• Journal of Digital Contents Society
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• v.18 no.3
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• pp.499-508
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• 2017

With the recent advance of IT technology and the change of education paradigm, vocational training has been also evolved. In the background of mobilization of learning, increase of bite-size contents, and the agility of just-in-time learning, this study surveyed the online learners' motivation, perceptions, and learning behaviour. Total 4,021 learners from 6 distance learning institutions revealed that learners take the e-learning courses due to more for their self-development than the company's supports and policy. Also, they perceived the subject matter in contents are the most important. The results from this study suggest that the development of contents should focus on the subject matter that can be utilized for their jobs immediately. Lastly, the study confirms that learning space and time has been changed in the flexible way to use their spare time between work and life. Irregularity of learning and hasty preparations were one of major characteristics in the aspect of learning behaviour.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.91-106
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• 2017

In This Study, we Analyze how the Market Orientation and Learning Orientation that can be Regarded as the Two core Factors of Small Business, Necessary for Companies to Grow Continuously Influence on Corporate Performance. This is an Empirical Study on the Influence of them. Small Companies have a Greater Impact on the Survival and Growth of Organization Commitment I Experienced that. In this Study, we Focused on the Mediating Effect of Organization Commitment when the Company's Market Orientation and Learning Orientation Influenced on the Corporate Performance as a Differentiated Element of Research. Research results have Revealed that Surprisingly, Small Companies Market Orientation and Influence on Corporate Performance. This is an Empirical Study on the Influence of them. Small Companies have a Greater Impact on the Survival and Growth of Organization Commitment I Experienced that. In this Study, we Focused on the Mediating effect of Organization Commitment when the Company's Market Orientation and Learning Orientation Influenced on the Corporate Performance as a Differentiated Element of Research. Research results have Revealed that Surprisingly, Small Companies Market Orientation and Learning Orientation had a Significant Influence on Corporate Performance. It was also Verified that Organization Commitment had Partially Mediated Effects. In Conclusion, as a Prerequisite for Small Enterprises to grow, we have to Create Market Oriented and Learning Oriented Organization and at the same time we should Strive to Ensure that all Organization Members have Attachment Relationships with their Organization. It is Understood that it must be. The Results of these Studies will be Helpful for not only Individuals who Prepare for Founding and Founded but also Start-up Related Officials.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.120-125
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• 2020

Supply chain managers seek to achieve global optimization by solving problems in the supply chain's business process. However, companies in the supply chain hide the adverse information and inform only the beneficial information, so the information is distorted and cannot be the information that describes the entire supply chain. In this case, supply chain managers can directly collect and analyze supply chain activity data to find and manage the companies described by the data. Therefore, this study proposes a method to collect the order-inventory information from each company in the supply chain and detect the companies whose data characteristics are explained through deep learning. The supply chain consists of Manufacturer, Distributor, Wholesaler, Retailer, and training and testing data uses 600 weeks of time series inventory information. The purpose of the experiment is to improve the detection accuracy by adjusting the parameter values of the deep learning network, and the parameters for comparison are set by learning rate (lr = 0.001, 0.01, 0.1) and batch size (bs = 1, 5). Experimental results show that the detection accuracy is improved by adjusting the values of the parameters, but the values of the parameters depend on data and model characteristics.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.1157-1168
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• 2021

Hotels drive the growth and development of tourism. Despite their important role, many hotels are small and medium-sized firms (SME) that are struggling to survive against fierce competition. Experts agree that strategic planning is vital for SME survival, but it is not wholly applicable for SME managers. Meanwhile, Mintzberg's concept of crafting strategy offers a more productive insight into SME strategic planning, but its abstract nature has historically discouraged empirical research on its practical benefits. This study will be the first to empirically explore the operationalization of Mintzberg's crafting strategy characteristics, and analyze its influence on organizational learning using structural equation model. Using a sample of 50 hotels in Bali, Indonesia, this study reveals that managing pattern and stability, detecting discontinuity, and knowing the business have a positive but weak effect, whereas reconciling change and continuity proves to have a positive and significantly strong effect on organizational learning. This study has bridged the gap between the abstract concepts of crafting strategy, which is a potentially better approach for SMEs, with daily operational practices. This study also proves that Mintzberg's approach can be used to predict organizational learning. This relationship is crucial since previous studies concluded that organizational learning improves company performance.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.1959-1974
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• 2024

