• Knowledge Management Research
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• v.22 no.3
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• pp.273-293
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• 2021

Due to the COVID-19 pandemic, the size of the e-commerce has been increased rapidly. This pandemic, which made contact-less communication culture in everyday life made the e-commerce market to be opened even to the consumers who would hesitate to purchase and pay by electronic device without any personal contacts and seeing or touching the real products. Consumers who have experienced the easy access and convenience of the online purchase would continue to take those advantages even after the pandemic. During this time of transformation, however, the size of information source for the consumers has become even shrunk into a flat screen and limited to visual only. To provide differentiated and competitive information on products, companies are adopting AR/VR and steaming technologies but the reviews from the honest users need to be recognized as important in that it is regarded as strong as the well refined product information provided by marketing professionals of the company and companies may obtain useful insight for product development, marketing and sales strategies. Then from the consumer's point of view, if the ratings of reviews are widely diverged how consumers would process the review information before purchase? Are non-converged ratings always unreliable and worthless? In this study, we analyzed how consumer's regulatory focus moderate the attitude to process the diverged information. This experiment was designed as a 2x2 factorial study to see how the variance of product review ratings (high vs. low) for cosmetics affects product attitudes by the consumers' regulatory focus (prevention focus vs. improvement focus). As a result of the study, it was found that prevention-focused consumers showed high product attitude when the review variance was low, whereas promotion-focused consumers showed high product attitude when the review variance was high. With such a study, this thesis can explain that even if a product with exactly the same average rating, the converged or diverged review can be interpreted differently by customer's regulatory focus. This paper has a theoretical contribution to elucidate the mechanism of consumer's information process when the information is not converged. In practice, as reviews and sales records of each product are accumulated, as an one of applied knowledge management types with big data, companies may develop and provide even reinforced customer experience by providing personalized and optimized products and review information.

• The Korean Journal of Archival Studies
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• no.23
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• pp.141-178
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• 2010

The Administration of Labor was responsible for the technical and practical functions like policy-making of labor matters and implementing the relevant laws. However, there has been a few record transferred to the National Archives to help find out the labor policy-making process. This is one of the typical examples that shows the discontinuity and unbalance, and disorderly filing of the administrative records in Korea. Naturally it is almost impossible to retrieve the appropriate content through the records file-name. Users should be at the trouble to compare the record items and their content one by one. For the re-organization of the Administration of Labor' records, this research suggests the four-level analysis of functions of the Administration. The Administration of Labor' survived records could be linked to each level function. And the publication of the 'Records Abstract Catalog' providing users with more information about the records would pave the way for easier access to the records. In addition, it also suggests the logical re-filing of the survived records of which we cannot find the order or sequence. This re-organization of the survived records would help to establish the acquisition and appraisal policy of the labor records as well as the new way of description and finding tool hereafter. Drawing up labor history map is a starting point for the acquisition strategy of the labor records, which could allow users to gain systematic access on the survived records. Of course, extensive investigation and research on the survived records is a prerequisite for the map. It would be required to research on the survived records of the other government agencies, including economic-social area ministries and investigation agencies and the National Assembly as well. It is also needed to arrange and typify the significant incidents and activities on thematic and periodic frames in the labor history. If possible to understand or connect the survived records and these accomplishments comprehensively, it would be of great help for the acquisition of the labor records and the related oral records projects.

• Journal of Venture Innovation
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• v.5 no.4
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• pp.109-115
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• 2022

As the 4th industrial revolution progresses, foreign countries are promoting smart manufacturing innovation through digital transformation as a priority task early on to secure a competitive edge in the manufacturing industry. In response, the Korean government is also promoting a policy to enhance the competitiveness of small and medium-sized manufacturing companies by promoting digital transformation in the corporate sector to meet the global trend of the 4th industrial revolution era. Manufacturing powerhouses such as Germany and Japan see manufacturing as a key sector in digital transformation and are leading related policies, while emerging countries such as China are also promoting manufacturing innovation strategies such as building digital infrastructure and creating a digital innovation ecosystem. Korea is promoting the 'Korean-style smart factory dissemination and expansion strategy' by transforming Germany's manufacturing innovation strategy for smart factory supply to suit the domestic situation. However, the policy to supply smart factories so far has been conducted with support from individual companies under the leadership of the government, and most of the smart factories are at the basic level, and it is evaluated that there are limitations such as the lack of manpower to operate smart factories. In addition, while the current policy focuses on expanding the supply of smart factories in SMEs, it is necessary to establish a smart manufacturing system through linkages between large and small businesses in order to achieve the original goal of establishing a smart manufacturing system. Therefore, it can be said that from the standpoint of small and medium-sized enterprises (SMEs), who are consumers of smart factories, it can be said that the digital transformation policy can achieve the expected results only when appropriate incentives are provided for the introduction of smart factories in a situation where management resources such as funds, technology, and human resources are lacking. In addition, it is judged that the uncertainty of the performance of digital investment always exists, and as long as large and small companies are maintained as an ecosystem of delivery and subcontracting, there is very little incentive for small and medium-sized manufacturing companies to voluntarily invest in or advance digital transformation. Therefore, the digital transformation policy of small and medium-sized manufacturing companies in the future has practical significance in that it suggests that there is a need to seek ways to attract SMEs' digital-related voluntary investment.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• 대한공업교육학회지
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• v.38 no.2
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• pp.48-67
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• 2013

