• International Commerce and Information Review
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• v.15 no.4
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• pp.391-418
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• 2013

The development of web 2.0 technologies created the popularization of social media. People use social media for information communication with many purposes. Under such an environment, this paper examines the acceptance of word-of-mouth information dissemination through social media. The determinants of acceptance and the effect of acceptance on purchase intention as the result of information on social media pertaining to overseas tourism are researched in detail. The consumer choice for international travel involves a decision making with high uncertainty and thus people are using the word of mouth information strongly. Empirical analysis using SPSS, AMOS analysis software was performed on sample data consisting of 385 collected surveys. This paper shows the neutrality of eWOM, the professionalism of senders, and that the practicability of eWOM significantly affects the acceptance of the information. In addition, the acceptance of eWOM information has a significant effect on the spread of eWOM and customers' purchase intention. The paper shows that the practicability of information and the professionalism of word-of-mouth information should be improved.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.265-284
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• 2010

B2B e-commerce guarantee service is a guarantee service combining the electronic systems among Korea Credit Guarantee Fund(KCGF), banks and e-marketplaces to process all procedures on internet ranging from application for credit guarantee, issue of written guarantee and contracting for a commerce to payment. B2B e-commerce guarantee service plays as an intermediary role in financial support for small and mediumsized enterprise(SME), which are small size, low credit level, and unfavorable status in many aspects compared to major companies. Despite the B2B e-commerce guarantee service has various advantages conducive to promotion of e-commerce among small and medium businesses as well as development of e-commerce itself, it has yet to be diffused due to lack of acknowledgement, misunderstanding of its functions and vague psychological fear of the on-line settlement. Thus, this study identifies the values and effects of the B2B e-commerce guarantee service using financial data and cases. The process of this study is 4 phase. first phase is analysis of B2B e-commerce guarantee service and e-Marketplace. second phase is analysis of performance from the Perspective of Diverse Participants. third phase is analysis of economic performance and support for SME. last phase is policy suggestions and conclusion.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.123-136
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• 2017

The evaluation and analysis method of information system (IS) is studied from the system perspective, the user perspective, and the management viewpoint. The detailed analysis method performs qualitative evaluation by user questionnaire or expert opinion. In this study, Measures the productivity and the effect of building administrative information systems. In the previous study, qualitative productivity and universal effect indicators were used, but in this study, quantitative productivity indicators and indicators specific to administrative complaints were selected. KONEPS, an administrative service system, used electronic contract records and information recorded in the intermediate process. The information was converted into the number of days, and the productivity based on the input manpower was calculated. The effect analysis analyzed the questionnaire related to civil affairs, which is the goal of the administrative work system. Each factor was divided into reflective structural variable and formal structural variable, and internal consistency and multi-collinearity were diagnosed. In order to verify the model, the influence of the work was set as a hypothesis, the reliability was verified according to the descriptive statistics method, the influence was measured through the regression analysis, and the model was analyzed by the multiple regression model path coefficient. Model validation methods are Chi-square (df, p), RMR, GFI, AGFI, NFI, CFI and GFI as indicators according to CFA.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.127-137
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• 2017

The role of smartphones is changing from a communication system for exchanging calls and information into a universal platform for cultural services. Also, satisfaction for mobile application services on smartphones is a very important factor in the smart business. In This paper, we analyze the effects of the outcome, service scape, costs, and especially the impact of whether costumers having to pay or free for the app on customer satisfaction. For this purpose, we analyzed survey data on service quality of mobile app service from Chinese mobile app service users. We also analyzed the moderating effects of paid and free mobile app services. As a result, it was confirmed that the quality, servicescape quality and cost of mobile app service that customers perceive have a positive effect on customer satisfaction. In addition, the effect of the cost of mobile app service perceived by the customer on customer satisfaction showed that free mobile app service was more significant than paid mobile app service. This paper can be used as an alternative to monetization for providing a mobile app service provider or a mobile app service provider who wants to switch mobile app service from free to paid service.

• Journal of Korea Port Economic Association
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• v.30 no.4
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• pp.169-198
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• 2014

Due to the recent worldwide economic downturn, companies are required to put more effort into their innovation and quality improvement. In particular, business relationship is increasingly emphasized to be changed from a vertical relationship to a more horizontal relationship, such as collaborative partnership based on trust. In the logistics industry, through the collaboration, consignors can gain competitive advantages by focusing on their core capabilities, and freight forwarders also take advantages of securing stable cargoes and specialist expertise in distribution. Therefore, this study aims to identify key factors for developing a collaborative partnership between freight forwarders and consignors, and further examine the differences between the two groups empirically by using questionnaire survey. Based on the results, the main factors were found as follows: 1) Trust Building, 2) Competence Improvement, 3) Business Ecosystem and 4) Government Assistance. According to the analysis on sub-factors, first, among the four main factors, it turned out that trust is the most important variable. Specifically, the sub-factor of providing regular and stable service was revealed to be most critical. Second, it was found that forwarders need to improve services on 'Information Exchange System' and 'Electronic Data Interchange'. Finally, it is necessary for both consignors and forwarders to have better understanding of partnership. Key implications for both groups are highlighted based on the results.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.9-19
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• 2016

