• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.578-581
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• 2020

제품을 추천하는 기능은 사용자의 콘텐츠 또는 제품 소비량에 직결되기에 다양한 인터넷 플랫폼에서 많은 관심을 받고 있다. 이러한 제품 추천 시스템의 성능은 다양한 머신러닝 알고리즘과 딥러닝의 발전에 의해 성능을 비약적으로 개선되어왔다. 하지만 여느 딥러닝과 머신러닝 알고리즘과 마찬가지로 추천 시스템들의 성능은 빅데이터의 품질에 따라 매우 민감한 영향을 받는다. 본 논문에서는 모바일 배달 플랫폼에서 사용자들의 리뷰 데이터들을 통해 딥러닝과 빅데이터를 사용하여 음식을 추천하는 방법을 제안한다. 또한 사용자들의 리뷰 데이터들을 정제하여 데이터의 품질을 높이는 과정을 추가하여 그 결과가 성능에 얼마만큼 영향을 미치는 지를 실험을 통하여 분석한다.

• Journal of Nutrition and Health
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• v.53 no.5
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• pp.547-561
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• 2020

Purpose: This study was conducted to segment the delivery food market and to develop customized products and services. Methods: This study analyzed 636 responses collected from customers who ordered delivery food. Statistical analyses were conducted using the SPSS program (ver. 25.0) for frequency analysis, χ²-test, one-way analysis of variance, factor analysis, and cluster analysis. Results: Four factors were extracted by exploratory factor analysis (safety-orientation, convenience-orientation, taste-orientation, and economy-orientation) to explain the consumers' food-related lifestyles. The results of cluster analysis indicated that the 'low-interest group', 'convenience and economy-oriented group', and 'gourmet and economy-oriented group' should be regarded as the target segments. Characteristic analysis of each cluster showed that lowinterest group had higher rates of married (67.1%) and living with family (85.4%) than other clusters. The convenience and the economy-oriented group had higher rates of living alone (28.9%) than others. The gourmet and the economy-oriented group had a higher percentage of unmarried (62.0%) than the others. In addition, the average age of convenience and economy-oriented group (32.3 years) and gourmet and economy-oriented group (32.5 years) were significantly lower than the safety seeker (40.0 years) (p < 0.001). Difference analysis of the consumption practice according to the cluster, revealed significant differences in the order frequency (p < 0.001), main day to order (p < 0.05), source of information about delivery food (p < 0.001), order method (p < 0.001), and co-consumer (p < 0.01). In addition, the convenience and the economy-oriented group had significantly higher overall satisfaction than the others (p < 0.001). Conclusion: These findings suggest that customer segmentation based on a food-related lifestyle can be used to build a successful marketing strategy. Therefore, restaurant managers and delivery platform operators should consider developing products and services according to the segmentation to maximize customer satisfaction.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.163-177
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• 2023

In this study, delivery workers were regarded as workers and industrial accident and serious accident prevention were studied. As a result of the study, first, it was confirmed that awareness of safety guidelines has an effect on disaster prevention and is related to reducing serious accidents. Second, among the forms of organizational culture, rational culture was shown to have a positive impact on serious accidents. Third, the moderating effect of organizational culture Rational culture, a sub-concept, was found to have a moderating effect on serious accidents. Fourth, according to the opinions of workers for disaster prevention of delivery workers, it was classified into policy part, environmental part, and worker's duty part, and the necessity of strengthening safety education and strong regulation was suggested in the policy part.

• Journal of the Korea Safety Management & Science
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• v.24 no.2
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• pp.41-50
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• 2022

The food delivery platform labor market has been continuing to grow rapidly in Korea, which resulted in traffic accident increases of delivery riders. To prevent traffic accidents while delivery, this study conducted a survey for 462 delivery riders and analyzed the statistical relationships of delivery characteristics and risk perception with delivery accidents. The results of this study revealed that riders with young age (20s: 46.6%) and/or low delivery experience (less than 1 year: 50.6%) had significantly higher proportion of accident experience than other age groups (over 40s: 36.2%) and high delivery experience (more than 2 years: 36.4%). In addition, side job riders (61.5%) showed significantly higher proportion of accident experience than main job riders (39.1%). The riders with accident experience had more number of deliveries per hour (weekday: 3.56, weekend: 3.91) than the riders without accident experience (weekday: 3.29, weekend: 3.68). Lastly, the riders with accident experience rated significantly higher perceived level of risk on weather, violation of traffic laws, uninspected motorcycle, receiving calls while driving, missing safety training, missing personal protective equipment than the riders without accident experience. This study suggested four aspects based on the study results to prevent traffic accidents for delivery riders.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.687-694
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• 2022

