• The Journal of Industrial Distribution & Business
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• v.15 no.4
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• pp.11-18
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• 2024

Purpose: The primary purpose of this research is to investigate the multidisciplinary effect of food delivery apps (FDAs) in urban hotels in the wake of the lockdown due to Covid-19 pandemic. Specifically, the study aims: To explore and scrutinize the primary shifts in customer behavior and preferences in modern urban hotels, and to explore and scrutinize the primary shifts in customer behavior and preferences in modern urban hotels. Research design, data and methodology: This study conducted a systematic literature review to gather evidence of the FDA's effect on customer behavior and the hospitality industry during the Covid-19 pandemic. Complying with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) principles guarantees a structured and transparent method to search the literature and its analysis. Results: The result based on the systematic review has indicated that the booming business of food delivery at home companies and changing consumer tastes prove the FDA's growing circuit in the hotel industry, thus demonstrating their ability and power to adapt to changing trends. Conclusions: Therefore, this study concludes that using FDA's platform, future hospitality managers have to focus on agility in operations, innovation, and technology integration to keep up with changing consumer trends and market conditions.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.261-268
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• 2024

This study focused on social connection apps and support among various measures to prevent 'killing and abandonment of infants', which has recently become a social issue. The research method attempted to show the necessity of a social-linked app by analyzing the contents of 12 cases with peculiarities in the infant murder process in the judgment after 2021. Infanticide mothers were found to be economically and socially vulnerable, and they killed infants to continue their lives. Focusing on the mind of human respect rather than the judicial meaning of punishing crime, the development of social connection apps and support services that allow both mothers and infants to be healthy and socially protected were proposed. The first is a great transformation of economic support and awareness for pregnancy, childbirth, and parenting. Second, it is necessary to develop a confidentiality counseling and information app that can comprehensively support medical directions and social welfare in consideration of the health status of the fetus and women and the socio-economic situation. Third, it is proposed to promote the use of the Internet such as joint childcare facilities of social communities, child protection institutions, and adoption systems. The government should investigate the reasons for not being able to register birth, the root causes of killing and abandonment of infants, and come up with practical plans and policies for them.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.89-106
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• 2017

In advanced mobile devices environment, the market share of mobile application has been increased. Among various mobile services, Location-based Service (LBS) is an important feature to increase user motivation related to purchase intention on mobile. However, individual privacy has also increased as an important problem for invasion of privacy and information leakage while too many LBS based applications (App) rapidly launched in the App market. In this study, we focused on perceived values of LBS App users who use Apps related to recommending best restaurants in China and South Korea. The purpose of this study is to identify important factors for perceived value when users provide personal information for LBS service provider. The result of this study is follows: perceived value can increase while LBS customers can more control self-information and information useability. Also information ability of users affected perceived values for LBS Apps. Also users' app user ability and perceived value were effects on privacy revenue. In addtion, perceived weakness of users and perceived value increased privacy threat.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.561-570
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• 2010

The purpose of this study is to develop an Android smartphone app providing analysis capabilities of remote sensing images, by using mobile browsing open sources of gvSIG, open source remote sensing software of OTB and open source DBMS of PostgreSQL. In this app, five kinds of remote sensing algorithms for filtering, segmentation, or classification are implemented, and the processed results are also stored and managed in image database to retrieve. Smartphone users can easily use their functions through graphical user interfaces of app which are internally linked to application server for image analysis processing and external DBMS. As well, a practical tiling method for smartphone environments is implemented to reduce delay time between user's requests and its processing server responses. Till now, most apps for remotely sensed image data sets are mainly concerned to image visualization, distinguished from this approach providing analysis capabilities. As the smartphone apps with remote sensing analysis functions for general users and experts are widely utilizing, remote sensing images are regarded as information resources being capable of producing actual mobile contents, not potential resources. It is expected that this study could trigger off the technological progresses and other unique attempts to develop the variety of smartphone apps for remote sensing images.

