• Journal of Convergence for Information Technology
• /
• v.11 no.7
• /
• pp.75-83
• /
• 2021

Recently, as consumer interest in DIY increases and the industry develops, theoretical interest in DIY is also gradually increasing, but in-depth research has hardly been conducted. In particular, research on DIY marketing from a marketing perspective is lacking, and moreover, the influence of the characteristics of individuals participating in DIY has hardly been studied. Therefore, the purpose of this study is to supplement the limitations of these existing studies by examining the effect of individual characteristics on DIY experience and intention to continue. We propose affect intensity, need for cognition, and self-efficacy as personal characteristics that influence DIY experience. In addition, we hypothesized the effects of these variables on the DIY experience such as sense, feel, think, act, relate, and the effect of the DIY experience on intention to continue DIY. We analyzed 231 copies of data for consumers who have experienced DIY in various fields, and the results are as follows. As expected, it was found that affect intensity positively influenced sense and feel, need for cognition had a positive effect on think, and self-efficacy had a positive effect on act and relate. As expected, it was found that affect intensity had an effect on sense and feel, need for cognition had an effect on think, and self-efficacy had a positive effect on act and relate. And it was confirmed that all DIY experiences had a positive effect on the intention to continue DIY. This study provides theoretical and strategic implications by confirming the influence of personal characteristics of DIY consumers and approaching DIY from the perspective of a comprehensive experience.

• Journal of Korea Port Economic Association
• /
• v.37 no.4
• /
• pp.103-126
• /
• 2021

The purpose of this study is described in detail as follows. First, I would like to define what digital transformation is in the maritime transport sector. Second, it is intended to derive success factors for digital transformation in the maritime transportation field by examining various preceding studies related to digital transformation. Finally, in order to derive priorities for the derived success factors, an AHP analysis model is built and an expert survey is conducted for practical experts in the maritime transportation field. Based on the survey results, we would like to provide guidelines on what factors should be considered first among the success factors of digital transformation in the maritime transportation sector. In this study, in order to derive the priority of success factors for digital transformation in the maritime transportation field, the hierarchical structure was divided into four high-level evaluation items(strategic factors, organizational culture and human factors, technology factors, and environmental factors) and 21 sub-evaluation items. A relative evaluation method of weighting items among AHP(Analytic Hierarchy Process) was applied. AHP analysis of 24 questionnaires with a consistency ratio of 0.1 or less in order to increase the accuracy of information among questionnaires collected through maritime transportation related university professors, research groups, shipping companies, container terminals, and experts engaged in shipping related IT companies was carried out. As a result of the analysis, the priority of the first-tier factors for the success factors of digital transformation in the maritime transport sector was shown in the order of strategic factors, organizational culture and human factors, technology factors, and environmental factors. In addition, when looking at the priorities of 21 detailed items, it was found that the development of new business models, the creation of an active future digital strategy, and the leadership of the chief digital officer were high.

• Journal of Korea Port Economic Association
• /
• v.37 no.4
• /
• pp.41-50
• /
• 2021

This study investigated what the general public thinks about the shipping industry and how important it is. As a result of the study, more than half of the respondents answered that they knew a little about the shipping industry or that they were normally knew about the shipping industry. Regarding the necessity of budget input to prevent bankruptcy of national shipping companies, it was found that more than half of the respondents answered that it was necessary or moderate. Regarding the necessity of maintaining a national shipping companies, 53% of respondents said it was necessary, and 23% of respondetns said it was normal. However, when asked if they thought that maintaining a national shipping companies would benefit me and my family, 39% of respondetns answered "normal" and 28% of respondetns answered "mostly". As for the cause of Hanjin Shipping's bankruptcy, 49% of respondents said that the owners' family members were immoral and incompetent, and 17.4% of respondetns said that the shipping market conditions deteriorated. Regarding the necessity of fostering the shipping industry, foreign currency acquisition and service balance improvement through export of shipping services accounted for 43.5%, and smooth transportation of import and export cargo accounted for 36.5%. When asked what kind of damage I suffered from Hajin Shipping's bankruptcy, 54.6% answered other (not much), and 14.5% said inflation. Abouve these results, this study gave implication in terms of public promotion and transparent business management.

• Journal of Korea Port Economic Association
• /
• v.39 no.3
• /
• pp.33-46
• /
• 2023

The Autonomous ships are equipped with a function to judge and navigate the sea conditions on their own, so the job of the ship officer who operates it changes. The educational curriculum to nurture ship officer with the ability to operate and manage autonomous ships must also be changed. This study aimed to develop the curriculum for training autonomous ship officer by using the Delphi survey method suitable for predicting the uncertain future. Among the current 61 subjects for training ship officer identified in the Delphi survey, 32 subjects with high importance should be maintained in the training for autonomous ship officer, and subjects with low importance should be abolished or integrated into other subjects. These subjects were collectively referred to as 'general courses'. The expert panel of the Delphi survey suggested 42 items as new subjects, with 18 items of 'high', 14 items of 'middle', and 10 items of 'low'. Through in-depth analysis of these items by experts, 27 subjects were adjusted and three courses were proposed : 1)'Basic course(10 courses)' for developing basic capabilities such as basic theories for understanding advanced technology and information applied to autonomous ships, 2)'Job course(10 courses)' for practical competency directly related to autonomous ship operation, 3)'Intensive course(7 subjects)' for fostering land remote operators of autonomous ships. Since the introduction and spread of autonomous ships will progress rapidly, research to develop and supplement autonomous ship pilot training courses should be continued by reflecting the level of autonomous navigation of autonomous ships.

• Journal of Mushroom
• /
• v.21 no.1
• /
• pp.1-7
• /
• 2023

This study addresses the current demand of the Korean mushroom export industry to establish an export strategy and governing policies.The enoki mushroom exports increased by 89% in 2009 and 23% in 2010, resulting in the largest export volume (17,163 tons) and export value ($26,292,000) being recorded in 2010. In contrast, exports in 2020 yielded only $18,525,000, which was 29% lower than that in 2010. In case of king oyster mushrooms, exports increased by 10% in 2012, 13% in 2013, and 2% in 2014, maintaining a moderate-growth trend. Moreover, Korea's mushroom exports are focused on a few specific countries. Enoki mushrooms accounted for more than 50% of the total exports to North America and Vietnam from 2012 to 2022, whereas king oyster mushrooms accounted for more than 50% of the total exports to Europe and North America (USA and Canada) from 2009 to 2022. Another characteristic trend in Korean mushroom exports is the diversification of export markets. The number of countries importing enoki mushrooms and king oyster mushrooms from Korea is increasing.

• The Journal of Society for e-Business Studies
• /
• v.19 no.4
• /
• pp.231-249
• /
• 2014

We define $21^{st}$ century as an amalgamation of globalization and localization, or Glocalization. Additionally, due to the increasing supply of smart phones and wide usage of social networking services, the ability to utilize such global and regional information has increased a coperation's competitiveness in its market, and even the business models have evolved from the conventional "production and distribution" to E-commerce, through which either a direct or a non-direct transaction is possible. My hypothesis is that the ability to adapt to this trend is possible through transfer of learning, and consequently, this will have an impact on company's performance. Thus, this thesis analyzes the mid- to the long-term impact of such ability and environmental factors on the performance and technology innovation of Korean companies in China. Ultimately, this study intends to engender a basic foundation for a corporation's management strategy in China. Finally this research focuses on those Korean companies in China only and on the proof of influential factors' impact on technological innovation and technological innovation's impact on those corporations' future performances. Section I is an abstract and section II, the case examines the uniqueness and current status of Korean companies in China identifies the concept and the definition of influential factors such as education-orientation, technological innovation, and performance, and then scrutinizes each factors through a closer look at their past researches. Section III explains the thesis model, the survey's method and target, the thesis, variable factors, the content, and the method of analysis. In section IV, the thesis is proved based on the outcome of the survey. The result in Section V highlights the high comprehension of technological innovation: both education-orientation and technological innovation prove to have a positive (+) correlation with the performance. The vision on education orientation proves to have a positive (+) influence on technological innovation. The vision on education-orientation and technological innovation prove to have a positive (+) influence individually on company's performance.

