• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.89-111
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• 2008

Due to the development of digital technology, studies regarding smart wear integrating daily life have rapidly increased. However, consumer research about perception and attitude toward smart clothing hardly could find. The purpose of this study was to identify innovative characteristics and perceived risk of smart clothing and to analyze the influences of theses factors on product attitudes and intention to adopt. Specifically, five hypotheses were established. H1: Perceived attributes of smart clothing except for complexity would have positive relations to product attitude or purchase intention, while complexity would be opposite. H2: Product attitude would have positive relation to purchase intention. H3: Product attitude would have a mediating effect between perceived attributes and purchase intention. H4: Perceived risks of smart clothing would have negative relations to perceived attributes except for complexity, and positive relations to complexity. H5: Product attitude would have a mediating effect between perceived risks and purchase intention. A self-administered questionnaire was developed based on previous studies. After pretest, the data were collected during September, 2006, from university students in Korea who were relatively sensitive to innovative products. A total of 300 final useful questionnaire were analyzed by SPSS 13.0 program. About 60.3% were male with the mean age of 21.3 years old. About 59.3% reported that they were aware of smart clothing, but only 9 respondents purchased it. The mean of attitudes toward smart clothing and purchase intention was 2.96 (SD=.56) and 2.63 (SD=.65) respectively. Factor analysis using principal components with varimax rotation was conducted to identify perceived attribute and perceived risk dimensions. Perceived attributes of smart wear were categorized into relative advantage (including compatibility), observability (including triability), and complexity. Perceived risks were identified into physical/performance risk, social psychological risk, time loss risk, and economic risk. Regression analysis was conducted to test five hypotheses. Relative advantage and observability were significant predictors of product attitude (adj $R^2$=.223) and purchase intention (adj $R^2$=.221). Complexity showed negative influence on product attitude. Product attitude presented significant relation to purchase intention (adj $R^2$=.692) and partial mediating effect between perceived attributes and purchase intention (adj $R^2$=.698). Therefore hypothesis one to three were accepted. In order to test hypothesis four, four dimensions of perceived risk and demographic variables (age, gender, monthly household income, awareness of smart clothing, and purchase experience) were entered as independent variables in the regression models. Social psychological risk, economic risk, and gender (female) were significant to predict relative advantage (adj $R^2$=.276). When perceived observability was a dependent variable, social psychological risk, time loss risk, physical/performance risk, and age (younger) were significant in order (adj $R^2$=.144). However, physical/performance risk was positively related to observability. The more Koreans seemed to be observable of smart clothing, the more increased the probability of physical harm or performance problems received. Complexity was predicted by product awareness, social psychological risk, economic risk, and purchase experience in order (adj $R^2$=.114). Product awareness was negatively related to complexity, meaning high level of product awareness would reduce complexity of smart clothing. However, purchase experience presented positive relation with complexity. It appears that consumers can perceive high level of complexity when they are actually consuming smart clothing in real life. Risk variables were positively related with complexity. That is, in order to decrease complexity, it is also necessary to consider minimizing anxiety factors about social psychological wound or loss of money. Thus, hypothesis 4 was partially accepted. Finally, in testing hypothesis 5, social psychological risk and economic risk were significant predictors for product attitude (adj $R^2$=.122) and purchase intention (adj $R^2$=.099) respectively. When attitude variable was included with risk variables as independent variables in the regression model to predict purchase intention, only attitude variable was significant (adj $R^2$=.691). Thus attitude variable presented full mediating effect between perceived risks and purchase intention, and hypothesis 5 was accepted. Findings would provide guidelines for fashion and electronic businesses who aim to create and strengthen positive attitude toward smart clothing. Marketers need to consider not only functional feature of smart clothing, but also practical and aesthetic attributes, since appropriateness for social norm or self image would reduce uncertainty of psychological or social risk, which increase relative advantage of smart clothing. Actually social psychological risk was significantly associated to relative advantage. Economic risk is negatively associated with product attitudes as well as purchase intention, suggesting that smart-wear developers have to reflect on price ranges of potential adopters. It will be effective to utilize the findings associated with complexity when marketers in US plan communication strategy.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.25 no.3
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• pp.79-87
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• 2019

