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

• Smart Media Journal
• /
• v.12 no.11
• /
• pp.27-35
• /
• 2023

Fourth Industrial Revolution and COVID-19 pandemic have boosted the use of Government 24 app for public service complaints in the era of non-face-to-face interactions. there has been a growing influx of complaints and improvement demands from users of public apps. Furthermore, systematic management of public apps is deemed necessary. The aim of this study is to analyze the grievances of Government 24 app users, understand the current dissatisfaction among citizens, and propose potential improvements. Data were collected from the Google Play Store from May 2, 2013, to June 30, 2023, comprising a total of 6,344 records. Among these, 1,199 records with a rating of 1 and at least one 'thumbs-up' were used for topic modeling analysis. The analysis revealed seven topics: 'Issues with certificate issuance,' 'Website functionality and UI problems,' 'User ID-related issues,' 'Update problems,' 'Government employee app management issues,' 'Budget wastage concerns ((It's not worth even a single star) or (It's a waste of taxpayers' money)),' and 'Password-related problems.' Furthermore, the overall trend of these topics showed an increase until 2021, a slight decrease in 2022, but a resurgence in 2023, underscoring the urgency of updates and management. We hope that the results of this study will contribute to the development and management of public apps that satisfy citizens in the future.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.36 no.2
• /
• pp.39-48
• /
• 2013

The development of mobile communication technology is transforming the market of mobile communication devices, which is used to be merely for simple communication, into the one which offers features of personal digital assistant (PDA), fax communication and Internet access. Unlike a mobile phone which comes out as a complete package and whose functions cannot be changed, a smart phone can be upgraded by its user, adding or removing apps as he pleases. OS's of smart phones are iOS-based Apple, Google Android, Window Mobile, and others. Due to its convenience and powerful features, many people use smart phones its high price. On the other hand, consumer complaints are rising on poor A/S for occasional malfunction. This study analyzes how A/S cases can be classified into groups according to quality factors. We evaluate factors such as consumer impression and consumer satisfaction. By dual quality evaluation using KANO method, we would like to show the different A/S strategy for smart phones, compared with mobile phones.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.9
• /
• pp.427-438
• /
• 2020

This study aims to analyze and confirm brand awareness' role in influencing the repurchase intention both directly and indirectly on customer satisfaction variables and repurchase intention variables. The contribution brought by this study is to reflect manifest variables such as recall, purchase, and consumption. The number of respondents in this study was 200 samples using the online survey data collection method (Google form), while the research approach is quantitative explanatory. The data analysis test tools include the Structural Equation Modeling (SEM) approach with AMOS as a statistical data analysis software and Sobel test to indirectly test the relationship. This study consists of four hypotheses, of which three hypotheses are positively and significantly related (brand awareness on repurchase intention, brand awareness on customer satisfaction, and customer satisfaction on repurchase intention). Through indirect relationship, namely, brand awareness on repurchase intention through customer satisfaction, the study showed no significant effect. In a comprehensive way, this study emphasizes the factor of customer satisfaction as a determinant of consumer loyalty and repurchase intention. Therefore, creating optimal customer satisfaction, service excellence, promotion and massive advertising, guaranteeing the safety and ease-of-use apps, and ease of shopping, especially for e-commerce industry, is a serious concern.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.1
• /
• pp.107-115
• /
• 2021

This paper presents a smartphone application for the clinical practice education conducted in hospitals, with an aim to evaluate its effectiveness. A nonequivalent control group posttest design was used, which included a total of 100 nursing of school students who conducted their clinical practice. They were divided into one control and one experimental group (50 students each). The control group was directly trained in the clinical practice orientation, and the experimental group was a group who self-learned the clinical practice orientation using a smartphone application. Research data were collected between March 5 and April 27, 2019. They were analyzed with descriptive statistics and independent t-test, using the SPSS Statistics Version 24. The smartphone application customized for the clinical practice education was implemented through the following four phases: analysis, design, development, and evaluation. The developed application was registered in Google Play (for Android apps) and Apple Store, and related information was provided, making it available for download. The study showed that the satisfaction with and self-confidence in learning differed significantly between the groups. However, technology acceptance and knowledge acquired through practice showed no statistically significant difference. The research results serve as basic data for applying smartphone applications as an educational method that can replace traditional modes of education, serving as a significant indicator of the education delivery method diversification.

