• 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.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Journal of Korea Entertainment Industry Association
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• v.14 no.5
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• pp.87-102
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• 2020

The purpose of this study was to develop regional dance contents in order to receive attention from the region and re-illuminate the peacock fan, the intangible cultural property of Seocheon, Chungnam, which has been preserved in history and has been preserved in the face of rapid urbanization and modernization. The representative four series are composed of one-person dance, two-person dance, military dance, and creative dance. The titles of each piece are basic dance , male and female love dance , military dance , and finally Korean creative dance . The commonality of the four series is the traditional dance using peacock fan, and each dance showed unique emotion and atmosphere through different themes and music, costumes, and stages. It was found that the development of regional dance contents re-created reflecting the characteristics of regional cultural heritage should create an environment that can be steadily revitalized through modernization. Through this study, it was found that the intangible cultural properties, which are our traditional cultural resources, have unlimited potential to contribute to enhancing regional and national competitiveness along with the growth potential of regional differentiation. Through such research, if existing cultural resources are preserved for globalization and produced as contents that can be easily accessed by the public, various contents besides regional dance using regional unique culture can be developed and utilized.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.211-226
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• 2023

As we transition into the post-COVID era, economic activities that were stagnant are regaining momentum. In particular, there is a growing trend of technology entrepreneurship driven by the opportunities of digital transformation in the Fourth Industrial Revolution. However, entrepreneurship education content is struggling to keep up with the rapid pace of technological change. This study aims to emphasize the importance of entrepreneurship mentoring as a crucial component of entrepreneurship education content that requires adaptation and advancement due to the increasing demand for technology entrepreneurship. This study redefines startup mentoring, which is differentiated from general mentoring, at the present time when the demand for startups, which increases with the declining employment rate, increases, and the development of quality startup education contents and securing professional startup mentors are required. According to the start-up stage, it is divided into preliminary entrepreneurs and early entrepreneurs, and the effect of entrepreneurship knowledge and self-efficacy among start-up mentoring functions on entrepreneurial will and mentoring satisfaction is improved by empirically researching the effects of start-up mentoring functions in the case of initial entrepreneurs as a moderating effect. To confirm the importance of entrepreneurship mentoring effect for. To this end, among the mentoring functions, entrepreneurship knowledge and self-efficacy were set as independent variables, and entrepreneurial will and mentoring satisfaction were set as dependent variables. The research model was designed and hypotheses were established. In addition, empirical analysis was conducted by conducting a questionnaire survey on trainees who received entrepreneurship mentoring education at ICCE Startup School and Opus Startup School. To summarize the results of the empirical analysis, first, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on entrepreneurial will. Second, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on mentoring satisfaction. Third, it was analyzed that entrepreneurship had no significant moderating effect on entrepreneurial knowledge and entrepreneurial will. Fourth, it was analyzed that entrepreneurship had no significant moderating effect on mentoring satisfaction. Fifth, it was found that entrepreneurship had a significant moderating effect between self-efficacy and will to start a business. As a result of the research analysis, the first implication is that the mentoring function in start-up education is analyzed to produce meaningful results for both the initial entrepreneurs and the prospective entrepreneurs in the will to start a business and satisfaction. . Second, it was analyzed that there was no significant relationship between whether a business was started and the mentoring function and effect. However, it was analyzed that the will to start a business through improvement of self-efficacy through mentoring was significantly related to whether or not to start a business. turned out to be helpful. Many start-up education programs currently conducted in Korea educate both early-stage entrepreneurs and prospective entrepreneurs at the same time for reasons such as convenience. However, through the results of this study, even in small-scale entrepreneurship mentoring, it is suggested that customized mentoring through detailed classification such as whether the mentee has started a business can be a method for successful entrepreneurship and high satisfaction of the mentee.

• Journal of Korean Home Economics Education Association
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• v.28 no.3
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• pp.1-16
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• 2016

The purpose of this study was to develop and evaluate the teaching-learning process plan of senior cohousing to improve understanding of active and independent living in later life through Home Economics subject. The plan consisting of 5 lessons has been developed and implemented according to the ADDIE model. Various activity materials (28 individual activity sheets, 2 working sheets, and 26 teacher's reading texts) and visual materials (4 sets of pictures & photos and 10 moving pictures) as well as questionnaire were developed for the 5-session lessons. The plans were implemented to 6 classes 150 freshmen of P high school in Jeju-do during August 17th to 3rd of September, 2015. Students were highly satisfied regardless of gender with the whole 5-lessons in the aspects such as the level of participation in the lesson, understanding of the contents, adequacy of materials and activities, and usage in their future life. Students also reported that they highly accomplished the goal of each lesson to reinforce the understanding on necessity of preparing later life, senior cohousing, and senior friendly business. It can be concluded that the teaching learning process plan for senior cohousing would improve understanding and practical competency of active and independent living in later life with senior neighbors through the home economics subject.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.363-384
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• 2008

This study aims at improving Korea's competitiveness in port logistics through marketing strategy with integrating the conceptual approach into the empirical one and combining both the oldest military treatise and the newest evaluating model in social science that was applied by the HFP(hierarchical fuzzy process) model enhanced by the KJ method. The empirical results of this study show Busan in the middle among subject ports. At present, Korea plays a reciprocal role in the port market in East Asia, but in the medium- and long-term, Korea's ports will vie together with most major ports in the East Asian region. A descriptive investigation shows that Korea's developing tasks in port logistics must be considered in the context of the direction for developing port policies, the necessity of expanding port facilities in the capital region, securing the sufficient traffic volume through the establishment of the hinterland linking system and its positive utilization, and reforming the direction for developing the global logistics through increased port competitiveness. In the short- and medium-term, Korea must use the opportunity factor of 'Growth and open door policy of China' as a geoeconomic advantage and to utilize Korea's ports as a gate to Chinese foreign trade. With the rise of China's economy, China also plays a significant role in both port and airport markets. Hence, the linking system between the two must be established to meet the expanding traffic volume, especially in the capital area. Moreover, it is necessary for Korea to secure port logistics through the establishment of the hinterland linking system and its positive utilization. The great accomplishment of this paper is to present strategies to increase Korea's port competitiveness in the rapidly changing environments of world logistics with the focus on both the oldest military strategic treatise and the newest empirical method in social science. In order to reinforce this study, it needs further compensative research because the evaluation structure could be subdivided with more extensive and precise criteria.

