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数据分析与知识发现  2021, Vol. 5 Issue (12): 60-73     https://doi.org/10.11925/infotech.2096-3467.2021.0588
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
基于信息采纳模型的知识付费行为研究*——产品类型的调节效应
齐托托1,白如玉2,王天梅1()
1中央财经大学信息学院 北京 100081
2北京大学汇丰商学院 深圳 518055
Analyzing Knowledge Payment Behaviors with Information Adoption Model and Product Types
Qi Tuotuo1,Bai Ruyu2,Wang Tianmei1()
1School of Information, Central University of Finance and Economics, Beijing 100081, China
2HSBC Business School, Peking University, Shenzhen 518055, China
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摘要 

【目的】 探讨产品描述的信息质量和知识生产者的可信度对用户知识付费行为的影响机制以及考查产品类型的调节机理。【方法】 基于信息采纳模型,运用知乎Live的Python爬虫数据,结合文本分析与稳健回归分析方法,从产品描述的信息质量和知识生产者的可信度两个方面探究知识付费行为的影响因素,并将知识付费产品划分为实用型产品和享乐型产品,比较不同产品类型之间作用路径的差异性。【结果】 产品描述的详尽性、生动性和相关性显著正向影响知识付费行为;知识生产者的声誉、经验和信息完备性显著正向影响知识付费行为;与实用型产品相比,享乐型产品中知识生产者的声誉和经验对知识付费行为的作用关系更强。【局限】 尚未比较不同文化背景下知识付费行为的差异性,且仅采用截面数据研究了单一知识付费商业模式。【结论】 全面归纳了影响用户知识付费行为的关键因素,深化了信息采纳模型的应用价值,为知识付费产品的设计和营销提供了实践参考。

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齐托托
白如玉
王天梅
关键词 知识付费行为产品描述信息质量产品类型信息源可信度    
Abstract

[Objective] This paper explores the information quality of product description and the credibility of knowledge producers, aiming to investigate their impacts on users’ knowledge payment behaviors moderated by product types. [Methods] First, we retrieved data from Zhihu Live with the help of a Web crawler. Then, we studied the impacts with the robust regression and text analysis methods based on the information adoption model. We also divided knowledge payment products into the utilitarian and hedonic ones, and then compared their different action paths. [Results] The elaborateness, vividness, and relevance of product descriptions as well as the reputation, experience, and information completeness of knowledge producers positively affect knowledge payment behaviors. Compared with utilitarian products, the reputation and experience of knowledge producers in hedonic products have stronger impacts on knowledge payment behaviors. [Limitations] We did not compare the knowledge payment behaviors in different cultures, and only studied the single knowledge payment business model with cross-section data. [Conclusions] This paper summarizes the key factors affecting knowledge payment behaviors and the information adoption model. It provides practical guidelines for designing and marketing knowledge payment products.

Key wordsKnowledge Payment Behavior    Product Description    Information Quality    Product Type    Information Source Credibility
收稿日期: 2021-06-15      出版日期: 2022-01-20
ZTFLH:  G203  
基金资助:* 国家自然科学基金项目(72072194)
通讯作者: 王天梅,ORCID:0000-0002-1019-2339     E-mail: wangtianmei@cufe.edu.cn
引用本文:   
齐托托, 白如玉, 王天梅. 基于信息采纳模型的知识付费行为研究*——产品类型的调节效应[J]. 数据分析与知识发现, 2021, 5(12): 60-73.
