• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.235-243
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• 2022

This paper aims to find promising export items for market expansion of defense export items. Germany, the UK, and France were selected as export target countries to obtain unstructured forecast data on weapons system acquisition plans for the next ten years by each country. Using the TF-IDF in text mining analysis, keywords that appeared frequently in data from three countries were derived. As a result of this paper, keywords for each country's major acquisition projects drawing. However, most of the derived keywords were related to mainstay weapon systems produced by domestic defense companies in each country. To discover promising export items from text mining, we proposed that the drawn keywords are distinguished as similar weapon systems. In addition, we assort the weapon systems that the three countries will get a plan to acquire commonly. As a result of this paper, it can be seen that the current promising export item is a weapon system related to the information system. Prioritizing overseas demands using key words can set clear market entry goals. In the case of domestic companies based on needs, it is possible to establish a specific entry strategy. Relevant organizations also can provide customized marketing support.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.811-819
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• 2023

Understanding the local conditions is a crucial factor in enhancing the success potential of overseas construction projects. This can be achieved through the analysis of news articles of the target market using topic modeling techniques. In this study, the authors aimed to analyze news articles using two topic modeling methods, namely Latent Dirichlet Allocation (LDA) and BERTopic, in order to determine the optimal approach for market condition analysis. To evaluate the alignment between the generated topics and the actual themes of the news documents, the research collected 6,273 BBC news articles, created ground truth data for individual news article topics, and finally compared this ground truth with the results of the topic modeling. The F1 score for LDA was 0.011, while BERTopic achieved a score of 0.244. These results indicate that BERTopic more accurately reflected the actual topics of news articles, making it more effective for understanding the overseas construction market.

• Clean Technology
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• v.21 no.4
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• pp.209-216
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• 2015

Indium-Tin-Oxide (ITO) is a material that is widely used for transparent conductive electrodes (TCEs). Indium (In), chief element of the ITO, is expected to be depleted in the near future owing to its high cost and limited reserves. To overcome the issue, ITO has to be retained by recycling redundant ITO targets after manufacturing processes. In this article, we proposed an efficient recycling way of the redundant ITO targets with investigation of the current recycling tendencies in domestic and foreign countries. As a result, it was revealed that only In is recycled from the redundant targets in domestic and Japan. As well, fabrication of TCEs is being researched with ITO nanoparticles solutions. However, since the TCEs fabricated with ITO target is superior to those with other materials, it is thought that establishment of regeneration technology of ITO itself is demanded for an efficient recycling and fabrication of ITO target.

• Journal of Agricultural Extension & Community Development
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• v.20 no.4
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• pp.1181-1216
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• 2013

This study was accomplished to enhance brand value for hanwoo and to develop strategy for brand positioning that move customer's heart. This study in order to achieve the research was carried out as follows: First, the cluster analysis based on demographic characteristics for consumer on the basis of three types segmentation on market was conducted. Market A was consisted of a well-educated, high-income and young bracket. Market B was consisted of a well-educated, high-income and middle-aged bracket. Market C was consisted of a low-income and middle-aged class. Second, consumer's positioning map was analyzed based on perceiving data which are products' functional, emotional, and self-expressive benefits about consumer's feeling beef products. This study was analyzed each relative brand advantage and structure of competition on segmented market by conjoining each brands positioning map and feature vectors map. By the result of the analysis, each brand's positioning strategy was devised. As a result of the study, the hoengseong hanwoo is competitive about all kinds of market. We chooses that hoengseong hanwoo's target is A market, because that brand is evaluated as a high-ranked quality by high-class image of luxury price, quality, brand image. For management improvement sake, this brand(the hoengseong hanwoo) is needed to effort for promoting consumer's awareness about safety and reliability.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Journal of Applied Tourism Food and Beverage Management and Research
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• v.10
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• pp.109-138
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• 1999

