• Science of Emotion and Sensibility
• /
• v.25 no.1
• /
• pp.41-54
• /
• 2022

The purpose of this study was to propose a "user experience (UX)-centered product development process" so that the product design development process using the service design process can be systematized and used in practice. In a situation in which usability research on office phones is lacking compared to general home phones, this study expands to a product-based service design point of view rather than simple product development, intending to research ways to provide user experience value through office phone design in smart office. This study focused on extracting UX-centered user needs using the service design process and developing product design that realizes user experience value. In particular, the service design process was applied to systematically extract user needs and experience value elements in the product development process and to discover ideas that were converged with product-based services. For this purpose, the "Double Diamond Design Process Model," which is widely used in the service design field, was adopted. In addition, a product design development process was established so that usability improvement plans, user experience value elements, and product-service connected ideas could be extracted through a work-flow in which real users and people from various fields participate. Based on the double diamond design process, in the "Discover" information collection stage, design trends were identified mainly in the office phone markets. In the "Define" analysis and extraction stage, user needs were analyzed through user observation, interview, and usability survey, and design requirements and user experience issues were extracted. Persona was set through user type analysis, and user scenarios were presented. In the "Develop" development stage, ideation workshops and concept renderings were conducted to embody the design, and people from various fields within the company participated to set the design direction reflecting design preference and usability improvement plans. In the "Deliver" improvement/prototype development/evaluation stage, a working mock-up of a design prototype was produced and design and usability evaluation were conducted through consultation with external design experts. It is meaningful that it established a "UX-centered product development process" model that converged with the existing product design development process and service design process. Ultimately, service design-based product design development process was presented so that I Corp.'s products could realize user experience value through service convergence.

• Journal of agriculture & life science
• /
• v.50 no.4
• /
• pp.169-177
• /
• 2016

This study was carried out to compare microbiological and hygienic quality characteristics of the products reached expiration date among meat products distributing in markets. A total of 20 meat products(6 hams, 3 bacons and 11 sausages) were examined for analyses of pH, Aw, TBARS, VBN, total aerobic microbial counts, and meat colors. The pH values of samples were between 5.33 and 6.59. The water activity (Aw) of samples ranged 0.90-0.93. TBARS and VBN values of samples were 0.11-0.59 and 2.37~14.75, respectively. The contaminated levels of total aerobic bacteria were less than 2.80 CFU/g. In meat color, L*, a*, and b* values of samples were in the range of 56-72, 5.2-34 and 0.7-16, respectively. It is suggested that the quality difference of meat products is attributed to the different additives and manufacturing processes. Therefore, we suggest that the results of this study are not only applied for evaluation of the microbiological and hygienic safety but also served as fundamental information for re-establishing the shelf-life of meat products.

• Journal of Food Hygiene and Safety
• /
• v.38 no.3
• /
• pp.99-111
• /
• 2023

The purpose of this study was to provide basic data for setting more detailed standards for baby food and to provide food information that can be used in real-world settings. We purchased 80 snacks and 40 drinks for infants and toddlers from supermarkets and online markets and analyzed tar color, artificial sweeteners, mycotoxins, and nutritional components (e.g., sucrose, sodium, and calcium). Fortunately, it was confirmed that both tar color and sodium saccharin, which do not have detection criteria for labeled foods for infants and toddlers, were not detected. However, acesulfame potassium was detected at 0.07 g/kg in one snack sample. As for myxotoxins, aflatoxin (B1, B2, G1, and G2) and ochratoxin A were not detected. Fumonisin B1, fumonisin B2, and zearalenone were detected in the ranges of 9.78-78.94 ㎍/kg, 5.58-11.73 ㎍/kg, and 2.96-8.83 ㎍/kg, respectively, but only in snacks. Sucrose was detected in 65 of the snacks (0.02-40.94 g/net weight [g]) and in 24 of the drinks (0.12-27.60 g/net weight [g]). Minerals were detected in most of the samples, and in four snacks, the zinc content per net exceeded the tolerable upper intake level for infants. Sixteen snacks exceeded the food standards for sodium content for infants and toddlers, but none of them were labeled as food for infants and toddlers in the product manufacturing report, such that the corresponding standards could not be applied. Therefore, it seems necessary to establish institutional improvements, such as strengthening labeling standards, so that the currently enforced standards can be appropriately applied, and establishing standards for labeled foods for infants and toddlers.

