• Asia Marketing Journal
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• v.24 no.2
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• pp.39-50
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• 2022

Live streaming has become one of the most important communication tools for influencers to synchronously interact with viewers. It is critical to understand the effect of the reciprocal and synchronously interactive relations built between influencers and viewers, so-called trans-parasocial relations, in the context of live streaming. In this study, we investigate how trans-parasocial relations impact viewers' stickiness and purchase intention on live streaming platforms. Furthermore, we investigate fanship as a mediating factor in the relationship between trans-parasocial relations and viewers' behaviors. Overall, the results reveal significant direct and indirect effects of trans-parasocial relations on viewers' stickiness and purchase intention. Higher trans-parasocial relations further lead to stronger viewers' fanship toward influencers and increases their willingness to stay longer or make purchases on live streaming platforms. These findings further the understanding of influencer-viewer relations and viewers' behavior on live streaming platforms and provide valuable insights into influencer marketing and live streaming.

• Journal of Distribution Science
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• v.22 no.10
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• pp.55-63
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• 2024

Purpose: This study explores the impact of interactivity and professionalism on consumer trust and purchase intentions in live-streaming distribution channels, explicitly focusing on Shopee Live in Indonesia. While prior research has examined trust as a general mediator between live-streaming features and consumer behavior, this study focuses on the distinct effects of trust in sellers versus in platforms. Utilizing the S-O-R framework, this research provides a novel exploration of how these trust dimensions act as an intermediary between live-streaming features and purchase intentions. Research Methods: Data were collected from 373 Shopee Live users who purchased fashion products via online surveys. The research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the proposed model and hypotheses. Results: Findings reveal that interactivity positively affects trust in both sellers and platforms but does not directly influence purchase intentions. Conversely, professionalism directly impacts purchase intentions and enhances trust. Trust in sellers and platforms significantly mediates the relationship between interactivity, professionalism, and purchase intentions. Specifically, trust in sellers substantially affects purchase intentions more than trust in platforms. Conclusion: The study concludes that while interactivity builds essential trust, professionalism directly drives purchase intentions, highlighting the importance of professional conduct in live-streaming distribution channel contexts.

• Asia pacific journal of information systems
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• v.34 no.2
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• pp.421-446
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• 2024

Through Information and Communication Technology (ICT), the growth of music streaming platforms has revolutionized music consumption. "Digital Shadow Work" (DSW) refers to unpaid labor in digital spaces, with some prior research on its aspects. However, a comprehensive understanding is hindered by limitations in existing studies such as a lack of universality and dynamic exploration. To address these gaps and enable a comprehensive investigation into the role of DSW within highly versatile digital applications such as digital streaming platforms, this study employs a grounded theory methodology, a qualitative approach well-suited for exploring the intricacies of DSW among users of Chinese music streaming applications over a two-month period, involving longitudinal interviews with nine participants. The study findings elucidate the dynamic nature of DSW perceptions, which fluctuate across different stages of use and change in intensity over time. This study uncovers mixed attitudes towards DSW tasks, and observes a waning enthusiasm for social features over time, prompting some users to consider switching platforms. This study highlights the importance of thoughtful and user-centric feature development to enhance user satisfaction and the understanding of DSW, providing practical design and enhancement implications for music streaming applications.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.98-100
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• 2005

This paper, proposes concept of personal robot middleware core also called streaming layer. Based on openness and portability, the streaming layer is proposed in order to meet requirements of different kinds of applications. The streaming layer architecture provides effective management of data flows and allows integration of different systems with ease regardless software of hardware platform. With extensibility support additional features can be build in without affect to performance. Therefore, heterogeneous network support, real-time communications, embedded boards support can be easily achieved. In order to achieve high performance together with portability into different platforms, the most functions has to be implemented in C language, while critical parts, such as scheduling, priority assignment has to be made using native functions of tested platforms.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.18-30
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• 2024

