• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.623-628
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• 2021

The paid knowledge platforms market is growing rapidly due to the constant demand for high-quality knowledge and a change in the positive perception of paid contents. Among them, the growth of paid knowledge platforms in China is overwhelming. The various paid knowledge platforms have emerged in China over the years, and Zhihu occupies the largest share among them. There have been some studies on paid knowledge platforms in China, but studies centered on Zhihu were relatively insufficient, so I conducted the research on Zhihu. In this paper, the development status of China's paid knowledge platform was investigated, the functions provided to users based on the menu configuration of the Zhihu app were analyzed and the business model of Zhihu was explored. In addition, the features of Zhihu were analyzed. It is expected that this paper will be an important data for research on paid knowledge platform.

• Knowledge Management Research
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• v.23 no.3
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• pp.285-311
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• 2022

In this study, based on the S-O-R framework, how individual's stimuli (i.e., video characteristics, YouTuber characteristics, real-time broadcasting characteristics of YouTube channel) form organisms (i.e., perceived usefulness, perceived pleasure, social presence), leading to viewers' responses (i.e., continuous watching intention, paid sponsorship intention) on real-time YouTube channels. For this purpose, a research model and hypotheses were constructed, and 369 questionnaire data collected from users of real-time broadcasting channel services on the YouTube platform were analyzed. Result findings confirmed that some video/YouTuber/real-time broadcasting characteristics significantly affect viewers' perceived usefulness/perceived pleasure/social presence, and further influence continuous watching/paid sponsorship intentions. Theoretical and practical implications of the findings are discussed in conclusion.

• Knowledge Management Research
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• v.24 no.4
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• pp.63-85
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• 2023

This study aims to identify the primary user group in the growing metaverse space based on the increased interest during the COVID-19 era. It also aims to explore the predictive factors for metaverse adoption. To predict online activities, the study examined user purposes, motivations, and relevant demographic factors as predictive variables through model analysis. The data from the Korean Media Panel Survey were used, and a two-stage analysis with the Heckman two-stage sample selection model was conducted to predict metaverse users. The analysis revealed that the key factors influencing metaverse adoption were offline activities, openness, OTT usage, and purchasing of paid content. Moreover, in the second stage model, openness, gender, and paid content purchases were identified as significant variables for increasing metaverse usage time. These results indicate that understanding metaverse users is essential in the context of the rising interest in online activities during the COVID-19 era and can provide valuable insights for metaverse platform-related companies and developers.