• Journal of the Korean Society of Industry Convergence
• /
• v.27 no.2_2
• /
• pp.445-456
• /
• 2024

This study aims to suggest service improvement opportunities by analyzing user review data of the top three OTT service apps(Netflix, Coupang Play, and TVING) on Google Play Store. To achieve this objective, we proposed a framework for uncovering service opportunities through the analysis of negative user reviews from OTT service providers. The framework involves automating the labeling of identified topics and generating service improvement opportunities using topic modeling and prompt engineering, leveraging GPT-4, a generative AI model. Consequently, we pinpointed five dissatisfaction topics for Netflix and TVING, and nine for Coupang Play. Common issues include "video playback errors", "app installation and update errors", "subscription and payment" problems, and concerns regarding "content quality". The commonly identified service enhancement opportunities include "enhancing and diversifying content quality". "optimizing video quality and data usage", "ensuring compatibility with external devices", and "streamlining payment and cancellation processes". In contrast to prior research, this study introduces a novel research framework leveraging generative AI to label topics and propose improvement strategies based on the derived topics. This is noteworthy as it identifies actionable service opportunities aimed at enhancing service competitiveness and satisfaction, instead of merely outlining topics.

• Informatization Policy
• /
• v.25 no.3
• /
• pp.75-94
• /
• 2018

Today, Software as a Service(SaaS) is being recognized as a key means to enable the innovation of software distribution. Despite the increase in the interest in SaaS, individuals as well as businesses are not yet making an extensive use of it. This research is aimed at identifying and analyzing the antecedents of intentions to use SaaS. We proposed a research model to predict an individual's intention to use SaaS based on the Technology Acceptance Model(TAM). To this end, we conducted a questionnaire survey in which actual software users participated. An empirical analysis has been performed to test the reliability and validity and the hypotheses using SPSS and AMOS software packages. The results of the analysis revealed that functionality, interoperability and economic benefits have positive effects on the intention to use SaaS, while system quality has no significant effect on the behavioral intention. We discussed practical as well as academic implications, and provided research directions.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.3
• /
• pp.159-168
• /
• 2017

Smartphone malware has increased because Smartphone users has increased and smartphones are widely used in everyday life. Since 2012, Android has been the most mobile operating system. Owing to the open nature of Android, countless malware are in Android markets that seriously threaten Android security. Most of Android malware detection program does not detect malware to which bypass techniques apply and also does not detect unknown malware. In this paper, we propose lightweight method for detection of Android malware using static analysis and deep learning techniques. For experiments we crawl 7,000 apps from the Google Play Store and collect 6,120 malwares. The result show that proposed method can achieve 98.05% detection accuracy. Also, proposed method can detect about unknown malware families with good performance. On smartphones, the method requires 10 seconds for an analysis on average.

• International Journal of Computer Science & Network Security
• /
• v.22 no.5
• /
• pp.225-233
• /
• 2022

Due to the large number of documents that are important to people and many of their requests from time to time to perform an essential official procedure, this requires a practical arrangement and organization for them. When necessary, many people struggle with effectively arranging official documents that enable display, which takes a lot of time and effort. Also, no mobile apps specialize in professionally preserving essential electronic records and displaying them when needed. Dataset consisting of 10,841 rows and 13 columns was analyzed using Anaconda, Python, and Mito Data Science new tool obtained from Google Play. The research was conducted using the quantitative descriptive approach. The presented solution is a model specialized in saving essential documents, categorizing according to the user's desire, and displaying them when needed. It is possible to send in an image or a pdf file. Aside from identifying file kinds like PDFs and pictures, the model also looks for and verifies specific file extensions. The file extension and its properties are checked before sharing or saving it by applying the similarity algorithm (Levenshtein). Our method effectively and efficiently facilitated the search process, saving the user time and effort. In conclusion, such an application is not available, which facilitates the process of classifying documents effectively and displaying them quickly and easily for people for printing or sending to some official procedures, and it is considered one of the applications that greatly help in preserving time, effort, and money for people.

• The Journal of Information Systems
• /
• v.32 no.3
• /
• pp.151-164
• /
• 2023

Purpose This study aims to analyze the current status of consumer awareness on Internet banks by conducting a full investigation and collecting user opinions presented on Google Play. After cateogorizing the current dissatisfaction, we would like to present not only the direction of the Internet bank service of but also the improvements of the platform. Design/methodology/approach Using opinion mining, subjectivity analysis, polarity analysis, and polarity information analysis of comments were conducted step by step to extract negative and positive keywords. The extracted keywords analyzed the weights of the frequently appearing positive and negative keywords using the TF-IDF model. Based on previous studies that negative information is more sensitive to positive information, we tried to confirm the connection, proximity, and mediation of negative keywords. Semantic Network Analysis (SNA) was used to visualize the connection relationship between the negative comment keywords of the three Internet banks. Findings Domestic Internet banks such as Kakao Bank, K-Bank, and Toss Bank have attracted a lot of attention even before they were established, and after establishment, they have secured a wide range of users through platforms that are completely different from existing banks. This study found out that the convenience of the app affects the opening and transaction of non-face-to-face accounts, which are characteristics of domestic Internet banks, which also affects the bank's business strategy. In addition, this study shows that the business characteristics of the company can be identified.