The degree of cosmetic's oxidation depends on the storage conditions and external conditions when using the product. The microbial contamination and oxygen exposure often results in the quality deterioration of cosmetics. In addition, the problem is that consumers often use cream-type cosmetics, which have short expiration period (6-12 months), even after the product is expired. When using the deteriorated cosmetics, it can be fatal to consumers' safety including some symptoms such as folliculitis, rashes, edema, and dermatitis. Therefore, it is necessary to develop sealed smart packaging for cosmetics to prevent the deterioration of cosmetics and improve consumer safety. In this study, we have developed smart packaging design for cosmetics that can measure the surrounding environment and expiration date for the cosmetics in the real time. In addition, the smart packaging includes sensor, which are linked to the mobile application. Users can find out the measurement results through the application. Also, the packaging design and functions were set up based on the survey results by the user and feasible model can be produced based on user choice. The measurement in the three environment has been done after manufactured the sensor, PCB, and mobile application. As a result, it works normally within a certain range under all three environmental conditions. It is believed that the information on expiration dates and storage environment can be efficiently delivered to the consumers through developed cosmetics smart packaging and applications. The development of UI/UX design for consumer is further studied. The UX/UI design of the application plays an essential role in achieving this goal through the commercialization the cosmetic products in the wide range.

• Korean Journal of Plant Resources
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• v.25 no.1
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• pp.156-168
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• 2012

Chrysanthemum is a cut flower species that normally lasts for 1 to 2 weeks, in some cases 3-4 weeks. This has been attributed to low ethylene production during senescence. Reduction in cut flower quality has been attributed to the formation of air embolisms that partially or completely blocks the water transport from the vase solution to the rest of the cut flower stem, increasing hydraulic resistance which may cause severe water stress, yellowing, wilting of leaf, and chlorophyll degradation. Standard type chrysanthemum can be harvested when buds were still tightly closed and then fully opened with the simple bud-opening solution. Standard type chrysanthemum can also be harvested when the minimum size of the inflorescence is about 5-6 cm bud which opened into the first flower full-sized flower. While spray varieties can be harvested when 2-4 most mature flowers have opened (40% opening). Cut flowers are sorted by stem length, weight, condition, and so on. Standard chrysanthemum is 80 cm length for standard type and 70cm for spray type. Pre-treatment with a STS, plant regulator such as GA, BA, 1-MCP, chrysal, germicide, and sucrose, significantly improved the vase life and quality of cut flowers. It is well established that vase solutions containing sugar can improve the vase life of cut chrysanthemum. Chrysanthemum is normally packed in standard horizontal fiberboard boxes. Chrysanthemum should normally be stored at $5{\sim}7^{\circ}C$. Precooling resulted in reduction in respiration, decomposition, and transpiration activities as well as decoloration retardation. There was significant difference between "wet" storage in 3 weeks and "dry" storage in 2 weeks. In separate pulsing solution trials, various germicides were tested, as well as PGRs to maintain the green color of leaves and turgidity. Prolonging vase life was attained with the application of optimal solution such as HQS, $AgNO_3$, GA, BA and sucrose. This also retarded senescence in leaves of cut flower stems. Fresh cut chrysanthemum can be transported using a refrigerated van with $5{\sim}7^{\circ}C$. Increasing consumption and usage of cut chrysanthemum of various cultivars would require efficient transport system, and effective information exchange among producer, wholesaler, and consumer.

