• Journal of Korea Port Economic Association
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• v.34 no.4
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• pp.141-160
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• 2018

In this paper, to analyze the perception and response strategy of Korean ship owners on Global Sulphur Cap 2020, examined the IMO environmental regulation status focusing on MARPOL Annex VI regulation about air pollution prevention, technological measures to reduce SOx emission, shipping industry and management status of Korean ship owners. First of all, the questionnaire was conducted for Korean ship owners after selecting the evaluation factors. The purpose of this study was to investigate the difference of the perception and response strategy of Korean ship owners by corporation size and main vessel type using frequency and cross analysis. It is confirmed that various researches on SOx emission reduction have been carried out from various points of view at home and abroad. In this study, existing studies related to technical factors for regulatory response and economics analysis were examined and evaluation factors were selected. As a result of analysis, it is found that large-sized shipping companies are more prepared for regulatory response than small and medium-sized bulk carrier owners. There were similar perception and the direction of response strategy about the impacts by corporation size and main vessel type. In about two years to be implemented in 2020, It is necessary to find an appropriate response strategy based on the support policy of the government and related organizations and the systematic analysis of the ship owners. Through this study, although the difference between the perception and response strategy of the ship owners by corporation size and main vessel type was understood, it was found that there were limitations on specific response strategy and corporate data collection. In future research, we should overcome the limitations of this study and conduct an in-depth study.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Asia Marketing Journal
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• v.11 no.3
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• pp.185-203
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• 2009

Yuhan Kimberly, a joint-venture company of Korean Yuhan Company and American Kimberly-Clark, opened a premium diaper market in Korea by launching Pull-Ups which was pants-typed diapers in 1993. Pull-Ups was imported as finished goods from Kimberly-Clark. However, in spite of its huge market share in United States, it failed to land down in Korean market because of wrong positioning strategy which did not consider domestic customers' tastes. In 1996, Yuhan-Kimberly brought out a pants-typed diaper, Huggies-Toddler, to Korean market again. This paved the way for the combination of Kimberly-Clark's production power and Yuhan-Kimberly's marketing power and led to launch new product superior to Pull-Ups. However, this product was unsuccessful in the market because of wrong positioning which did not catch domestic customer's life styles such as cultural, environmental and habitual differences in toilet training, the cost increase coming from IMF crisis in Korea, weak trust within the company, weak trust within the company, and too much higher price than regular diapers. In 2005, Yuhan-Kimberly redeveloped new pants market business strategy. It was organically combined with winning product development plan, winning communication strategy and the market structure change through the pants market creation. Customer's habit, usage and attitude were studied with total 55 times market investigations. Also, all processes from planning to designing were executed in the customer's view by investigating product research, positioning research and advertisement research. Yuhan-Kimberly repositioned new product as a wearing diaper not as a toilet training diaper and launched Huggies Magic Panty as a premium product which had 25% higher price than previous Huggies. Huggies Magic Panty was recognized as a great hit product in domestic diaper market and the sales recorded 37.6 bill won in 2006, 57.2 bill won in 2007, and 90 bill won in 2008 since launching in 2005. The reason of Huggies Magic Panty's success was the repositioning strategy deduced from the precise check of customer's usage habit. It was the winning strategy of Huggies that were market investigation in order to survive in domestic baby goods market where a lot of companies struggled intensively, the exact positioning based on its market investigation and aggressive 360 degree communication strategy to give customers impressions efficiently.

• Asia Marketing Journal
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• v.11 no.4
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• pp.95-119
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• 2010

