• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.231-263
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• 2022

The understanding and capability to utilize artificial intelligence (AI) incorporated technology has become a required basic skillset for the people living in today's information age, and various members of the university have also increasingly become aware of the need for AI education. Amidst such shifting societal demands, both domestic and international university libraries have recognized the users' need for educational content centered on AI, but a user-centered service that aims to provide personalized recommendations of digital AI educational content is yet to become available. It is critical while the demand for AI education amongst university students is progressively growing that university libraries acquire a clear understanding of user intention towards an AI educational content recommender system and the potential factors contributing to its success. This study intended to ascertain the factors affecting acceptance of such system, using the Extended Technology Acceptance Model with added variables - innovativeness, self-efficacy, social influence, system quality and task-technology fit - in addition to perceived usefulness, perceived ease of use, and intention to use. Quantitative research was conducted via online research surveys for university students, and quantitative research was conducted through written interviews of university librarians. Results show that all groups, regardless of gender, year, or major, have the intention to use the AI-related Educational Content Recommendation System, with the task suitability factor being the most dominant variant to affect use intention. University librarians have also expressed agreement about the necessity of the recommendation system, and presented budget and content quality issues as realistic restrictions of the aforementioned system.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.116-126
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• 2022

Many studies using trademark information have suggested that trademark information is good data to monitor business trends. This study intends to analyze the trend change before and after COVID-19 using trademark information. Changes before and after COVID-19 were analyzed by using goods & service classification, similar group code, and designated goods information as trademark information. Among the trademark information, it was statistically significant that the change in trends before and after COVID-19 using designated goods names. To verify the results, the changes in keywords using designated goods names before and after COVID-19 were compared with the frequency of keywords in Google Trends. Among the top 8 keywords extracted from designated goods names, the frequency of Google trend searches for 'online, antibacterial, prevention of epidemics, meal kit, virtual' is on the rise, and 'mask, droplet' is not on the rise, but it increased rapidly at the time of COVID-19, and even after COVID-19, it showed a higher level than before. The frequency of 'unmanned' does not differ much before and after COVID-19, but it has been maintained at a consistently high level, and related businesses have been active since before COVID-19, and it can be interpreted as a keyword with high public interest. This study has academic achievements in that it specifically identified information that could be used in business trends by using three types of trademark information.

• The Korean Journal of Franchise Management
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• v.7 no.2
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• pp.15-25
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• 2016

Purpose - This study examined the effect of perceived corporate social responsibility (CSR) on cognitive trust, emotional trust, and loyalty among using Korean food buffet franchises. The result of this study is expected to provide practical implication to industry practitioners in expanding their understanding of the CSR effect in the marketing perspective. Research design, data, and methodology - The data was collected from a panel of online research companies who are over 20 years old and dined in at Korean style buffet franchise outlets more than five times. A total of 370 samples were used after eliminating outliers and missing data. the data were analyzed SEM with SPSS and AMOS. Result - The result of this study showed that: 1) social CSR activities have an effect only on emotional trust; 2) food-related CSR activities influence both cognitive trust and emotional trust; and 3) both cognitive trust and emotional trust have a significant impact on customer loyalty in Korean style buffet franchises. However, it is important to note that this study found no significant causal impact from environmental CSR activities. Furthermore, this study found that food-related CSR activities have the greater influence on the cognitive trust, and cognitive trust is more influential on the customer loyalty than the emotional trust. Conclusions - Based on the findings, this study provides practical implications to industry practitioners. First, that CSR has a significant impact on customer trust suggests that Korean style buffet franchises should focus on CSR activities to improve customer trust. Second, that food-related CSR activities have the greater influence on the cognitive trust implies that industry practitioners should reinforce food-related CSR activities as a marketing tool to enhance emotional trust and the overall credibility of their franchise. Third, we need to find CSR measures at the social level that can secure emotional trust so that customer loyalty can be formed. Fourth, Korean food buffet franchise food service companies should concentrate their efforts on CSR activities at food and social level among the three dimensions suggested by researchers in order to form customer loyalty. For next study, perceived concept of CSR on individual customer should be examined.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.111-128
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• 2023

Due to the coronavirus pandemic, interest in outdoor leisure activities is growing. Among outdoor leisure activities, marine sports can be seen as having good conditions to enjoy in Korea. In the case of yachting among marine sports, a number of yacht experience programs have recently been operated centered on Gwanganli and Suyeong Bay in Busan. This yacht experience is an attractive tourism product that can be enjoyed casually, and can bring stress relief to many users. This study tried to verify the effect of the attractiveness of the yacht experience on the stress recovery based on the tourists' experiences using the yacht experience tour. In addition, we tried to verify the intention of revisiting the yacht experience or sharing it with others through SNS through this stress recovery. In addition, as a moderator variable, the difference between the MZ generation and other generations, which use SNS more actively than other generations, was presented and its significance was verified. The survey of this study was conducted online for tourists who experienced yacht experience in Busan. As a result of the analysis, among the attractive factors of the yacht experience, the program, landscape, facilities and service was found to have a significant influence on the users' stress recovery, and satisfaction through stress recovery had a significant effect on the intention to revisit and to share the SNS. In the verification of the moderating effect according to age, a generational difference in revisit intention between the MZ generation and other generations was confirmed. Through this study, it was suggested that various programs of yacht experience should be developed to induce users to revisit, and various marketing using SNS should be carried out.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.791-800
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• 2023

