• 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.

• Informatization Policy
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• v.31 no.2
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• pp.82-104
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• 2024

Smart home services are growing rapidly as the development of the Internet of Things (IoT) opens the era of the so-called "Connected Living." Although personal information leaks through smart home cameras are increasing, however, users-while concerned-tend to take passive measures to protect their personal information. This study theoretically explained and verified how to design effective software update notification messages for smart home cameras to ensure that users comply with the recommended security behavior (i.e., update installation). In a survey experiment participated in by 120 actual users, the effectiveness of both emotional appeals (i.e., security breach warning images for fear appeals) and rational appeals (i.e., loss-framed messages emphasizing the negative consequences of not installing the updates) were confirmed. The results of this study provide theoretical interpretations and practical guidelines on the message design features that are effective for threat appraisals (i.e., severity, vulnerability) of smart home camera users and their protection motivation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.117-132
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• 2023

With the recent spread of COVID-19, the size of the online shopping market continues to increase, and various online platforms are appearing in the market, and many small and medium businesses are entering the platform. As the recent increase in the use of the platform by small andmedium businesses as raised the issue of appropriate platform fees, the need for social discussions on the use of the platform and fees is raised. Currently, most discussions regarding fees primarily focus on specific cases from a negative perspective, and discussions that comprehensively consider the platform's utilization value and fees are insufficient. Therefore, this study aims to systematically and comprehensively understand platform fees by considering the value of using platform services and commission costs together. To achieve this, the economic value of each platform service was estimated and analyzed in detail. It selected two industries that are actively using online platforms, delivery services and e-commerce, and paid attention to changes in expected profits generated by sellers using platform services, and compared and analyzed expected profits based on estimated sales and costs for each scenario, such as whether sellers entered the platform and whether they used the service. As a result of the study, our results that entering the platform and using the platform service enable sales increase and cost reduction, which have a positive effect on the seller's expected profit. Through this study, we intend to understand platform fees from the perspective of user fees for platform service use and value acquisition, and based on this, estimate the economic value of platform services and fees to expand the value and cost of using platform services to a comprehensive and systematic discussion.

• Information Systems Review
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• v.25 no.1
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• pp.233-255
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• 2023

The development of information technology(IT) has brought so-called "online experience" to satisfy our daily needs. The market for online experiences grew more during the COVID-19 pandemic. Therefore, this study attempted to analyze how the features of online experience services affect customer satisfaction by crawling structured and unstructured data from the online experience web site newly launched by Airbnb after COVID-19. As a result of the analysis, it was found that the structured data generated by service users on a C2C online sharing platform had a positive effect on the satisfaction of other users. In addition, unstructured text data such as experience introductions and host introductions generated by service providers turned out to have different subjectivity scores depending on the purpose of its text. It was confirmed that the subjective host introduction and the objective experience introduction affect customer satisfaction positively. The results of this study are to provide various implications to stakeholders of the online sharing economy platform and researchers interested in online experience knowledge management.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.343-348
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• 2024

Today, AI image creation programs are optimized for various and specialized purposes such as fashion product advertising, customized fashion style suggestions, and design development, and are actively utilized in the fashion industry. Meanwhile, color is a powerful formative element and plays an important role in expressing images for suggesting products or fashion styles. This study seeks to expand understanding of the use of Midjourney by identifying the characteristics of color combinations that appear in clothing images created using Midjourney among AI image creation tools. The results of this study are as follows. First, the initial image created in Midjourney reflects the existing image color used to create the image more than the color specified in the command. Second, the color combinations that appear in the clothes of the images created in Midjourney are divided into separate and mixed colors. The ratio of colors expressed in a separate color scheme is affected by the color order specified in the command. The number of colors combined in a mixed color scheme appears as a combination of fewer colors than the total number of colors of clothing in the existing image used to create the image in Midjourney and the number of colors specified in the command. Third, caution is needed because changes in background color can affect the user's color perception of the clothes in the image and the formation of the costume image. It is hoped that the results of this study will be helpful in fashion design education and practice.

• Journal of IKEEE
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• v.28 no.1
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• pp.90-96
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• 2024

In this paper, we propose an automated system. It utilizes a Raspberry Pi camera and a function generator to analyze luminance in an image. Then, it applies voltage based on this analysis to control light transmission through coloring smart windows. The existing luminance meters used to measure luminance are expensive and require unnecessary movement from the user, making them difficult to use in real life. However, after taking a photography, luminance analysis in the image using the Python Open Source Computer Vision Library (OpenCV) is inexpensive and portable, so it can be easily applied in real life. This system was used in an environment where smart windows were applied to detect the luminance of windows. Based on the brightness of the image, the coloring of the smart window is adjusted to reduce the brightness of the window, allowing occupants to create a comfortable viewing environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.