This study tried to suggest implications about operation direction of specialized high schools (SHS) by researching awareness of middle school students (MSS), school parents (SP), human resources directors in industrial institutions (HRDII) who will be the main users of SHS education, about entering SHS and career after graduating from SHS. Seniors of middle school, SP and HRDII in Asan, Chungnam were the subject of this survey research. The summary of the result of this study is as follow: First, MSS and SP usually hoped to enter general high schools rather than vocational education schools such as SHS, meister high schools, and MSS considered school records and SP considered aptitude and talent for the factors to choose high school. Second, MSS, SP, and HRDII recognized purposes of SHS as improvement of talent and aptitude, and getting a job. As for positive images of SHS, they recognized it as applying talent and aptitude to life early, getting good jobs easily, fast independence after graduation, and learning excellent technologies, and as for negative images of SHS, they recognized it as social prejudices and discrimination, students with bad school records enter them, disadvantages about promotion and wages, and being unfavorable for entering universities. They also recognized education of SHS as being effective for improvement of basic and executive ability and key competency, development of creative human resources, and improvement of right personality and courteous manners. Third, many MSS and SP showed intention to enter SHS if it is established in Asan. They wished to enter SHS because they would like to apply their aptitude and talent to life early, learn excellent skill, and hope for early employment, on the other hand, they did not wish to enter SHS because it was not suited for their aptitude and talent, awareness about SHS is low, it is unfavorable to enter universities, and there were social prejudices and discrimination. They also similarly hoped for getting jobs and entering universities after graduating from SHS. And the reason they wanted to get a job was usually because they want to be successful by advancing into society early, or because it is still hard to get a job even after graduate from the university, on the other hand, the reason they want to enter university is because is usually in-depth education about major and social discrimination about level of education. The ability to perform duties forms the greatest part of the employment standard that MSS, SP, and HRDII aware. MSS and SP usually hoped for industrial, home economics and housework and commercial majors in SHS, and considered aptitude and talent, the promising future, and being favorable for employment for choosing major. The reason HRDII hire SHS student was to develop student into talent of industrial institution, ability of student, and need for manpower with high school graduation level, and there were also partial answer that they can hire SHS student if they have ability to perform duties. The proposals about operation direction of SHS according to the results above are as follow: SHS should diversify major and curriculum to meet various requirements of student and parents, establish SHS admission system based on career guidance, and improve student's ability to perform duties by establishing work-based learning. The Government should organize work-to-school policy to enable practical career development of students from SHS, and promote relevant policy to reinforcing SHS education rather than quantitative evaluation such as employment rate, and cooperative support from each government departments is required to make manpower with skill related to SHS to get proper evaluation and treatment.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.55-78
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• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

• 대한공업교육학회지
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• v.38 no.2
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• pp.89-113
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• 2013

The study started from the point that learners should be basically equipped to quickly respond to changes in demand for future human resources efficiently and effectively, and an attitude to take part in learning voluntarily should thus be cultivated. To this end, the author applied the TAI model based on a module as a class strategy to solve problems related to several classes occurred in specialized high schools. This application of the TAI model was also motivated by the necessity for designing an appropriate teaching-learning method that encourages improvement of self-learning capacity, consistent learning motivation, and willingness rather than external factors. Through this work, the author aims to heighten the interest of learners and improve endurance in learning. The study results are as follows. First, the learning unit was structuralized as a module and then learning stages were proceeded with so that capacity to adapt to learning would improve. The achievement standard (learning goal) was structuralized in a module type by analyzing and reorganizing the textbook considering the link between the actual practice field and a curriculum based on subject characteristics. Through the process of module type learning stages, the student's capacity to ascertain characteristics of units and to adapt to learning both improved. Second, through application of a TAI model based on a module, Self-Directed Learning capacity and capacity to adapt to a new field improved. By applying the module, Self-Directed Learning could be accomplished more effectively than in the existing passive learning environment. By grafting cooperative learning of the TAI model, students had greater interest and achievement in classes, self-confidence and community consciousness, and an opportunity to broaden their thinking. In particular, improvement of self-confidence is effective in cultivating the capacity required in industrial society to transcend the learning of simple functions and knowledge, as well as the capacity to adapt to new environments. Third, by solving tasks focused on fields related to industrial sites, not only actual survey capacity but also additional capacity to identify and solve tasks through various experiences improved. Furthermore, it was helpful for students to have interest and motivation about their own life and learning to cultivate the qualities and capacity to adapt to the working world where new knowledge and technology rapidly change. Fourth, by applying a standard-based assessment system for technical subjects introduced in 2012 to model design for learning plans, clearer and more objective assessment criteria were arranged, and individual learning through instruction at each achievement level could be accomplished. This improved achievement level of individual learners was helpful in reaching achievement goals at specific levels by overcoming the disadvantages of cooperative learning in each group.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.1-24
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• 2021

