• 지역과문화
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• v.8 no.3
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• pp.27-48
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• 2021

In recent years, China's tourism performing art in a series of new completion of the project, increase the box office of tourism performing arts industry, higher economic income, at the same time led to the formation of brand of tourism performing arts and has a good reputation, with the regional culture, has a certain role in promoting economic development, including Large scenario experience drama is one of the key projects. Large scenario experience drama is a new form of drama that simulates the space design of real environment and enables the audience to have active experience in visual, auditory, smell, taste, touch and other senses with strong interactivity.Large scenario experience drama are adapted from traditional Chinese culture, regional culture and long-passed stories, and combine high technology such as lighting, sound effects, special effects and 3D effects to make the audience's experience more real.As the first Large scenario experience drama in China, 'You Jian Ping-yao' reflects the profound culture of Shanxi with new forms of expression and creative means, in the form of scene experience and make the audience more intuitive feel the 'Shanxi emotion', 'Shanxi sentiment' and 'Shanxi Morality', carry forward the traditional culture at the same time, also passed the Shanxi ancient and great values, strengthened the drama of China's movie village, impetus the development of the tourism industry in Shanxi, drive the Shanxi region of jingjing, gradually formed a complete industrial chain. However, there are also limitations such as improper plot connection and improper tourist management, which can improve the performance effect through more audience interaction and guidance. Therefore, it can be seen that large-scale situational experience dramas play a great role in promoting the dissemination of traditional culture and values, the development of tourism industry, the formation of regional brand characteristics and economic development. Through these, it can be seen that large-scale situational experience plays have enlightenments such as innovative thinking content, gradually forming an industrial chain closed-loop, and broadening publicity channels for the development of live-action performances.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.37-64
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• 2022

As the social acceptance of artificial intelligence increases, the number of cases of applying machine learning methods to companies is also increasing. Technical factors such as accuracy and interpretability have been the main criteria for selecting machine learning methods. However, the success of implementing machine learning also affects management factors such as IT departments, operation departments, leadership, and organizational culture. Unfortunately, there are few integrated studies that understand the success factors of machine learning selection in which technical and management factors are considered together. Therefore, the purpose of this paper is to propose and empirically analyze a technology-management integrated model that combines task-tech fit, IS Success Model theory, and John Rice's algorithm selection process model to understand machine learning selection within the company. As a result of a survey of 240 companies that implemented machine learning, it was found that the higher the algorithm quality and data quality, the higher the algorithm-problem fit was perceived. It was also verified that algorithm-problem fit had a significant impact on the organization's innovation and productivity. In addition, it was confirmed that outsourcing and management support had a positive impact on the quality of the machine learning system and organizational cultural factors such as data-driven management and motivation. Data-driven management and motivation were highly perceived in companies' performance.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.3-12
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• 2022

In general construction project planning ratio of manpower and quantity of outputs produced, such as the construction estimate standard, is used as the criterion for labor productivity. This method is highly effective in construction projects with repetitive work, however, there is a limit to apply in large-scale projects with high complexity. This is because the influence of non-work time caused by various work interruption factors that act complexly on the productivity of the project is greater than the average labor productivity derived from the performance data of the project. Therefore, this study proposes a productivity measurement method that can evaluate the characteristics of construction works and the cause of non-working time. To this end, first, detailed work processes and their non-work factors for each work type are defined, and the Adv-FMR technique is developed for quantitatively measuring them. Next, based on the concept of obtainable productivity, methods for comparative productivity analysis by work type, evaluating non-work factors, and deriving productivity improvement methods are proposed. Finally, a case study is conducted to validate that the analysis results based on Adv-FMR data can support the decision-making of construction managers on productivity management.

• Asia Marketing Journal
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• v.13 no.3
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• pp.233-248
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• 2011

This case illustrates a story of passionate and innovative new market development by Pulmuone, a fresh food provider in Korea. The company has been successfully developing a new market by introducing a (non-frying) fresh ramen, 'Jayeonun Masitda - The Nature Is Tasty' in the packaged ramen market dominated by fried ones. In this case, a detailed new market development process by Pulmuone will be investigated including; company overview, a new product development process, marketing strategy formulation, marketing mix implementation, market performance, and future directions. Pulmuone has been making efforts to create a new product category by marketing non-frying ramens since 1995, but with a modest success. In 2011, Pulmuone finally succeeded to develop an innovative product, 'Jayeonun Masitda' that brought more health and nutrition conscious consumers' attention in the ramen market. The company intended to change the current competitive structure in the ramen market, i.e., from the strength of taste and the amount of ingredient to fried/non-fried and the freshness of ingredient. By this new positioning, Pulmuone aimed to reshaping the ramen market into competition between healthy and unhealthy ramens. Pulmuone has been successful in developing a new market. Sales revenue of 'Jayeonun Masitda' has been continuously increasing, and customers are found to be highly satisfied with the product resulting in a high repeat purchase rate. The company's successful new market development can be attributed to a faithful new product development process, innovative technology, an appropriate positioning strategy, and consistent marketing communication. In addition, Pulmuone's eco-friendly corporate image and the organization's passion to grow are also important factors for success of this new market development.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.510-516
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• 2021

