Skip to main content
Springer Nature Link
Log in

Factors Influencing Chinese Users’ Willingness to Pay for O2O Knowledge Products Based on Information Adoption Model

  • Conference paper
  • First Online:
Big Data and Security (ICBDS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1796))

Included in the following conference series:

  • 503 Accesses

Abstract

The China’s knowledge payment industry has entered the “pan-knowledge payment” period, and the overall situation of industry is gratifying. O2O paid knowledge platforms, which are not under the public media spotlight, are also developing slowly. The non-standardized knowledge services provided by this type of platform have a unique charm that standardized online knowledge payment products do not have because they can be personalized and socially interacted on site, and their business value is worthy of attention. The research issue of this paper is what factors influencing users’ willingness to pay can be identified and verified using statistical models from the user behavior and content information available on a typical China’s O2O paid knowledge platform. From the perspective of Information Adoption theory, we construct a model of the factors influencing the willingness to pay for O2O paid knowledge products, which includes two aspects: information quality and source credibility. We collected a total of 9,907 actual behavioral data and topic data from users of the China’s O2O paid knowledge platform, “Zaih.com”, and used log-linear regression model to verify the hypotheses. The results show that: in terms of information quality, content integrity, information relevance, information applicability and interactive empathy have significant positive effects on users’ willingness to pay; in terms of credibility of information sources, the expertise and attractiveness of knowledge providers indicated by integrity of their profile and their high level residence have significant positive effects on users’ willingness to pay. The above findings have important guiding implications for the three parties of O2O knowledge payment, especially for the service improvement and personal development of knowledge providers of this type of platform.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. iResearch China. 2019 China Knowledge Services Industry Survival Strategy Guidelines [EB/OL] http://report.iresearch.cn/report_pdf.aspx?id=3467, 2019-11-7/2021-9-1 (2019)

  2. iiMedia Consulting. Trafficking in anxiety? The current dilemma and trend analysis of the development of China’s knowledge payment industry in 2020[EB/OL]. https://www.iimedia.cn/c1020/69216.html, 2020-2-21/2020-3-17 (2020)

  3. Analysys Consulting. China Pan Knowledge Payments Market Thematic Analysis 2019 [EB/OL]. https://www.analysys.cn/article/detail/20019604, 2019-12-13/2021-9-1 (2019)

  4. Liu, Q., Wang, W., He, G.: Research on user choice behavior of offline knowledge payment platform based on social capital theory. Res. Libr. Sci. (22), 34–41 (2019) (in Chinese)

    Google Scholar 

  5. Zhang, S., Wang, W., Li, J.: Research on the influencing factors of users online knowledge payment behavior. Libr. Inf. Serv. 61(10), 94–100 (2017). (in Chinese)

    Google Scholar 

  6. Yang, X., Hu, X.: Factors influencing knowledge payment behaviors on chinese mobile internet from a MOA perspective: taking Ximalaya FM for example. New Century Libr. 10, 29–36 (2019). (in Chinese)

    Google Scholar 

  7. Dou, W.: Will internet users pay for online content? J. Advert. Res. 44(4), 349–359 (2004)

    Article  Google Scholar 

  8. Wang, C.L., Zhang, Y., Ye, L.R., et al.: Subscription to fee-based online services: what makes consumer pay for online content? J. Electron. Commer. Res. 6(4), 304–311 (2005)

    Google Scholar 

  9. Punj, G.: The relationship between consumer characteristics and willingness to pay for general online content: implications for content providers considering subscription-based business models. Mark. Lett. 26(2), 175–186 (2013)

    Article  Google Scholar 

  10. Cai, S., Shi, H.R., Fu, X., et al.: Paying for knowledge in online community: an ex-ploratory study for Zhihu live. J. Ind. Eng./Eng. Manage. (03), 71–83 (2019) (in Chinese)

    Google Scholar 

  11. Zhao, Y., Zhao, Y., Yuan, X., et al.: How knowledge contributor characteristics and reputation affect user payment decision in paid Q&A? An empirical analysis from the perspec-tive of trust theory. Electron. Commer. Res. Appl. 31, 1–11 (2018)

    Article  Google Scholar 

  12. Goyanes, M.: An empirical study of factors that influence the willingness to pay for online news. Journal. Pract. 8(6), 742–757 (2014)

    Article  Google Scholar 

  13. Zhang, Z., Deng, Y.: The factors affecting the willingness to pay for knowledge payment behavior. Mod. Educ. Technol. (11), 86–92 (2018) (in Chinese)

    Google Scholar 

  14. Chen, H., Jiao, W., Li, W.: Empirical study on consumer’s intention to purchase knowledge services-a trial perspective. J. Mod. Inform. (2), 136–143 (2019) (in Chinese)