Qi Tuotuo, Bai Ruyu, Wang Tianmei. Analyzing Knowledge Payment Behaviors with Information Adoption Model and Product Types. Data Analysis and Knowledge Discovery, 2021, 5(12): 60-73.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2021.0588      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2021/V5/I12/60
Fig.1  研究模型
领域 频数 占比/% 销量
均值 标准差 中值 最小值 最大值
教育 966 18.17 448.83 884.88 128.00 0 8 795
职业 678 12.75 305.34 551.48 120.50 0 8 473
互联网 597 11.24 292.29 597.49 104.00 0 8 535
金融与经济 505 9.50 289.31 578.12 87.00 0 5 200
生活方式 420 7.90 650.59 3 587.38 117.50 0 71 163
音乐、影视和游戏 325 6.11 301.06 536.05 103.00 0 5 443
艺术 231 4.35 263.58 433.37 96.00 0 3 886
科学技术 247 4.65 466.50 1 101.07 113.00 0 9 068
医学与健康 218 4.10 899.20 1 353.50 424.50 0 12 325
阅读与写作 176 3.32 361.33 701.43 87.00 2 5 312
法律 148 2.78 236.28 446.74 67.50 0 2 683
心理学 198 3.72 1 171.07 2 851.00 244.50 0 17 531
设计 166 3.12 276.67 416.67 113.50 0 2 664
商业 122 2.29 219.40 338.52 77.00 0 1 575
体育 150 2.82 634.29 830.05 297.00 0 5 715
旅游 112 2.11 127.02 209.73 50.50 0 1 301
美食 57 1.07 319.42 738.92 73.00 1 4 004
总计 5 316 100.00 420.45 1 352.21 113.00 0 71 163
Table 1  领域的描述性统计分析结果
变量类型 变量名 变量计算方法 变量说明
因变量 知识付费行为 统计 2019年1月至2020年1月间的产品销量差值
自变量 详尽性 统计 产品描述的总字数
生动性 统计 产品描述中插入的图片数
相关性 信息抽取 采用TF-IDF法计算的产品描述与产品标题之间的文本相似度
声誉 直接获取 知识生产者的粉丝数
经验 统计 知识生产者已发布的知乎Live数
信息完备性 统计 知识生产者披露的居住地、从事行业、职位经历以及教育经历的数量
调节变量 产品类型 分类 虚拟变量,实用型产品取值为0,享乐型产品取值为1
控制变量 价格 直接获取 知乎Live的产品定价
文件数 直接获取 知乎Live上传的文件数
评论数 直接获取 2019年1月知乎Live的累计评论数
启动年份 分类 虚拟变量,从2016年至2019年
Table 2  变量说明
变量 均值 标准差 中值 最小值 最大值
知识付费行为 420.40 1 352.00 113.00 0 71 163
详尽性 178.30 98.55 162.50 0 862
生动性 0.12 0.65 0.00 0 9
相关性 0.16 0.12 0.13 0 0.73
声誉 54 522.00 120 000.00 11 551.00 2 2 049 568
经验 5.93 6.59 4.00 1 39
信息完备性 2.70 1.24 3.00 0 4
产品类型 0.24 0.43 0.00 0 1
产品价格 20.16 20.59 18.72 0 500
文件数 16.72 21.51 10.00 0 328
评论数 142.30 527.40 43.00 0 23 050
Table 3  变量的描述性统计
1 2 3 4 5 6 7
1.知识付费行为 1
2.详尽性 0.153 1* 1
3.生动性 0.000 2 -0.032 3* 1
4.相关性 0.062 4* 0.071 5* -0.069 7* 1
5.声誉 0.390 0* 0.025 2* -0.126 4* 0.010 4 1
6.经验 0.192 0* 0.049 1* -0.059 7* 0.074 8* 0.531 4* 1
7.信息完备性 0.086 0* 0.030 8* 0.012 0 0.046 2* 0.178 5* 0.189 5* 1
Table 4  关键变量的Pearson相关系数
作用类型 主要变量 模型1 模型2 模型3
主要作用 详尽性 0.061(2.64)*** 0.047(1.86)*
生动性 0.176(3.39)*** 0.123(2.05)**
相关性 0.897(5.74)*** 0.780(4.39)***
声誉 0.035(3.50)*** 0.026(2.49)**
经验 0.164(6.44)*** 0.139(4.96)***
信息完备性 0.189(4.75)*** 0.190(4.18)***
调节作用 产品类型*详尽性 0.056(1.01)
产品类型*生动性 0.211(1.90)*
产品类型*相关性 0.497(1.34)
产品类型*声誉 0.037(1.77)*
产品类型*经验 0.111(1.80)*
产品类型*信息完备性 0.011(0.12)
控制作用 产品类型 -0.149(-3.69)*** -0.139(-3.50)*** -0.167(-2.91)***
价格 0.168(5.99)*** 0.073(2.58)*** 0.069(2.42)**
文件数 0.096(7.82)*** 0.077(6.35)*** 0.075(6.16)***
评论数 0.820(78.30)*** 0.778(62.39)*** 0.778(62.33)***
启动年份 控制 控制 控制
截距项 常数项 0.611(5.55)*** -0.191(-1.25) 0.030(0.18)
R 2 0.543 0.561 0.562
F 1 132.868*** 613.126*** 411.547***
N 5 316 5 316 5 316
Table 5  回归结果
[1] 邢小强, 周平录. 互联网知识付费的商业模式研究[J]. 管理评论, 2019, 31(7): 75-85.