• Journal of Korea Technology Innovation Society
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• v.17 no.2
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• pp.380-420
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• 2014

We increasingly see the importance of employees acquiring enough expert capability or innovation capability to prepare for ever growing uncertainties in their operation domains. However, despite the above circumstances, there have not been an enough number of researches on how operational input components for employees' innovation outcome, innovation activities such as acquisition, exercise and promotion effort of employee's innovation capability, and their resulting innovation outcome interact with each other. This trend is believed to have been resulted because most of the current researches on innovation focus on the units of country, industry and corporate entity levels but not on an individual corporation's innovation input components, innovation outcome and innovation activities themselves. Therefore, this study intends to avoid the currently prevalent study frames and views on innovation and focus more on the strategic policies required for the enhancement of an organization's innovation capabilities by quantitatively analyzing employees' innovation outcomes and their most suggested relevant innovation activities. The research model that this study deploys offers both linear and structural model on the trio of learning, innovation capability and innovation outcome, and then suggests the 4 relevant hypotheses which are quantitatively tested and analyzed as follows: Hypothesis 1] The different levels of innovation capability produce different innovation outcomes (accepted, p-value = 0.000<0.05). Hypothesis 2] The different amounts of learning time produce different innovation capabilities (rejected, p-value = 0.199, 0.220>0.05). Hypothesis 3] The different amounts of learning time produce different innovation outcomes. (accepted, p-value = 0.000<0.05). Hypothesis 4] the innovation capability acts as a significant parameter in the relationship of the amount of learning time and innovation outcome (structural modeling test). This structural model after the t-tests on Hypotheses 1 through 4 proves that irregular on-the-job training and e-learning directly affects the learning time factor while job experience level, employment period and capability level measurement also directly impacts on the innovation capability factor. Also this hypothesis gets further supported by the fact that the patent time absolutely and directly affects the innovation capability factor rather than the learning time factor. Through the 4 hypotheses, this study proposes as measures to maximize an organization's innovation outcome. firstly, frequent irregular on-the-job training that is based on an e-learning system, secondly, efficient innovation management of employment period, job skill levels, etc through active sponsorship and energization community of practice (CoP) as a form of irregular learning, and thirdly a model of Yί=f(e, i, s, t, w)+${\varepsilon}$ as an innovation outcome function that is soundly based on a smart system of capability level measurement. The innovation outcome function is what this study considers the most appropriate and important reference model.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.37 no.4
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• pp.302-307
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• 2001

The underwater background noise measured in Geoje and Tongyoung diving fishing ground from May to December, 2000 and analyzed to get optimum carrier frequency and transmitter power level for underwater wireless telephone design. The results obtained are summarized as follows: 1. At the Geoje and Tongyoung diving fishing ground, the lowest ambient noise band was 25~30kHz with 57dB and 52dB re 1$\mu$Pa, respectively. 2. At the Geoje and Tongyoung diving fishing ground, the lowest noise band during fishing activity was 67dB and 62dB re 1$\mu$Pa, respectively. 3. At the Geoje diving fishing ground, the noise of water jetter which is a digging machine for subbottom shells was 102dB re 1$\mu$Pa. 4. Considering the design parameters of underwater wireless telephone, it is found that the optimum carrier frequency band is around 30kHz and the transmitter source level should be at least 131dB re 1$\mu$Pa for 500m range telephone.

• Proceedings of the Korean Ceranic Society Conference
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• 2005.06a
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• pp.1-112
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• 2005

This report is results of a research on recent R&D trends in electroceramics, mainly focusing on the papers submitted to the organizing committee of the International Conference on Electroceramics 2005 (ICE-2005) which was held at Seoul on 12-15 June 2005. About 380 electroceramics researchers attended at the ICE-2005 from 17 countries including Korea, presenting and discussing their recent results. Therefore, we can easily understand the recent research trends in the field of electroceramics by analyses of the subject and contents of the submitted papers. In addition to the analyses of the papers submitted to the ICE-2005, we also collected some informations about domestic and international research trends to help readers understand this report easily. We analysed the R&D trends on the basis of four main categories, that is, informatics electroceramics, energy and environment ceramics, processing and characterization of electroceramics, and emerging fields of electroceramics. Each main category has several sub-categories again. The informatics ceramics category includes integrated dielectrics and ferroelectrics, oxide and nitride semiconductors, photonic and optoelectronic devices, multilayer electronic ceramics and devices, microwave dielectrics and high frequency devices, and piezoelectric and MEMS applications. The energy and environment ceramics category has four sub-categories, that is, rechargable battery, hydrogen storage, fuel cells, and advanced energy conversion concepts. In the processing and characterization category, there exist domain, strain, and epitaxial dynamics and engineering sub-category, innovative processing and synthesis sub-category, nanostructured materials and nanotechnology sub- category, single crystal growth and characterization sub-category, theory and modeling sub-category. Nanocrystalline electroceramics, electroceramics for smart sensors, and bioceramics sub-categories are included to the emerging fields category. We hope that this report give an opportunity to understand the international research trend, not only to Korean ceramics researchers but also to science and technology policy researchers.