    Google Scholar 

  15. Sussman, S.W., Siegal, W.S.: Informational influence in organizations: an integrated approach to knowledge adoption. Inf. Syst. Res. 14(1), 47–65 (2003)

    Article  Google Scholar 

  16. Zhang, Y., Li, Z., Zhao, Y.: How the Information quality affects the online review usefulness—An empirical analysis based on Taobao review data. Chin. J. Manage. 14(01), 77–85 (2017). (in Chinese)

    Google Scholar 

  17. Li, J., Qi, X., Chen, M.: Understanding the Impact of perceived information quality on information acquisition and information adoption. Inf. Sci. (3), 123–129 (2015) (in Chinese)

    Google Scholar 

  18. Petty, R.E., Cacioppo, J.T.: The elaboration likelihood model of persuasion. In: Communication and persuasion, pp. 1-24. Springer, New York, NY (1986)

    Google Scholar 

  19. King, W.R., He, J.: A meta-analysis of the technology acceptance model. Inf. Manage. 43(6), 740–755 (2006)

    Article  Google Scholar 

  20. Petty, R.E., Cacioppo, J.T.: The effects of involvement on responses to argument quantity and quality: central and peripheral routes to persuasion. J. Pers. Soc. Psychol. 46(9), 135–146 (1984)

    Google Scholar 

  21. Petty, R.E., Cacioppo, J.T.: Communication and persuasion: central and peripheral routes to attitude change. Springer Science & Business Media (2012)

    Google Scholar 

  22. Boritz, J.E.: IS practitioners’ views on core concepts of information integrity. Int. J. Account. Inf. Syst. 6(4), 260–279 (2005)

    Article  Google Scholar 

  23. Connelly, B.L., Certo, S.T., Ireland, R.D., et al.: Signaling theory: a review and assessment. J. Manag. 37(1), 39–67 (2011)

    Google Scholar 

  24. Dunk, A.S.: Product life cycle cost analysis: the impact of customer profiling, competitive advantage, and quality of IS information. Manag. Account. Res. 15(4), 401–414 (2004)

    Article  Google Scholar 

  25. Wixom, B.H., Todd, P.A.: A theoretical integration of user satisfaction and technology acceptance. Inf. Syst. Res. 16(1), 85–102 (2005)

    Article  Google Scholar 

  26. Xu, J., Li, Q., Zhang, J.: The impact of information quality on customer information adoption behavior and information quality improvement in shared services platform. Inf. Sci. 37(05), 148–154 (2019). (in Chinese)

    Google Scholar 

  27. Zhao, Y., Liu, Z., Song, S.: Exploring the influencing factors of askers’ intention to pay in knowledge Q&A platforms. Data Anal. Knowl. Disc. (8), 16–30 (2018) (in Chinese)

    Google Scholar 

Download references

Acknowledgements

This paper is supported by the National Natural Science Foundation of China (No. 72171102), Major Projects of Jiangsu Universities Philosophy and Social Science (No.2021SJZDA178), the Open Research Fund of Jiangsu Collaborative Innovation Center for Smart Distribution Network, Nanjing Institute of Technology (No. XTCX202212), the Open Research Fund of NJIT Institute of Industrial Economy and Innovation Management (No. JGKA202202).

Author information

Authors and Affiliations

  1. School of Economics and Management, Nanjing Institute of Technology, Nanjing, 211167, China

    Zhu Zhentao, Yue Wen & Zhang Yan

  2. School of Electrical Engineering, Nanjing Institute of Technology, Nanjing, 211167, China

    Wu Qiuchi

Authors
  1. Zhu Zhentao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yue Wen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhang Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wu Qiuchi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhu Zhentao .

Editor information

Editors and Affiliations

  1. Nanjing Institute of Technology, Nanjing, China

    Yuan Tian

  2. Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China

    Tinghuai Ma

  3. Chinese Academy of Sciences, Shenzhen, China

    Qingshan Jiang

  4. Nanjing University of Information Science and Technology, Nanjing, China

    Qi Liu

  5. King Saud University, Riyadh, Saudi Arabia

    Muhammad Khurram Khan

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhentao, Z., Wen, Y., Yan, Z., Qiuchi, W. (2023). Factors Influencing Chinese Users’ Willingness to Pay for O2O Knowledge Products Based on Information Adoption Model. In: Tian, Y., Ma, T., Jiang, Q., Liu, Q., Khan, M.K. (eds) Big Data and Security. ICBDS 2022. Communications in Computer and Information Science, vol 1796. Springer, Singapore. https://doi.org/10.1007/978-981-99-3300-6_20

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-3300-6_20

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-3299-3

  • Online ISBN: 978-981-99-3300-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics