• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.58-73
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• 2022

The purpose of this study is to construct a predictable estimation model that reflects the relationship between the variables of mobile app performance and to verify how app reviews affect app performance. In study 1 and 2, the relationship between app performance indicators was derived using correlation analysis and random forest regression estimation of machine learning, and app performance estimation modeling was performed. In study 3, sentiment scores for app reviews were by using sentiment analysis of text mining, and it was found that app review sentiment scores have an effect one lag ahead of the number of daily installations of apps when using multivariate time series analysis. By analyzing the dissatisfaction and needs raised by app performance indicators and reviews of apps, companies can improve their apps in a timely manner and derive the timing and direction of marketing promotions.

• Journal of Information Technology Services
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• v.15 no.2
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• pp.169-184
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• 2016

Smartphone use is rapidly spreading due to the advantage of being able to connect to the Internet anytime, anywhere--and mobile app development is developing accordingly. The characteristic of the mobile app market is the ability to launch one's app into foreign markets with ease as long as the platform is the same. However, a large amount of prior research asserts that consumers behave differently depending on their culture and, from this perspective, various studies comparing the differences between consumer behaviors in different countries exist. Accordingly, this research, which uses online product reviews (OPRs) in order to analyze the cultural differences in consumer behavior comparatively by nationality, proposes to compare the U.S. and South Korea by selecting ten apps which were released in both countries in order to perform a sentimental analysis on the basis of star ratings and, based on those ratings, to interpret the sentiments in reviews. This research was carried out to determine whether, on the basis of ratings analysis, analysis of review contents for sentiment differences, analysis of LDA topic modeling, and co-occurrence analysis, actual differences in online reviews in South Korea and the U.S. exist due to cultural differences. The results confirm that the sentiments of reviews for both countries appear to be more negative than those of star ratings. Furthermore, while no great differences in high-raking review topics between the U.S. and South Korea were revealed through topic modeling and co-occurrence analyses, numerous differences in sentiment appeared-confirming that Koreans evaluated the mobile apps' specialized functions, while Americans evaluated the mobile apps in their entirety. This research reveals that differences in sentiments regarding mobile app reviews due to cultural differences between Koreans and Americans can be seen through sentiment analysis and topic modeling, and, through co-occurrence analysis, that they were able to examine trends in review-writing for each country.

• Journal of Distribution Science
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• v.20 no.8
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• pp.105-114
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• 2022

Purpose: The technology acceptance model (TAM) refers to a theory that maps the possibility or extent to which users can accept an innovative technology. The purpose of the current research is to investigate the mediating effect of TAM between online review and behavior intention for promoting golf app's distribution. Research design, data and methodology: In order to examine the relationship between app usage reviews, TAM, and behavioral intentions of golf app participants, the present author collected total 170 responses from South Korean participants based on web-based survey system. The main methodology which was selected by this study is mediation causality analysis that Baron and Kenny suggested. Results: The statistical findings definitely indicated that TAM mediating role exists between the positive emotion of golf app users regarding online reviews and positive behavior intention of golf app, which means that all three steps of mediation causality analysis were statistically significant. Conclusions: The present research concludes that the correct utilization of innovation in the design and implementation of the technology features translates into performance excellence. The model can be used to increase the online presence through innovation as a primary drive toward providing more convenience and accessibility to the users through mobile golf apps.

• Culinary science and hospitality research
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• v.22 no.2
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• pp.234-251
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• 2016

The purpose of this study is to verify the effects of service quality and usage review of smartphone Maiib application(apps) on satisfaction, and reuse intention, convenience sampling method was employed and survey was conducted during the 15th of September, 2015 to the 30th on October as perceived by smartphone Maiib app users. Total of 312 responses were collected, and 295 usable data were used for statistical analysis excluding missing data. Descriptive analysis, factor analysis, and SEM were used to verify the hypothesis. The results from this study are as follows: first, reliability, empathy, usefulness of service quality significantly impact on Majib app satisfaction except informativeness and mobility; second, review assentation of the usage review characteristics significantly impact on Majib app satisfaction but review usefulness of the usage review characteristics significantly did not influence on Majib app satisfaction; third, smartphone Majib app satisfaction critically influences on reuse intention. Based on these results, current study can contribute to verify useful information is very important antecedent to construct the effective marketing strategy by smartphone app.

