• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.213-226
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• 2022

The importance of gamification is garnering increased attention in the corporate world. Gamification refers to using game mechanics and thinking patterns in non-game domains to promote user engagement. By reviewing the definition of gamification and related literary research, we aim to understand how to put theory into practice and determine the organization of gamification's main features. Next, in order to understand the current implementation methods of mobile payment gamification marketing. We analyze popular mobile payment apps as case studies. To examine the effectiveness of game mechanics on mobile payment marketing to determine whether there is a positive impact on brand loyalty and stickiness. The results are used to identify shortcomings in gamified mobile payment systems. Finally, we propose a gamification framework model for mobile payments and offer recommendations for underutilized game mechanics based on previous cases. Future research can reference our model for deeper studies on the effectiveness and impact of gamified mobile payments.

• Journal of Information Technology Services
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• v.21 no.1
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• pp.127-144
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• 2022

Recently, Korea is promoting cooperation with various countries, centering on ASEAN countries, with the aim of exporting Korean smart cities for the globalization of smart cities. The purpose of this study is to select excellent smart city technologies through analysis of smart city technologies owned by domestic companies and company status, and to prepare a plan for revitalization of companies with smart city technologies. Through prior research, the implications were derived through research on the existing smart city. Next, established a smart city policy analysis and smart city technology classification criteria through Korea and Overseas smart city policy and Korea smart city technology status DB. And the big data of smart city technology possessed by Korea companies and a plan for selecting a smart city export technology was prepared through analysis by region and company. As a result, to activate the technology possessed by Korea companies and to export overseas, it seems to need financial support and tax incentives that secure a pathway to export specialized smart technologies of SMEs, along with citizen participation and institutional supplementation. The smart city technology fields with the highest utilization in Korea were traffic, green energy, e-government, crime prevention, and construction, and the service types were platform, IoT, AI, big data, and GIS/GPS. These technologies are expected to contribute to building a platform for overseas smart city technology exports.

• Journal of Preventive Medicine and Public Health
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• v.55 no.6
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• pp.539-548
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• 2022

Objectives: The purpose of this study was to assess the organizational effectiveness of the introduction of a healthcare information system (electronic medical records and databases) in healthcare in Kazakhstan. Methods: The authors used a combination of 2 methods: expert assessment and strengths, weaknesses, opportunities, and threats (SWOT) analysis. SWOT analysis is a necessary element of research, constituting a mandatory preliminary stage both when drawing up strategic plans and for taking corrective measures in the future. The expert survey was conducted using 2 questionnaires. Results: The study involved 40 experts drawn from specialists in primary healthcare in Aktobe: 15 representatives of administrative and managerial personnel (chief doctors and their deputies, heads of medical statistics offices, organizational and methodological offices, and internal audit services) and 25 general practitioners. Conclusions: The following functional indicators of the medical and organizational effectiveness of the introduction of information systems in polyclinics were highlighted: first, improvement of administrative control, followed in descending order by registration and movement of medical documentation, statistical reporting and process results, and the cost of employees' working time. There has been no reduction in financial costs, namely in terms of the costs of copying, delivery of information in paper form, technical equipment, and paper.

• Journal of Information Technology Services
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• v.23 no.1
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• pp.1-10
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• 2024

The IT environment is changing due to the acceleration of digital transformation in enterprises and organizations. This expansion of the digital space makes centralized cybersecurity controls more difficult. For this reason, cyberattacks are increasing in frequency and severity and are becoming more sophisticated, such as ransomware and digital supply chain attacks. Even in large organizations with numerous security personnel and systems, security incidents continue to occur due to unmanaged and unknown threats and vulnerabilities to IT assets. It's time to move beyond the current focus on detecting and responding to security threats to managing the full range of cyber risks. This requires the implementation of asset Inventory for comprehensive management by collecting and integrating all IT assets of the enterprise and organization in a wide range. IT Asset Management(ITAM) systems exist to identify and manage various assets from a financial and administrative perspective. However, the asset information managed in this way is not complete, and there are problems with duplication of data. Also, it is insufficient to update of data-set, including Network Infrastructure, Active Directory, Virtualization Management, and Cloud Platforms. In this study, we, the researcher group propose a new framework for automated 'Comprehensive IT Asset Management(CITAM)' required for security operations by designing a process to automatically collect asset data-set. Such as the Hostname, IP, MAC address, Serial, OS, installed software information, last seen time, those are already distributed and stored in operating IT security systems. CITAM framwork could classify them into unique device units through analysis processes in term of aggregation, normalization, deduplication, validation, and integration.

• Journal of Korean Public Health Nursing
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• v.16 no.2
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• pp.354-377
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• 2002

