• Food Science of Animal Resources
• /
• v.37 no.3
• /
• pp.469-476
• /
• 2017

This study analyzed consumers' preferences and price sensitivity to native chickens. A survey was conducted from Jan 6 to 17, 2014, and data were collected from consumers (n=500) living in Korea. Statistical analyses evaluated the consumption patterns of native chickens, preference marketing for native chicken breeds which will be newly developed, and price sensitivity measurement (PSM). Of the subjects who preferred broilers, 24.3% do not purchase native chickens because of the dryness and tough texture, while those who preferred native chickens liked their chewy texture (38.2%). Of the total subjects, 38.2% preferred fried native chickens (38.2%) for processed food, 38.4% preferred direct sales for native chicken distribution, 51.0% preferred native chickens to be slaughtered in specialty stores, and 32.4% wanted easy access to native chickens. Additionally, the price stress range (PSR) was 50 won and the point of marginal cheapness (PMC) and point of marginal expensiveness (PME) were 6,980 won and 12,300 won, respectively. Evaluation of the segmentation market revealed that consumers who prefer broiler to native chicken breeds were more sensitive to the chicken price. To accelerate the consumption of newly developed native chicken meat, it is necessary to develop a texture that each consumer needs, to increase the accessibility of native chickens, and to have diverse menus and recipes as well as reasonable pricing for native chickens.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2005.10a
• /
• pp.133-164
• /
• 2005

Mobile games have emerged as the most innovative entertainment technology, adding new revenue streams, taking advantage of the potential of wireless applications and service offerings. Mobile games, like any other types of computer game, offer a unique value for users in providing an exciting digital experience in virtual worlds. Players can become empowered through the development of new characters and strategies within games to achieve rewarding successes against the computers and other players. The overall trend for mobile games is towards bigger, more colorful, more involving and exciting contents, which will build upon the developing capabilities of mobile phones and networks in order to bring new styles, concepts and experiences of game play to the users. In this paper, we attempt to investigate the demographic factors which play critical roles in determining the level of playing times; classify mobile gamers based on their motives for playing games; and empirically test differences in their demographic factors and mobile game usage. Statistical results show that significant differences in playing times exist, depending upon their age, gender, mobile device, mobile phone usage, mobile game experiences, and preferred games genres. Applying Factor analysis, we have identified Escape, Social interaction, Challenge and Competition, Fantasy, Diversion and Relaxation, Ease of Accessibility as key motivators for playing mobile games. Additional cluster analysis shows that the categorization of gamers, according to their usage habits and the key motivators for playing, can be made as follows: M-gamers, Multi-gamers and Communication-focused gamers. Further correlation of these grouping with socio-economic data shows the significant differences in gaming habits and patterns of mobile phone use.

• Journal of Practical Engineering Education
• /
• v.16 no.1_spc
• /
• pp.51-58
• /
• 2024

This paper examines the differences between the Korean and American stock markets using the Kospi and S&P 500 indices and discusses policy implications through them. To this end, in addition to the existing time series analysis method, a deep learning method was used to compare markets, and the comparison was made in terms of stock price forecasting ability and data generation ability. In monthly data, the difference between time series was not large, and in daily data, the difference in terms of stability was weak, and there was no significant difference in predictive power or simulation data generation. As shown in the results of this study, if there is not much difference in market price movement patterns between Korea and the United States, tax benefits for long-term stocks investment will be effective against the side effects of short selling.

• Journal of Korea Technology Innovation Society
• /
• v.10 no.1
• /
• pp.73-97
• /
• 2007

R&D into future technologies should be conducted in conjunction with technological innovation strategies that are linked to corporate survival within a framework of information and knowledge-based competitiveness. As such, future technology strategies should be ensured through open R&D organizations. The development of future technologies should not be conducted simply on the basis of future forecasts, but should take into account customer needs in advance and reflect them in the development of the future technologies or services. This research aims to select as segmentation variables the customers' attitude towards accepting future telecommunication technologies and their value orientation in their everyday life, as these factors wilt have the greatest effect on the demand for future telecommunication services and thus segment the future telecom service market. Likewise, such research seeks to segment the market from the stage of technology R&D activities and employ the results to formulate technology development strategies. Based on the customer attitude towards accepting new technologies, two groups were induced, and a hierarchical customer segmentation model was provided to conduct secondary segmentation of the two groups on the basis of their respective customer value orientation. A survey was conducted in June 2006 on 800 consumers aged 15 to 69, residing in Seoul and five other major South Korean cities, through one-on-one interviews. The samples were divided into two sub-groups according to their level of acceptance of new technology; a sub-group demonstrating a high level of technology acceptance (39.4%) and another sub-group with a comparatively lower level of technology acceptance (60.6%). These two sub-groups were further divided each into 5 smaller sub-groups (10 total smaller sub-groups) through two rounds of segmentation. The ten sub-groups were then analyzed in their detailed characteristics, including general demographic characteristics, usage patterns in existing telecom services such as mobile service, broadband internet and wireless internet and the status of ownership of a computing or information device and the desire or intention to purchase one. Through these steps, we were able to statistically prove that each of these 10 sub-groups responded to telecom services as independent markets. We found that each segmented group responds as an independent individual market. Through correspondence analysis, the target segmentation groups were positioned in such a way as to facilitate the entry of future telecommunication services into the market, as well as their diffusion and transferability.