[1] (Xing Xiaoqiang, Zhou Pinglu. Research on E-Business Model of Paying for the Knowledge[J]. Management Review, 2019, 31(7): 75-85.)
[2] Qi T T, Wang T M, Ma Y L, et al. Knowledge Payment Research: Status Quo and Key Issues[J]. International Journal of Crowd Science, 2019, 3(2): 117-137.
doi: 10.1108/IJCS-01-2019-0007
[3] 艾媒咨询. 2020年中国知识付费行业运行发展及用户行为调研分析报告[R/OL]. (2020-02-14). [2021-06-10]. https://www.iimedia.cn/c400/69029.html.
[3] (iiMedia Research. 2020 Operation and Development of China’s Knowledge Payment Industry and User Behavior Report[R/OL]. (2020-02-14). [2021-06-10]. https://www.iimedia.cn/c400/69029.html.)
[4] 千聊. 2021知识付费行业研究报告[R/OL]. (2021-01-25). [2021-06-10]. https://www.sohu.com/a/446594672_104421.html.
[4] (Qlchat. 2021 knowledge Payment Industry Report[R/OL]. (2021-01-25). [2021-06-10]. https://www.sohu.com/a/446594672_104421.html.)
[5] 齐托托, 刘倩, 王天梅, 等. 知识付费产品描述语言风格的说服效应研究——知识生产者声誉的调节作用[J]. 南开管理评论, 2020, 23(5): 159-170.
[5] (Qi Tuotuo, Liu Qian, Wang Tianmei, et al. The Persuasive Effect of Linguistic Styles in the Description of Paying for Knowledge Product: The Moderating Effect of Knowledge Producer’s Reputation[J]. Nankai Business Review, 2020, 23(5): 159-170.)
[6] 赵梓辰. 知识付费平台“90后”用户持续使用意愿影响因素研究[D]. 哈尔滨: 黑龙江大学, 2020.
[6] (Zhao Zichen. Research on the Influencing Factors of “Post-90s” Users’ Continued Willingness to Use of Knowledge Payment Platform[D]. Harbin: Heilongjiang University, 2020.)
[7] 朱祖平, 张丽平. 社群服务背景下在线知识付费产品用户持续付费意愿研究[J]. 东南学术, 2020 (5): 158-166.
[7] (Zhu Zuping, Zhang Liping. A Research on the Continuous Payment Willingness of Users of Online Paid Knowledge Products in the Context of Community Services: Empirical Analysis Based on PLS-SEM Model[J]. Southeast Academic Research, 2020(5): 158-166.)
[8] 金小璞, 徐芳, 毕新. 知识付费平台用户满意度调查与提升策略[J]. 情报理论与实践, 2021, 44(5): 146-152.
[8] (Jin Xiaopu, Xu Fang, Bi Xin. Investigation on the User Satisfaction of Knowledge Payment Platforms and Improvement Strategies[J]. Information Studies: Theory & Application, 2021, 44(5): 146-152.)
[9] 郭宇, 郭勇, 赵宇翔. 内容还是情境: 在线用户知识付费行为机理研究: 一项基于CCC-B框架的组态分析[J]. 图书情报工作, 2020, 64(1): 120-130.
[9] (Guo Yu, Guo Yong, Zhao Yuxiang. Content or Context: A Study on the Behavior Mechanism of Online Users’ Knowledge Payment: A Configuration Analysis Based on CCC-B Framework[J]. Library and Information Service, 2020, 64(1): 120-130.)