With the recent popularity and technological development of online streaming video, interactive digital narrative (IDN hereafter) videos became one of the main formats for users. The current study proposed that the level of interactivity of IDN videos influences users' evaluation of the video. The concept of flow was introduced as a mediating variable between interactivity and the users' evaluation. Further, the type of IDN videos, users' familiarity with IDN videos and trust toward platforms were employed as moderating variables. Data from a survey verified the mediating role of flow, moderating role of users' familiarity and trust toward platforms. the type of IDN videos, users' familiarity with IDN videos and trust toward platforms. We have observed a significant moderating effect of users' trust toward the platform on users' evaluation resulting from flow experience. It is evident that the higher the level of users' trust towards the platform, the less pronounced the impact of flow experience on users' evaluation. Theoretical and managerial implications are discussed.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.370-379
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• 2024

In this paper, we explore the historical development and revolutionary impact of music in mass media across various forms, including radio, television, film, and digital platforms. The evolution of music in mass media reflects significant technological and cultural shifts over the past century. From the early days of radio to the advent of digital streaming, music has played a crucial role in shaping the types of mass media. Early radio broadcasts in the 1920s relied on live performances and recordings to captivate audiences, establishing music as a central element of media content. The rise of television in the 1950s brought new opportunities for music integration, with theme songs, variety shows, and music videos becoming staples of TV programming. The film industry further revolutionized the use of music, with iconic scores enhancing cinematic storytelling and emotional depth. The digital revolution of the late 20th century introduced new formats and services, expanding access to music and transforming consumption patterns. Recently, streaming platforms and social media allow for personalized music experiences and direct artist-fan interactions. Through an analysis of technological advancements, this study highlights the integral role of music in enhancing narrative, evoking emotions, and creating cultural identities. We present our understanding of this evolution to provide insights into future trends and potential innovations in the integration of music with mass media, including the use of artificial intelligence and virtual reality to create immersive auditory experiences.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.94-99
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• 2024

In this paper, we aim to examine the recent state of the streaming industry in the U.S., and its future prospects as the most important force shaping the media landscape across the globe. First, we examine the launch of Disney's streaming services in late 2019 that heralded the start of the so-called streaming war to win subscribers and how the outbreak of COVID-19 in early 2020 helped its rapid growth. Then, we look at the crisis of the streaming industry in 2022, as subscriber growth slowed down for the first time and losses increased, and how this led to the growing emphasis on profitability. We also explore the subsequent attempts by streaming companies to cut costs and create more revenue, with the result that they were retreating from the previous strategy to grow their platforms at all costs. From this, we highlight that, while the future course of the streaming industry is not yet determined, the recent upheavals certainly made it more cost-conscious and conservative and less consumer-friendly.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.161-170
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• 2023

In this study, based on existing studies on music streaming services and e-services, the selection factors for music streaming platforms were derived, and the AHP technique was implemented to calculate the importance of each factor. As a result of this study, economic feasibility was found to be the most important factor among security, economic feasibility, informativeness, convenience, and responsiveness, which are the first-step selection factors of music streaming platforms. As a result of synthesizing the weights of the first and second factors, reasonable price was found to be the most important factor. Finally, an additional analysis was conducted to determine whether there was a difference in importance between the selection factors of the music streaming platform according to gender and age. Through this study, it will be possible to figure out the factors that consumers consider most important when using a music streaming platform.

• Asian Journal for Public Opinion Research
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• v.10 no.3
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• pp.254-259
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• 2022

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.53-60
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• 2023

Recently, the demand and traffic volume for various multimedia contents are rapidly increasing through real-time streaming platforms. In this paper, we predict real-time streaming traffic to improve the quality of service (QoS). Statistical models have been used to predict network traffic. However, since real-time streaming traffic changes dynamically, we used recurrent neural network-based deep learning models rather than a statistical model. Therefore, after the collection and preprocessing for real-time streaming data, we exploit vanilla RNN, LSTM, GRU, Bi-LSTM, and Bi-GRU models to predict real-time streaming traffic. In evaluation, the training time and accuracy of each model are measured and compared.