• Knowledge Management Research
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• v.22 no.2
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• pp.119-144
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• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Maritime Security
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• v.4 no.1
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• pp.57-82
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• 2022

The objective of this treatise is to explore the limitations of the current navy manpower utilization system and the ways to improve it from the perspective of Generation Z. As Generation Z, following Millennials, has finally come of age, this new group is constituting a gradually greater proportion of military personnel. Due to the typical characteristics of naval operations, the harmony between Millennials and Generation Z, which is differentiated from Generation X in view of dispositions and traits, is one of the essential issues to be discussed. Generally, in a naval vessel, there are numerous pieces of equipment necessary to carry out a wide range of missions and a large number of crew members who operate them with consistent levels of fighting power. This is all while members are living together within the narrow space throughout the 24 hours of each day. Under such particular circumstances, any inter-generational conflicts may have a disruptive effect on the successful accomplishment of naval missions. Currently, new generations of military personnel are facing social difficulties in different aspects compared with the previous generations, and also have different viewpoints on the military. In this regard, in order to foster true harmony between generations, it is considered necessary to take a closer look at the inter-generational differences from their respective standpoints and to examine whether the military organization has taken adequate steps to respond to such changes. Accordingly, Chapters 1 and 2 cover the environments in which Millennials and Generation Z were raised during their childhood to young adulthood, which are distinct from those of older generations, their viewpoints formed based on such backgrounds, and the need to resolve various conflicts between generations. In Chapter 3, the current actions taken by overseas military powers to enhance the coexistence with Generation MZ are analyzed to find the significant implications they had. Chapter 4 examines the operation environments specific to the navy; identifies the potential barriers to achieving harmony between generations by assessing the current status of personnel utilization in the Korean navy in terms of the seaman, petty officer, and the officer, as well as policy; and outlines the solutions to drive harmony. Finally, Chapter 5 emphasizes the need to establish a genuine empathy between generations based on the understanding of unique inter-generational characteristics. This section also discusses the importance of addressing difficulties in utilizing technology-centered naval manpower, and forecasts a scenario of a naval organization that resolves the problem of utilizing naval personnel and the inter-generational conflicts in the future.

• Journal of Nutrition and Health
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• v.43 no.5
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• pp.533-542
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• 2010

The objective of this study is to provide basic information and policy implications needed to balance the supply and demand for dietitian by projecting supply and demand for dietitian. The data from the Ministry of Health Welfare and Family on the number of licensed nutritionist, resident registration data of the Ministry of Public Administration and Security, and health insurance qualification data of the National Health Insurance Corporation were used to examine the current status of supply. To project the supply of nutritionist workforce, the in-out moves method and demographic method were used. The ratios of nutritionist to population and GDP, and that of other countries were applied as the demand projection method. According to the study results, the projection on the imbalance of supply and demand for dietitian by year 2021 differs depending on the method used. First, according to the results based on age-adjusted population ratio, there is an oversupply of 1,643 dietitians in year 2010, and 2,076 dietitians in year 2020. Second, although the projection on the imbalance of the supply and demand for dietitian differs depending on whether the GDD is calculated in won(￦) or dollar($). it is expected that there will be an oversupply in general. Third, as to the scenario using the nutritionist ratio in foreign countries, the oversupply of dietitian is likely in Korea, under any scenario, when comparing the nutritionist supply projection with the demand projection based on the nutritionist ratio in the United States. However, the projection of the supply and demand varies in each scenario when the European nutritionist ratio is applied. Under European 'scenario 1', an oversupply is expected, whereas under 'scenario 2', a shortage of supply is expected. A careful approach is required in interpreting the supply and demand projection using criteria of other countries, because dietitian assumes different roles and functions in each country. Although a slight oversupply of nutritionist workforce is projected, it does not cause a major problem as the demand for diet therapy is expected to rise due to aging and the increase of chronic diseases, and as the demand for clinical dietitians in hospitals increases. Accordingly, the demand for dietitians will rise and, in this context, the oversupply of nutritionist will not incur much problem. However, the nutritionist qualification is much too open in Korea, and this has a negative effect on the quality of the nutritionist workforce. Therefore, it is important that the nutritionist qualifications and requirements are reinforced in the future, enhance the quality level of the nutritionist supply, and maintain the balance between the supply and demand.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.169-196
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• 2017

The fourth industrial revolution represents a revolutionary change in the business environment and its ecosystem, which is a fusion of Information Technology (IT) and other industries. In line with these recent changes, the Ministry of Employment and Labor of South Korea announced 'the Fourth Industrial Revolution Leader Training Program,' which includes five key support areas such as (1) smart manufacturing, (2) Internet of Things (IoT), (3) big data including Artificial Intelligence (AI), (4) information security, and (5) bio innovation. Based on this program, we can get a glimpse of the South Korean government's efforts and willingness to emit leading human resource with advanced IT knowledge in various fusion technology-related and newly emerging industries. On the other hand, in order to nurture excellent IT manpower in preparation for the fourth industrial revolution, the role of educational institutions capable of providing high quality IT education services is most of importance. However, these days, most IT educational institutions have had difficulties in providing customized IT education services that meet the needs of consumers (i.e., learners), without breaking away from the traditional framework of providing supplier-oriented education services. From previous studies, it has been found that the provision of customized education services centered on learners leads to high satisfaction of learners, and that higher satisfaction increases not only task performance and the possibility of business application but also learners' recommendation intention. However, since research has not yet been conducted in a comprehensive way that consider both antecedent and consequent factors of the learner's satisfaction, more empirical research on this is highly desirable. With the advent of the fourth industrial revolution, a rising interest in various convergence technologies utilizing information technology (IT) has brought with the growing realization of the important role played by IT-related education services. However, research on the role of IT education service quality in the context of IT education is relatively scarce in spite of the fact that research on general education service quality and satisfaction has been actively conducted in various contexts. In this study, therefore, the five dimensions of IT education service quality (i.e., tangibles, reliability, responsiveness, assurance, and empathy) are derived from the context of IT education, based on the SERVPERF model and related previous studies. In addition, the effects of these detailed IT education service quality factors on learners' educational satisfaction and their work application/recommendation intentions are examined. Furthermore, the moderating roles of learner position (i.e., practitioner group vs. manager group) and participation motivation (i.e., voluntary participation vs. involuntary participation) in relationships between IT education service quality factors and learners' educational satisfaction, work application intention, and recommendation intention are also investigated. In an analysis using the structural equation model (SEM) technique based on a questionnaire given to 203 participants of IT education programs in an 'M' IT educational institution in Seoul, South Korea, tangibles, reliability, and assurance were found to have a significant effect on educational satisfaction. This educational satisfaction was found to have a significant effect on both work application intention and recommendation intention. Moreover, it was discovered that learner position and participation motivation have a partial moderating impact on the relationship between IT education service quality factors and educational satisfaction. This study holds academic implications in that it is one of the first studies to apply the SERVPERF model (rather than the SERVQUAL model, which has been widely adopted by prior studies) is to demonstrate the influence of IT education service quality on learners' educational satisfaction, work application intention, and recommendation intention in an IT education environment. The results of this study are expected to provide practical guidance for IT education service providers who wish to enhance learners' educational satisfaction and service management efficiency.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.