• Asia pacific journal of information systems
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• v.23 no.4
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• pp.103-128
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• 2013

When a consumer needs a product or service and multiple sellers are available online, the process of selecting a seller to buy online from is complex since the process involves many behavioral dimensions that have to be taken into account. As a part of this selection process, consumers may set minimum trust expectation that can be used to screen out less trustworthy sellers. In the previous research, the level of consumers' trust expectation has been anchored on two important factors: product involvement and perceived risk. Product involvement refers to the extent to which a consumer perceives a specific product important. Thus, the higher product involvement may result in the higher trust expectation in sellers. On the other hand, other related studies found that when consumers perceived a higher level of risk (e.g., credit card fraud risk), they set higher trust expectation as well. While abundant research exists addressing the relationship between product involvement and perceived risk, little attention has been paid to the integrative view of the link between the two constructs and their impacts on the trust expectation. The present paper is a step toward filling this research gap. The purpose of this paper is to understand the process by which a consumer chooses an online merchant by examining the relationships among product involvement, perceived risk, trust expectation, and intention to buy from an e-tailer. We specifically focus on the mediating role of perceived risk in the relationships between enduring product involvement and the trust expectation. That is, we question whether product involvement affects the trust expectation directly without mediation or indirectly mediated by perceived risk. The research model with four hypotheses was initially tested using data gathered from 635 respondents through an online survey method. The structural equation modeling technique with partial least square was used to validate the instrument and the proposed model. The results showed that three out of the four hypotheses formulated were supported. First, we found that the intention to buy from a digital storefront is positively and significantly influenced by the trust expectation, providing support for H4 (trust expectation ${\rightarrow}$ purchase intention). Second, perceived risk was found to be a strong predictor of trust expectation, supporting H2 as well (perceived risk ${\rightarrow}$ trust expectation). Third, we did not find any evidence of direct influence of product involvement, which caused H3 to be rejected (product involvement ${\rightarrow}$ trust expectation). Finally, we found significant positive relationship between product involvement and perceived risk (H1: product involvement ${\rightarrow}$ perceived risk), which suggests that the possibility of complete mediation of perceived risk in the relationship between enduring product involvement and the trust expectation. As a result, we conducted an additional test for the mediation effect by comparing the original model with the revised model without the mediator variable of perceived risk. Indeed, we found that there exists a strong influence of product involvement on the trust expectation (by intentionally eliminating the variable of perceived risk) that was suppressed (i.e., mediated) by the perceived risk in the original model. The Sobel test statistically confirmed the complete mediation effect. Results of this study offer the following key findings. First, enduring product involvement is positively related to perceived risk, implying that the higher a consumer is enduringly involved with a given product, the greater risk he or she is likely to perceive with regards to the online purchase of the product. Second, perceived risk is positively related to trust expectation. A consumer with great risk perceptions concerning the online purchase is likely to buy from a highly trustworthy online merchant, thereby mitigating potential risks. Finally, product involvement was found to have no direct influence on trust expectation, but the relationship between the two constructs was indirect and mediated by the perceived risk. This is perhaps an important theoretical integration of two separate streams of literature on product involvement and perceived risk. The present research also provides useful implications for practitioners as well as academicians. First, one implication for practicing managers in online retail stores is that they should invest in reducing the perceived risk of consumers in order to lower down the trust expectation and thus increasing the consumer's intention to purchase products or services. Second, an academic implication is that perceived risk mediates the relationship between enduring product involvement and trust expectation. Further research is needed to elaborate the theoretical relationships among the constructs under consideration.

• Journal of the Korea Society for Simulation
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• v.28 no.4
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• pp.57-65
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• 2019

Recently, the Korean military has been drastically reducing its active-duty troops due to rapid demographic changes and the reconciliatory mode between the two Koreas. Under these circumstances, the wartime reserve forces play an important role. In times of war, a successful personal mobilization is critical especially in early combat stage. Previous research has been carried out using insufficient data collected only within the military and there have been limitations on empirical analysis due to changes in the designation methods for personal mobilization. This study analyzes how much of the reserve forces can be filled at the prescribed time by analyzing the transportation route of the reserve forces in wartime by utilizing military-related data and credit card usage data of the reserve forces residing in Yong-in city. The analysis showed that all reserve forces could not be called up within the prescribed time. In particular, Gangwon Province has shown results of less than 70 percent call-ups, and could cause serious weakening of combat capabilities in the early stages of the war. The main reasons could be the difference between the actual residence and the residence address and the excessive time caused by the traffic congestion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.101-112
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• 2017

The purpose of this paper is the comparative analysis of factors affecting the intention to use mobile payment services. This research compares the types of mobile payment services and different age groups. The result reveals that consumers' innovativeness has a positive impact on the intention to use mobile payment services in case of smartphone-only pay and compatibility and image have a positive effect on the intention to use mobile payment services in case of online pay. There is no significant influencing factor in the case of mobile app card. Moreover, the study reveals that consumers' innovativeness, trust in other domains, and compatibility positively affect the intention to use mobile payment services in the 30-49 age group. In the 50-69 age group, image has a positive impact and perceived risk has a negative impact on the intention to use mobile payment services. There is no significant influence factor in the 10-29 age group. This study is a first-time comparative analysis of factors affecting the intention to use mobile payment services focusing on the types of mobile payment services and different age groups.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.343-361
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• 2015

The financial industry in South Korea has witnessed a paradigm shift from selling traditional loan/deposit products to diversified consumption channels and financial products. Consequently, personification of financial services has accelerated and the value of finance-related personal information has risen rapidly. As seen in the 2014 card company information leakage incident, most of major finance-related information leakage incidents are caused by personnel with authorized access to certain data. Therefore, it is strongly required to confirm whether there are problems in the existing access control policy for personnel who can access a great deal of data, and to complement access control policy by considering risk factors of information security. In this paper, based on information of IT personnel with access to sensitive finance-related data such as job, position, sensitivity of accessible data and on a survey result, we will analyze influence factors for personnel risk measurement and apply data access control policy reflecting the analysis result to an actual case so as to introduce measures to minimize IT personnel risk in financial companies.