[10] 张帅, 王文韬, 李晶. 用户在线知识付费行为影响因素研究[J]. 图书情报工作, 2017, 61(10): 94-100.
[10] (Zhang Shuai, Wang Wentao, Li Jing. Research on the Influencing Factors of User’s Online Knowledge Payment Behavior[J]. Library and Information Service, 2017, 61(10): 94-100.)
[11] 李钢, 卢艳强, 滕树元. 用户在线知识付费行为研究———基于计划行为理论[J]. 图书馆学研究, 2018(10): 49-60.
[11] (Li Gang, Lu Yanqiang, Teng Shuyuan. Analysis of Users’ Online Knowledge Payment Behavior: Based on Theory of Planned Behavior[J]. Research on Library Science, 2018(10): 49-60.)
[12] Horng S M, Lee Y Y, Wu C L. A Study of the Paying Behavior for Subscribing Social Network Sites[J]. Computer Communications, 2016, 73: 282-290.
doi: 10.1016/j.comcom.2015.08.014
[13] Shi X, Zheng X, Yang F. Exploring Payment Behavior for Live Courses in Social Q&A Communities: An Information Foraging Perspective[J]. Information Processing & Management, 2020, 57(4): 102241.
doi: 10.1016/j.ipm.2020.102241
[14] 邓胜利, 蒋雨婷. 用户交互特征对知识付费行为预测的贡献度研究[J]. 图书情报工作, 2020, 64(8): 93-102.
[14] (Deng Shengli, Jiang Yuting. Research on the Contribution of User Interaction Characteristics to the Prediction of Knowledge Payment Behavior[J]. Library and Information Service, 2020, 64(8): 93-102.)
[15] 刘齐平, 王伟军, 何国卿. 基于社会资本理论的线下知识付费平台用户选择行为研究[J]. 图书馆学研究, 2019(22): 34-41.
[15] (Liu Qiping, Wang Weijun, He Guoqing. Research on User Choice Behavior of Offline Knowledge Payment Platform Based on Social Capital Theory[J]. Research on Library Science, 2019(22): 34-41.)
[16] 赵杨, 袁析妮, 李露琪, 等. 基于社会资本理论的问答平台用户知识付费行为影响因素研究[J]. 图书情报知识, 2018(4): 15-23.
[16] (Zhao Yang, Yuan Xini, Li Luqi, et al. The Impact Factors of Users’ Paying Behavior for Knowledge on Social Q&A Platform Based on Social Capital Theory[J]. Documentation, Information & Knowledge, 2018(4): 15-23.)
[17] 李武, 艾鹏亚, 宾锋. 粉丝力量与知识付费:在线问答平台用户付费围观行为研究[J]. 图书馆杂志, 2019, 38(4): 74-81.
[17] (Li Wu, Ai Pengya, Bin Feng. The Power of Fans and Knowledge Economy: Understanding Users’ Paying Behavior for Existing Answers on Q&A Platforms[J]. Library Journal, 2019, 38(4): 74-81.)
[18] 杨东红, 贺红梅, 徐畅. 移动音频有声阅读平台用户知识付费行为研究[J]. 情报科学, 2020, 38(7): 105-111.
[18] (Yang Donghong, He Hongmei, Xu Chang. Consumer Purchase Behavior of Online Mobile Audio Platform[J]. Information Science, 2020, 38(7): 105-111.)
[19] Sussman S W, Siegal W S. Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption[J]. Information Systems Research, 2003, 14(1): 47-65.
doi: 10.1287/isre.14.1.47.14767
[20] Tseng S Y, Wang C N. Perceived Risk Influence on Dual-Route Information Adoption Processes on Travel Websites[J]. Journal of Business Research, 2016, 69(6): 2289-2296.
doi: 10.1016/j.jbusres.2015.12.044
[21] Peng L F, Liao Q Y, Wang X R, et al. Factors Affecting Female User Information Adoption: An Empirical Investigation on Fashion Shopping Guide Websites[J]. Electronic Commerce Research, 2016, 16(2): 145-169.
doi: 10.1007/s10660-016-9213-z
[22] Rabjohn N, Cheung C M K, Lee M K O. Examining the Perceived Credibility of Online Opinions: Information Adoption in the Online Environment [C]//Proceedings of the 41st Annual Hawaii International Conference on System Sciences. Waikoloa, HI, USA. IEEE, 2008: 286.
