• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.8-11
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• 2021

This paper proposes a method of estimating the optimal position of a robot in order to provide a service by approaching a user located outside the sensing area of the robot in an indoor environment. First, in order to estimate the user's location, the location in the indoor environment was estimated by applying a trilateral approach to the beacon-tag module data, and Voronoi thinning to set the optimal movement goal from the user's estimated location. Based on the generated nodes, the final location was estimated through the calculation of the user location, obstacle, and movement path, and the location accuracy of the service robot was verified through the movement of the destination of the actual robot platform.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.112-114
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• 2022

This paper proposes an E-Commerce service that supports large quantities of food waste sales generated by collective residences, including apartments, to consumers in urban areas, such as livestock farmers, through online transactions. Unlike general E-Commerce, the proposed service uses a smart food waste bin equipped with an IoT-based sensor and communication module to automatically collect the location information of each apartment and the amount of food waste to be displayed in a specialized E-Commerce platform. The key of this system is to provide information and sell it to consumers. The smart food waste bin periodically delivers its current capacity and location using a weight sensor, GPS sensor and LoRa communication module to a cloud-based database to be used in web or mobile applications. The proposed E-Commerce service is expected to help resolve the food waste disposal problem and revitalize the local economy by linking with a service that delivers food waste from each apartment to a nearby location where the buyer is located.

• Knowledge Management Research
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• v.24 no.4
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• pp.153-176
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• 2023

Generative AI, especially conversational AI like ChatGPT, has recently gained traction as a technological alternative for automating customer service. However, there is still a lack of research on whether current generative AI technologies can effectively replace traditional human managers in customer service automation, and whether they are advantageous in some situations and disadvantageous in others, depending on the conditions and environment. To answer the question, "Can generative AI replace human managers in customer service activities?", this study conducted experiments and surveys on customer online reviews of a food delivery platform. We applied the perspective of the elaboration likelihood model to generate hypotheses about whether there is a difference between positive and negative online reviews, and analyzed whether the hypotheses were supported. The analysis results indicate that for positive reviews, generative AI can effectively replace human managers. However, for negative reviews, complete replacement is challenging, and human managerial intervention is considered more desirable. The results of this study can provide valuable practical insights for organizations looking to automate customer service using generative AI.

• Journal of Information Technology Services
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• v.20 no.2
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• pp.13-31
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• 2021

Recently, delivery app services based on the O2O platform are increasing rapidly. Accordingly, various studies on O2O service have been conducted. Most of the studies are on consumer behavior in O2O services, and few studies on platform vendors have been conducted. Therefore, this study empirically analyzed the factors affecting the vender's intention to continuous use in the O2O delivery app platform service. Based on prior researches, we set the quality characteristics and network characteristics of the O2O platform as independent variables. The quality characteristics of the O2O platform consisted of system quality, information quality, and service quality, and the O2O platform network characteristics consisted of network externality and platform reputation. Perceived value and switching cost were set as mediated variables, and vender's intention to continuous use was set as dependent variables. For empirical analysis, we conducted a survey targeting vendors of O2O delivery app platform service, and conducted frequency analysis, factor analysis, reliability analysis, and regression analysis. As a result of the analysis, the quality characteristics of the O2O platform, such as system quality, information quality, service quality, and O2O platform network characteristics, showed that network externality and platform reputation had a positive effect on perceived value. The perceived value was found to have a positive effect on the switching cost and the intention to continuous use, and the switching cost was found to mediate the perceived value and the intention to continuous use. This study can contribute to the establishment of platform operation strategy as an empirical analysis on the factors that influence the intention of O2O platform vendors to use the platform continuously.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.241-250
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• 2022

Due to the COVID-19 pandemic, with increased 'untact' services and with unstable household economy, the bike insurance fraud is expected to surge. Moreover, the fraud methodology gets complicated. However, the fraud detection model for bike insurance is absent. we deal with the issue of skewed class distribution and reflect the criterion of fraud detection expert. We utilize a balanced random-forest algorithm to develop an efficient bike insurance fraud detection model. As a result, while the predictive performance of balanced random-forest model is superior than it of non-balanced model. There is no significant difference between the variables used by the experts and the confirmatory models. The important variables to detect frauds are turned out to be age and gender of driver, correspondence between insured and driver, the amount of self-repairing claim, and the amount of bodily injury liability.