• Korean small business review
• /
• v.31 no.1
• /
• pp.73-88
• /
• 2009

This study examines the characteristics of 24 Korean hidden champions such as key success factors, core competences, strategic problems, and desirable future directions. The study categorized them into 8 types with Danny Miller's four trajectories and top manager's decision making style(rationality and passion). Danny Miller argued in his book, Icarus paradox, that outstanding firms will extend their orientations until they reach dangerous extremes and their momentum will result in common trajectories of decline. He suggested four very common success types: Craftsmen, Builders, Pioneers, Salesmen. He also suggested common trajectories of decline:Focusing(from Craftsmen to Tinkers), Venturing(from Builders to Imperialists), Inventing(from Pioneers to Escapists), Decoupling(from Salesmen to Drifts). In Korea, successful startups appear to possess three kinds of drive: Technology-drive, Vision-drive, Market-drive. Successful technology-driven firms tend to grow as craftsmen or pioneers. Successful vision-driven and market-driven ones tend to grow as builders and salesmen respectively. Korean top managers or founders seem to have two kinds of decision making style: Passion-based and Rationality-bases. Passion-based(passionate) entrepreneurs are biased towards action or proactiveness in competing and getting things done. Rationality- based ones tend to emphasis the effort devoted to scanning and analysing information to better understand a company's threats, opportunities and options. Consequently this study suggested 4*2 types of Korean hidden champions: (1) passionate craftsmen, (2) rational craftsmen, (3) passionate builders, (4) rational builders, (5) passionate pioneers, (6) rational pioneers, (7) passionate salesmen, (8) rational salesmen. These 8 type firms showed different success stories and appeared to possess different trajectories of decline. These hidden champions have acquired competitive advantage within domestic or globally niche markets in spite of the weak market power and lack of internal resources. They have maintained their sustainable competitiveness by utilizing three types of growth strategy; (1) penetrating into the global market, (2) exploring new service market, (3) occupying the domestic market. According to the types of growth strategy, these firms showed different financial outcomes and possessed different issues for maintaining their competitiveness. This study found that Korean hidden champions were facing serious challenges from the transforming economic structure these days and possessed the decline potential from their success momentum or self-complacence. It argues that they need to take a new growth engine not to decline in the turbulent environment. It also discusses how firms overcome the economic crisis and find a new business area in promising industries for the future. It summarized the recent policy of Korean government called as "Green Growth" and discussed how small firms utilize such benefits and supports from the government. Other implications for firm strategies and governmental policies were discussed.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.11
• /
• pp.471-480
• /
• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• The Korean Journal of Air & Space Law and Policy
• /
• v.25 no.2
• /
• pp.139-162
• /
• 2010

In terms of the international air transport, the open skies policy implies freedom in the sky or opening the sky. In the normative respect, the open skies policy is a kind of open-door policy which gives various forms of traffic right to other countries, but on the other hand it is a policy of free competition in the international air transport. Since the Airline Deregulation Act of 1978, the United States has signed an open skies agreement with many countries, starting with the Netherlands, so that competitive large airlines can compete in the international air transport market where there exist a lot of business opportunities. South Korea now has an open skies agreement with more than 20 countries. The frequent flyer program (FFP) is part of a broad-based marketing alliance which has been used as an airfare strategy since the U.S. government's airline deregulation. The membership-based program is an incentive plan that provides mileage points to customers for using airline services and rewards customer loyalty in tangible forms based on their accumulated points. In its early stages, the frequent flyer program was focused on marketing efforts to attract customers, but now in the environment of intense competition among airlines, the program is used as an important strategic marketing tool for enhancing business performance. Therefore, airline companies agree that they need to identify customer needs in order to secure loyal customers more effectively. The outcomes from an airline's frequent flyer program can have a variety of effects on international competition. First, the airline can obtain a more dominant position in the air flight market by expanding its air route networks. Second, the availability of flight products for customers can be improved with an increase in flight frequency. Third, the airline can preferentially expand into new markets and thus gain advantages over its competitors. However, there are few empirical studies on the airline frequent flyer program. Accordingly, this study aims to explore the effects of the program on international competition, after reviewing the types of strategic alliance between airlines. Making strategic airline alliances is a worldwide trend resulting from the open skies policy. South Korea also needs to be making open skies agreements more realistic to promote the growth and competition of domestic airlines. The present study is about the performance of the airline frequent flyer program and international competition under the open skies policy. With a sample of five global alliance groups (Star, Oneworld, Wings, Qualiflyer and Skyteam), the study was attempted as an empirical study of the effects that the resource structures and levels of information technology held by airlines in each group have on the type of alliance, and one-way analysis of variance and regression analysis were used to test hypotheses. The findings of this study suggest that both large airline companies and small/medium-size airlines in an alliance group with global networks and organizations are able to achieve high performance and secure international competitiveness. Airline passengers earn mileage points by using non-flight services through an alliance network with hotels, car-rental services, duty-free shops, travel agents and more and show high interests in and preferences for related service benefits. Therefore, Korean airline companies should develop more aggressive marketing programs based on multilateral alliances with other services including hotels, as well as with other airlines.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.135-149
• /
• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• 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.

• Journal of Global Scholars of Marketing Science
• /
• v.20 no.1
• /
• pp.15-26
• /
• 2010

Due to the globalization across various industries and cultural trade among many countries, oriental concepts have been attracting world’s attentions. In fashion industry, one's traditional culture is often developed as fashion theme for designers' creation and became strong strategies to stand out among competitors. Because of the increase of preferences for oriental images, opportunities abound to introduce traditional fashion goods and expand culture based business to global fashion markets. However, global fashion brands that include Korean traditional culture are yet to be developed. In order to develop a global fashion brand with Korean taste, it is very important for native citizen to accept their own culture in domestic apparel market prior to expansion into foreign market. Loungewear is evaluated to be appropriate for adopting Korean traditional details into clothing since this wardrobe category embraces various purposes which will easily lead to natural adaptation and wide spread use. Also, this market is seeing an increased demand for multipurpose wardrobes and fashionable underwear (Park et al. 2009). Despite rapid growth in the loungewear market, specific studies of loungewear is rare; and among research on developing modernized-traditional clothing, fashion items and brands do not always include the loungewear category. Therefore, this study investigated the Korean loungewear market and studied consumer evaluation toward loungewear with Korean traditional fashion design elements. Relationship among antecedents of purchase intention for Korean traditional fashion design elements were analyzed and compared between lifestyle groups for consumer targeting purposes. Product quality, retail service quality, perceived value, and preference on loungewear with Korean traditional design elements were chosen as antecedents of purchase intention and a structural equation model was designed to examine their relationship as well as their influence on purchase intention. Product quality and retail service quality among marketing mixes were employed as factors affecting preference and perceived value of loungewear with Korean traditional fashion design elements. Also effects of preference and perceived value on purchase intention were examined through the same model. A total of 357 self-administered questionnaires were completed by female consumers via web survey system. A questionnaire was developed to measure samples' lifestyle, product and retail service quality as purchasing criteria, perceived value, preference and purchase intention of loungewear with Korean traditional fashion design elements. Also, loungewear purchasing and usage behavior were asked as well in order to examine Korean loungewear market status. Data was analyzed through descriptive analysis, factor analysis, cluster analysis, ANOVA and structural equation model was tested via AMOS 7.0. As for the result of Korean loungewear market status investigation, loungewear was purchased by most of the consumers in our sample. Loungewear is currently recognized as clothes that are worn at home and consumers are showing comparably low involvement toward loungewear. Most of consumers in this study purchase loungewear only two to three times a year and they spend less than US$10. A total of 12 items and four factors of loungewear consumer lifestyle were found: traditional value oriented lifestyle, brand-affected lifestyle, pursuit of leisure lifestyle, and health oriented lifestyle. Drawing on lifestyle factors, loungewear consumers were classified into two groups; Well-being and Conservative. Relationships among constructs of purchasing behavior related to loungewear with Korean traditional fashion design elements were estimated. Preference and perceived value of loungewear were affected by both product quality and retail service quality. This study proved that high qualities in product and retail service develop positive preference toward loungewear. Perceived value and preference of loungewear positively influenced purchase intention. The results indicated that high preference and perceived value of loungewear with Korean traditional fashion design elements strengthen purchase intention and proved importance of developing preference and elevate perceived value in order to make sales. In a model comparison between two lifestyle groups: Well-being and Conservative lifestyle groups, results showed that product quality and retail service quality had positive influences on both preference and perceived value in case of Well-being group. However, for Conservative group, only retail service quality had a positive effect on preference and its influence to purchase intention. Since Well-being group showed more significant influence on purchase intention, loungewear brands with Korean traditional fashion design elements may want to focus on characteristics of Well-being group. However, Conservative group's relationship between preference and purchase intention of loungewear with Korean traditional fashion design elements was stronger, so that loungewear brands with Korean traditional fashion design elements should focus on creating conservative consumers' positive preference toward loungewear. The results offered information on Korean loungewear consumers' lifestyle and provided useful information for fashion brands that are planning to enter Korean loungewear market, particularly targeting female consumers similar to the sample of the present study. This study offers strategic and marketing insight for loungewear brands and also for fashion brands that are planning to create highly value-added fashion brands with Korean traditional fashion design elements. Considering different types of lifestyle groups that are associated with loungewear or traditional fashion goods, brand managers and marketers can use the results of this paper as a reference to positioning, targeting and marketing strategy buildings.

• Journal of Intelligence and Information Systems
• /
• v.16 no.2
• /
• pp.19-32
• /
• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.