• Human Ecology Research
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• v.58 no.4
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• pp.613-633
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• 2020

This study identifies consumers' perceived benefits and costs when using Samsung Health (a healthcare app) based on consumer reviews from Google Play Store's app and social media discourse. We examine the differences in the benefits and the costs of Samsung Health using these two sources of data. We conducted text frequency analysis, clustering analysis, and semantic network analysis using R programming. The major findings are as follows. First, consumers experience benefits and costs on several functions of the app, such as step counting, device interlocking, information acquisition, and competition with global consumers. Second, the results of semantic network analysis showed that there were eight benefit factors and three cost factors. We also found that the three costs correspond to the benefits, indicating that some consumers gained benefits from certain functions while others gained costs from the same functions. Third, the comparison between consumer app review and social media discourse showed that the former is appropriate to assess the performance of app functions, while the latter is appropriate to examine how the app is used in daily life and how consumers feel about it. The current study suggests managerial implications to healthcare app service providers regarding what they should strengthen and improve to enhance consumers' satisfaction. It also suggests some implications from the two media, which can be mutually complementary, for researchers who study consumer opinions.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.124-131
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• 2020

As users of internet-based software applications increase, functional and non-functional problems for software applications are quickly exposed to user reviews. These user reviews are an important source of information for software improvement. User review mining has become an important topic of intelligent software engineering. This study proposes a user review mining method for software improvement. User review data collected by crawling on the app review page is analyzed to check user satisfaction. It analyzes the sentiment of positive and negative that users feel with a machine learning method. And it analyzes user requirement issues through topic analysis based on structural topic modeling. The user review mining process proposed in this study conducted a case study with the a non-face-to-face video conferencing app. Software improvement through user review mining contributes to the user lock-in effect and extending the life cycle of the software. The results of this study will contribute to providing insight on improvement not only for developers, but also for service operators and marketing.

• Review of Korea Contents Association
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• v.9 no.3
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• pp.43-52
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• 2011

• The Journal of the Korea Contents Association
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• v.15 no.1
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• pp.300-307
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• 2015

The purpose of this review was to evaluate the effects of diabetes management program using mobile appllication. A systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA Statement was conducted. Studies published between 2004 and 2014 were reviewed using the following databases: Ovid, CINAHL and Cochrane library. The keywords used were (app*OR mobile) AND (nurs* OR health* OR medic*) AND (diabet*). Selected studies were assessed for methodological quality using Scottish Intercollegiate Guidelines Network (SIGN)' Checklist. Three hundred seventy five studies were identified, All the 3 studies found mobile application as a valid strategy on clinical usefulness in diabetes management. This review provides updated evidence for app-based management program in diabetes management. Further studies are needed to increase generalizability using randomized controlled trials, enough sample size. In addition, valid measurements are needed to assess the main outcomes.

• The Journal of Information Systems
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• v.30 no.4
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• pp.227-245
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• 2021

Purpose The purpose of this study is to examine the variables affecting user satisfaction through previous studies and to examine the differences between apps. Differences are based on factors that determine the quality of real estate service apps and derived by the topic modeling results. Design/methodology/approach This study conducts topic modeling to find factors affecting user satisfaction of real estate service apps using user reviews. Sentiment analysis is additionally conduct on the derived topics to examine the user responses. Findings Users give high sentiment scores for services that can manage factors such as usefulness of information, false sales, and hype. In addition, managing the basic services of app is an important factor influencing user satisfaction.

• Journal of Korea Trade
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• v.24 no.7
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• pp.1-28
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• 2020

Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.