In this paper, we proposed an autonomous vehicle platform that delivers goods to a designated destination based on the SLAM (Simultaneous Localization and Mapping) map generated indoors by applying the Visual SLAM technology. To generate a SLAM map indoors, a depth camera for SLAM map generation was installed on the top of a small autonomous vehicle platform, and a tracking camera was installed for accurate location estimation in the SLAM map. In addition, a convolutional neural network (CNN) was used to recognize the label of the destination, and the driving algorithm was applied to accurately arrive at the destination. A prototype of an indoor delivery autonomous vehicle was manufactured, and the accuracy of the SLAM map was verified and a destination label recognition experiment was performed through CNN. As a result, the suitability of the autonomous driving vehicle implemented by increasing the label recognition success rate for indoor delivery purposes was verified.

• Journal of Information Technology Services
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• v.18 no.5
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• pp.119-132
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• 2019

This study aims to analyze how specific features of a mobile platform such as economic feasibility, interactivity, safety, and design are correlated with perceived ease of use and customer satisfaction, targeting those who purchase delivery food on a mobile platform dedicated to delivery services. A survey was conducted on customers who had bought delivery food on a mobile platform and the data collection was conducted from August 19, 2019 to September 18, 2019, using 300 mobile platform service users. A total of 300 copies were retrieved. 249 valid samples of 300 copies were analyzed with SPSS 23.0 and AMOS 23, and In addition, programs including SPSS and AMOS were used for the analysis of frequency, confirmatory factor, reliability and validity, correlation and structural equation model. Major findings of such analysis are as follows. First, design characteristic of a mobil platform had relevant impacts on perceived ease of use. However, economic feasibility, interactivity, and safety did not significantly affect perceived ease of use. Second, perceived ease of use had a significantly influenced on the extent of customer satisfaction. Hence, from practical and academical point of views based on the results of this analysis, this study is expected to provide directions and some practical and useful implications for a mobile platform for food delivery services.

• 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.

• The Korean Journal of Franchise Management
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• v.12 no.4
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• pp.41-54
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• 2021

Purpose: Delivery food orders are on the rise due to the COVID 19 pandemic. Many customers are ordering food through delivery apps rather than visiting restaurants to eat out. Delivery application platforms are growing due to the development of O2O. Most of the people who provide gig worker for delivery applications are rider. Rider provides labor on their own terms and have more work flexibility and autonomy than ordinary workers. Trust can be transferred from a well-known entity to an unknown entity. From the customer's point of view of using the delivery application, trust can be seen through the third-party trust of the delivery application platform-rider-customer. Therefore, this study intends to investigate the effect on delivery application trust and rider trust through the well-known characteristics of delivery applications. Research design, data, and methodology: This study was conducted on Korean consumers over 20 years of age who have ordered food through a delivery application for the past month. After educating 5 investigators about the purpose of this study, 60 copies of the survey were conducted per person. During the investigation period, from September 2 to September 26, 2021, 322 copies were collected over 25 days. Among the collected questionnaires, 37 were excluded from insincere or partially unanswered, and 285 were used for analysis. In addition, the collected data were analyzed using SPSS 25.0 and AMOS 25.0. Result: As a result of the study, convenience, price, and variety of restaurants were found to have a significant positive (+) effect on app trust, but design did not have a significant effect on app trust. Also, it was found that convenience had a significant positive (+) effect on trust in rider, but design, price, and variety of restaurants did not have a significant effect. App trust was found to have a significant positive (+) effect on rider trust and intention to use, and it was found to have a significant positive (+) effect on rider trust and intention to use. Conclusions: First, this study established a structural framework between delivery application characteristics-delivery-app trust-rider trust-intention to use. Second, in this study, it was found that customer trust in well-known delivery applications was transferred to less-known rider trust. Third, the delivery application should increase the convenience of use. Fourth, delivery application should set the delivery fee appropriately. Fifth, delivery application must continuously train the rider.

• 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.

• 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.