• Information Systems Review
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• v.22 no.4
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• pp.75-92
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• 2020

As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.

• Information Systems Review
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• v.22 no.4
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• pp.163-184
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• 2020

The information on SNS, which is created by the forms of postings and comments, is being magnified and redistributed to news media expanding its impacts on real words. This amplifying effects of SNS comments have been increasingly discussed but there still lacks the answers for which dimensions of information is magnified, and what affects the direction and the degree of the amplification. This study, therefore, explores the detailed dimensions that are magnified by SNS comments and how SNS posting structure and social network characteristics affect them by using sentiment analysis. By analyzing 2,378 Facebook postings and news articles and their 26,312 SNS and 74,730 news site comments, this study shows that SNS comments magnify the sentiments of the posting articles they are attached to. In comparison to news site comments, SNS comments magnify the cognitive and social dimensions more than the news site comments. In the affective dimension, they tend to magnify only the positive emotion more than news site comments. Also, the findings reveal that whether the article in the posting is written by the posting owner affects the degree of amplification when the comments are remained positive or switched positive, while the opposite determines the amplification when comments remain negatively, suggesting that the user relationship in social network is the important factor that affects the direction and the degree of the information amplification in SNS.

• Tunnel and Underground Space
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• v.34 no.3
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• pp.218-230
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• 2024

Recently, many studies have been conducted for safety management in construction sites by incorporating computer vision. Anchor box parameters are used in state-of-the-art deep learning-based object detection and segmentation, and the optimized parameters are critical in the training process to ensure consistent accuracy. Those parameters are generally tuned by fixing the shape and size by the user's heuristic method, and a single parameter controls the training rate in the model. However, the anchor box parameters are sensitive depending on the type of object and the size of the object, and as the number of training data increases. There is a limit to reflecting all the characteristics of the training data with a single parameter. Therefore, this paper suggests a method of applying multiple parameters optimized through data split to solve the above-mentioned problem. Criteria for efficiently segmenting integrated training data according to object size, number of objects, and shape of objects were established, and the effectiveness of the proposed data split method was verified through a comparative study of conventional scheme and proposed methods.

• Food Science and Preservation
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• v.30 no.2
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• pp.262-271
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• 2023

The objective of this study is to compare and assess the effectiveness of real-time polymerase chain reaction (RT-PCR), loop-mediated isothermal amplification (LAMP), and the selective agar plate method for the detection of Salmonella spp. and Listeria monocytogenes in ready-to-eat (RTE) foods. In RTE foods, the detection performance of the three methods (RT-PCR [SureTect^TM kit and PowerChek^TM kit], LAMP [3M MDS], selective agar) were similar at 0-10, 10-50, 50-100, and 100- CFU/mL of Salmonella spp. and L. monocytogenes. We found that with RT-PCR, the Ct value of salad was significantly higher (p<0.05) than other RTE foods, indicating that fiber plays a critical role as an obstacle to the rapid detection of Salmonella spp. However, the Ct value displayed a mixed pattern according to the inoculation level of L. monocytogenes. The use of rapid detection kits and machines mostly depends on the user's choice, with accuracy, ease of use, and economy being the primary considerations. As an RT-PCR kit, SureTect^TM and PowerChek^TM showed high accuracy in detecting Salmonella spp. and L. monocytogenes in RTE foods, showing that they can replace the existing RT-PCR kits available. Additionally, LAMP also showed excellent detection performance, suggesting that it has the potential to be used as a food safety management tool.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.710-723
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• 2023

The purpose of this study is to investigate the effect on the revisit intention and recommendation intention on the golf course selection attribute factors of Chinese golf course users using IPA. In order to carry out this study, a survey was conducted on 388 Chinese golfers, data processing and IPA analysis were conducted, and the following conclusions were obtained. First, the importance of the selection attribute was the highest in employee etiquette, and the price of restaurants and food and beverage was the highest in satisfaction. Second, as a result of the IPA matrix analysis, there were 8 selection attributes for continuous maintenance, 14 for concentration improvement, 5 for low priority, and 3 for excessive effort avoidance. Third, cost, accessibility, course facilities, auxiliary facilities, caddy expertise, and satisfaction with user management were found to affect both revisit and recommendation intentions. Since this study was limited to Chinese golfers, there may be differences in comparing the results with previous studies conducted in other countries on golf culture. Therefore, studies considering cultural diversity should be conducted in the future.

