• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1621-1633
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• 2022

The present study aims to design an application for anger control training of individuals and test its practical usability with the goal of encouraging preventive training in daily life. This study also investigates, through usability evaluation, whether users can use the application to carry out the actual anger management training program, whether it is useful and convenient, and whether it produces adequate learning effects. In order to conduct usability evaluation, a usability evaluation scale comprised of six factors-utility, reuse intention, learning, error, and reflectivity-was derived, and survey items tailored to each factor were produced. The association between usability evaluation elements, user demographic parameters, mobile usage behavior, and state anger was also examined. The result demonstrated that additional menus and features are necessary to increase the usability of the application for anger management. The result also revealed that it is vital to build an intuitive application interface that users unfamiliar with mobile app functionality can easily navigate, as well as to add entertaining components in the content, as users may be somewhat bored. On the basis of the findings, ideas of modifying and creating anger management training programs were discussed.

• The Journal of Industrial Distribution & Business
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• v.9 no.1
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• pp.51-65
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• 2018

Purpose - This paper aims to identify factors that influence the users' word-of-mouth intention (WOMI) regarding mobile apps, focussing on the impacts of technology acceptance model (TAM) and social network theory. Research design, data and methodology - Based on TAM, this study integrates social network theory into the research model. The 317 sets of data collected in a survey were tested against the model using SmartPLS. Results - Our findings suggest the following: 1) Personal innovativeness positively influences perceived usefulness (PU), perceived ease of use (PEU) and perceived enjoyment (PE); 2) PEU affects PU and PE; 3) Both PU and Satisfaction are directly correlated with WOMI. Although PEU and PE has no direct impact on WOMI, they may indirectly affect WOMI via Satisfaction, as PU, PEU and PE all positively influence satisfaction; 4) Network density and network centrality both play a mediating role in the relation between PEU and WOMI. Referral Reward Program have a positive moderating effect on the relation between PU and WOMI. Conclusions - The findings of this study illustrate the traits of Apps that can promote users' WOMI, as well as the characteristics of people who are more likely to participate in the word-of-mouth process. The findings provide a theoretical basis for app developers to make word-of-mouth a marketing strategy.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.119-127
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• 2014

As the disclosure of privacy information has grown steadily, concerns about mobile services based on the personal information also increased. We aspired to reveal factors influencing the use of Location-Based services(LBS) App and analyse how the perceived risk affected between these factors and the use of LBS App. Results showed that usefulness and social influence influenced on the use of LBS App. We also found that the group who highly recognized the perceived risk was highly affected by usefulness and the group who lowly recognized the perceived risk was highly affected by social influence. Findings show that the company's strategy should be different depending on the level of consumers' perceived risk.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.279-290
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• 2022

The popularization of mobile Internet applications has accelerated the development of smart tourism industry. Based on TAM and VAM theories, this paper studies the influencing factors of tourism App users' willingness to continue using through complex network and data analysis methods. Through the research, it is found that the improvement of service level and design concept of smart tourism application can accelerate the aggregation of complex networks and improve user engagement. At the same time, reasonable price service experience value, convenience service experience value, interactive service experience value, emotional design perception, ease of use design perception, entertainment design perception and other factors can have a direct impact on users' intention to continue to use, and there is a significant correlation. The smart tourism App's convenience and price advantage are the root of its competitiveness. The design concept can affect users' emotional experience and perceptual experience, and help smart tourism App improve users' satisfaction.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.89-106
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• 2017

In advanced mobile devices environment, the market share of mobile application has been increased. Among various mobile services, Location-based Service (LBS) is an important feature to increase user motivation related to purchase intention on mobile. However, individual privacy has also increased as an important problem for invasion of privacy and information leakage while too many LBS based applications (App) rapidly launched in the App market. In this study, we focused on perceived values of LBS App users who use Apps related to recommending best restaurants in China and South Korea. The purpose of this study is to identify important factors for perceived value when users provide personal information for LBS service provider. The result of this study is follows: perceived value can increase while LBS customers can more control self-information and information useability. Also information ability of users affected perceived values for LBS Apps. Also users' app user ability and perceived value were effects on privacy revenue. In addtion, perceived weakness of users and perceived value increased privacy threat.

• Fashion & Textile Research Journal
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• v.23 no.5
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• pp.611-623
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• 2021

In the era of COVID-19 and advanced ICT technology, retail technologies such as those that use virtual reality(VR) have been drawing significant attention in the fashion industry. This study investigated the impact of shopping motivation and telepresence on consumer attitude, trust, and behavioral intentions in VR fitting room application environments. An online survey was conducted on female consumers in their 20s and 30s after exploring a VR fitting room application. Overall, 225 responses were used for the analysis. The study demonstrated that usefulness had a significant effect on attitude toward product (ATP) and trust toward app (TTA), while enjoyment had a significant effect on ATP, but did not significantly affect TTA. Telepresence did not significantly affect TTA, but had a significant influence on ATP and behavioral intention. TTA had a significant influence on ATP, and both ATP and TTA had significant effects on behavioral intention. Moreover, the effects of usefulness, enjoyment, and telepresence on ATP, TTA, and behavioral intention were significant, as the self-congruity between consumers and avatars increased. The application of the motivation theory and technology acceptance model offers theoretical perspectives for understanding VR fitting room application users' attitudinal and behavioral responses in mobile shopping environments. In addition, this study provides practical implications to mobile retailers that utilize advanced technologies.

• Information Systems Review
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• v.24 no.2
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• pp.41-66
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• 2022

With the development of IT, mobile apps and the expansion of contactless services due to COVID-19, "smart orders" have recently been activated in the food and beverage service. Even in recent years, when sales have declined, the number of orders made by smart orders has been steadily increasing, and this ordering method can accumulate customer data, enabling effective customized services in the future. In the present study, satisfaction with smart orders and continuous use intention were studied based on the technology acceptance model (TAM). And it focused on whether there is a difference in personality when using smart orders. For this purpose, a survey was conducted on 317 smart order users, and the hypothesis was verified by structural equation model analysis. Perceived benefits had a significant effect on satisfaction; also, satisfaction had a significant effect on continuous use intention. There is a significant disparity between introvert and extrovert type. As a consequence, the introverted type has a greater intention to perceive usefulness of smart orders and continuously use them. These results suggest that the customer's personality type should be considered in future customer customization strategies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.143-153
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• 2017

This was a descriptive survey to determine the intention of users to use smartphone healthcare applications (SHAs) and to clarify factors that may influence such intention. The data were collected during the month of April in 2015, using a structured self-report questionnaire that was distributed to 300 participants aged 20 to 70 years; 285 complete copies were used for the final analysis. The data were analyzed using descriptive statistics, independent t-test, one-way ANOVA, Pearson correlation coefficients, and hierarchical multiple regression. First, according to the results, the average intention to use SHAs was 3.28 out of 5, which varied according to age, final education, economy level, vacation, current disease, total period of smartphone use, and etc. Second, significant correlations were shown by exercise behavior, dietary management behavior, stress management, satisfaction with smartphone use, and satisfaction with using SHAs. Third, the explanatory power of the predictive model involving all general, health-related, smartphone use-related, and SHA use-related factors was 45.5%; and the economic level, interest, status, and awareness satisfaction of patients using SHA were identified to be the main influential factors. The results indicate that SHA developers need to put efforts into improving consumers' app recognition and to develop plans in provoking consumers' interests to increase the use of SHAs.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.