Nuclear energy plays a crucial role in energy supply in the 21st century, and more and more Nuclear Power Plants (NPPs) will be in operation to contribute to the development of human society. However, as a typical complex system engineering, the operation and development of NPPs require efficient and stable control methods to ensure the safety and efficiency of nuclear power generation. Reinforcement learning (RL) aims at learning optimal control policies via maximizing discounted long-term rewards. The reward-oriented learning paradigm has witnessed remarkable success in many complex systems, such as wind power systems, electric power systems, coal fire power plants, robotics, etc. In this work, we try to present a systematic review of the applications of RL on these complex systems, from which we believe NPPs can borrow experience and insights. We then conduct a block-by-block investigation on the application scenarios of specific tasks in NPPs and carried out algorithmic research for different situations such as power startup, collaborative control, and emergency handling. Moreover, we discuss the possibilities of further application of RL methods on NPPs and detail the challenges when applying RL methods on NPPs. We hope this work can boost the realization of intelligent NPPs, and contribute to more and more research on how to better integrate RL algorithms into NPPs.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.361-368
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• 2012

The e-Learning contents producing industry has been situated at the difficult status because of excessive competition and small-scale business company in unprofitable contents development market. One of the most important issues is low cost for e-Learning contents development. This paper is focus on analysis of e-Learning contents development cost and suggest the rational alternatives for policy making. In order to make successful study, this paper tell about various contents development cost, comparison analysis among them, and e-Learning contents development cost model. As a result of the study, this paper suggest the rational alternatives of of policy making for e-Learning contents development cost.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.1-22
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• 2018

The value chain has been utilized as a strategic tool to improve competitive advantage, mainly at the enterprise level and at the industrial level. However, in order to conduct value chain analysis at the enterprise level, the client companies of the parent company should be classified according to whether they belong to it's value chain. The establishment of a value chain for a single company can be performed smoothly by experts, but it takes a lot of cost and time to build one which consists of multiple companies. Thus, this study proposes a model that automatically classifies the companies that form a value chain based on actual transaction data. A total of 19 transaction attribute variables were extracted from the transaction data and processed into the form of input data for machine learning method. The proposed model was constructed using the Random Forest algorithm. The experiment was conducted on a automobile parts company. The experimental results demonstrate that the proposed model can classify the client companies of the parent company automatically with 92% of accuracy, 76% of F1-score and 94% of AUC. Also, the empirical study confirm that a few transaction attributes such as transaction concentration, transaction amount and total sales per customer are the main characteristics representing the companies that form a value chain.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.175-186
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• 2014

The purpose of this study is to demonstrate the effectiveness of core competency courses by scrutinizing H Corporation case. The primary data survey was taken from direct and indirect participants of H Corporation core competency courses. The findings from the study are as follow. Firstly, before-and-after average differences were significant in inspecting core competency courses. Secondly, participants' own expected core competency was comparatively lower than how observers evaluated the participants. Thirdly, Core competency courses directly and indirectly influenced on the business performance. Therefore, the conclusions of the study are firstly, core competency courses may work effectively for the goal of the company in changing employees' organizational behavior. Secondly, for the better result of the core competency courses, customized and integrated learning transfer model for the particular company should be designed from the beginning of the education.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.175-180
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• 2020

Through case studies for insurance service marketing using artificial intelligence(AI) in the insurtech industry, it investigated how innovative technologies(artificial intelligence, machine learning etc.) are being used in the insurance ecosystems. In particular, through domestic and international case studies, it was examined by Lemonade's service of insurance contracts and getting the indemnity and AI company's service of calculating the compensation through a medical certificate image based on OCR, which brought disruptive innovations using artificial intelligence. As a result of the case analysis, these services have drastically shortened the lead time of insurance contracts and payment through machine learning using numerous customer data based on artificial intelligence. And accurate and reasonable compensation was calculated in the estimation of indemnity, which has a lot of disputes between customers and insurance companies. It was able to increase customer satisfaction and customer value.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.111-116
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• 2019

New technologies such as the IoT, Big Data, and Artificial Intelligence, starting from the Web, mobile, and smart device, enable new business models that did not exist before, and various types of Internet companies based on these business models has been emerged. In this research, we examine the factors that influence the success and failure of Internet companies. To do this, we review the recent studies on business model and examine the variables affecting the success of Internet companies in terms of network effect, user interface, cooperation with actors, creating value for users. Using the five derived variables, we will select 14 Internet companies that succeeded and failed in seven commercial business model categories. We derive decision tree by applying inductive learning based on ID3 algorithm to the analysis result and derive rules that affect success and failure based on derived decision tree. With these rules, we want to present the strategic implications for actors to succeed in Internet companies.