• International Area Studies Review
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• v.22 no.1
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• pp.141-159
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• 2018

The study aims to explore the factors that affect the value perception, satisfaction, and frequency of smart phone taxi applications in Shanghai, China, and commuters. According to a survey conducted on the actual use of taxi application, the majority of the customers responded that they have been using taxi apps for more than one or two years, and the results showed that they use taxi apps once or twice a week. It also showed that the actual use of taxi apps varies depending on their age and academic background. Among the value attributes of smart phone taxi applications, the respondents perceived ease of use as the highest at 4.41 points out of 5 point scale, while the risk perception was the lowest at 3.34 points. Finally, when social demographic characteristics and the nature of taxi app use were controlled, the value perception variables had a significant influence on taxi application satisfaction. The higher the perception of service quality, usefulness, and system usability, the higher the satisfaction levels were. In particular, the impact of perceived usefulness and system usability perception was high.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.355-365
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• 2021

Online teaching has become a daily routine in schools after 2020, and at the same time, the ability to design and conduct classes using smart devices and apps is becoming more important to teachers. Therefore, in this study, we tried to find out how the demonstration of classes using smart devices and apps online has an effect on the intentions of prospective teachers who want to use them in the future. To this end, classes were designed according to the design principles for improving smart education capabilities of pre-service teachers, and the classes were conducted for pre-service teachers. Afterwards, the variables included in the UTAUT model, such as Performance Expectancy, effort Expectancy, social influence, Voluntariness of Use, Behavioral Intention, and Facilitating Conditions, were measured before and after classes, respectively, and the effectiveness of the class was verified through t-test of response samples. As a result, it was confirmed that all variables except the Facilitating Conditions had a significant positive(+) effect. These results suggest that online class demonstration education can be a way for pre-service teachers to more practically adapt to the educational field where smart education is required.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.313-325
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• 2022

The purpose of this study is to examine the changes in the elderly healthcare app market through text mining analysis and to present basic data for activating elderly healthcare apps. Data collection was conducted on Naver, Daum, blog web, and cafe. As for the research method, text mining, TF-IDF(Term frequency-inverse document frequency), emotional analysis, and semantic network analysis were conducted using Textom and Ucinet6, which are big data analysis programs. As a result of this study, a total of six categories were finally derived: resolving the healthcare app information gap, convergence healthcare technology, diffusion media, elderly healthcare app industry, social background, and content. In conclusion, in order for elderly healthcare apps to be accepted and utilized by the elderly, they must have a good diffusion infrastructure, and the effectiveness of healthcare apps must be maximized through the active introduction of convergence technology and content development that can be easily used by the elderly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.377-380
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• 2022

An application called an app can be downloaded and used on mobile devices. Among them, Android-based apps have the disadvantage of being implemented on an open source basis and can be exploited by anyone, but unlike iOS, which discloses only a small part of the source code, Android is implemented as an open source, so it can analyze the code. However, since anyone can participate in changing the source code of open source-based Android apps, the number of malicious codes increases and types are bound to vary. Malicious codes that increase exponentially in a short period of time are difficult for humans to detect one by one, so it is efficient to use a technique to detect malicious codes using AI. Most of the existing malicious app detection methods are to extract Features and detect malicious apps. Therefore, three ways to select the optimal feature to be used for learning after feature extraction are proposed. Finally, in the step of modeling with optimal features, ensemble techniques are used in addition to a single model. Ensemble techniques have already shown results beyond the performance of a single model, as has been shown in several studies. Therefore, this paper presents a plan to select the optimal feature and implement a learning model for Android app-based malicious code detection.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.835-844
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• 2018

Recently, as the number of smartphone users has been increasing worldwide, various services such as electronic payment, internet use, and financial settlement are being used as a smartphone. In addition, researches for home appliance control and automobile control using smartphone are conducted. As such, smartphone users can enjoy a more convenient life, but by hacking smartphones, tapping texts and conversations on smartphones, tracking location through spy apps, DDoS attacks using smartphones, and malicious apps When a message is received at a specific telephone number when using a micropayment, the corresponding text message is transmitted to a remote server, thereby increasing the risk of leakage of personal information and the like. Therefore, in this paper, we define the risk factors of the smartphone that are caused by the internal and external environmental, physical, contents (apps) of the smartphone through the smartphone that we use in real life, We propose a method to check vulnerability of smartphone security solution such as CC evaluation and the most effective response technique for each risk of smartphone by defining the technique.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.69-90
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• 2023

The purpose of this study is to evaluate the service attributes and consumer reactions of telemedicine apps in South Korea and visualize their differentiation by constructing positioning maps. We crawled 23,219 user reviews of 6 major telemedicine apps in Korea from the Google Play store. Topics were derived by BERTopic modeling, and sentiment scores for each topic were calculated through KoBERT sentiment analysis. As a result, five service characteristics in the application attribute category and three in the medical service category were derived. Based on this, a two-dimensional positioning map was constructed through principal component analysis. This study proposes an objective service evaluation method based on text mining, which has implications. In sum, this study combines empirical statistical methods and text mining techniques based on user review texts of telemedicine apps. It presents a system of service attribute elicitation, sentiment analysis, and product positioning. This can serve as an effective way to objectively diagnose the service quality and consumer responses of telemedicine applications.