The hotel does not sell one-time services, and the customer has many choices, especially today. And hotel is vulnerable to new competition. Most customers likes to try a new place and new product. The questions are 1) offering competitive products that are meaningful to customers 2) solving customers problems 3) offering a competitive products that are difficult for competitors to duplicate. This report is for studying about the relationship between the results of National Customer Satisfaction Index(NCSI) and the hotels' revenue. And explore the ways to identify opportunities for creating the desired image that differentiates from the competition and for serving the target market better than anyone else. For the about objectives, the following items are reviewed: 1) Customer behavior and customers' needs and wants 2) Customer decisions 3) Integrated marketing 4) Customer satisfaction 5) Major factors of the hotel customers satisfaction 6) Moment of truty Market positioning is to creat a distinctive place in the minds of potential customer. To position successfully requires recognizing the marketplaces. the competition, value for money and customers' perceptions. Finally, internal marketing efforts can be used to examine one's own position to see if it is perceived by it's customers. It means that the benefits exist in the mind of the customer and are determinable only by asking the customer. These kinds of efforts are essential to proper positioning analysis and long term relationship marketing.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.295-299
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• 2007

Today, ubiquitous technology (e.g. computers or networked devices pervade everywhere we are) has enlarged by great advancement of information and communication technologies. If ubiquitous technologies is applied to, innovation of spatial information technology is expected. traditional spatial information technologies such as survey, GIS, GPS, LBS, and RS and ubiquitous technology gradual1y have been converged. The aim of this study is to create shared visions in spatial information technologies by scenario based roadmapping. So, we surveyed the state of the art in main spatial information technologies, market status and patent map. Consequently, prospects of spatial information technologies is suggested. The aim of 1st and 2nd NGIS project focused on map supplier was to develop digital map(e.g. framework data, various thematic map). As a result, the best technology of digital mapping is achieved in the world. But, there is not enough to develop GIS and LBS solution. Current market in GIS S/W and Telematics is about 384billon won and 250billion won. a patent is applied in the order, like a USA(1571case, 47%), Japan(883case, 26%), EU(478case, 14%), Korea(446case, 13%). In the future, spatial information technology fused on ubiquitous technology will be focused on user's demand and developing convenience context. The developing target will be realtime monitoring of 3D spatial data based on high resolution coordinate system, sharing and supplying multi-sensor data considered users demand, location service by ubiquitous technologies.

• Fashion & Textile Research Journal
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• v.16 no.4
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• pp.520-531
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• 2014

Jeju, the biggest island in Korea, was registered as a World Natural Heritage in 2007. Recently, it was also voted as one of the New Seven Wonders of Nature. The need for academic awareness and tourist values on Jeju Island are understood. Gal-ot, one of the ten symbols for Jeju, is known for working clothes in general, despite its potential for cultural products because of its regional uniqueness and useful functional advantages. The authors conducted a comprehensive literature review and researched market trends of Gal-ot stores in Jeju to present development directions for cultural goods and to contribute to local economic improvement. Most stores were located in a semi-residential area and Jeju-si in Jeju Special Self-Governing Province. Most products were not available for sale due to difficulties in the production process and online utilization. High prices and similar color, fabric and style hurt competitiveness. Various experiencing programs of Gal-ot and persimmon dyeing were necessary to expand the main target from residents to tourists. Also, marketing strategies using the internet and design plans reflecting current trends were needed. This study would contribute to prepare developmental projects of cultural product and result in economical advantages on Jeju Island.

• Fashion & Textile Research Journal
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• v.5 no.3
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• pp.251-259
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• 2003

The young casual wear market has been recently increased by the great buying power of the target consumers, although they don't have their own discretionary income. The purpose of this study was to investigate clothing attitudes of the adolescent consumers of the young casual wear market according to the groups of personality types. The questions on introversion/extroversion of MBTI test were adopted to measure introversion/extroversion in personal characteristics. The questions in "The personality diagnosis of high school students" developed by Lee, Chongseung and Chung, Bummo were adopted to measure stability, dominance, sociability and autonomy. Variables of clothing attitudes were composed with attentiveness, modesty and conformity. A total 488 high school students in Seoul participated in the survey. SPSS Win 10 statistical package was used to analyze the data: frequency, t-test, ANOVA and factor analysis. After statistical analysis, the following results were found. Groups of introversion and extroversion, and groups of low, medium and high degree of stability, dominance, sociability and autonomy showed no significant difference based on sex difference and school types. Students who has a high extroversion showed a high degree of attentiveness in clothing attitudes. Students who has the lowest sociability and the lowest autonomy showed a high degree of attentiveness. Students with the lowest autonomy showed a high degree of conformity. The younger the students were, the higher their attentiveness and modesty in clothing attitudes.