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Despite the growing adoption of the mobile health (mHealth) applications (apps), few studies address concerns with low retention rates. This study aimed to investigate how the usage patterns of mHealth app functions affect user retention. We collected individual usage logs for 1,439 users of single tethered personal health record app, which spanned an 18-months period from August 2011 to January 2013. The user logs contained timestamps whenever an individual uses each function, which enables us to identify the usage patterns based on the intensity of using a particular function in the app. We then estimated how these patterns were related to 1) the app usage over time (using the random effect model) and 2) the probability of stopping the use of the application (using the Cox proportional hazard model). The analyses suggested that the users utilize the app most at the time of the adoption and gradually reduce their usage over time. The average duration of use after starting the app was 25.62 weeks (SD: 18.41). The degree of the usage eduction, however, decreases as the self-monitoring function is more frequently used (coefficient = 0.002, P = 0.013); none of the other functions has this effect. Moreover, engaging with the self-monitoring function frequently (coefficient = −0.18, P = 0.003) and regularly (coefficient = 0.10, P = 0.001) significantly also reduces the probability of abandoning the application. Specifically, the estimated survival rate indicates that, after 40 weeks since the adoption, the probability of the regular users of self-monitoring to stay in use was about 80% while that of non-user was about 60%. This study provides the empirical evidence that sustained use of mHealth app is closely linked to the regular usage on self-monitoring function. The implications can be extended to the education of users and physicians to produce better outcomes as well as application development for effective user interfaces.
In 1982, Betamax, the world’s first personal recording service was ruled as a fair use in court. Although the copyright holders of TV content claimed that Betamax was an infringement of copyright, the court determined that the benefits of personal recording services were significant and that the copyright holder’s profits could be protected because the original service was of better quality and had a better cost structure. It also ruled that the loss from manual advertisement skip was minimal. However, recent advancements in information technology have allowed new kinds of personal recording services such as a cloud DVR that provides unlimited storage and flawless quality, and an Auto-hop feature that automatically removes embedded advertisements. This paper introduces a microeconomic model for reviewing the copyright holder’s business model and social welfare under the court’s decision in relation to newer personal recording services powered by information technologies. Before cloud DVR existed, applying fair use to personal recording services increased social welfare while protecting the copyright holder’s profits; however, after the introduction of cloud DVR, it may no longer do so.
This paper suggests a computational model which investigates the sustainability of MMORPGs from the social distance perspective by considering the major differences of the virtual world in an MMORPG and the real world. The effects of social distance on the actual playtime are empirically tested. The analysis results suggest that social distance can initiate positive feedback of abandonment, resulting in the rapid collapse of the number of players. Increasing uncertainty in rewarding players’ effort may have better results for MMORPG managers in the long run since the managers care about profits, not social welfare. Also, a fine- tuned retirement plan may be vital to MMORPG sustainability, because MMORPG players usually do not retire by natural causes such as growing old. This paper offers a relatively new approach by combining characteristics of MMORPG and social distance with both a computational model and empirical support.
This research investigates the interaction effects of factors, namely, advertiser awareness, advertisement appeal, and customer involvement and need for cognition, selected from the parties involved in public service advertisement. Manipulating the participant’s involvement, attitude toward the advertisement and the advertiser and intention to donate according to 2 (awareness) X 2 (cognitive/affective appeal) factors were surveyed. In result, participants with high involvement were relatively less affected by advertiser awareness. Also, high need for cognition indicated less effect of advertiser awareness on intention to donate. Moreover, when cognitive appeal is used, advertiser awareness affected less on consumers’ attitude toward the advertisement and the advertiser and intention to donate. Further issues on changing customers’ attitudes and behaviors are discussed.
The Korean government enforced the shutdown system for children aged under 16, starting from November 20th, 2011. Based on data from a Korean social game company, we found the structural change of play time of the user and the difference of network effects among two different groups. The results show that the enforcement of the shutdown system makes the structural change for play time of users. There is a negative network effect on play time for users, and when the policy is implemented, network effect gets worse as more people are online, users play the game less. This study shows some interesting implications for the characteristics of users on social game.
Society sometimes suffers from the erroneous valuation of very large scale, like the Enron incident. Since any individual reasonable risk evaluation or existence of greedy arbitragers should have prevented such long-term, large scale valuation errors, such events are often considered as a matter of errors of the valuation system. This study suggests a computational model that describes interactions such as emergence and feedback, between individual valuation behavior and group behavior, which discovered a clear and distinctive pattern that the group's valuation may seem to converge into a consensus, even if it is not real. The model is a relatively new approach in explaining valuation behavior, linking individual decision and group behavior with a feedback mechanism. Implications from the analysis can be helpful to managers who handle complex and uncertain goods.
Apparatus for recommending game contents based on the psychology of a game user and an operation thereof
Apparatus for data preprocessing for classifying the psychology of a game user and an operation thereof
Data security maintenance method for data analysis application
Data security maintenance method for data analysis application
Apparatus for proving information about marketing performance contribution and method of assessing marketing performance by multi-channel encounter
Apparatus for data preprocessing for classifying the psychology of a game user and an operation thereof
Apparatus for recommending game contents based on the psychology of a game user and an operation thereof
Apparatus for generating standardized table for classifying the psychology of a game user and an operation thereof