• Journal of Intelligence and Information Systems
• /
• v.23 no.3
• /
• pp.139-153
• /
• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.34 no.2
• /
• pp.177-183
• /
• 1989

Lower leaves of aromatic tobacco are also much lower in Quality than upper leaves. So feasibility test of no harvesting and curing of lower leaves was conducted under high planting density and high nitrogen conditions with conventional cultural system. Effect of harvesting time on yield and Quality were investigated under 2 nitrogen levels. Among harvesting methods of conventional harvest with priming under high planting density, no-harvest of first priming, removal of lower leaves which relevant to first prime stalk before maturity, no-harvest of first and second priming. no-harvesting or pruning of first prime stalk before maturity was best in yield, price and in crude income. The shortor the harvest period became, the lower the yield, price and contents of reducing sugar and nicotine became, but reverse in this trends with total nitrogen and protein nitrogen. So 6 or 8 days interval of harvest is most recommendable.

• 대한공업교육학회지
• /
• v.40 no.2
• /
• pp.155-174
• /
• 2015

The purposes of this study were to analyze the property of educational needs of teachers for educational contents of invention and intellectual property in secondary vocational education and provide fundamental data for the development of job training programs so as to develop the capabilities of teachers, the base for effective education of invention intellectual property in secondary vocational education. To achieve them, educational needs for the educational contents of invention intellectual property and the priority of the educational needs in secondary vocational education based on the recognition of the teachers were analyzed and suggested. Concrete results of this study can be suggested as follows. First, the average of educational needs of the teachers for the educational contents of invention intellectual property in secondary vocational education was 5.02. There were 23 items of the educational contents whose educational needs were higher than the average of the whole items and for those items and the average of each item, there were F4(The average of patent applications) 6.72, F5(Modification and supplementation of specification sheets) 6.46, F2(Writing of patent floor plans) 6.39, F3(Writing of patent specification sheets and abstraction) 6.31, A5(Invention method and activity) 6.27, E6(Invention design project) 6.15, H3(Invention commercialization) 5.97, F1(Patent information and application) 5.90, E5(Design obligation) 5.78, E3(Designing process of inventional design) 5.77, A4(Invention and problem solving) 5.57, G2(Patent investigation and classification) 5.47, C2(Thinking method of inventional problem solution) 5.45, E4(Production of inventional design product) 5.45, B5(Inventional patent project) 5.42, A2(Creativity development) 5.26, C4(Inventional problem solving project) 5.26, H4(Invention marketing) 5.26, H2(Analysis on invention commercialization) 5.20, D4(Invention and management) 5.16, C3(Problem solving activity) 5.14, E2(Inventional design devise and expression) 5.11, B3(Actuality of inventional method) 5.08 in order. Second, for the priority of educational needs of the teachers for the educational contents of invention intellectual property in secondary vocational education, there were 13 items of the educational contents for the first rank, 10 for the second rank and 17 for the third rank. The items of the educational contents for the first rank were A4(invention and problem solving), A5(inventional method and activity), B5(Invention patent project), C2(Thinking method of inventional problem solution), C4(Inventional problem solving project), E3(Inventional design process), E4(Production of inventional design product), E5(Design obligation), E6(Invention design project), F1(Patent information and application), F2(Writing of patent floor plan), F3(Writing of patent specification sheet and abstract), and H3(Invention commercialization. The items of the educational contents for the second rank were A2(Creativity development), B3(Actuality of inventional method), C3(Problem solving activity), D4(Invention and management), E2(Invention design devise and expression), F4(Range of patent demand), F5(Modification and supplementation of specification sheet), G2(Patent investigation and classification), H2(Analysis on invention commercialization), and H4(Invention marketing). The items for the third rank were the educational contents except the ones of the first rank and the second rank.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.67-83
• /
• 2018

The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.