• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.43-48
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• 2021

The article proposes a method of modeling a comprehensive indicator for evaluating the effectiveness of regional management of innovation activity. This will make it possible to assess the effectiveness of personnel, financial and credit and foreign economic activity of the regions from the standpoint of an integrated approach. The modeling technique is proposed to be carried out using the tools of taxonomic analysis and the calculation of a complex indicator of the effectiveness of the innovation activity management.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.4
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• pp.233-244
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• 2018

The purpose of this study was to improve awareness of network marketing business in South Korea, which takes a quite negative view of network marketing, to raise awareness of "starting up a business" as independent business owners, to assist them in building their own subjecthood in network business and entrepreneurial identity, and ultimately to give some suggestions on how to improve their self-directed entrepreneurial competency and the quality of their business management. To make an empirical analysis of 121 independent business owners of Korean native network marketing, the personal and background variables of the entrepreneurs were selected as independent variables, and entrepreneurship was selected as a mediator variable. The selected dependent variables were financial and non-financial business performances. A multiple regression analysis was conducted by inputting the variables. The findings of the study were as follows: It produced an effect of more financial performance when the innovation of the independent business owners of network marketing was better, and this innovation was possible to have only when they improved in entrepreneurial efficacy and locus of control. In contrast, only authenticity had an effect on boosting non-financial business performance among the factors of entrepreneurship. To have authenticity, it's necessary to strengthen achievement needs and awareness of locus of control among the personal characteristics of the independent business owners of network marketing. Among the factors of entrepreneurship, there was better authenticity when their personal networks were broader among their background characteristics. In addition, self-efficacy that was one of personal characteristics made a direct contribution to the enhancement of non-financial performance. As a result, independent business owners of network marketing are required to hold a strong belief in their own business, to be active in business activities and to have a high efficacy as spontaneous principal agents, and they also are required to have more adventurous, planned, active and propulsive achievement needs that enable them to attain the goals of their business and keep moving forward. Besides, they should foster their locus-of-control competency that is to control, endure and be responsible for a variety of phenomena or incidents that they face, and there will be better financial performance or non-financial performance only when they demonstrate their self-belief and confidence and when they have faith in and conviction about themselves. For independent business owners of network marketing, a consumer-centered thinking that entails authenticity and trustworthiness and touches the hearts of customers is a more effective marketing strategy than an egocentric thinking as sellers when they approach customers. And they are expected to make progress in terms of the quality of business management when their business attachment or enthusiasm is great enough to match their own efficacy with entrepreneurial identity or strike a balance between them.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.19-25
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• 2017

The research is to identify social networks of problems that have an influence on the quality of ageing people's lives by using social network analysis, based on the premise that there are differences in networks of ageing problems in urban and rural areas. From analyzing network of ageing people's problems using NodeXL, vertices in the networks of both urban and rural areas are well-connected. For urban areas, financial poverty is the core problem related to the quality of life. It has direct connections with illness and health, family responsibility, housing, role loss in community, and employment, which have positive or negative interactions with the quality of older people's lives. For rural areas, on the other hand, role loss in community is the major problem. It has direct connections with the elderly abuse, financial poverty, leisure activity, divorce, isolation and loneliness from society, education, and suicide. As a result, the research shows that the problems of ageing people have strong linkages and interactive effects with a structure of network, and the networks are different depending on types of places for living.

• Asia pacific journal of information systems
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• v.9 no.4
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• pp.23-40
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• 1999

This paper proposes a hybrid intelligent system that predicts the failure of firms based on the past financial performance data, combining neural network and rough set approach, We can get reduced information table, which implies that the number of evaluation criteria such as financial ratios and qualitative variables and objects (i.e., firms) is reduced with no information loss through rough set approach. And then, this reduced information is used to develop classification rules and train neural network to infer appropriate parameters. Through the reduction of information table, it is expected that the performance of the neural network improve. The rules developed by rough sets show the best prediction accuracy if a case does match any of the rules. The rationale of our hybrid system is using rules developed by rough sets for an object that matches any of the rules and neural network for one that does not match any of them. The effectiveness of our methodology was verified by experiments comparing traditional discriminant analysis and neural network approach with our hybrid approach. For the experiment, the financial data of 2,400 Korean firms during the period 1994-1996 were selected, and for the validation, k-fold validation was used.