Although there have been many studies regarding the inconsistency between consumers' attitudes and behavior, prior research has almost exclusively focused on the relationship between the attitude before behavior and the initial behavior. Relatively little research has been conducted on consumer satisfaction after purchase and post-purchase behavior. This research proposed that the relationship between satisfaction and post-purchase behavior is moderated by consumers' psychological characteristics such as need for cognitive closure(NCC) and temporal self-construal(SC). The need for cognitive closure refers to individuals' desire for a firm answer to a question and an aversion toward ambiguity. We assumed the need for cognitive closure as a major moderating variable because it is judged that the requirement for cognition clearly varies between when a consumer repurchases the same product and seeks a new alternative. Individuals who tend to end cognition due to time constraints or inappropriate conditions may display considerable cognitive impatience or impulsivity and has a higher probability in repurchasing the same product than a consumer without such limitations. They would avoid further consideration for new alternatives and the likelihood of the repurchase for prior alternative would increase. As hypothesized, significant moderating effect of the NCC was confirmed. This result gives a significant implication for a corporate to establish effective marketing strategies. For a corporate or product brand that has been occupying the market after entering the market earlier, it would be effective to maintain need for cognitive closure high in the existing consumers and thereby preventing the consumers from being interested in the new alternatives. On the other hand, new brands that have just entered the market need to lower the potential consumers' need for cognitive closure so that the consumers can be interested in new alternatives. Along with need for cognitive closure, temporal self-construal also turned out to moderate the satisfaction-repurchase. temporal SC reflects the extent to which individuals view themselves either as an individuated entity or in relation to others. Consumers under a temporarily independent SC would repurchase former alternative again according to their prior satisfaction and evaluation. In contrast, consumers in temporal interdependent SC tended to switch to a new alternative because they value interpersonal relationships above anything else and have a tendency to rely heavily on in-group opinions. When they are confronted with additional opinions, it is highly probable that he/she will choose a new product as an alternative. By proving the impact that temporal self-construal has on repurchasing behavior, this study is providing the marketers with new standards for establishing successful promotional strategies. For example, if the buyer and the user is the same for a product, it would be effective for the seller to convince the consumer to make decision subjectively by encouraging temporal independent self-construal. On the contrary, in the case where the purchase is made by an individual but the product is consumed by a group of people. For example, a housewife is more likely to choose the products or brands that her husband or children prefer rather than the ones that she likes by herself. In that case, emphasizing how the whole family can be satisfied and happy about the product would be effective for promoting repurchase.

• Information Systems Review
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• v.25 no.4
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• pp.131-159
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• 2023

Recently, amidst the backdrop of the COVID-19 pandemic shifting towards an endemic phase, there has been a rise in discussions and debates about the future of the metaverse. Simultaneously, major metaverse platforms like Roblox have been launching services integrated with generative AI, and Apple's mixed reality hardware, Vision Pro, has been announced, creating new expectations for the metaverse. In this situation where the outlook for the metaverse is divided, it is crucial to diagnose the metaverse from an ecosystem perspective, examine its key ecological features, driving forces for development, and future possibilities for advancement. This study utilized Wang's (2021) Information Ecology Theory (IET) framework, which is representative of ecosystem research in the field of Information Systems (IS), to derive the Metaverse Industrial Ecosystem (MIE). The analysis revealed that the MIE consists of four main domains: Tech Landscape, Category Ecosystem, Metaverse Platform, and Product/Service Ecosystem. It was found that the MIE exhibits characteristics such as digital connectivity, the integration of real and virtual worlds, value creation capabilities, and value sharing (Web 3.0). Furthermore, the interactions among the domains within the MIE and the four characteristics of the ecosystem were identified as driving forces for the development of the MIE at an ecosystem level. Additionally, the development of the MIE at an ecosystem level was categorized into three distinct stages: Narrow Ecosystem, Expanded Ecosystem, and Everywhere Ecosystem. It is anticipated that future advancements in related technologies and industries, such as robotics, AI, and 6G, will promote the transition from the current Expanded Ecosystem level of the MIE to an Everywhere Ecosystem level, where the connection between the real and virtual worlds is pervasive. This study provides several implications. Firstly, it offers a foundational theory and analytical framework for ecosystem research, addressing a gap in previous metaverse studies. It also presents various research topics within the metaverse domain. Additionally, it establishes an academic foundation that integrates concept definition research and impact studies, which are key areas in metaverse research. Lastly, referring to the developmental stages and conditions proposed in this study, businesses and governments can explore future metaverse markets and related technologies. They can also consider diverse metaverse business strategies. These implications are expected to guide the exploration of the emerging metaverse market and facilitate the evaluation of various metaverse business strategies.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.17-30
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• 2022