The Korean government is currently expanding the business startup incubator support program and funds for new ventures with innovative technology in order to spread the second venture boom. However, despite the fact that entrepreneurial education and mentoring that entrepreneurs should have are important parts for the sustainable growth of the startup, some companies selected for government support programs are reluctant to participate in programs such as entrepreneurship education and mentoring for the sole purpose of funding commercialization. This research addressed the effects of entrepreneurial alertness with opportunity awareness as its medium and the small business mentoring service along with the number of times the mentoring has taken place, on the corporate performances. The results of empirical research are as follow: the first one is that scanning-search and evaluation-judgment can influence a company's performance (financial, non-financial) through opportunity recognition, with the exception of association-connection, which is a sub-factor of entrepreneurial alertness. Secondly, it was found to affect a company's financial and non-financial performance through opportunity recognition for financing mentoring, technical support mentoring, and management support mentoring. Thirdly, it was found that the number of mentoring also affects the financial and non-financial performance of a company through opportunity recognition. The implications of this study are that it should be revisited that program managers consider rooms that do not violate the startup founder's strategic decision-making opportunities when designing and operating the program as entrepreneurial alertness sub-factor association-connection does not affect corporate performance through opportunity recognition. This study also emphasizes the need for customized mentoring to meet the outcome goals of each startup, as it has been empirically clarified that the mentoring provided to the startup by the government's support is important. The contribution of this research is that entrepreneurial alertness and opportunity recognition that are treated as important components in research for entrepreneurship, and the factors of mentoring and mentoring frequency that are recognized as important elements in the practical aspect of startup business are clarified theoretically and empirically as an influential factor in corporate performance. And this study also provide a rationale for the startup business support agency supplying mentoring.

• The Korean Society of Law and Medicine
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• v.22 no.4
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• pp.3-35
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• 2021

Inmitten der Flut der privaten und öffentlichen Information gilt die riesige Informationsmenge als Schlüsselressource im Zeitalter der 4. industriellen Revolution, repräsentiert durch Big-Data. Das Interesse an diesen wächst weltweit. Es gibt eine aktive Diskussion darüber, wie man Daten sichert und akkumuliert und wie man die gesammelten Daten sicher und effektiv nutzt. Gesundheitsdaten werden vor allem als die wertvollste Ressource bewertet, für die Big-DataTechnologie eingesetzt wird. Um Gesundheitsdaten sinnvoll zu nutzen, müssen verteilte Gesundheitsdaten integriert und den Benutzern in einer Form zur Verfügung gestellt werden, die für Forschung oder Inspektion verwendet werden kann. In einer Situation, in der große Länder um den Aufbau bzw. die Führung der Datenwirtschaft konkurrieren, wurden im August 2020 auch in Südkorea die sog. „3-Daten-Gesetze" geändert, die das Datenschutzgesetz(DSG) enthälten. Das DSG führte das Konzept der pseudonymen Informationen ein und baute eine Rechtsgrundlage für deren Verwendung auf. Als Folgemaßnahme kündigte die, Kommission für den Schutz personenbezogener Daten(Personal Information Protection Commission: PIPC)' die „Richtlinien für die Bahandlung mit pseudonymen Informationen" und, Ministerium für Gesundheit und Wohlfahrt' die „Richtlinien für die Verwendung von Gesundheitsdaten" an. Gesundheitsdaten stehen direkt in Zusammenhang mit Leben und Körper des Menschen und damit enthalten viele sensible Daten. Es handelt sich also um ein System, das aus einer vorsichtigeren und konservativeren Sicht unter der Voraussetzung verwendet werden kann, personenbezogene Daten sicherer zu schützen. Um die Hauptinhalte der „Richtlinien für Verwendung von Gesundheitsdaten" zu analysieren, überprüften wir zunächst die Hauptinhalte des überarbeiteten DSG. Danach durch die Analyse der wesentlichen Inhalte der „Richtlinien für Verwendung von Gesundheitsdaten" wurden Probleme wie Konflikte mit anderen Gesetzen und Verbesserungsmaßnahmen überprüft.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.