making processes and methods and results are transparently disclosed and processed in accordance with the internal rules of the company, the employees will be able to fully understand and accept them. The results of this study also show that positive and negative emotions of service-based franchise employees have different effects on job attitude and organizational behavior. In particular, when negative emotions of employees are passed on to others and the results are negative, employees may feel that they are disoriented or wrong. Therefore, the franchise headquarters should try to inspire employees' sense of organizational community, and should pay attention to how to relieve the job stress and the fair distribution of work and rewards.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.200-215
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• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

• Journal of Distribution Science
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• v.14 no.2
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• pp.73-82
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• 2016

Purpose - Counterproductive work behavior(CWB) was typically categorized according to the behavior whether it targets other people(i.e., interpersonal CWB: I-CWB). Employing organizations(i.e., organizational CWB: O-CWB) has emerged as major concerns among researchers, managers, and the general public. An abundance of researches has informed us about the understanding for the antecedents of CWB, whereas little is known about the antecedents of CWB directed distribution service in employee's emotional labor. Therefore, the purpose of this research is to propose a research model in which surface acting enhances emotional exhaustion as an emotional labor strategy, which eventually increases counterproductive work behavior(including I-CWM and O-CWB). Research design, data, and methodology - This empirical research data were gathered from the samples of full time frontline hotel employees(including front office, call center, food/beverage, concierge, and room service) in South Korea. Six hotels were selected ranged from four to five stars, including privately owned and joint-venture properties. A convenience sampling method was used to select hotels. Full time frontline hotel employees from the six hotels were surveyed using a self-administered instrument for data collection. With the strong support of hotel managers, a total of 300 questionnaires were distributed, and 252 responses were collected indicating a response rate of 84.0%. In the process of working with the 252 samples, structural equation modeling is employed to test research hypotheses(H1: The relationship between surface acting and Interpersonal counterproductive work behavior(I-CWB) is mediated by emotional exhaustion, H2: The relationship between surface acting and organizational counterproductive work behavior(O-CWB) is mediated by emotional exhaustion). SPSS 18.0 and M-Plus 7.31 software were used for the data analysis. Descriptive statistics were used to assess the distribution of the employee profiles and correlations between factors. M-Plus 7.31 software was used to test the model fit, validity, and reliability of the factors, significance of the relationship between factors, and the effects of factors in the model. Results - To test our mediation hypotheses, we used an analytical strategy suggested by Preacher & Hayes (2008) and Shrout & Bolger (2002). This mediation approach directly tests the indirect effect between the predictor and the criterion variables through the mediator via a bootstrapping procedure. Thus, it addresses some weaknesses associated with the Sobel test. We found that surface acting was positively related to emotional exhaustion. Furthermore, emotional exhaustion was a significant predictor from the two kinds of counterproductive work behavior. In addition, surface acting was not significantly associated with the two kinds of counterproductive work behavior. These results indicated that the surface acting by frontline hotel employees was associated with higher emotional exhaustion, which is related with higher interpersonal counterproductive work behavior(I-CWB) and organizational counterproductive work behavior(O-CWB). In sum, we confirmed that the positive relationship between surface acting and the two kinds of counterproductive work behavior was fully mediated by emotional exhaustion. Conclusions - The current research broadens the conceptual work and empirical studies in counterproductive work behavior literature by representing a fundamental mechanism that how surface acting affects counterproductive work behavior.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

• Journal of Hospice and Palliative Care
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• v.9 no.2
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• pp.67-76
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• 2006

Purpose: The purpose of this study was to develop education program for physicians who work at hospice palliative care settings in Korea, to practice abridged education program extracted from the full contents of the proposed education, and to improve the quality of hospice palliative care service. Methods: To develop the education program, questionnaire for hospice education need assessment (total 79 items) was distributed to 125 organizations practicing hospice service via mail and the data was collected from 1 Sep. to 10 Oct. 2004. Another questionnaire for hospice education importance assessment was asked to the palliative specialists from Sep. 23 to 17 Oct. 2004. Based on the analysis of the questionnaires, and reviewing various references and actual hospice palliative education programs of other countries, the education programs were developed. Results: Ore-day-Hospice education 2004 was conducted based on the suggested education program, and it was practiced four times on a national basis (2 times in Seoul, and once in Busan and Gwangju, respectively). 47 physicians attended the education program. The education program lasted about 7 hours, comprising 5 hours of common lectures for all attendants regardless of their professions and 2 hours of specific seminar for physicians only. Attendants positively responded to the contents of the education program. But they pointed out that the program should be offered on weekday and it should be more in-depth and more discussion based lesson. Conclusion: The suggested education program was not fully conducted yet. After practicing the abridged education program, more in-depth and discussion oriented rather than lecture-based education were suggested. It may be argued that the proposed education, which requires much longer period education, should also reflect the evaluation of the 1-day education program to successfully implement the proposed education program.