Aging population is a global trend and Korea is no exception. Due to the progress of the medical and scientific sectors, increase in the average lifetime incurred increase in the number of elderly people. Meanwhile, the family function of supporting the elderly has become a major issue in a society due to the changes in the society's structure and increased entry of the women into the workforce. As a means to substitute the protection of the elderly who are not protected at their respective homes and to replace the tending needs, weekly protection centers and short-stay centers for the elderly were established and operated in Seoul since 1992. However, structured and satisfactory services are not yet to be provided, thus this research intends to understand the current situation at the short-stay centers for the elderly, to identify users' characteristics and to conduct study on nursing need for the health reasons so that the results of the research can be utilized as basic data for the development of nursing care program. Towards this end, this research targeted 142 elderly people who were undergoing treatment at the 11 short-stay centers for the elderly out of total of 13 located in Seoul that were willing to cooperate. The research was conducted from April to May 2002, with the measurement tool developed by Rhee, Seon-ja (2001) to measure the level of nursing need. Then data was collected and analyzed using SPSS program. The results are as follows. The general characteristics of users of the short-stay centers for the elderly were: 123 females $(86.6\%)$, 19 males $(13.4\%)$ and 72 elderly were over the age of 80 $(50.7\%)$. Among these, 24$(16.9\%)$ were living by themselves. Among the illnesses that the subjects were inflicted with were: dementia $(54.2\%)$, stroke $(54.1\%)$ and high blood pressure $(50.7\%)$, in the respective order. Despite the fact that they were diagnosed with illnesses, $47.2\%$ responded that they do not undergo special treatment due to financial reasons. When the level of needs for nursing care among the elderly who use the short-stay centers is divided into informational. physical. and emotional need levels and scored between zero to two, the level of emotional need is the highest with 1.80, followed by physical (1.45) and informational (1.44) need levels. As for the realities of services at the centers and improvement areas, restriction on term was cited as the greatest inconvenience with $38.7\%$, followed by lack of budget (24 respondents, $16.9\%$). Wishful services were financial assistance $(46.5\%)$, medical and nursing services $(40.1\%)$, meal provision service $(8.5\%)$ and counseling service $(4.9\%)$, in the respective order. Based on the above mentioned results, the research identified the need to develop nursing program for the patients of dementia that can be applied onto the short-stay centers and the need to develop volunteer service, backed by societal support. Also, placement of specialized cadre of professionals is needed so that medical and nursing service functions can be provided in a complementary manner.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.6
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• pp.857-872
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• 2014

This study investigates the effect of service ubiquity perceptions on consumers' responses to virtual stores such as benefit and risk perceptions, shopping value perceptions, and service usage intention. Data were collected via a self-administered online survey from nationwide consumer panels of an online marketing research firm. Questionnaire items were adopted from previous literature and developed by authors via pretesting to measure variables. The results revealed that virtual store service ubiquity affects consumer benefit perceptions as well as risk perceptions. All benefit perceptions (including time effectiveness, user control, and compatibility) had significant mediating effects between service ubiquity and hedonic/utilitarian shopping service value perceptions. The mediating effect of financial risk was significant only in the relationship between service ubiquity and utilitarian value perception. The findings offer retailers and marketers information in regards to consumers' perception of a virtual store usage, which can enhance service and product strategy.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.877-884
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• 2020

The main aim of the present study is to investigate the factors that are considered affecting the adoption of Activity-Based Costing (ABC) in the autonomous public universities in Vietnam. A quantitative research was carried out. The data was collected through an online questionnaire survey between June 2020 and September 2020 addressed to the target respondents comprising 168 managers and accountants from 23 autonomous public universities in Vietnam, which participated in the resolution project No. 77/NQ-CP of the Vietnamese government on the pilot renovation of operational mechanisms of public tertiary education institutions during the period of four years, from 2014 to 2017. The findings resulted from hypothesis testing by a binary regression analysis based on the SPSS 20.0 software show that training, competition, support of top manager, and university size are the four main factors that positively affect the adoption of Activity-Based Costing (ABC) in studied universities. On the other hand, no statistically significant impact was found on two other variables, namely the variety of services provided and the usefulness of cost information factors. From the research results, discussions and policy recommendations have been presented to promote the adoption of Activity-Based Costing (ABC) in Vietnamese autonomous public universities in the coming time.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.145-175
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• 2005

In 2001, e-Credit guarantee system was introduced by the Korea Credit Guarantee Fund(KCGF) to extends the credit guarantee services for the purchasing amount on credit in the B2B e-Marketplace. It combines both the merits of bill of exchange and credit card and eliminates the uneasiness related to the unpaid accounts due to the non-facial e-Marketplace. The purpose of this paper is to empirically analyze both the causal relationship and influences among theoretical variables by the structural equation model(SEM). e-Credit guarantee system can be a good strategy for promoting B2R e-Marketplace. The level of application of e-Credit guarantee system is attributable to both the characteristics of B2B e-Marketplace and products. The cost reduction or saving in purchasing procedures, production and stockpiling will be possible through e-Credit guarantee system. The close linkage of financial institutions with the enterprises based on e-Credit guarantee system will further promote B2B e-Marketplace in Korea.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.65-71
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• 2017

This paper proposes a smart phone authentication method based on user's behavior and habit that is an authentication method against shoulder surfing attack and brute force attack. As smart phones evolve not only storage of personal data but also a key means of financial services, the importance of personal information security in smart phones is growing. When user authentication of smart phone, pattern authentication method is simple to use and memorize, but it is prone to leak and vulnerable to attack. Using the features of the smart phone pattern method of the user, the pressure applied when touching the touch pad with the finger, the size of the area touching the finger, and the time of completing the pattern are used as feature vectors and applied to user authentication security. First, a smart phone user models and stores three parameter values as prototypes for each section of the pattern. Then, when a new authentication request is made, the feature vector of the input pattern is obtained and compared with the stored model to decide whether to approve the access to the smart phone. The experimental results confirm that the proposed technique shows a robust authentication security using subjective data of smart phone user based on habits and behaviors.