• Journal of Digital Convergence
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• v.19 no.5
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• pp.81-92
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• 2021

The purpose of this study is to present an approach to the "Digital Health Passport" (DHP), which will be the most important in the change of the travel industry among the sudden environmental changes brought about by COVID-19. To this end, this study reviewed a variety of empirical literature on DHP, and proposed a framework for DHP based on literature review. The framework is composed of travel intention, health information provision intention, and new technology acceptance/adoption of tourists. First, in terms of travel intention, providing information to DHP should not undermine the travel intention of the travelers. It should be possible to facilitate the travelers' enjoyment by using the information provided by the traveler. In addition, there is a need to assure that the data provided by travelers is managed in a reliable way. Second, it is necessary to understand why the travelers want to provide additional personal information (information disclosure), rather than seeing healthcare information only in terms of mandatory information provision. Finally, from the perspective of new technology, it is necessary to understand the intention of travelers to use/adopt DHP. The key implication of this work is that it proposed a DHP framework for realizing the travel bubble to predict and respond to foreign travelers' behaviors.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.187-193
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• 2021

In February 2020, Gyeonggi-do paid the world's first Data Dividend to local residents of Gyeonggi Province who produced data using local currency. Currently, Data Dividend is being paid to consumers who have produced data, but this paper studied the expansion of Data Dividend qualifications according to the contribution to creating added value. First, it raised the question of whether it is right for the recipient of Data Dividend to have only the consumers who produced the data. Second, by analyzing the four elements of data valuation criteria that influenced the creation of added value identified the objects that influence the creation of added value. The 4 factors were divided into productivity, effectiveness, concreteness, and usability, and the objects corresponding to each factor were analyzed. Accordingly, it was determined whether platform workers contributed to the creation of added value. In conclusion, it was confirmed that not only consumers, who were the first data producers, but also platform workers who contributed to the concreteness of data valuation to create added value can qualify for Data Dividend. Since this paper focuses on the necessity of data allocation centered on platform workers among the objects, the validity of objects that influence added value other than platform workers are excluded.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.161-171
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• 2021

According to the equity home bias theory, foreign investors are considered to have less information than native investors. However, as the economy becomes liberalized and overseas economic innovation has a great influence on the local economy, it is possible for foreign investors to invest as informed traders. This study analyzes whether information on trade amount by nationality has specific characteristics. The findings are summarized as follows. First, the increase in trading by foreign investors has negative effects on stock returns. There is no significant difference in these negative effects by nationality. This means that foreign investors show strong herd behavior regardless of nationality. Second, foreigners' investment activities increase stock price volatility, but the impact is not significant. Third, the behavior of foreign investors is still positive feedback. However, there are signs that positive feedback behavior may be changing, especially for funds from the United States and the Cayman Islands. Finally, tax haven zone funds have different investment strategies than other foreign investors. However, Cayman Islands funds, which are estimated to be closely related to Korea, are different from Luxembourg and Ireland funds. These findings undermine the fundamentals of the equity home bias theory.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.655-660
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• 2022

This paper analyzes the problem of the economic order quantity (lot size) of a retailer in a two-stage supply chain consisting of a supplier, a retailer(distributor), and a customer. In this two-stage supply chain, the supplier permits the retailer to defer payment for a certain fixed period of time for the purchase cost to be paid by the retailer as a price differentiation strategy with his competitor. In addition, in the case of customer goods such as food and grain, it is common to see that end-customer demand is generally depend on the level of inventory displayed by the retailer. From this perspective, this paper analyzes the inventory problem of retailers under the assumption that the supplier may allow a certain period to suspend payments for the purchase of goods and the end customer demand is a function of the retailer's inventory level increasing with size. In this regard, we need to analyze how much the length of the grace period for product purchase costs affect the retailer's lot-sizing policy. Therefore, we formulate the retailer's annual net profit and analyze the effect of the length of credit period on the retailer's inventory policy numerically.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.313-323
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• 2021

The purpose of this study is to propose rules that can identify the speaker referred by the speaker directive in the text for the realization of a machine learning-based virtual character using a literary text. Through previous studies, we found that when applying literary texts to machine learning, the machine did not properly discriminate the speaker without any specific rules for the analysis of speaker directives such as other names, nicknames, pronouns, and so on. As a way to solve this problem, this study proposes 'nine rules for finding a speaker indicated by speaker directives (including pronouns)': location, distance, pronouns, preparatory subject/preparatory object, quotations, number of speakers, non-characters directives, word compound form, dispersion of speaker names. In order to utilize characters within a literary text as virtual ones, the learning text must be presented in a machine-comprehensible way. We expect that the rules suggested in this study will reduce trial and error that may occur when using literary texts for machine learning, and enable smooth learning to produce qualitatively excellent learning results.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.387-392
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• 2022

