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Data Analysis and Knowledge Discovery  2020, Vol. 4 Issue (8): 119-129    DOI: 10.11925/infotech.2096-3467.2020.0271
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The Determinants of Continuance Intention to Pay: Empirical Research from Online Knowledge Payment Users
Wei Wu1,Xie Xingzheng2()
1College of Journalism and Communications, Shih Hsin University, Taipei 116, China
2School of Journalism, Fudan University, Shanghai 200433, China
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Abstract  

[Objective] The current study aims to investigate the relationship among the characteristics of online knowledge payment products, individual needs, and continuance intention to pay, which offers the guideline to the industry. [Methods] Based on the Elaboration Likelihood Model and Uses and Gratifications Theory, the conceptual model of continuance intention to pay is conducted. Both structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) are used to analyze the collected data. [Results] According to the results of SEM, the argument quality has positive effect on individual needs, which can further affect users’ continuance intention to pay. The fsQCA findings reveal that three causal recipes of motivations predicting high continuance intention to pay. [Limitations] Most of the samples are audio knowledge content users, which reflects that the sample representativeness is limited. Also, the conceptual model ignores the moderators, namely, usage scenarios. [Conclusions] The current online knowledge payment products do not fully meet the individual needs of knowledge payment users. The knowledge content and the individual needs are the key factors of enhancing their continuance intention to pay.
Key words： Online Knowledge Payment      Individual Needs      Continuance Intention to Pay      Elaboration Likelihood Model      Uses and Gratifications Theory     
Received: 31 March 2020      Published: 05 June 2020
ZTFLH:  G206  
Corresponding Authors: Xie Xingzheng     E-mail: 278347285@qq.com
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Cite this article:

Wei Wu, Xie Xingzheng. The Determinants of Continuance Intention to Pay: Empirical Research from Online Knowledge Payment Users. Data Analysis and Knowledge Discovery, 2020, 4(8): 119-129.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2020.0271     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2020/V4/I8/119

Research Model
基本信息 题项 频率 占比/%
性別 男 113 31.3
女 248 68.7
总计 361 100.0
年龄 20以下 161 44.6
21~30岁 174 48.2
31~40岁 15 4.2
41~50岁 5 1.4
51岁以上 6 1.6
总计 361 100.0
教育程度 高中或中专 18 5.0
大专 13 3.6
本科 282 78.1
硕士 28 7.8
博士 20 5.5
总计 361 100.0
工作年限 5年以下 318 88.1
5~10年 21 5.8
10~15年 8 2.2
15~20年 6 1.7
20年以上 8 2.2
总计 361 100.0
所在城市 一线城市 39 10.8
二线城市 142 39.3
三线城市 104 28.8
其他 76 21.1
总计 361 100.0
职业 行政/事业单位 18 5.0
工薪族 3 0.8
设计师 3 0.8
白领 8 2.2
教师 25 6.9
自由职业者 5 1.4
研究人员 3 0.8
个体户/小业主 1 0.3
学生 284 78.8
其他 11 3.0
总计 361 100.0
月收入 4000元以下 289 80.0
4000~6000元 22 6.1
6000~8000元 13 3.6
8000~10000元 14 3.9
10000元以上 23 6.4
总计 361 100.0
Sample Profile
维度 题项 内容 因子载荷量 组成信度 AVE
CQ CQ1 知识付费内容的论据是令人信服的 0.886 0.962 0.807
CQ2 知识付费内容的论据有着良好的支撑 0.926
CQ3 知识付费内容的论据是强而有力的 0.941
CQ4 知识付费内容的逻辑非常周密 0.937
CQ5 知识付费内容包含了足够的资料 0.867
CQ6 知识付费内容涉及的信息非常广泛 0.826
SoC SoC1 知识内容的提供者是值得信赖的 0.949 0.949 0.861
SoC2 知识内容的提供者是可靠的 0.980
SoC3 知识内容的提供者是知名的 0.850
IR IR1 知识付费的内容可以让我学习到新的事物 0.937 0.977 0.916
IR2 知识付费的内容可以让我获取到有用的信息 0.969
IR3 知识付费的内容有助于我的个人提升 0.960
IR4 知识付费的内容对我而言是有帮助的 0.961
ER ER1 知识付费的内容使我精神愉悦 0.962 0.964 0.871
ER2 知识付费的内容能够给我带来欢乐 0.962
ER3 知识付费的内容能够打发闲暇时光 0.895
ER4 我很享受知识付费的内容 0.912
SR SR1 我希望参与该知识内容的讨论 0.852 0.900 0.693
SR2 我希望通过知识付费平台结交朋友 0.836
SR3 我希望了解他人对于事物的看法 0.815
SR4 我希望能够在知识付费平台中扮演与现实生活中不同的身份 0.827
CPI CPI1 未来,我愿意付更多的钱去购买知识内容 0.909 0.900 0.752
CPI2 在下次购买知识内容时,我将首先考虑曾经购买过的知识平台 0.776
CPI3 未来,我会增加知识付费平台的使用 0.909
Results of Confirmatory Factor Analysis
CPI SR ER IR SoC CQ
CPI 0.867
SR 0.775 0.832
ER 0.765 0.768 0.933
IR 0.737 0.709 0.858 0.957
SoC 0.654 0.605 0.728 0.800 0.928
CQ 0.661 0.629 0.767 0.841 0.922 0.898
Results of Discriminant Validity Testing
假设 路径 β值 t值 p值 结果
H1 工具性需求→继续付费意向 0.228 3.993 *** 接受
H2 娱乐性需求→继续付费意向 0.288 5.210 *** 接受
H3 社交性需求→继续付费意向 0.427 7.928 *** 接受
H4 内容质量→工具性需求 0.961 9.309 *** 接受
H5 内容质量→娱乐性需求 0.995 8.373 *** 接受
H6 内容质量→社交性需求 0.845 5.640 *** 接受
H7 来源可信度→工具性需求 -0.098 -1.008 0.313 拒绝
H8 来源可信度→娱乐性需求 -0.203 -1.776 0.076 拒绝
H9 来源可信度→社交性需求 -0.186 -1.285 0.199 拒绝
Results of the Hypotheses Testing
构型 继续付费意向
模式一(S1) 模式二(S2) 模式三(S3)
内容质量 ◆ ◇ ◇
来源可信度 ● ○ ●
工具性需求 ◆ ◇ ◇
娱乐性需求 ● ● ○
社交性需求 ◇ ◆
一致性 0.940 0.867 0.921
覆盖率 0.613 0.599 0.537
净覆盖率 0.141 0.095 0.034
总体一致性 0.847
总体覆盖率 0.789
Configurations Leading to Users' Continuance Intention to Pay
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