• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.644-660
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• 2016

With the development of Fintech industry, research interest in crowdfunding is growing. Crowdfunding, originated from crowdsourcing, involves the participation of many individuals' contributions to funding a new project. Specifically, lending based crowdfunding provides a platform for raising funds in the form of loans by connecting borrowers to funders(investors) via Internet, not through traditional financial institutions. Recently, lending based crowdfunding attracts much attention as a new investment alternative; however, there is a lack of research about lending based crowdfunding. This study aims to examine the factors influencing an investor's participation in lending based crowdfunding by focusing on platform features, investor features, and project features. Based on the findings, this study discusses theoretical and practical implications for promoting the crowd's investments through crowdfunding platforms.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.229-235
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• 2021

Blockchain, recognized as one of the core technologies of the 4th industrial revolution, is an Internet-based distributed data management system which does not require centralized control. Blockchain is characterized by the integrity and reliability of information, and blockchains can be used where such characteristics are required. Typical applications of blockchain include finance, transaction, and evaluation management. In this paper, we designed a blockchain-based evaluation management system that allows users to freely create and manage evaluation instances. Evaluation managers can create an evaluation instance according to their purpose and allocate evaluation items and evaluators. When the evaluators finish evaluating the evaluation items, the evaluation manager can aggregate the evaluation results for the instance. Someone, who want to perform evaluation for various purposes but do not have an evaluation system, can implement the evaluation system relatively simply by using this system. In addition, due to the characteristic of the blockchain, evaluators cannot modify the evaluation scores they have already recorded, and neither the system administrator nor the evaluation administrator can modify the evaluation scores. For this reason, the reliability of the evaluation increases.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.130-145
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• 2023

The digital transformation of finance is accelerating, and digital banking has already become a major banking channel. Banks have traditionally placed importance on CRM(Customer Relationship Management) and have tried to retain their loyal customers, who contribute significantly to the bank, such as long-term transactions, holding accounts with a certain balance or more, and holding loans. In this situation, this study exploratorily analyzed the consumer behavior of digital banking deposits in a major bank of Korea(1,145 samples). Statistical analysis was performed using SPSS. The main findings of the study are summarized as follows. It was found that there were differences of consumer behavior in digital banking deposits by generation, and the MZ generation used digital banking more on holidays than other generations. As a result of analyzing the behavior of existing loyal customers and regular customers of digital banking deposit, there was a significant difference in both the amount and period of the deposit. It was confirmed that the existing loyal customers of the bank also engage in consumer behavior that contributes to the bank in digital banking. In addition, the interaction between the customer type and the date of sign up for the deposit period, which is the goal setting of financial consumers, it was found that there was a significant effect. This study empirically analyzed the consumer behavior of digital banking in a situation where decrease of bank branches and encounters with digital banking. The major concepts of the consumer behavior theory are Loyal Customer, Goal Pursuit, and Habit, which were confirmed in an example of digital banking. The results of this study can suggest practical implications for existing banks and Internet-only banks, including the importance of customer management in digital banking.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.6
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• pp.91-101
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• 2019

Tourism or travel business consists of a set of services for people who visit exotic places. Payment is usually marking the end of the series of activities relating to tourism, and it becomes the linkage for the next activity. With the recent advancement of mobile Fintech technologies, we have learned that more convenient and more secure financial transactions are improving the quality of tourism. It should be noted that tourism counts on information technology heavily in terms of mobile Internet and smart devices use, which yields to a wide business opportunities for Fintech startups. However, payment information has not been highlighted for additional marketing promotion activities. The lack of research into information technology-based business models that extend Fintech services related to payment in venture start-up studies hinders the understanding of the possibility of creating new business through the value creation process after payment. This study attempts to investigate this issue based on the theory of smart tourism and service-dominant logic with developing a new information system. More specifically, marketing promotion activities after payment for Chinese tourists visiting Korea are examined. Specifically, WeChat Pay and instant tax refund service were considered while the system was developed by following desing science research methodology. This study is meaningful in that it finds a new possibility of Fintech business model by applying scientific and academic methods, and it reminds the necessity of service automation system centered on instant tax refund.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.781-793
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• 2014

A Public Key Infrastructure (PKI) is security standards to manage and use public key cryptosystem. A PKI is used to provide digital signature, authentication, public key encryption functionality on insecure channel, such as E-banking and E-commerce on Internet. A soft-token private key in PKI is leaked easily because it is stored in a file at standardized location. Also it is vulnerable to a brute-force password attack as is protected by password-based encryption. In this paper, we proposed a new method that detects private key compromise and is probabilistically secure against a brute-force password attack though soft-token private key is leaked. The main idea of the proposed method is to use a genuine signature key pair and (n-1) fake signature key pairs to make an attacker difficult to generate a valid signature with probability 1/n even if the attacker found the correct password. The proposed method provides detection and notification functionality when an attacker make an attempt at authentication, and enhances the security of soft-token private key without the additional cost of construction of infrastructure thereby extending the function of the existing PKI and SSL/TLS.