• Informatization Policy
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• v.25 no.1
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• pp.3-29
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• 2018

The Federal Communications Commission voted to repeal net neutrality protections on December 14, 2017. This is the very opposite decision of the net neutrality rule that the Obama administration has consistently maintained. The ensuing storm from the repeal of net neutrality protections has an extensively effect enough on individuals and businesses to cover the entire spectrum, and the impact is hard to assess in the U. S. content industry, which dominates the worldwide Internet content and platform market. On the other hand, Korea's net neutrality protections have been firmly pursued, and there is no sign of change even after the decision happened in the U. S. Net neutrality is not a simple theme that is associated with the Constitution, such as freedom of expression, as well as the issue of network enhancement to prepare for 5G. Accordingly, this study examines how the net neutrality has been carried out in the U. S. and Korea over the years, and provides the issues of Internet enhancement, perspectives of ISP and ICP, and implications for the Constitution, market economy, fair competition and zero rating. This research delivers future direction and implications of domestic net neutrality policies.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.52-52
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• 2017

연구목적: 생산자와 소비자의 물리적 사회적 거리가 가까워지고, 1일 유통체계 준수에 의한 높은 신선도 유지, 먹거리에 대한 생산자와 생산정보 공유에 의한 농산물 안전성 향상 등 여러 장점 때문에 늘어나고 있는 로컬 푸드의 지속발전을 모색하고자 로컬 푸드 참여농가의 농작업 어려움 조사 및 기계화 방안 제시 조사방법: 전북 완주군 소재 용진농협에서 운영 중인 로컬 푸드 직매장에 농산물을 공급하는 농업인 21인을 대상으로 2016년 11월에 로컬 푸드의 어려운 점, 주요 생산품목, 가장 힘든 농작업, 기계화가 시급한 농작업, 농기계 도입에 어려운 점, 의견 및 건의사항을 설문 조사 분석하였음 결과 및 고찰: 로컬 푸드 참여 농가들은 4~5개 품목을 소량 생산하고, 농가에서 수확 소포장 라벨 부착 후 매장에 직접 진열하고 있었음. 농협은 정선 선별기, 소형 도정기, 포장기, 바코드 기계 등을 설치하여 농가 공동이용, 안전성 신선도 관리 등 교육, 스마트폰 앱을 매장 재고 현황을 농업인에게 실시간으로 제공 등 지원하고 있음. 조사에 응한 농업인 21명 중 60대(13명) > 50대(5명) > 70대(3명)로 모두 50대 이상이었음. 어려운 점에 대한 물음에 대해서는 '판매가 어렵다'(45%) > '인력이 부족하다'(40%) > '생산비가 많이 든다'(8.5%) > 기타(6.5%) 순이었음. '인력부족'은 파종과 수확 시기에 노동력이 집중적으로 필요한 것에 기인하고, 경지 규모가 다소 큰 농가에서는 농사일을 전문으로 하는 외국인 노동자를 고용함으로 노동력 부족 문제를 해소하지만, 소규모 농가는 품삯을 주고 고용할 경우 오히려 적자이기 때문에 고되더라도 자체 노동력으로 해결하고 있는 것으로 조사되었음. 가장 힘든 작업은 수확(81%) > 파종 정식(19%)으로 수확이 절대적으로 힘든 작업이라고 응답하였고, 기계화가 시급한 작업은 수확(71%) > 파종 정식(29%)으로 응답하였음. 힘든 이유로는 적기에 수확을 끝내야 상품성을 인정받을 수 있기 때문에 단기간에 많은 노동력이 요구된다고 응답하였음. 농기계 도입에 어려운 원인으로는, '적합한 수확기계가 없다'(48%)와 '재배면적이 적어 필요성을 못 느낀다'(29%)가 대부분이었고, 이밖에 '가격이 비싸다'(10%), '기계 정확도가 떨어진다'(10%), '기계 조작이 어렵다'(5%)로 나타났음. 결론: 로컬 푸드 참여 농가를 대상으로 농작업 기계화 현황에 대하여 조사하였음. 로컬 푸드의 지속 발전을 위한 방안을 제시하면; 첫째, 중 소농을 위한 수확기 개발이 가장 시급한 것으로 조사되었고, 둘째, 농기계가 아니더라도 우선 힘든 일을 해소하면서 편하게 자세를 유지할 수 있는 작업 보조기구 또는 편이장비의 개발 보급이 필요함. 셋째, 농가의 영세성과 지역의 특성을 고려하여 기술센터 농기계임대사업이나 시군 보조사업을 통해서 소형 농기계, 농기구, 보조 및 편이장비 보급이 확대되어야 함.