• Human Ecology Research
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• v.57 no.1
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• pp.1-13
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• 2019

Internet-based financial services are being increasingly integrated into consumers' daily lives. Internet-only banks have emerged as a powerful tool accelerating financial inclusion. This study investigates the satisfaction and continuous use intention predictors for Internet-only banks. We employed an extended post-acceptance model and used six antecedent factors that included perceived usefulness, perceived ease of use, privacy risk, functional risk, subjective norms, and network externality. All 351 participants used Internet-only banks and were 20-40 years of age. A self-administration online survey was conducted. SPSS 23.0 analyzed the frequency, description, and multiple regression analysis. The results of current study are as follows. The education, perceived usefulness, perceived ease of use, and network externality positively influenced the satisfaction of Internet-only banks. Privacy risk negatively influenced satisfaction with Internet-only banks. Perceived ease of use, subjective norm, network externality, and satisfaction positively influenced the continuous use intention of Internet-only banks. The results of our study provide a better explanation of important factors that could enhance the understanding of satisfaction and continuous use intention for Internet-only banks. Furthermore, this study extends the antecedent variables to the knowledge of financial services and enlarges the understanding of users' post-adoption behaviors.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.29-38
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• 2022

The growth of digitalization processes around the world, covering almost all areas of human life, including the Fintech sector. In the field of financial technology, radical changes are taking place with increasing levels of automation, openness and consumer focus. In addition, in the context of the spread of coronavirus infection, quarantine and forced isolation, the role of digital technology is coming to the fore worldwide, including in Ukraine. The purpose of the article is to assess the development of Fintech ecosystem of European countries and outline the strategic parameters of domestic Fintech development. The study concluded that the investment raised for the Fintech industry increases annually and the quality and size of transactions gradually increases. Today, Fintech maintains its position as one of the most attractive markets for venture capitalists and the image of an industry with high potential, especially in the era of open banking. The most attractive markets for investors are mature markets, such as the United States, Germany and the United Kingdom, and the preferred niches for investment - the vertical of payments and lending. Trends in investment activity in terms of investing in financial technologies are studied. Moreover, investors prefer businesses that already have a significant scale or considerable potential to achieve it and become sustainable businesses.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.29-34
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• 2022

The innovative process of digitalization and creation of innovation from an idea to its commercialization requires certain financial costs, labor and mental efforts. The amount of investment (corporate and public) is the most important imperative to enhance innovation and is traditionally considered as the main "input" indicators of the development of innovation infrastructure, in this case, the financial infrastructure of innovation. At the same time, the modern theory of innovation development assumes a systematic approach to the organization of innovation activity, which provides for the close interaction of several subsystems: human (including intellectual) potential, financial and technological capital, as well as relevant institutions and methods of regulation.. Thus, the main task of the study is to analyze the features of investment support for the process of digitalization of socio-economic systems in the context of strengthening international economic relations. As a result of the study, current trends and prerequisites of investment support for the process of digitalization of socio-economic systems in the context of strengthening international economic relations were revealed.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.53-63
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• 2020

Electronic financial transactions are also actively increasing due to the rapid spread of information communication media such as the Internet, smart devices, and IoT, but as a derivative by-product, threats of financial security such as leakage of various personal information and hacking are also increasing. Therefore, the importance of financial security against this is increasing, but in Korea, financial security technology is relatively insufficient compared to advanced countries in the field of financial security, such as Active-X. Therefore, this study aims to present the major development direction in the domestic financial security field by comparing key technology trends with IPC classification frequency analysis, keyword frequency analysis, and keyword network analysis based on domestic and foreign financial security-related patent data. In conclusion, it seems that recent domestic and foreign trends have focused on the development of related technologies according to the development of smart device-based electronic financial services. Accordingly, it is intended to be used as the basis data for technology development of financial security by mapping the trend of financial security research trend and technology trend analysis through thesis data analysis that reflects the research of the preceding aspect as the technology of commercialization in the future.

• Journal of Information Technology Services
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• v.16 no.2
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• pp.33-44
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• 2017

The financial industry recently introduces several issues for utilizing the blockchain technology as the core infrastructure of future finance. Blockchain, first introduced as the underlying technology of Crypto-currencies, Bitcoin is a technology that can ensure the integrity and reliability of data by verifying, recording, and storing data jointly in the network without a central administration organization or a manager. This blockchain has its potential power as a technology for issuing digital currencies, providing transparency, and securing record management, that is expected to be useful in the financial sector. At the same time, considering the characteristics of financial transactions which emphasize privacy, questions are raised about whether a blockchain structure in which information is distributed and shared among participants can be successful. How will we support to implement the potential of the blockchain in order to change the paradigm of the financial industry? How can we manage the side effects of blockchain effectively? Such a policy discussion is necessary. This study introduces the meaning of the blockchain technology, various utilization attempts, and possible problems facing technology from the viewpoint of financial industry, and suggests a policy direction for utilizing this technology as a catalyst to the progress of the financial industry or as a new technology power.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.