This study was conducted to lay the foundation for creating a society safe from radiation by investigating the establishment of a radiation social safety net and the establishment of safety awareness and safety culture among citizens living in Busan. Data was collected through an online survey, and 200 copies of the survey were analyzed. Data were analyzed using SPSS Window Ver 28.0. To verify differences between groups, t-test and one way ANOVA were performed, and correlation analysis was performed to confirm the relationship between variables. In addition, multiple linear regression analysis was conducted to confirm the influence between variables. As a result, first, in terms of building a social safety net, citizens' safety awareness, and establishing a safety culture, the scores of the group with male gender, age in 20s, and high school graduation were found to be high. Among them, there was a statistical difference in gender at the significance level of .01 for building a social safety network and at the significance level of .05 for establishing a safety culture. In terms of occupation, there was a statistical difference between professionals and service workers at the significance level of .05 regarding the building of a radiation social safety network. Second, as a result of multiple regression analysis, it was found that 'local government radiation safety education', a subordinate factor in building a radiation social safety network, had a positive effect on citizens' safety awareness and establishment of a safety culture. Third, the results of the correlation analysis between the building of a social safety network, citizens' safety awareness, and establishment of a safety culture showed a positive correlation. Therefore, it is believed that a good radiation social safety network will have a positive impact on citizens' safety awareness and the establishment of a safety culture.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.73-89
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• 2023

This study aims to analyze the frequency of keywords used in Korean abstracts, which are unstructured text data in the domestic record management research field, using text mining techniques to identify domestic record management research trends through distance analysis between keywords. To this end, 1,157 keywords of 77,578 journals were visualized by extracting 1,157 articles from 7 journal types (28 types) searched by major category (complex study) and middle category (literature informatics) from the institutional statistics (registered site, candidate site) of the Korean Citation Index (KCI). Analysis of t-Distributed Stochastic Neighbor Embedding (t-SNE) and Scattertext using Word2vec was performed. As a result of the analysis, first, it was confirmed that keywords such as "record management" (889 times), "analysis" (888 times), "archive" (742 times), "record" (562 times), and "utilization" (449 times) were treated as significant topics by researchers. Second, Word2vec analysis generated vector representations between keywords, and similarity distances were investigated and visualized using t-SNE and Scattertext. In the visualization results, the research area for record management was divided into two groups, with keywords such as "archiving," "national record management," "standardization," "official documents," and "record management systems" occurring frequently in the first group (past). On the other hand, keywords such as "community," "data," "record information service," "online," and "digital archives" in the second group (current) were garnering substantial focus.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.2
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• pp.1-25
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• 2023

This study aims to propose implications for the development of archival content of archives management institutions in Korea by analyzing cases of the archival content on Instagram of the national archives in the Anglosphere. The basic information of the research target's Instagram account, including the creation date, content, and the number of followers, was investigated, and the posts' contents and interaction types with high user responses were analyzed. As a result, to spread the records information service using Instagram, producing images and short-form content that can be intuitively checked through mobile screens and creating content that will attract the attention of primary users are required. Moreover, it is necessary to develop content for informative communications that can be shared with other users. There is also a need to enhance the exposure and searchability of the institution's Instagram account by strengthening connections with the institution's existing online resources and enabling communications, such as using hashtags, following related institutional accounts, and providing feedback on the contents' comments with followers. This study is meaningful in that it examined cases of archival content for Instagram and suggested their applications, and it can be used as basic data to help plan archival contents to spread the archival culture.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.1-31
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• 2009

This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

• KDI Journal of Economic Policy
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• v.32 no.2
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• pp.144-170
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• 2010

This paper considers the effect of various types of procurement auction system on competition focusing on the rate of successful bidding. We analyze the number of bidders and the rate of successful bids using online procurement data of the Public Procurement Service. The average number of bidders is 301 and the average rate of successful bids is 87.42% while the weighted average rate is 75.13%. These numbers show that there is quite strong competition among bidders and the rate is lower as the expected price is higher. When we analyze the data of price procurement auction, the rate is also shown to be lower as the expected price is higher. Furthermore, the rate decreases as the number of bidders increases which naturally makes the competition stronger. Meanwhile, the analysis finds that the inclusion of the onsite bidding, the PQ(Pre-Qualification) result, or major-10 winning companies cannot explain the rate much in our data. In case of turnkey-alternative, the average rate of successful bidding for 484 cases record 90.20%. The average is 84.89% with 120 alternatives and 91.97% with 364 cases of turnkey. The reason why the rate of turnkey-alternative is lower than that of price procurement auction is the lack of competition as well as the systematic difference. By setting up a model, we are able to explain the difference in rate caused by the respective reason. When we suppose there are 3 bidders in case of price procurement auction for a project that exceeds 100 billion won, the rate is expected to be around 64%. This implies that difference of 26% is caused by the systemic difference and 3% by the lack of competition. Therefore, we conclude that the difference in rate between turnkey-alternative and price procurement auction is caused mainly by the systemic difference. In case of PPP(Public Private Partnership) projects, among 154 projects in total, only 40% has more than 2 bidders that compete. The average number of bidders is 1.88 which is less than 2, and the average rate of successful bids is 90%. In sum, under the price procurement auction, there is strong competition which is reflected by the rate of successful bids. However, there is room to decrease the rate by strengthening the competition under the turnkey-alternative. Also with PPP projects, we expect the rate can be steadily reduced with revived competition among bidders.