[23] Jin J H, Yan X B, Li Y J, et al. How Users Adopt Healthcare Information: An Empirical Study of an Online Q&A Community[J]. International Journal of Medical Informatics, 2016, 86: 91-103.
doi: 10.1016/j.ijmedinf.2015.11.002
[24] Hendijani F M, Marvi R. Viral Marketing and Purchase Intentions of Mobile Applications Users[J]. International Journal of Emerging Markets, 2019, 15(2): 287-301.
doi: 10.1108/IJOEM-06-2018-0291
[25] Chong A Y L, Khong K W, Ma T, et al. Analyzing Key Influences of Tourists’ Acceptance of Online Reviews in Travel Decisions[J]. Internet Research, 2018, 28(3): 564-586.
doi: 10.1108/IntR-05-2017-0212
[26] Erkan I, Evans C. The Influence of eWOM in Social Media on Consumers’ Purchase Intentions: An Extended Approach to Information Adoption[J]. Computers in Human Behavior, 2016, 61(C): 47-55.
doi: 10.1016/j.chb.2016.03.003
[27] Mudambi S M, Schuff D. What Makes a Helpful Review? A Study of Customer Reviews on Amazon. com[J]. MIS Quarterly, 2010, 34(1): 185-200.
doi: 10.2307/20721420
[28] Adamic L A, Zhang J, Bakshy E, et al. Knowledge Sharing and Yahoo! Answers: Everyone Knows Something [C]//Proceedings of the 17th International Conference on World Wide Web. 2008: 665-674.
[29] Agichtein E, Castillo C, Donato D, et al. Finding High-Quality Content in Social Media [C]//Proceedings of the 2008 International Conference on Web Search and Data Mining. 2008: 183-194.
[30] 李中梅, 张向先, 郭顺利. 移动商务环境下O2O用户在线评论有用性影响因素研究[J]. 情报科学, 2017, 35(2): 130-137.
[30] (Li Zhongmei, Zhang Xiangxian, Guo Shunli. A Study of the Factors’ Analysis of O2O Users’ Online Useful Reviews in the Mobile Business Environment[J]. Information Science, 2017, 35(2): 130-137.)
[31] Oh S, Worrall A, Yi Y J. Quality Evaluation of Health Answers in Yahoo! Answers: A Comparison Between Experts and Users[J]. Proceedings of the American Society for Information Science and Technology, 2011, 48(1): 1-3.
[32] Zhang Y L, Li X M, Fan W G. User Adoption of Physician’s Replies in an Online Health Community: An Empirical Study[J]. Journal of the Association for Information Science and Technology, 2020, 71(10): 1179-1191.
doi: 10.1002/asi.v71.10
[33] Cai S, Luo Q F, Fu X, et al. What Drives the Sales of Paid Knowledge Products? A Two-Phase Approach[J]. Information & Management, 2020, 57(5): 103264.
doi: 10.1016/j.im.2019.103264
[34] Zhao Y, Zhao Y, Yuan X N, et al. How Knowledge Contributor Characteristics and Reputation Affect User Payment Decision in Paid Q&A? An Empirical Analysis from the Perspective of Trust Theory[J]. Electronic Commerce Research and Applications, 2018, 31: 1-11.
doi: 10.1016/j.elerap.2018.07.001
[35] Hillen M A, de Haes H C J M, Stalpers L J A, et al. How Can Communication by Oncologists Enhance Patients’ Trust? An Experimental Study[J]. Annals of Oncology, 2014, 25(4): 896-901.
doi: S0923-7534(19)36509-3 pmid: 32018923
[36] Wu J, Ma P H, Xie K L. In Sharing Economy We Trust: The Effects of Host Attributes on Short-Term Rental Purchases[J]. International Journal of Contemporary Hospitality Management, 2017, 29(11): 2962-2976.
doi: 10.1108/IJCHM-08-2016-0480
[37] Dhar R, Wertenbroch K. Consumer Choice Between Hedonic and Utilitarian Goods[J]. Journal of Marketing Research, 2000, 37(1): 60-71.
