Author(s)

Hua Zhang ¹, Yelin Guo ¹, Xin Huo ¹, Yu Li ¹

Affiliation(s)

¹ School of Business Administration/Guangdong Business College, Guangdong University of Finance & Economics, Guangzhou, China

Corresponding Author

Hua Zhang

ABSTRACT

This article uses the elaboration likelihood model (ELM) as the foundational theoretical framework to comprehensively analyze various factors that affect the behavior of users paying for educational content in the central and peripheral pathways. This study fills the gaps in research perspectives and systems from the past and expands the application areas of the elaboration likelihood model. From a practical perspective, the research results of this paper partially address the series of problems in knowledge payment, provide feasible suggestions to enhance user stickiness of educational content payment platforms. Furthermore, the research results can also promote the high-quality development of the content payment industry and provide support for economic recovery after the pandemic.

KEYWORDS

Educational content payment; Elaboration likelihood model; Willingness to pay

CITE THIS PAPER

Hua Zhang, Yelin Guo, Xin Huo, Yu Li, Research on User's Willingness to Pay for Educational Content Based on the ELM. Information Systems and Economics (2023) Vol. 4: 23-29. DOI: http://dx.doi.org/10.23977/infse.2023.040504.

REFERENCES

[1] Wang Yuting. Research on Customer Experience Value of Online Education Knowledge Payment Products—Taking Tencent Classroom as an Example. Journal of Tianjin Business Vocational College, 2022, 10(03): 76-82. DOI: 10.16130/j.cnki.12-1434/f. 2022.03.003. 
[2] Huang He, Yang Xiaohan, Fu Yangqi. The Manifestation and Promotion of Fitness Short Videos on National Fitness—Based on the Inspection of an Elaboration Likelihood Model. China Sport Science and Technology, 2023, 59(01): 23-30. DOI: 10.16470/j.csst.2021070. 
[3] Zeng Jianghong, Huang Xiangrong, Yang Yalan. Research on the Influencing Factors of Crowdfunding Brand Promotion Effect: Based on the Perspective of an Elaboration Likelihood Model. Management Review, 2022, 34(09): 170-180. DOI: 10.14120/j.cnki.cn11-5057/f.2022.09.001. 
[4] Zhou Min, Chen Ao, Kou Zonglai. How Do User Evaluations Affect Online Market Purchases? Consumption Economics, 2018, 34(03): 72-79. 
[5] Zhang Aiqin. Strategies for Guiding Public Opinion on Emergency Incidents through Online Forums. China News Daily, 2007-11-28, (C01). 
[6] Yu Lu. Persuasion Research on Native Advertising Based on the Elaboration Likelihood Model. Huanan University, 2019. DOI: 10.27135/d.cnki.ghudu.2019.002938.

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