• Management & Information Systems Review
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• v.28 no.4
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• pp.175-197
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• 2009

Numerous researches related to internet shopping malls have been researched by numerous researchers. Such as, establishing criteria to evaluate service quality of electronic commerce, identifying factors affecting successful internet shopping mall operation, and examining relationships among the factors in electronic commerce based shopping mall needed to be focused on. However, most researches that have been undertaken only consider the service quality model or basic functional dimension. In accordance with this indispensability, the integrated structural relationship among variables, which are potentially inherent in customer's perception and affect personnel royalty on internet shopping mall needs to be acknowledged. The purpose of this study is to examine which factors should be able to facilitate performance of internet shopping mall. Based on the relevant literature, it has been empirically analyzed how corporate image, system quality, service quality and delivery quality affect customer satisfaction as well as customer royalty. The research's problem is that it was tested with data collected from 212 respondents. This study developed and empirically analyzed a model representing the relationship by using the Structural Equation Model. The major findings of this study are, firstly, that the higher corporate image is positively affecting the system quality and delivery quality. Secondly, the higher delivery quality is positively affecting the service quality. Thirdly, the higher service quality is positively affecting the customer satisfaction. Finally, the higher customer satisfaction is affecting the customer royalty.

• Information Systems Review
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• v.12 no.3
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• pp.49-73
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• 2010

The lack of customer satisfaction and trust remains a key barrier to electronic commerce. From the standpoint of online merchants, it is critical to build consumer trust by lessening sources of apprehensions and uneasiness associated with online transactions. This paper explores the relationships between customer satisfaction and intermediary's trustworthiness factors in B2C e-marketplaces. It also aims at examining the effects of consumer characteristics, including propensity to trust and Internet shopping self-efficacy, upon trust and purchase intentions. To meet the research objectives, an empirical study has been conducted by surveying 223 active e-marketplace buyers in Korea. The findings of the present research indicate that customer satisfaction positively affects all the three attributes of trustworthiness (i.e., competence, benevolence, and integrity), and more specifically it has a quite strong association with benevolence. In addition, propensity to trust has no significant influence on trust or purchasing intentions, and only affects benevolence and integrity with no direct effect on competence. Finally, Internet shopping self-efficacy was found to affect both trust and purchasing intentions, suggesting that e-marketplaces seek an online strategy designed to strengthen loyalty for customers with high self-efficacy, while they use a strategy to improve the usability and usefulness of their website to attract customers with low self-efficacy. The paper concludes with implications and directions for future research.

• Journal of Food Hygiene and Safety
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• v.23 no.3
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• pp.182-190
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• 2008

A survey on consumer's awareness and perception toward genetically-modified(GM) foods was conducted on 2110 random samples of Korean consumers. More than 65% of the respondents were exposed to some information related to GM foods. The respondents answered that the greatest benefit of the development of GM foods is remedy of potential food shortages in the future. More than 90% of Korean consumers wanted GM foods to be labeled as such. More than 50% of the respondents would not buy until they know more about GM foods. Only 35.8% of Korean consumers were found to know that food items originating from plants contained genes. More consumers responded that they would not buy herbicide-resistant GM soybean but buy vitamin-enriched GM soybean. Many Korean consumers' decision of acceptance or rejection of GM foods depend not on the basis of biotechnology, but on the basis of the degree of benefit to the consumers. Only 6.4% of Korean consumers responded that GM foods were the greatest threat to the safety of Korean foods. The perception of Korean consumers on GM foods has not changed significantly during the past 5 years.