To participate in global carbon neutrality, the Korean government is also planning to carry out zero-energy building certification for all buildings by 2030 through the enforcement decree of the 'Green Building Support Act'. Accordingly, the government is providing various projects related to solar power generation, which are relatively close to life. In particular, roof-mounted photovoltaic power generation systems are attracting attention in terms of using unused space to produce energy without destroying the environment, but low power generation efficiency compared to other photovoltaic power generation facilities is pointed out as a disadvantage. Therefore, in this paper, to solve this problem, we propose an efficient solar panel angle variable system through research on the solar panel structure for single-axial solar tracking, and also consider the application environment of the roof-mounted solar power generation system. Suggests measures to prevent damage and secondary damage. In addition, it is judged that it is possible to control the solar panel based on ICT convergence and configure the accident prediction safety system to link the project-based education program.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.397-404
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• 2022

This study aims to examine the effects of college students' teaching-friendly learning activities on college life adaptation, and to examine whether these effects differ according to learner characteristics. To this end, 214 people who participated in the learning program of universities located in G area in the first semester of 2022 were targeted. In order to find out the effect of teaching-friendly learning activities on college students' adaptability to college life, frequency analysis, response sample t-verification, and one-way analysis of variance (one-way Anova) were conducted using SPSS 20.0. The results are as follows. First, it was found that teaching-friendly learning activities significantly increased the scores of academic adaptation, emotional adaptation, and social adaptation in college life adaptation. Second, there was no difference in adaptation to college life according to college. Third, The score of the level of attachment to universities was found to be higher in the female group than in the male group. Fourth, as a result of the analysis according to the grade, it was found that the third-grade group had a high level of attachment to universities. Conclusions and suggestions for these research results were presented.

• Informatization Policy
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• v.29 no.3
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• pp.82-104
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• 2022

One of the interesting social phenomena in short-form video platforms is the hashtag challenge wherein ordinary users are encouraged to create by imitating short viral videos on a particular theme. Despite the increasing popularity of hashtag challenges, theoretical discussion on related user behavior is still very insufficient. In this study, we attempted to examine the impact of micro-influencers in order to understand users' willingness to participate in hashtag challenges. For this purpose, the para-social interaction theory and imitation behavior literature were adopted as key theoretical basis. In an empirical investigation using 243 survey data from TikTok users, our study found that a user's illusion of intimacy with a micro-influencer (i.e., para-social interaction) had significant positive impact on the intention to participate in a hashtag challenge. This study also showed that the degree of para-social interaction in a short-form video platform was determined by both media content-related factors and media character-related factors (i.e., content attractiveness, physical attractiveness, and attitude homophily). Our work in this study provided significant theoretical and practical implications on how to leverage micro-influencers for the success of hashtag challenges in a short-form video platform.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.159-165
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• 2023

While the frequency of seismic occurrence has been increasing recently, the domestic seismic response system is weak, the objective of this research is to compare and analyze the seismic vulnerability of buildings using statistical analysis and machine learning techniques. As the result of using statistical technique, the prediction accuracy of the developed model through the optimal scaling method showed about 87%. As the result of using machine learning technique, because the accuracy of Random Forest method is 94% in case of Train Set, 76.7% in case of Test Set, which is the highest accuracy among the 4 analyzed methods, Random Forest method was finally chosen. Therefore, Random Forest method was derived as the final machine learning technique. Accordingly, the statistical analysis technique showed higher accuracy of about 87%, whereas the machine learning technique showed the accuracy of about 76.7%. As the final result, among the 22,296 analyzed building data, the seismic vulnerabilities of 1,627(0.1%) buildings are expected as more dangerous when the statistical analysis technique is used, 10,146(49%) buildings showed the same rate, and the remaining 10,523(50%) buildings are expected as more dangerous when the machine learning technique is used. As the comparison of the results of using advanced machine learning techniques in addition to the existing statistical analysis techniques, in spatial analysis decisions, it is hoped that this research results help to prepare more reliable seismic countermeasures.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.289-305
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• 2023

The rapid increase in the use of mobile devices is changing consumers' online shopping behavior. However, the difference in the effect on the conversion rate according to the time when consumers switch from a small screen to a large screen has not been sufficiently studied. In addition, the differences in the effect of device conversion on purchase performance according to the characteristics of each country's infrastructure have not been sufficiently studied. Against this background, this study aims to analyze whether the timing of switching from mobile devices to PC devices and the country's mobile Internet penetration rate are moderating the positive effect of device switching on purchase performance. For empirical analysis, Google Merchandise Store data was collected and 101,466 data from 130 countries were analyzed with a multilevel model. As a result of the analysis, consumers' device switching (i.e., mobile to PC) had a positive effect when it occurred in the middle of the consumer journey. However, it was analyzed that when device switching occurred at the later stage of the consumer journey, it had a negative effect on purchase performance. In addition, it was analyzed that the higher the mobile Internet penetration rate, the weaker the positive effect of consumer device conversion on purchase performance.