• Information Systems Review
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• v.23 no.3
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• pp.159-176
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• 2021

Obviating user churn is a prominent strategy to capitalize on online games, eluding the initial investments required for the development of another. Extant literature has examined factors that may induce user churn, mainly from perspectives of motives to play and game as a virtual society. However, such works largely dismiss the service aspects of online games. Dissatisfaction of user needs constitutes a crucial aspect for user churn, especially with online services where users expect a continuous improvement in service quality via software updates. Hence, we examine the relationship between a game's quality management and its user base. With text mining and survival analysis, we identify complaint factors that act as key predictors of user churn. Additionally, we find that enjoyment-related factors are greater threats to user base than usability-related ones. Furthermore, subsequent quasi-experiment shows that improvements in the complaint factors (i.e., via game patches) curb churn and foster user retention. Our results shed light on the responsive role of developers in retaining the user base of online games. Moreover, we provide practical insights for game operators, i.e., to identify and prioritize more perilous complaint factors in planning successive game patches.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.47-58
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• 2018

Game bots distribute a large amount of goods or items used in a game, thereby lowering the value of game goods and items. Also, a large number of game bots hunt monsters and collect items, which hinders ordinary users from enjoying content normally. However, no research has been done on the type of user and the type of activity that the increase in bots specifically affects. Therefore, this study provides a practical implication to encourage users to use games by classifying types based on the game users' access data and analyzing the correlation with user departure due to the increase of bots.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1431-1439
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• 2017

In the security field, log analysis is important to detect malware or abnormal behavior. Recently, image visualization techniques for malware dectection becomes to a major part of security. These techniques can also be used in online games. Users can leave a game when they felt bad experience from game bot, automatic hunting programs, malicious code, etc. This churning can damage online game's profit and longevity of service if game operators cannot detect this kind of events in time. In this paper, we propose a new technique of PNG image conversion based churn prediction to improve the efficiency of data analysis for the first. By using this log compression technique, we can reduce the size of log files by 52,849 times smaller and increase the analysis speed without features analysis. Second, we apply data mining technique to predict user's churn with a real dataset from Blade & Soul developed by NCSoft. As a result, we can identify potential churners with a high accuracy of 97%.

• Journal of KIISE
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• v.44 no.3
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• pp.314-322
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• 2017

In MMORPG (Massively Multiplayer Online Role-Playing Game), users advance their own characters to get to the maximum (max) level by performing given tasks in the game scenario. Although it is crucial to retain users with high levels for running online games successfully, little efforts have been paid to investigate them. In this study, by analyzing approximately 60 million in-game logs of over 50,000 users, we aimed to investigate the process through which users achieve the max level and churn of such users since the moment of achieving the max level, and determine possible indicators related to churn after the max level. Based on the result, we can predict churn of the max level users by employing behavioral patterns before the max level. Moreover, we found users who are socially active and communicate with many people before the max level are less likely to leave the service (p<0.05). This study supports that communication patterns are important factors for persistent usage of the users who achieve the max level, which has practical implications to guide elite users on enjoying online games in the long run.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.98-105
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• 2021

As the average life expectancy is rising, the population is aging and the number of chronic diseases is increasing. This has increased the importance of healthy life and health management, and interest in mobile health services is on the rise thanks to the development of ICT(Information and communication technologies) and the smartphone use expansion. In order to meet these interests, many mobile services related to daily health are being launched in the market. Therefore, in this study, the characteristics of users who actually use mobile health services were analyzed and a predictive model applied with machine learning modeling was developed. As a result of the study, we developed a prediction model to which the decision tree and ensemble methods were applied. And it was found that the mobile health service users' continued use can be induced by providing features that require frequent visit, suggesting achievable activity missions, and guiding the sensor connection for user's activity measurement.

• Journal of Information Technology Services
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• v.11 no.2
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• pp.19-47
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• 2012

Contemporary smartphone competition is generally described as the battle between Apple's proprietary platform and Google's open platform. However, this competition is not limited within smartphone adoption itself. User's pre-adoption of one mobile platform via smartphone can be connected to the post-adoption of the same mobile platform based on the other smart devices (e.g. smart pad). In this study, we investigate whether user's preference to a certain platform is persistent over mobile ecology, from the pre-adoption of one smart device to the post-adoption of following devices. For this investigation, we adopt the dual-model as the ground theory, where post-adoption of IT product is explained by both dedication and constraint factors. The empirical testing first evidences that dual model works well as our research model for identifying the reasons of post-adoption. Next, we group our data into two parts in order to compare the switching behavior of iPhone users and Android phone users. iPhone users show much lower switching rate to Android based smart pads, while Android phone users show higher churn rate to iPad (49.3% : 96.3%). Especially, satisfaction showed much stronger effect than switching cost on the continuing intention of existing platform, when the analysis is given to the iPhone user's group. From this result, we can conjecture the relatively stronger loyalty of iPhone users. More managerial implications on the mobile platform strategy are driven.

• Knowledge Management Research
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• v.23 no.1
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• pp.203-225
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• 2022

Competition in the OTT (Over the Top) service market is getting fiercer since global OTT services enter the domestic market and existing platforms are actively reorganized. As powerful competitors with ultra-luxurious content continue to enter the marke with diversity required by users, various efforts are required for OTT service platforms to prevent subscriber churn in order to generate continuous revenue. Thus, this study tried to examine the effect of OTT service characteristics on continuous use intention through an empirical analysis based on Expectation-Confirmation Model(ECM). A total of 386 responses were collected from individuals who have experience or are currently using OTT service and analyzed using AMOS 24. Results show that content curation, content richness, and audience activity had a significant effect on expectation confirmation. Also, expectation confirmation had a significant effect on perceived usefulness and user satisfaction while perceived usefulness had a significant effect on user satisfaction, significantly influencing continuous intention to use OTT. Finally, price fairness was found to strengthen all proposed relationships. The findings are expected to provide useful information for service and content development for subscriber retention, which has the most direct impact on revenue generation of OTT service providers.