• Management & Information Systems Review
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• v.7
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• pp.21-51
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• 2001

For increasing the competitiveness and efficiency of Korea's finance industry under the new e-finance paradigm, this paper compared the practical use of finance portal site' on service parts and stage between Korea and U.S.A.. The services which can be served from site are banking, mortgage and credit loan, stock, card, retirement tax, PFM(Personal Finance Management), EBPP(Electronic Bill Presentment and Payment) and Account Aggregation and so on. The stage of site can be divided as the information provide stage which only gives information about service parts, on-line transaction stage which real-time transaction is possibile and PFM services provide stage according to development process. As a result, the beginning of finance portal service in Korea was lated about 10years and more than it of U.S.A. So the development stage of domestic portal site is still staying in the first step and the providing services and contents or business model development parts are also in the same stage than U.S.A. Resides, Korea's sites mainly focus on their first service parts even though they recently aim internet finance portal, and provide not real time transaction but finance information. On the other hand, the U.S.A. site support substantially not only various on-line transactions but also distinctive personal services like PFM(Personal Finance Management), EBPP(Electronic Bill Presentment and Payment), Account Aggregation and Trans-account, brokerage, education center, mortgage loan, mutual fund, option, pension fund and IPOs and so on. Thus, the site of Korea need to establish real type of internet finance portal which provides one-stop services on every type of finance to customers in the real time and also require the strategic integration among finance institutions. The next turn, they need to build information system and education center to give best satisfaction to customers and acquire customer information and marker environment changes and need to provide distinctive services to quality customers throughout database from this. Also the site should provide various type of banking services which refereed above like PEM, EBPP and education center etc, and the government of Korea should support the building of IT infrastructure to Physical, legal, systematic, sociocultural, technical and human resource sections. This paper provided the future movement direction of the domestic finance portal through comparison and analysis on the practical use of it between Korea and U.S.A. and also wanted to contribute for developing and reading of Korea finance portal in the new era of the finance paradigm.

• Archives of design research
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• v.17 no.3
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• pp.199-208
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• 2004

From the aspect that design should respond to the necessity of various cultural bases, design is important to be grafted to Korean traditional culture. This circumstance leads this study to clarify the plan of multimedia contents development of 'paintings and original forms of shaman spirit' in Korean shamanism as one of realistic re-illumination works for Korean cultural original forms. The main study results are conduded as followings through literature reviews, internet searches and case studies. First, 'the planning process' necessary for the development of scenarios, characters and multimedia contents are suggested based on the establishment of hierarchy structure among shaman spirits which are classified into necromancer, human being, nature and life after death. Second, relating to execution of process above, it is suggested that 'the strategic. plan by business items and its genres' such as blessing fancy goods, characters for mobile or game, scenarios for game or animation, online digital exorcisms, e-cards, e-talismans and so on. Finally, as future industrialization concerns, 'the industrial development plan' is suggested which can be extended to scenario-based original businesses such as game scenarios for online or mobile and heroism fictions. The study results highlight the fact that multimedia design approach are considered for expanding the target and scope of creative material for Korean cultural original forms. Future researches, based on the results of the study, are expected to be expanded to the various designerly-thinking approaches into 'Shaman' themes and rather to be re-illuminated to the development of Korean cultural original forms as a nation's strategic standpoint.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.648-655
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• 2019

This paper proposes the differential development of a Taekwondo electronic body protector. For this development, the most suitable sensor system was selected after analyzing and testing various sensor methods (magnetic sensors, electric capacity sensors, contact switch sensors, and piezo-film sensors) that could be applied in the electronic body protector, the selected sensors were distributed to the body and feet to make a more precise hit score, unlike the existing system in which all sensors are centralized on the body. Furthermore, it aims to illuminate using a lightweight film-type piezoelectric sensor on the body protector. In the case of an existing electronic body protector, all sensors and network device were concentrated on the body protector, so users need to purchase a set if they want it. On the other hand, the proposed system cloud can be used individually using a smart scoring WEP program. The effects of decreasing weight by up to 20% were compared with those of the existing system. Setting up a test facility is very difficult, so more study will be needed to analyze the effects of a hit.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.21-30
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• 2023

The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.96-107
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• 2023

The objective of this study is to explore future issues that Chinese users, who have the highest mobile payment service usage rate in the world, will be most interested in. For this purpose, after collecting text data from a Chinese SNS site, it classifies major keywords into 4 types of future signals by using Keyword Emergence Map (KEM) and Keyword Issue Map (KIM). Furthermore, to understand the four types of signals in detail, it performs the qualitative analysis on text related to each signal keyword. As a result, it finds that the strong signal, which is rapidly growing in keyword appearance frequency during this research period, includes the keywords related to the daily life of Chinese people, such as buses, subways, and household account books. Additionally, it find that the signal that appears frequently now, but with a low increase rate, includes various services that can replace cash payment, such as hongbao (cash payment) and bank cards. The weak signal and latent signal, which appear less often than other two signals, includes the keywords related to promotion events or changes in service regulations. Its result shows that the mobile payment services greatly have changed user's daily life beyond providing convenience. Furthermore, it shows that, in the Chinese market, in which card payment is not common, the mobile payment services have the great potential to completely replace cash payment.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.