The purpose of this study is to analyze the impact of the characteristics of start-up CEOs on the performance of investment attraction from the perspective of Series A investment. The results of the study are as follows. First, when the educational level of start-up CEOs was high and startup CEOs had start-up experience and investment attraction experience, venture investors such as venture capital had a significantly positive (+) effect on the investment for start-ups. This was systematically significantly positive even when control variables were introduced. When start-up CEOs had work experiences, there was no significantly positive effect on the total investment amount for start-ups but a significantly positive (+) effect on the average investment amount. Second, the standardization coefficient of total investment amount was larger in the case of start-up experience than that in the case of investment attraction experience while the standardization coefficient of average investment amount was larger in the case of investment attraction experience than that in the case of start-up experience. This suggests that the start-up experience is important for the total investment amount while the investment attraction experience is important for the average investment amount. Third, when the sales of start-ups were high at the time of Series A investment, the total investment amount and the average investment amount were also significantly high. Even if early start-ups are less profitable or have losses, the start-ups with a certain level of sales seem to be attractive investment targets for venture capital. The results of this study are useful for the investment decisions of venture capital and the financing strategies of start-ups. The implications for pre-CEOs preparing for start-ups art that the total amount of investment will increase if they have expertise through degree acquisition, challenge start-ups, gain start-up experience and implement investment attraction. Even if CEOs of start-ups do not have start-up experience, the average amount of investment for start-ups can increase if they have work experience in related industries.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.115-125
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• 2022

In today's era when the concept of a lifelong job has disappeared, starting a business is an essential consideration for university students not only as an alternative factor in finding employment, but also from the perspective of the entire life. Today, most universities in Korea are operating entrepreneurship education programs, such as entrepreneurship classes as a curriculum, and start-up clubs as a non-curricular program to foster entrepreneurship among university students. In previous studies, entrepreneurship is a factor influencing the entrepreneurship intention. The purpose of this study is to empirically examine the effects of university students' entrepreneurship and the entrepreneurship intention through a entrepreneurship education program (participation in a start-up club, taking an entrepreneurship course) on entrepreneurship behavior. There are some empirical studies on whether entrepreneurship education programs such as participation in startup contests affect the entrepreneurship intention of university students, but not much compared to their importance. It is difficult to find an empirical study examining the effects of entrepreneurship and start-up education programs on entrepreneurship intention and entrepreneurship behavior in domestic and foreign studies. Therefore, in this study, one domestic university that operates a start-up club and a entrepreneurship course was selected and the online questionnaire was distributed to all current students, and the collected 127 questionnaires were used for empirical analysis As a result of the study, first, it was confirmed that initiative and risk-taking, which are sub-factors of entrepreneurship of university students, had a significant positive effect on entrepreneurial intention, respectively, and that innovation did not have a significant positive effect. Second, it was confirmed that university students' participation in a start-up club, a sub-factor of the start-up education program, had a significant positive effect on their entrepreneurial intention, and that taking a start-up course did not have a significant positive effect. Third, it was confirmed that the entrepreneurial intention of university students had a significant positive effect on entrepreneurship behavior. Fourth, it was confirmed that the entrepreneurial intention had a mediating effect between each of the factors of risk-taking, and participation in a start-up club and entrepreneurial behavior. This study suggests that university students can increase their risk-taking, increase their entrepreneurial intention by participating in a startup club, and reach a entrepreneurial behavior through this as a medium.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.285-301
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• 2020

