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Blockchain-enabled Q&A communities: the impact of task technology matching on willingness to share knowledge

  • S.I.: Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT 2022)
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

Online Q&A communities provide Internet users with an online platform for knowledge dissemination, communication and sharing. The characteristics of blockchain technology, such as untampered, traceability, and data up-chaining, can help solve the problems of knowledge privacy protection, affirming knowledge Ownership, and trust deficit faced by users when sharing knowledge in traditional online Q&A communities, and enhance users’ willingness to share knowledge on the platform. Studying users’ perceived characteristics and usage attitudes toward blockchain embedded in online platforms is important for enhancing users’ willingness to share knowledge and exploring the management mechanism of blockchain technology on online platforms. Based on the task-technology matching theory and technology acceptance model, this paper explores the impact of task-technology matching on users’ perceived characteristics and digs deeper into how users’ perceived characteristics of blockchain technology affect users’ usage attitudes and thus stimulate users’ willingness to share knowledge. Task-technology matching also positively influences users’ willingness to share knowledge by positively affecting perceived characteristics and users’ attitudes toward using. The findings of the study provide inspiration and guidance on how platforms can use new technologies to enhance users’ willingness to share knowledge.

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Data availability

The datasets used during the current study are available from the corresponding author upon reasonable request.

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Funding

The author(s) received support for the National Nature Foundation, “Research on Knowledge Transmission Mechanism of Mobile Social Network wechat” (71571022, 2016.01–2019.12) in researching, writing and/or publishing this article.

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  1. Beijing University of Posts and Telecommunications, 10 Xitucheng Road, Haidian District, Beijing, China

    Shengtai Zhang, Wenjuan Shi & Mengtao Zhang

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  1. Shengtai Zhang
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  2. Wenjuan Shi
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  3. Mengtao Zhang
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Correspondence to Wenjuan Shi.

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Zhang, S., Shi, W. & Zhang, M. Blockchain-enabled Q&A communities: the impact of task technology matching on willingness to share knowledge. Neural Comput & Applic 36, 2171–2186 (2024). https://doi.org/10.1007/s00521-023-08618-6

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  • DOI: https://doi.org/10.1007/s00521-023-08618-6

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