• Journal of Multimedia Information System
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• 제9권3호
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• pp.201-208
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• 2022

Customized service is a vital and mandatory element for apps in improving their technical performance and app customer analysis. While apps require users' consent for their data extraction and usage, many of the terms and agreement forms are written intricately, making it harder for users to fully understand the whole concept of users' data collection for customized services. Ever since the Facebook-Cambridge Analytica scandal, personal data privacy has been re-examined, forcing many app companies to reinforce a reliable solution to data privacy issues. However, there has not been a secured solution, which worries many people about the future advanced issues when metaverse platforms are actively used in daily apps. The research aims to collect the reactions and behaviors of everyday app users who utilize apps with customized services to understand the nature of privacy data issues and the users' opinions about the future implementation of metaverse platforms. The method of the research was an online questionnaire that targeted university students. The study revealed many fearful and anxious reactions about personal data and further metaverse issues where most app users were uneducated about how current apps collect and utilize users' private data.

• 한국전자거래학회지
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• 제24권3호
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• pp.129-142
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• 2019

블록체인기술에 대한 관심은 지속적으로 증가되고 많은 분야에 활용되고 있다. 블록체인기술은 타인이 함부로 데이터와 거래를 제어할 수 없게 하는 분산 환경을 제공한다. 모바일앱 추천은 모바일 사용자에게 적당한 앱을 추천하는데 사용된다. 예를 들어, 사용자의 선호도 및 모바일 환경에 따라 서로 다른 모바일앱을 추천하는 복수의 안드로이드기반 추천앱이 개발되어왔다. 앱 추천은 사용자가 다른 사용자의 경험을 참조하여 앱을 발견하는 데 도움을 준다. 수집된 많은 양의 데이터 및 사용자 정보는 외부 공격에 대한 취약성과 사용자 개인 정보 보호 문제를 내포한다. 이 문제를 해결하는 방법으로 암호화 안전을 보장하는 블록체인 기술을 적용할 수 있다. 본 서베이 논문에서는 모바일앱 추천 기술과 전자상거래 기술 동향을 살펴본다. 개인화된 앱 추천에 대한 사용자의 개인 정보 선호 중요성 측면에서, 블록체인기술과 협업필터링 기술의 접목이 사용자에게 안전한 데이터 환경을 제공할 수 있는지도 살펴본다.

• 품질경영학회지
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• 제52권1호
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• pp.23-42
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• 2024

Purpose: This study aims to investigate the impact of two types of information quality, which are platform-oriented information quality and customer-oriented information quality, on customers' decision-making processes in the Online to offline (O2O) platform environment. Grounded in the product brokering efficiency model, which encompasses screening cost, evaluation cost, and decision quality, a model framework was developed. Furthermore, this study explores how these decision-making processes affect customer loyalty. Methods: Given that food delivery apps are the most widely used O2O service in Korea, this study targeted users of these apps for data analysis. We conducted hypothesis testing through a purposive sampling methodology focusing on food delivery app users. A Partial Least Squares Structural Equation Modeling analysis was conducted to analyze the data. The data collection occurred via an online survey from October to December 2021, with a total of 212 respondents participating. Results: The results of this study revealed the significant role of information quality in helping customers' decision processes while using food delivery apps. Specifically, it was found that platform-oriented information positively influences decision quality, while customer-oriented information significantly affects both the reduction of evaluation cost and the enhancement of decision quality. Additionally, the study indicated that lower evaluation costs and higher decision quality lead to increased platform loyalty. However, a reduction in screening cost did not have a significant impact on platform loyalty. Conclusion: While previous studies have overlooked the existence of two sides, service provider and user, in a platform, this research holds significance in its analysis of how information quality impacts loyalty by utilizing the two kinds of information quality. Practitioners can enhance customer loyalty to the platform by enriching customer-oriented information, thereby reducing customers' evaluation costs and encouraging more loyal usage of the platform.

• 품질경영학회지
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• 제47권2호
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• pp.237-254
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• 2019

Purpose: The purpose of this study is to analyze correlation of perceived cosmetics brand apps attributes and use intentions, mediating role of customer satisfaction, and relationship between customer satisfaction and continuous usage intention. Then provide basic data for development management strategy of beauty industry and enhancement of competitiveness corresponding to smart era. Methods: The questionnaires were surveyed by an online company(EMBRAIN). After data collection, frequency analysis was performed on the general attributes of questionnaire survey using SPSS 22.0, and data conclusions were derived by verifying reliability and validity of data and hypotheses. Results: First, perceived cosmetic brand app attributes have a positive effect on customer satisfaction, Second, perceived cosmetic brand app attributes have a positive effect on continuous usage intention. Third, customer satisfaction was found to have a mediating role in the effect of perceived cosmetic brand app attributes on continuous usage intention. Fourth, involvement proved to control the relationship between perceived cosmetic brand app attributes perceived interactivity and customer satisfaction. Finally, Involvement has proven to control the relationship between cosmetic brand app attributes perceived interactivity and continuous usage intention. Conclusion: Consumers buying products from cosmetics brand apps will be more likely to use cosmetics brand apps if they feel comfortable with calculation process, search, booking confirmation and payment methods.