Looking at the problem of aging in the nation from a demographic perspective, it is not a problem of the overall population, but of the structure of the population. It is the baby boomer and post-baby boomers, the largest population in the country. Baby boomers were born between 1955 and 1963, and currently have a population of 7001,333, which is 13.6 percent (as of 2015). The Post-Baby Boomer generation was born between 1964 and 1974, with a total population of 9,567,171, accounting for 18.8 percent of the total population. In particular, baby boomers and post-baby boomers (32.4% of the total population) have begun to retire or will retire soon. The average life expectancy continues to increase due to the development of medical technology, and the falling birth rate of newborns and the declining population of the production population are darkening the domestic economy. In a policy proposal aimed at easing the nation's falling economic growth rate, women's participation rate is as high as Sweden and men's efforts to increase it as high as Japan's, while the elderly rate is desirable to maintain Korea's high level. This is because the expansion of the elderly generation's participation in economic activities could ease a sharp drop in economic growth and reduce the burden of supporting the elderly population. The study, based on this social problem awareness and problem solving plan, looks at the relationship between career orientation and satisfaction in start-up education based on the diverse career base of active seniors, and also suggests the importance of customized start-up education on the diversity of active seniors by clarifying the relationship between them, and suggests the desirable direction of senior start-up policy design, funding, and start-up education. Based on the theoretical background, the concept of five factors was defined: active senior, career-oriented, satisfaction level of start-up education, willingness to start a business, and the concept definition of an active senior, which is particularly key to the baby boomers in their 50s and 60s, is generally regarded as a source of consumption or welfare benefits, but in this study, the concept of active start-up is reflected in the domestic start-up market by young people in their 40s, 50s and 60s. As a result of a hypothesis test. Hypothesis 1 and Hypothesis 5: Career orientation has been verified to affect the willingness to start a business and the behavior of preparation for a start-up. Hypothesis 3: The willingness to start a business has been verified as having an effect between startup preparation actions. Hypothesis 4: The satisfaction level of start-up education has been verified to affect start-up preparation behavior. However, hypothesis 2: The satisfaction level of education for start-ups does not affect the willingness to start a business. Such results can be inferred that satisfaction in start-up education does not have a direct effect on the will to start a business and increases the will to start a business through the influence of personal career orientation.

• Cartoon and Animation Studies
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• s.41
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• pp.455-486
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• 2015

The 3D printing technology, which started from the patent registration in 1986, was a technology that did not attract attention other than from some companies, due to the lack of awareness at the time. However, today, as expiring patents are appearing after the passage of 20 years, the price of 3D printers have decreased to the level of allowing purchase by individuals and the technology is attracting attention from industries, in addition to the general public, such as by naturally accepting 3D and to share 3D data, based on the generalization of online information exchange and improvement of computer performance. The production capability of 3D printers, which is based on digital data enabling digital transmission and revision and supplementation or production manufacturing not requiring molding, may provide a groundbreaking change to the process of manufacturing, and may attain the same effect in the character merchandise sector. Using a 3D printer is becoming a necessity in various figure merchandise productions which are in the forefront of the kidult culture that is recently gaining attention, and when predicting the demand by the industrial sites related to such character merchandise and when considering the more inexpensive price due to the expiration of patents and sharing of technology, expanding opportunities and sectors of employment and cultivating manpower that are able to engage in further creative work seems as a must, by introducing education courses cultivating manpower that can utilize 3D printers at the education field. However, there are limits in the information that can be obtained when seeking to introduce 3D printers in school education. Because the press or information media only mentions general information, such as the growth of the industrial size or prosperous future value of 3D printers, the research level of the academic world also remains at the level of organizing contents in an introductory level, such as by analyzing data on industrial size, analyzing the applicable scope in the industry, or introducing the printing technology. Such lack of information gives rise to problems at the education site. There would be no choice but to incur temporal and opportunity expenses, since the technology would only be able to be used after going through trials and errors, by first introducing the technology without examining the actual information, such as through comparing the strengths and weaknesses. In particular, if an expensive equipment introduced does not suit the features of school education, the loss costs would be significant. This research targeted general users without a technology-related basis, instead of specialists. By comparing the strengths and weaknesses and analyzing the problems and matters requiring notice upon use, pursuant to the representative technologies, instead of merely introducing the 3D printer technology as had been done previously, this research sought to explain the types of features that a 3D printer should have, in particular, when required in education relating to the development of figure merchandise as an optional cultural contents at cartoon-related departments, and sought to provide information that can be of practical help when seeking to provide education using 3D printers in the future. In the main body, the technologies were explained by making a classification based on a new perspective, such as the buttress method, types of materials, two-dimensional printing method, and three-dimensional printing method. The reason for selecting such different classification method was to easily allow mutual comparison of the practical problems upon use. In conclusion, the most suitable 3D printer was selected as the printer in the FDM method, which is comparatively cheap and requires low repair and maintenance cost and low materials expenses, although rather insufficient in the quality of outputs, and a recommendation was made, in addition, to select an entity that is supportive in providing technical support.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.