• Information Systems Review
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• v.19 no.2
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• pp.159-183
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• 2017

Despite the rapid increase in the use of mobile Internet, only a few studies examined digital divide issues in the mobile internet environment. Prior studies on digital divide mainly focused on the usage environments of consumers. The present study analyzes mobile digital divide by considering user environments and the cognitive values of users. Therefore, we estimated the cognitive value of users in mobile Internet environments through contingent valuation method (CVM). We also analyzed the digital divide factors that cause this value difference. We found that domestic users perceive mobile Internet value up to 51,723 Korean Won per month. We analyzed the value differences of digital divide factors, such as "accessibility," "competency," and "usability." Based on this analysis, we found that a difference of 31,878 Korean Won was generated due to accessibility. Competitiveness resulted in a difference of 7,736 Korean Won, whereas that of usability resulted in 6,463 Korean Won. Accessibility is the most important digital divide factor that maximizes the difference of cognitive value of users in a domestic mobile Internet environment.

• Information Systems Review
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• v.20 no.2
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• pp.63-85
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• 2018

Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.

• Information Systems Review
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• v.19 no.1
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• pp.101-121
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• 2017

This study explored the emotional and social implications of social media "like" behavior and examined the difference in this behavior across gender. Most studies on social media have analyzed the "like" behavior quantitatively and determined the number of "likes" produced and exchanged. The current study presented a different view by applying a social perspective and analyzing the user intrinsic motives embedded in the "like" behavior. Specifically, we identified empathy and social support as the "like" motivations and used relationship building and information sharing as the mediators. Furthermore, we hypothesized that empathy and social support exhibit different effects on the use of social media across gender: the female group shows strong empathy, and the male group shows strong social support. Validation was performed through a survey of 285 social media users. The results confirmed that empathy and social support have significant effects on the use of social media. However, gender difference in the use of social media was not evident and was only partially evident in the effects of empathy and social support.

• Information Systems Review
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• v.20 no.1
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• pp.1-16
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• 2018

The development and generalization of the Internet increased the popularity of food delivery service applications in Korea. The food delivery market based on online-to-offline service is growing rapidly. This study compares the usability of Korean food delivery service application between that of Chinese food delivery service application. This study suggests improvement points for Korean food delivery service applications. To conduct this study, we explore the status of various food delivery service applications and conduct interviews and surveys based on the honeycomb model developed by Peter Morville. This study obtained the following results. First, all restaurants participating in the Korean food delivery service must be able to accept order through the application. Second, the shopping cart function must be able to accept order of all restaurants simultaneously. Third, when users look for menu recommendation, their purchase history and shopping cart functions should appear at the first page of the website. Users should be able to perceive the improved usability of the website using those functions. Fourth, when the search window is fixed on the top of each page, users should be able to find the information they need. Fifth, the application must allow users to find the exact location of the delivery person and the estimated delivery time. Finally, the restaurants'address should be disclosed and fast delivery time should be confirmed to enhance users'trust on the application. This study contributes to academia and industry by suggesting useful insight into food delivery service applications and improving the point of food delivery service application in Korea.

• Information Systems Review
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• v.19 no.4
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• pp.135-156
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• 2017

An intelligent personal assistant (IPA) is a software agent that assists people to perform basic tasks or services for an individual by commonly providing information via natural language. In spite of the versatile capabilities of the IPA to answer a user's simple information-based queries, such as the weather and driving directions, the actual usage rates for IPA services are limited to date. In this research, to evaluate the factors affecting the intention to use IPA, we develop an empirical model based on technology acceptance model, innovation diffusion theory, and IS success model. Afterward, we collect 203 questionnaires from actual users of IPAs. Finally, the structural equation model validates the causal relationship between the constructs of the model. Consequently, the innovation characteristics of IPA drawn from innovation diffusion theory, namely, relative advantage, compatibility, observability, all exerted a positive influence on perceived usefulness. Furthermore, information quality, a quality characteristic of IPA obtained from DeLone and McLean's IS success model, presented a positive effect on perceived usefulness and perceived ease of use. Finally, the perceived intelligence of IPA displayed a positive influence on perceived usefulness and ease of use. This characteristic was also a major factor that can increase the intention to use the IPA. Given these research findings, this study is significant for identifying factors that may influence the intention to use the IPA by providing strategic guidelines to relevant business operators and establishing an integrated model.