• Proceedings of the Korea Database Society Conference
• /
• 1999.06a
• /
• pp.175-186
• /
• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 1999.03a
• /
• pp.175-186
• /
• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Journal of Korea Technology Innovation Society
• /
• v.16 no.4
• /
• pp.1109-1133
• /
• 2013

In an effort to discover new technologies and to forecast social changes of technologies, a number of technology life-cycle models have been developed and employed. The hype cycle, a graphical tool developed by a consulting firm, Gartner, is one of the most widely used models for the purpose and it is recognised as a practical one. However, more research is needed on theoretical frames, relations and empirical practices of the model. In this study, hype cycle comparisons in Korean and global search websites were performed by means of web-search traffic which is proposed as an empirical measurement of public expectation, analysed in a specific product or country in previous researches. First, search traffic and market share for new cars were compared in Korea and the U.S. with a view to identifying differences between the hype cycles in the two countries about the same product. The results show the similarity between the two countries with the statistical significance. Next, comparative analysis between search traffic and supply rate for several products in Korea was conducted to check out their patterns. According to the analysis, all the products seem to be at the "Peak of inflated expectations" in the hype cycles and they are similar to one another in the hype cycle. This study is of significance in aspects of expanding the scope of hype cycle analysis with web-search traffic because it introduced domestic web-search traffic analysis from Naver to analyse consumers' expectations in Korea by comparison with that from Google in other countries. In addition, this research can help to explain social phenomina more persuasively with search traffic and to give scientific objectivity to the hype cycle model. Furthermore, it can contribute to developing strategies of companies, such as marketing strategy.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
• /
• v.23 no.2
• /
• pp.89-95
• /
• 2017

Although the global coffee market is growing every year and the demand for coffee wrapping paper is increasing accordingly, research on the effect of PE material and PP material on the coffee aroma used in the sealant layer, which will directly contact the product, is lacking. In this study, we studied the change of aroma patterns and flavor materials by adding coffee to PP and PE pouches. In addition, we observed changes in aroma patterns depending on the temperature and the presence of the deoxidizer. As a result, it was found that the PP type packaging material was slightly better than the PE type packaging material, but the performance was hardly changed by the material. Rather, the change in the aroma pattern due to temperature was dominant rather than the material. It is ideal that refrigerated distribution ($4^{\circ}C$) is the best storage temperature and sales are done within a short period of time. Among the indicators, pyridine was the most suitable material to study and there are many data about pyridine. Therefore, it is expected that the results can be derived by using pyridine.

• Journal of the Korea Furniture Society
• /
• v.16 no.1
• /
• pp.53-69
• /
• 2005

This research has a significant meaning to observe and understand the historical condition of a furniture industry and the characteristics of Korean home furniture's formation, ability, skill and materials from 1980s when there were an economic growth and a historical development of Korean home furniture occurred to present days. During 1980s, there was an automatic system available and has enforced and settled the standards on its quality and price in a furniture industry. Also, there was a big trend of black furniture as well as an entrance of corporation and high glossy furniture due to technical cooperation from Europe. In 1990s, there was an entrance of furniture which various techniques was applied due to a high development of the materials and skills, and also various sizes of height and weight and enlargement of acceptance function using highly-technological hardware. After 2000 and now, pro-environmental products is embossed in the Korean home furniture where they added a public issue which is the concept of well being, and A.I and sub material has been pro-environment. There also was a natural unity between nature and technology because of increased usage of trees with its natural patterns, metals, and glasses. For the future development of home furniture design, This problem should be promptly recognized that current home furniture designs are now on the verge of being lack of originality and are just following the market demand and recent trend as it is. Then, there should be a development of its specialized, detailed, unique design as well as a development of advanced materials, production management, distribution, and so on, and carrying out a diversified research continuously. There also should be a systematic education, which is necessary for training specialists to lead the Korean home furniture design industry as well as preparing a basic level for the future without a negligence.

• Korean Journal of Organic Agriculture
• /
• v.30 no.1
• /
• pp.1-20
• /
• 2022

With the recent rapid increase in single-person households, food companies are releasing small packaging and small-capacity products regardless of product line such as beverages, fresh foods, and home snacks, and food consumption patterns are also changing. Meanwhile, as a series of accidents related to food safety occurred during cost-effective consumption pursuing price-performance, more consumers wanted to choose products that have been proven safe even with higher money due to food safety anxiety. Considering the concept of 'safety' of food, this study by using the 'ordered probit model' empirically investigated whether there is a difference in the degree of preference for safety in food consumption behavior between single-person and multi-person households. Summarizing the results, it was found that women rather than men, and elderly households among young and single-person households had a higher demand for food safety. The results of marginal effects considering food safety variables show that respondents with low frequency of delivery and take-out use are considering food safety more, and that single-person households are considering safety more than multi-person households. In the future, the population structure of Korea will continue to increase in single-person and elderly households, and women's economic activities will also continue to increase. Therefore, the growing home convenience food market needs marketing strategies to secure and emphasize food safety, such as sterilizing treatment technology for hygiene and safe container development from environmental hormones, and needs a lot of support and attention to meet changes in food culture trends and demographic structure.