doi: 10.1509/jmkr.37.1.60.18718
[38] Rocklage M D, Fazio R H. The Enhancing Versus Backfiring Effects of Positive Emotion in Consumer Reviews[J]. Journal of Marketing Research, 2020, 57(2): 332-352.
doi: 10.1177/0022243719892594
[39] O’Donnell M, Evers E R K. Preference Reversals in Willingness to Pay and Choice[J]. Journal of Consumer Research, 2019, 45(6): 1315-1330.
doi: 10.1093/jcr/ucy052
[40] Voss K E, Spangenberg E R, Grohmann B. Measuring the Hedonic and Utilitarian Dimensions of Consumer Attitude[J]. Journal of Marketing Research, 2003, 40(3): 310-320.
doi: 10.1509/jmkr.40.3.310.19238
[41] Blut M, Teller C, Floh A. Testing Retail Marketing-Mix Effects on Patronage: A Meta-Analysis[J]. Journal of Retailing, 2018, 94(2): 113-135.
doi: 10.1016/j.jretai.2018.03.001
[42] Moore S G. Attitude Predictability and Helpfulness in Online Reviews: The Role of Explained Actions and Reactions[J]. Journal of Consumer Research, 2015, 42(1): 30-44.
doi: 10.1093/jcr/ucv003
[43] Ren J, Nickerson J V. Arousal, Valence, and Volume: How the Influence of Online Review Characteristics Differs with Respect to Utilitarian and Hedonic Products[J]. European Journal of Information Systems, 2019, 28(3): 272-290.
doi: 10.1080/0960085X.2018.1524419
[44] 杨东红, 吴邦安, 陈天鹏, 等. 基于京东商城评价数据的在线商品好评、中评、差评比较研究[J]. 情报科学, 2019, 37(2): 125-132.
[44] (Yang Donghong, Wu Bangan, Chen Tianpeng, et al. A Comparative Study on Positive, Neutral and Negative Reviews of Online Products Based on Jingdong Mall Data[J]. Information Science, 2019, 37(2): 125-132.)
[45] 何有世, 李娜. 搜索型商品评论有用性影响因素研究[J]. 情报杂志, 2016, 35(12): 202-206.
[45] (He Youshi, Li Na. Research on the Impact Factors of the Helpfulness of the Search Product Reviews[J]. Journal of Intelligence, 2016, 35(12): 202-206.)
[46] 李宗伟, 张艳辉, 夏伟伟. 卖家反馈能否引发高质量的在线评论信息? 基于淘宝网的实证分析[J]. 中国管理科学, 2021, 29(5):221-230.
[46] (Li Zongwei, Zhang Yanhui, Xia Weiwei. Can Seller Feedback Trigger High Quality Online Reviews?: Based on the Empirical Analysis of Taobao[J]. Chinese Journal of Management Science, 2021, 29(5): 221-230.)
[47] 王君珺, 闫强. 不同热度搜索型产品的在线评论对销量影响的实证研究[J]. 中国管理科学, 2013, 21(S2): 406-411.
[47] (Wang Junjun, Yan Qiang. An Empirical Study on the Impact of Online Reviews of Different Product Popularity on Product Sales[J]. Chinese Journal of Management Science, 2013, 21(S2): 406-411.)
[48] 吴江, 靳萌萌. 在线短租房源图片对消费者行为意愿的影响[J]. 数据分析与知识发现, 2017, 1(12): 10-20.
[48] (Wu Jiang, Jin Mengmeng. Online Room Listing Photos Affect Consumer’s Intentions[J]. Data Analysis and Knowledge Discovery, 2017, 1(12): 10-20.)
[49] 彭丽徽, 李贺, 张艳丰, 等. 基于品牌声誉感知差异的在线评论有用性影响因素实证研究[J]. 情报科学, 2017, 35(9): 159-164.
[49] (Peng Lihui, Li He, Zhang Yanfeng, et al. An Empirical Study on the Factors Influencing the Usefulness of Online Reviews Based on Perceived Brand Reputation[J]. Information Science, 2017, 35(9): 159-164.)
