• Journal of Digital Convergence
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• v.13 no.6
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• pp.327-339
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• 2015

The present study explored how 1) individuals' perception about attributes of exercise/fitness apps and 2) their motivation for exercise/fitness behaviors influence perceived usefulness and usage of the apps. A survey of 323 males and females in their 20's and 30's revealed that attributes of apps that satisfy their basic psychological needs are crucial in promoting perceived usefulness and usage of the apps. Participants were more likely to perceive exercise/fitness apps useful as they perceive them having more attributes related to autonomy and competence. The perception regarding relatedness attributes did not have the main effect on perceived usefulness but showed an interaction effect with relative autonomous motivation. This convergence study which examined health apps from the perspectives of psychology and public health provides practical implications to development and evaluation of health apps.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.12-22
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• 2016

The present study aims to evaluate the self-determined motivational features of smartphone addiction management apps. This study analyzed whether smartphone addiction management apps have features to support adolescent users' basic needs, that is, autonomy, competence, and relatedness. 26 apps were analyzed. Among them, 8 apps were parental management apps installed on a parent's phone and a child's phone, and 18 apps were self-management apps installed on a child's phone. According to a content analysis, only 3 of 26 apps addressed all three basic needs. Overall, the functions to support users' competence and relatedness were rarely found. Particularly, parental management apps had a high level of controlingness. The results suggest that the addiction management apps have limitations in stimulating adolescent users' self-determined motivation to manage their phone use.

• Information Systems Review
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• v.18 no.2
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• pp.107-125
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• 2016

With the rapid growth of the mobile application market, mobile donation applications have emerged as a new type of application that enables users to donate without actual payments. To date, limited research has been conducted to provide guidelines on how to design new types of mobile donation applications. Using cause-related marketing theory as theoretical framework, this study aims to identify the features of mobile donation applications that increase the intention of users to use such applications. To achieve this goal, we conducted two experiments. The results of an ANOVA test in the first experiment showed that indirect mobile donation applications (i.e., applications without actual payment) have a stronger positive effect on perceived effectiveness and cause involvement than direct mobile donation applications (i.e., applications with actual payment). In addition, perceived effectiveness and cause involvement yield positive effects on the intention to use mobile donation applications. The results of the second experiment showed that indirect mobile donation applications with utilitarian functions have a greater positive effect on perceived effectiveness and cause involvement than mobile donation applications with hedonic functions. These results contribute to mobile application and donation research as well as provide guidelines for practitioners on the design of mobile donation applications.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.615-620
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• 2013

With the development of smartphones, the number of applications for smartphone increases sharply. As a result, users need to try several times to find their favorite apps. In order to solve this problem, we propose a recommendation system to provide an appropriate app list based on the user's log information including time stamp, location, application list, and so on. The proposed approach learns three recommendation models including Naive-Bayesian model, SVM model, and Most-Frequent Usage model using temporal and spatial attributes. In order to figure out the best model, we compared the performance of these models with variant features, and suggest an hybrid method to improve the performance of single models.

• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.103-119
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• 2012

In this paper, we conducted for information search process of users, who have experience to buy paid-application in Appstore, to find out difference of information searching efforts and information sources, reliance on the information in term of attributes of Apps and buyes' innovativenss. As a result, Innovative buyers take a effort to search various information source but they get help buying decision-making supports by own their efforts like searching in category. On the other hand, non-Innovative buyers who search informtion less than Innovative buyers, get information like recommendation from friend and Apps, then they keep those information help buying decision-making supports highly. Besides buyers of Utility Apps search on objective information sources mainly, but those sources have influence on buying decision-making supports. On the other side buyers of Enjoyment Apps consider reliance on the information more than information searching efforts to buying decision-making supports as they get information source like popularity. This research suggests operators of Appstore and app developers how to promote their Apps to users.

• 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 Korea Society of Computer and Information
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• v.25 no.12
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• pp.305-313
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• 2020

In this paper, We Propose a ways how franchise service of delivery app should be made by analyzing the effect of delivery app usage properties of food service franchisee on satisfaction, business performance and intention of reusing, and suggest support plan of delivery app for franchise by food service franchisee. This study conducted survey on 212 franchises that have experience using delivery app among food service franchisees. To verify the hypothesis of the study, single regression and multiple regression analysis were conducted for verifying the relationship between variables. Key results of the study are as follows. First, it was found that the delivery app usage properties of food service franchisee had a positive relationship with satisfaction. Second, it was found that the delivery app usage properties of food service franchisee had positive relationship with business performance. Third, the satisfaction was found to affect business performance. Fourth, it was found that the satisfaction didn't affect the intention of reusing, and business performance was found to have a positive effect on the intention of reusing. It is necessary to increase the satisfaction of using of franchises through continuous management and reasonable pricing policies, and the headquarter of franchisee should be able to contribute to energetic sales of franchises through effective cooperation with delivery app companies.

• Journal of Digital Contents Society
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• v.13 no.4
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• pp.559-565
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• 2012

The remarkable development of IT is contributed to popularization of smart phones, which in turn creates a new domain called app store. Smartphone apps have grown fast because they can be easily purchased through an app store. As the volume of apps traded in app stores is so huge that it is extremely hard for users to find the exact app they want. In general, an app store recommends an app to users based on the search words they entered. In terms of recommendation of app, this kind of content-based method is not effective. To increase accuracy in recommending app, this paper proposes a characteristic similarity-based app recommendation method. This method creates attributes on the app based on the related information such as genre, functionality and number of downloads and then compares them with the propensity to use the app. According to diverse simulations, the method proposed in this paper improved the performance of app recommendation by 33% in average, compared to the conventional method.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.259-266
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• 2023

In this paper, we propose an algorithm that can improve the accuracy performance of collaborative filtering using attribute-based opinion mining (ABOM). For the experiment, a total of 1,227 online consumer review data about smartphone apps from domestic smartphone users were used for analysis. After morpheme analysis using the KKMA (Kkokkoma) analyzer and emotional word analysis using KOSAC, attribute extraction is performed using LDA topic modeling, and the topic modeling results for each weighted review are used to add up the ratings of collaborative filtering and the sentiment score. MAE, MAPE, and RMSE, which are statistical model performance evaluations that calculate the average accuracy error, were used. Through experiments, we predicted the accuracy of online customers' app ratings (APP_Score) by combining traditional collaborative filtering among the recommendation algorithms and the attribute-based opinion mining (ABOM) technique, which combines LDA attribute extraction and sentiment analysis. As a result of the analysis, it was found that the prediction accuracy of ratings using attribute-based opinion mining CF was better than that of ratings implementing traditional collaborative filtering.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.165-175
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• 2022

The objective of this study is to identify the relationships among app attribution(perceived usefulness, design, information quality, and mobility), user satisfaction, trust, and continuous use intention of bus information apps; The structural equation of AMOS 21.0 was used to test the hypothesis of this study. The results of the analysis are as follows. First, perceived usefulness, design, information quality, and mobility positively impact user satisfaction. Second, only mobility has a positive effect on trust, but the remaining perceived usefulness, design, and information quality have no effect at the significance level of 5%. Third, user satisfaction has a positive impact on trust and continuous use intention. Fourth, trust has a positive impact on continuous use intention. Therefore, it was confirmed that the characteristics of the bus information mobile app are important influencing factors for the improvement of user satisfaction, trust, and continuous use intention. Local governments and bus companies will be able to establish strategic directions for the activation of bus information mobile apps. The limitation of this study is that it is somewhat lacking in generalizing the study results, so future research needs to focus on improving this part.