Recently, the range of utilization and demand for unmanned aerial vehicle (UAV) has been continuously increasing, and research on the construction of a separate operating system for low-altitude UAV is underway through the development of a management system separate from manned aircraft. Since low-altitude UAVs also fly in the airspace, it is essential to establish technical standards and certification systems necessary for the operation of the aircraft, and research on this is also in progress. If the operating standards and certification requirements of the aircraft are presented, a test method to confirm this should also be presented. In particular, the accuracy of small UAV's navigation required during flight is required to be more precise than that of a manned aircraft or a large UAV. It was necessary to calculate a separate navigation error. In this study, we presented a test method for deriving navigation errors that can be applied to UAVs that have difficulty in acquiring long-term operational data, which is different from existing manned aircraft, and conducted verification tests.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.245-256
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• 2022

The purpose of this study is to provide comprehensive insights on the current research trends in entrepreneurship based on topic modeling and keyword co-occurrence analysis. This study queried Web of Science database with 'entrepreneurship' and collected 14,953 research articles between 2002 and 2021. The study used R program for topic modeling and VOSviewer program for keyword co-occurrence analysis. The results of this study are as follows. First, as a result of keyword co-occurrence analysis, 5 clusters divided: entrepreneurship and innovation cluster, entrepreneurship education cluster, social entrepreneurship and sustainability cluster, enterprise performance cluster, and knowledge and technology transfer cluster. Second, as a result of the topic modeling analysis, 12 topics found: start-up environment and economic development, international entrepreneurship, venture capital, government policy and support, social entrepreneurship, management-related issues, regional city planning and development, entrepreneurship research, and entrepreneurial intention. Finally, the study identified two hot topics(venture capital and entrepreneurship intention) and a cold topic(international entrepreneurship). The results of this study are useful to understand current research trends in entrepreneurship research and provide insights into research of entrepreneurship.

• Information Systems Review
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• v.24 no.2
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• pp.67-88
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• 2022

This study proposed a research model that can explain the usage intentions of users and non-users by considering the performance aspects of personal mobility and external environmental factors based on the SOR (Stimulus-Organism-Response) model, A survey was conducted targeting domestic users and non-users, and research models and hypotheses were verified through Partial Least Square (PLS) and Artificial Neural Network (ANN). As a result of the analysis, it was confirmed that the users' perceived satisfaction and perceived trust had a positive effect on their intention to use, and that perceived risk and environmental value had a significant relationship with perceived satisfaction and perceived trust. For non-users, it was found that there was a positive correlation between perceived satisfaction and intention to use, and it was verified that perceived risk and environmental value, like users, were significant antecedents of perceived satisfaction and perceived trust. Among the remaining variables, the perceived mobility of users and the perceived ease of use of non-users were respectively presented as important influencing factors on perceived satisfaction.

• Information Systems Review
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• v.19 no.3
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• pp.23-45
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• 2017

The ROK military is making a great effort and investment in establishing network-centric warfare, a future battlefield concept, as a major step in the establishment of a basic plan for military innovation. In the military organization level, an advanced process is introduced to shorten the command control time of the military and the business process is improved to shorten the decision time. In the information system dimension, an efficient resource management is achieved by establishing an automated command control system and a resource management information system by using the battle management information system. However, despite these efforts, we must evaluate the present level of informatization in an objective manner and assess the current progress toward the future goal of the military by using objective indicators. In promoting informatization, we must systematically identify the correct areas of improvement and identify policy directions to supplement in the future. Therefore, by analyzing preliminary research, workshops, and expert discussions on the major informatization level evaluation models at home and abroad, this study develops an evaluation model and several indicators that systematically reflect the characteristics of military organizations. The developed informatization level evaluation model is verified by conducting a feasibility test for the troops of the operation class or higher. We expect that this model will be able to objectively diagnose the level of informatization of the ROK military by putting budget and resources into the right place at the right time and to rapidly improve the vulnerability of the information sector.

• Information Systems Review
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• v.21 no.1
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• pp.1-22
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• 2019

Mindfulness is the process of actively noticing new things. Today, companies have introduced and run mindfulness programs because the mindfulness has possible applications of productivity and innovation in corporation. However, role of mindfulness has not been clearly investigated in behavior research of Information System. The purpose of this study is to confirm the effects of mindfulness on technology acceptance process. Based on UTAUT Model, we examined how mindfulness in technology acceptance process moderate antecedent factors of acceptance intentions and use behavior. For empirical research, we conducted a survey on acceptance of smart watch of internet of things for employees of companies applying the mindfulness programs. then, we analyzed survey sample in empirical methodologies. Based on the empirical analysis, cognizance of alternative technologies in mindfulness factors increased the impact of performance expectancy on acceptance intention. Novelty seeking in mindfulness factors increased the impact of effort expectancy on acceptance intention. Awareness of local context in mindfulness factors decreased the impact of social influence on acceptance intention. engagement with technology in mindfulness factors increased the impact of facilitating conditions on use behavior. This study suggests academic implications and practical implications based on the results of the research. The implications will help to support and extend the theory of technology acceptance model while providing practical insights for IT acceptance by suggesting ways to utilize mindfulness in corporation.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.