• Knowledge Management Research
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• v.17 no.1
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• pp.17-47
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• 2016

People use social network services (SNSs) for various purposes, for example, to share information, to express themselves, and to strengthen social relationships with others. Meanwhile, problems of personal information leakage and privacy infringement become a social issue and thus information privacy concerns about inappropriate collection and use of personal information increase in SNSs (e.g., Facebook). Although people have privacy concerns in SNSs, they behave in a contradictory way, voluntarily presenting themselves and disclosing personal information. This phenomenon is called 'privacy paradox'. Using dual factor theory, this study investigates the phenomenon of privacy paradox by looking into enablers (e.g., self-presentation) and inhibitors (e.g., information privacy concern) for continuous use of Facebook that can co-exist independently of each other. It also includes antecedents of self-presentation (i.e., narcissism, need for affiliation, involvement, and self-efficacy) and those of information privacy concern (i.e., previous experience of privacy infringement, privacy awareness, and privacy control). The results show that most hypothesized relationships were supported. These findings provide strategic implications for SNS providers who want to promote continuous use of SNS. Under the current circumstances in which enhanced privacy policies are required, this study would be a useful reference for future research on information privacy issues in SNSs.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.129-135
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• 2018

In this study, we designed a model that can measure the level of user's concentration by measuring and analyzing EEG data of the subjects who are performing Continuous Performance Test based on visual stimulus. This study focused on alpha and beta waves, which are closely related to concentration in various brain waves. There are a lot of research and services to enhance not only concentration but also brain activity. However, there are formidable barriers to ordinary people for using routinely because of high cost and complex procedures. Therefore, this study designed the model using the portable EEG measurement device with reasonable cost and Visual Continuous Performance Test which we developed as a simplified version of the existing CPT. This study aims to measure the concentration level of the subject objectively through simple and affordable way, EEG analysis. Concentration is also closely related to various brain diseases such as dementia, depression, and ADHD. Therefore, we believe that our proposed model can be useful not only for improving concentration but also brain disease prediction and monitoring research. In addition, the combination of this model and the Brain Computer Interface technology can create greater synergy in various fields.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.456-457
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• 2021

Recently, in order to more accurately provide indoor location-based services, technologies using Wi-Fi fingerprints and deep learning are being studied. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. When using an RNN model for indoor positioning, the collected training data must be continuous sequential data. However, the Wi-Fi fingerprint data collected to determine specific location information cannot be used as training data for an RNN model because only RSSI for a specific location is recorded. This paper proposes a region clustering technique for sequential input data generation of RNN models based on Wi-Fi fingerprint data.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.1-18
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• 2024

This study analyzed the impact of YouTube creator characteristics and channel access factors on the intention to continue watching content, noting that the development of the digital media environment has diversified media audiences' content preferences and access routes. Specifically, we analyzed the effects of YouTube creator trustworthiness, attractiveness, familiarity, and social influence, as well as the effects of recommendation services on perceived usefulness, perceived ease, and perceived enjoyment. The study found that creator credibility and recommendation service had a positive impact on the perceived usefulness of content, while intimacy and charm were important factors in increasing the easy of use and playfulness of content. These perceived usefulness, ease, and playfulness also had a strong positive impact on users' intention to continue watching the channel. This suggests that trust and intimate relationships with creators and appropriate content recommendations play an important role in increasing user satisfaction and channel persistence. The significance of this study's analysis of creator and channel access factors based on the extended technology acceptance model is that it shows the potential for extending and applying the existing technology acceptance model to the digital content environment.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.11-28
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• 2015

Due to the mobil-centered lifestyle following the wider use of Smartphones, Mobile services, including mobile banking and mobile shopping business have increased rapidly. Also with the emergence of "Fintech", which finance combined with technology, IT based financial market is going to be highly promising. In this trend, interests mobile credit cards are increasing. But diffusion of the mobile credit card services is still in the low level. In this situation, to identify factors that influencing satisfaction and continuous usage intention on mobile credit card, this study applied innovation diffusion theory (IDT) and post acceptance model (PAM). To conducting this research, survey data were collected, and we used SmartPLS to analyze survey data. As a result of the study, perceived easy of use, image, compatibility and facilitation positively affect user's satisfaction in mobile credit cards and that such satisfaction have a positive impact on continuous intention to use. The facilitation influences user satisfaction more strongly for those who use mobile credit cards more than plastic credit cards. Also, perceived of use and image influence user satisfaction more strongly for those who use plastic credit cards more than mobile credit cards. It is expected that this study can be a guideline for credit card service providers and policy makers to invigorate mobile credit card business. Also it worths as a early-stage research on Fintech-related studies.

• Information Systems Review
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• v.17 no.3
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• pp.135-157
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• 2015

Mobile giving platform is a new type of giving platform which offers donation service through mobile application. Mobile giving platform has developed differently from offline giving platform in the way that induces continuous donation. The purpose of this study is to investigate why mobile giving platform has adopted different strategy, and how it leads to continuous contribution. We conducted a case study with two successful mobile giving platforms; Bigwalk and Tree Planet. The analysis of the strategy is based on the construal level theory which explains the relationship between psychological distance and construal level. The result shows that the users' psychological distance toward giving platform has decreased with the environmental change, offline to mobile. Consequently the mobile giving platform offers services which form low level of construal for encouraging continuous participation. This finding suggests the importance of offering suitable construal level in services, and design guideline for mobile giving platforms.

• 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.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.30-42
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• 2015

In this paper, we propose a new skyline query processing scheme to enhance accuracy of query processing and communication cost in mobile P2P environments. The proposed scheme consists of three stages such as the pre-skyline processing, the query transmission range extension policy, and the continuous skyline query processing. In the pre-skyline processing, a peer selects the candidate filtering objects who have the potential to be selected. By doing so, the proposed scheme reduces the filtering cost when processing the query. In the query transmission range extension policy, we have improved the accuracy by extending the query transmission range. In addition, it can handle continuous skyline query by performing the monitoring after the first skyline query processing. In order to show the superiority of the proposed method, we compare it with the existing schemes through performance evaluation. As a result, it was shown that the proposed scheme outperforms the existing schemes.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.691-700
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• 2004

This paper proposes a user's mobility based cooperative proxy caching policy for effective resource management of continuous media objects in mobile environments. This policy is different from the existing proxy caching policies in terms of how to exploit users' mobility. In other words, existing caching policies work based on the information about objects by referring to user's requests within a specified domain whereas the proposed caching policy runs by utilizing a number of user's requests across several domains. So, the proposed policy is applicable to random requests in mobile environments Moreover, we also propose a replacement policy based on weights and playback time. To check the efficiency of the proposed caching policy, the proposed replacement policy is run with different size of caching unit object or segment. The result of performance analyze tells what a ratio of user's mobility is are major factors for the efficient operation of the cooperative caching.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.93-105
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• 2012

A data stream is a series of tuples which are generated in real-time, incessant, immense, and volatile manner. As new information technologies are actively emerging, stream processing methods are being needed to efficiently handle data streams. Especially, finding out an efficient evaluation for a multi-way join would make outstanding contributions toward improving the performance of a data stream management system because a join operation is one of the most resource-consuming operators for evaluating queries. In this paper, in order to evaluate efficiently a multi-way join continuous query, we propose a novel method to decrease the cost of a query by eliminating unsuccessful intermediate results. For this, we propose a matrix-based structure for monitoring data streams and estimate the number of final result tuples of the query and find out unsuccessful tuples by matrix multiplication operations. And then using these information, we process efficiently a multi-way join continuous query by filtering out the unsuccessful tuples in advance before actual evaluation of the query.