• The Journal of Society for e-Business Studies
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• v.20 no.1
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• pp.1-22
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• 2015

Due to recent growth in IT industry along with the expansion of smartphone, we came to connect to the Internet wherever and whenever we are. However, this causes negative side effects, though. One of them is a rapid increase of the financial crimes such as the Phishing and the SMishing. There have been many on-going researches about crimes such as Phishing and SMishing to protect users. However, the study about sharing knowledge on SNS to prevent such a crime can be hardly found. Based on social identity theory, we conduct the research about factors on SNS users' intention to share the information security knowledge on SNS. As a result, we found that knowledge provision self-efficacy has a significant impact on self-expression. In addition, it also found out self-expression, awareness about information security and the sense of belonging have a significant impact respectively on the intention to share the information security knowledge on SNS. On the other hand, the altruism didn't have a significant impact to the intention to share information security knowledge on SNS. With this research as a starting point, it seems necessary to expand its range to all types of online community in the future for the generalization of the hypotheses.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.53-65
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• 2011

As the Information and Communication Technologies continue to advance, some sensitive services (e.g. e-commerce, on-line financial service, and etc.) have spread rapidly. Accordingly, ensuring the safety of the sensitive service itself using personal Information as well as the protection of personal Information Is becoming very important. In addition, with the popularization of smart phone and the universalized use of wireless Internet, many services that have been provided on the basis of the conventional wired network are increasingly propagating to wired and wireless converged network environment. These changes in the network environment requires new paradigm for the pursuit of safe and stable communication. In this paper, we propose seamless and secure service framework that can facilitate a sustainable secure connection between the user terminal and the sensitive service system by using both the personal and network Information. The proposed service framework is capable of isolating the source of authorized use by a third party of the personal Information as far as the user terminal is not lost, although some personal Information is disclosed. Besides, it can provide a seamless and safe service environment even if the access network is changed by relocation of terminals in the heterogeneous mobile network environment.

• Management & Information Systems Review
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• v.36 no.3
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• pp.167-184
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• 2017

In this study, we investigated the effect of offline banking trust on smart banking trust. As influencing factors of smart banking trust, this study compared offline banking trust, smart banking's system quality, and information quality. For the empirical study, 186 questionnaire data were collected from smart banking users and the data were analyzed using Smart-PLS 2.0. As results, it was verified that there is trust transfer in FinTech service, by the significant effect of offline banking trust on smart banking trust. And it was proved that the effect of offline banking trust on smart banking trust is lower than that of smart banking itself. The contribution of this study can be seen in both academic and industrial aspects. First, it is the contribution of the academic aspect. Previous studies on banking were focused on either offline banking or smart banking. But this study, focus on the relationship between offline banking and online banking, proved that offline banking trust affects smart banking trust. Next, it is the industrial contribution. This study showed that offline banking characteristics of traditional commercial banks affect the trust of emerging smart banking service. This means that the emerging FinTech companies are not advantageous in the competition of trust building compared to traditional commercial banks. Unlike traditional commercial banks, the emerging FinTech is innovating the convenience of customers by arming them with new technologies such as mobile Internet, social network, cloud technology, and big data. However, these FinTech strengths alone can not guarantee sufficient trust needed for financial transactions, because banking customers do not change a habit or an inertia that they already have during using traditional banks. Therefore, emerging FinTech companies should strive to create destructive value that reflects the connection with various Internet services and the strength of online interaction such as social services, which have an advantage over customer contacts. And emerging FinTech companies should strive to build service trust, focused on young people with low resistance to new services.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.137-145
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• 2018

In this study, we categorized the subjective recognition of 20's young generation about virtual currency into a few meaningful types and analyzed the characteristics of each type using the Qmethodology. For the Qpopulation, we selected a total of 337 samples which were derived from the Internet search, in-depth interviews, and literature survey, chose the final 51 Qstatements, and performed the Q-classification for the 40 P samples of 20's, including university students. Then, we analyzed the results using the PC-QUANL program. From the analysis, we found meaningful differences between each recognition type, and, after classifying the recognition types into four, we named each of them as 'investment-vehicle' type, 'future-technology' type, 'kind of gambling-like plays' type, and 'foamy faddishness' type. We hope that this research result can contribute to follow-up research and social discussion as base materials.