• 한국컴퓨터정보학회논문지
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• 제23권3호
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• pp.101-106
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• 2018

The purpose of this study is to analyze the patterns of unconsciousness smartphone use by using an app and a self-administered survey on smartphone addiction comparatively and examine differences between recognition and behavior about actual smartphone use and examine how smartphone addiction influences learning. With an app installed in smartphones, this author collected and analyzed data about users' unconsciousness using patterns for a month. According to the results, there were significant differences found in users' recognition and actual time for use and also frequency of turning on the display. Also, 22% of the subjects used their smartphone over 8 hours a day, and 76% more than 5 hours. Over 95% turned on the display more than 100 times a day, and in extreme cases, they did more than 300 times. In the meantime, users not only in the smartphone addiction high risk group and the potential risk group but also in the general user group are found to use their smartphone too long and too much and frequently turn on the display. The apps that the general user group is mainly using are entertaining apps, and their school records are rather good, so excessive use does not always lead to addiction or learning disorder. Therefore, if we develop more diverse contents for learning and provide digital literacy education, smartphone use will bring more positive effects instead. In follow-up research, the app should be corrected to collect more accurate information, and as variables in personal areas, this researcher will also measure depression, anxiety, stress, self-esteem, and emotional control, and so on to see how they are associated with smartphone use.

• 유통과학연구
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• 제22권1호
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• pp.13-23
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• 2024

Purpose: Within the ever-changing realm of modern e-commerce, this study delves into the complex effects of factors like performance expectations, ease of use, social influence, favorable conditions, and enjoyment perception on users' intentions and usage patterns in online marketplace apps. The research centres on Tokopedia app users in Denpasar City, encompassing a wide and varied demographic. Methods: Utilizing a non-probability sampling method, 200 participants were selected for extensive data collection through surveys. Subsequent rigorous analysis of the gathered data was performed using Structural Equation Modeling-Partial Least Squares (SEM-PLS) techniques. Results: This study aims to contribute substantially to theoretical and practical knowledge regarding marketplace app usage. Theoretical contributions involve enhancing the marketing domain, especially in digital marketing, by revealing the intricate factors influencing user conduct in online marketplaces. From a practical standpoint, this research provides valuable insights for entrepreneurs aspiring to join or improve their positions in the Tokopedia app market. Conclusion: Based on the study, we suggest optimising online shopping apps for a more appealing and user-friendly interface. Enhancing the enjoyment and simplicity of finding desired products can prompt heightened usage of online shopping services, thereby reinforcing distribution management strategies and overall market presence.

• 한국컴퓨터정보학회논문지
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• 제23권2호
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• pp.99-107
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• 2018

This study started from the public interest purpose to help accessibility for the information acquisition of the vulnerable groups due to visual difficulties such as the elderly and the visually impaired. In this study, the server resources are minimized and implemented in most of the user smart phones. In addition, we implement a method to gather necessary information by collecting only pattern information by utilizing crawl & clipping without having to visit the site of the information of the various sites having the data necessary for the user, and to have it in the server. Especially, we applied the TTS(Text-To-Speech) service composed of smart phone apps and tried to develop a unified customized information collection service based on voice-based information collection method.

• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.126-136
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• 2022

The purpose of this study is to investigate the application experience and observation of young children's teachers' digital devices. The participants of this study were 6 young children teachers using digital devices. Individual interviews were conducted as a data collection method. It was conducted 2-3 times per research participant. Data collection was conducted from November to December 2020. The Data analysis was focused on the young children's teachers' digital device application experience and observation use. 'Easy and simple use', 'using existing familiar apps', 'providing healing to teachers', and 'improving the utilization of spare time' were derived as early childhood teachers' experience of applying digital devices. 'Easy use of observation records', 'Use together in various ways', 'Use for parent counseling', 'Use appropriate for observation of revised Nuri Curriculum' through early childhood teacher's experience of observing digital devices ' was derived. As a conclusion of this study, first, it is easy for young children's teachers to apply digital devices to the field. Second, if young children's teachers use digital devices, they can make a wide range of observations, enabling high-quality early childhood education practices.

• 융합정보논문지
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• 제11권6호
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• pp.120-130
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• 2021

본 연구는 유아의 자유놀이를 지원하는 융합인재교육(STEAM)기반 스마트 앱 활용 교육 프로그램을 개발하고 이의 효과를 검증하기 위한 목적으로 실시되었다. 연구의 목적을 달성하기 위하여 관련 분야 문헌 및 자료수집, 현장조사를 통하여 유아의 자유놀이에 STEAM기반 스마트 앱을 활용하기 위한 내용을 도출하고, 이에 기반하여 프로그램을 개발하였다. 본 프로그램은 스마트 폰에 개발된 'Free Play' 앱을 설치하고 자유놀이 시작, 중간, 종료 단계에서 유아의 놀이에 대해 교사와 유아가 상호작용하는 교수전략이다. 이러한 유아의 자유놀이를 지원하는 스마트 앱 활용 교육 프로그램의 효과를 검증하기 위하여 실험연구를 실시하였다. 연구결과, 본 프로그램의 적용으로 유아의 자기조절력과 자기조절력 하위요인이 향상됨을 확인하였다. 본 연구는 유아교육의 핵심인 자유놀이 시간에 교사와 유아 모두를 지원하기 위한 교수전략이자 공학과 교육이 융합된 발상으로 프로그램을 개발하고 적용하였으며 추후 교육현장에서 스마트 앱 활용 교육을 활성화하는 단초가 되길 기대한다.

• 반도체디스플레이기술학회지
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• 제18권2호
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• pp.1-5
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• 2019

As the number of IOT devices is growing rapidly, various 'see-thru connection' techniques have been reported for efficient communication with them. In this paper, we propose a deep learning based IOT device recognition system for interaction with these devices. The overall system consists of a TensorFlow based deep learning server and two Android apps for data collection and recognition purposes. As the basic neural network model, we adopted Google's inception-v3, and modified the output stage to classify 20 types of IOT devices. After creating a data set consisting of 1000 images of 20 categories, we trained our deep learning network using a transfer learning technology. As a result of the experiment, we achieve 94.5% top-1 accuracy and 98.1% top-2 accuracy.