In finance literature, stock liquidity showing how stocks can be cashed out in the market has received rich attentions from both academicians and practitioners. The reasons are plenty. First, it is known that stock liquidity affects significantly asset pricing. Second, macroeconomic announcements influence liquidity in the stock market. Therefore, stock liquidity itself affects investors' decision and managers' decision as well. Though there exist a great deal of literature about stock liquidity in finance literature, it is quite clear that there are no studies attempting to investigate the stock liquidity issue as one of decision making problems. In finance literature, most of stock liquidity studies had dealt with limited views such as how much it influences stock price, which variables are associated with describing the stock liquidity significantly, etc. However, this paper posits that stock liquidity issue may become a serious decision-making problem, and then be handled by using data mining techniques to estimate its future extent with statistical validity. In this sense, we collected financial data set from a number of manufacturing companies listed in KRX (Korea Exchange) during the period of 2010 to 2013. The reason why we selected dataset from 2010 was to avoid the after-shocks of financial crisis that occurred in 2008. We used Fn-GuidPro system to gather total 5,700 financial data set. Stock liquidity measure was computed by the procedures proposed by Amihud (2002) which is known to show best metrics for showing relationship with daily return. We applied five data mining techniques (or classifiers) such as Bayesian network, support vector machine (SVM), decision tree, neural network, and ensemble method. Bayesian networks include GBN (General Bayesian Network), NBN (Naive BN), TAN (Tree Augmented NBN). Decision tree uses CART and C4.5. Regression result was used as a benchmarking performance. Ensemble method uses two types-integration of two classifiers, and three classifiers. Ensemble method is based on voting for the sake of integrating classifiers. Among the single classifiers, CART showed best performance with 48.2%, compared with 37.18% by regression. Among the ensemble methods, the result from integrating TAN, CART, and SVM was best with 49.25%. Through the additional analysis in individual industries, those relatively stabilized industries like electronic appliances, wholesale & retailing, woods, leather-bags-shoes showed better performance over 50%.

• Korean small business review
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• v.42 no.1
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• pp.43-56
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• 2020

The technology conflict between the U.S. and China is deepening recently. The U.S.-China battle began as a national security issue but is comprehending as a U.S.'s check for China's rapid technological advancement. China is rapidly growing in several indexes including R&D expenditure, patent application, and publications, and is challenging the U.S. in 5G and Artificial Intelligence. In 2018, Huawei became the largest 5G network/equipment provider and second largest smart phone manufacturer in the world. Now, Huawei is outperforming at AI chipset manufacturing, Bigdata analysis and cloud, positioning to become a critical player in the 4th industrial revolution. The purpose of this research is to analyze the effect of recent Huawei issues to Korean SMEs focusing on the relation between Huawei and Korean companies; the cooperation status from the Global Value Chain (GVC) perpsective, and Korean government's policies related to Huawei's information security issues will be the three main frames for the analysis. Then, this research proposes policy implications such as increasing Korea's competitiveness in manufacturing and information security.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.165-184
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• 2023

Recently, Deep learning analysis of unstructured text data using language models, such as Google's BERT and OpenAI's GPT has shown remarkable results in various applications. Most language models are used to learn generalized linguistic information from pre-training data and then update their weights for downstream tasks through a fine-tuning process. However, some concerns have been raised that privacy may be violated in the process of using these language models, i.e., data privacy may be violated when data owner provides large amounts of data to the model owner to perform fine-tuning of the language model. Conversely, when the model owner discloses the entire model to the data owner, the structure and weights of the model are disclosed, which may violate the privacy of the model. The concept of offsite tuning has been recently proposed to perform fine-tuning of language models while protecting privacy in such situations. But the study has a limitation that it does not provide a concrete way to apply the proposed methodology to text classification models. In this study, we propose a concrete method to apply offsite tuning with an additional classifier to protect the privacy of the model and data when performing multi-classification fine-tuning on Korean documents. To evaluate the performance of the proposed methodology, we conducted experiments on about 200,000 Korean documents from five major fields, ICT, electrical, electronic, mechanical, and medical, provided by AIHub, and found that the proposed plug-in model outperforms the zero-shot model and the offsite model in terms of classification accuracy.

• Information Systems Review
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• v.25 no.1
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• pp.1-26
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• 2023

Consumers tend to trust information provided by other consumers more than information provided by sellers. Therefore, while inducing consumers to write high-quality reviews is a very important task for companies, it is not easy to produce such high-quality reviews. Based on previous research on review writing and memory recall, we decided to develop a way to use digital nudge to help consumers naturally write high-quality reviews. Specifically, we designed an experiment to verify the effect of uploading a photo during the online review process on the quality of review of the review writer. We then recruited subjects and then divided them into groups that upload photos first and groups that do not. A task was assigned to each subject to write positive and negative reviews. As a result, it was confirmed that the behavior of uploading a photo first increases the review length. In addition, it was confirmed that when online users who upload photos first have extremely negative satisfaction with the product, the extent of two-sidedness of the review content increases.

• Information Systems Review
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• v.18 no.4
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• pp.69-88
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• 2016

Nowadays, organizations have adopted Smart Work to efficiently manage tasks, such as electronic document approval, customer management, and site inspection, without spatial-temporal constraints. Smartphones, which are commonly used in Smart Work, enable individuals to perform their jobs anytime and anywhere, thus blurring the boundary between work and non-work. To solve the problem of blurred work/non-work boundaries, a construct of self-control and affective factors needs to be considered because business style is changed from command to autonomy in the Smart Work context. Moreover, employees can convey their emotions easily over smartphones. Recent marketing studies have analyzed consumers' behavior based on the combination of cognitive, affective, and behavioral components, and researchers of information systems are also interested in these factors. However, previous research has some limitations, such as not classifying factors into cognitive, affective, and behavioral as well as not covering all three factors. Therefore, we explore the roles of cognitive, affective, and behavioral components in emotional exhaustion and education performance, and conduct a survey on undergraduate and graduate students, who are the major users of smartphones. Findings show that when individuals improve their cognitive capability (self-control) and usage experience (smartphone communication and internet usage), they can decrease emotional exhaustion and increase education performance. In the role of affective capability, increasing education performance is partially accepted. These results imply that organizations should not focus on controlling the usage of smartphones but on promoting appropriate smartphone usage.