[50] 王翠翠, 陈雪, 朱万里, 等. 带图片评论与纯文字评论对消费者有用性感知影响的眼动研究[J]. 情报理论与实践, 2020, 43(6): 135-141.
[50] (Wang Cuicui, Chen Xue, Zhu Wanli, et al. Eye-tracking Study on the Impact of Photographic Reviews and Verbal Reviews on Consumers’ Perceived Usefulness[J]. Information Studies:Theory & Application, 2020, 43(6): 135-141.)
[51] Zajonc R B. Attitudinal Effects of Mere Exposure[J]. Journal of Personality and Social Psychology, 1968, 9(2): 1-27.
[52] Bornstein R F, D’Agostino P R. Stimulus Recognition and the Mere Exposure Effect[J]. Journal of Personality and Social Psychology, 1992, 63(4): 545-552.
pmid: 1447685
[53] Montoya R M, Horton R S, Vevea J L, et al. A Re-Examination of the Mere Exposure Effect: The Influence of Repeated Exposure on Recognition, Familiarity, and Liking[J]. Psychological Bulletin, 2017, 143(5): 459-498.
doi: 10.1037/bul0000085
[54] Zhou Y S, Yang S Q, Li Y X, et al. Does the Review Deserve More Helpfulness When Its Title Resembles the Content? Locating Helpful Reviews by Text Mining[J]. Information Processing & Management, 2020, 57(2): 102179.
doi: 10.1016/j.ipm.2019.102179
[55] 纪淑娴, 胡培. 基于“柠檬”理论的在线信誉反馈系统有效性研究[J]. 中国管理科学, 2010, 18(5): 145-151.
[55] (Ji Shuxian, Hu Pei. Analysis of the Validity of Online Reputation Feedback Systems Based on the Lemon Theory[J]. Chinese Journal of Management Science, 2010, 18(5): 145-151.)
[56] 杨华, 孙宝凤, 林天雪, 等. 网络口碑对消费者图书购买意愿的影响效应研究[J]. 图书情报工作, 2018, 62(2): 117-126.
[56] (Yang Hua, Sun Baofeng, Lin Tianxue, et al. The Effect of Electronic Word-of-Mouth on Consumer’s Book Purchase Intention[J]. Library and Information Service, 2018, 62(2): 117-126.)
[57] Allison T H, Davis B C, Webb J W, et al. Persuasion in Crowdfunding: An Elaboration Likelihood Model of Crowdfunding Performance[J]. Journal of Business Venturing, 2017, 32(6): 707-725.
doi: 10.1016/j.jbusvent.2017.09.002
[58] Jabr W, Calgary U O, Mookerjee R, et al. Leveraging Philanthropic Behavior for Customer Support: The Case of User Support Forums[J]. MIS Quarterly, 2014, 38(1): 187-208.
[59] Flynn L R, Goldsmith R E. Application of the Personal Involvement Inventory in Marketing[J]. Psychology & Marketing, 1993, 10(4): 357-366.
doi: 10.1002/(ISSN)1520-6793
[60] Kakar A K. Why Do Users Speak More Positively About Mac Os X but are More Loyal to Windows 7?[J]. Computers in Human Behavior, 2015, 44(C): 166-173.
doi: 10.1016/j.chb.2014.11.033
[61] Carroll B A, Ahuvia A C. Some Antecedents and Outcomes of Brand Love[J]. Marketing Letters, 2006, 17(2): 79-89.
doi: 10.1007/s11002-006-4219-2
[62] Park D H, Lee J, Han I. The Effect of On-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement[J]. International Journal of Electronic Commerce, 2007, 11(4): 125-148.
[63] 朱丽叶, 袁登华, 张静宜. 在线用户评论质量与评论者等级对消费者购买意愿的影响: 产品卷入度的调节作用[J]. 管理评论, 2017, 29(2): 87-96.
[63] (Zhu Liye, Yuan Denghua, Zhang Jingyi. The Impact of Online User Reviews Quality and Commentators Rank on Consumer Purchasing Intention: The Moderating Role of Product Involvement[J]. Management Review, 2017, 29(2): 87-96.)
[64] Chang K T T, Chen W, Tan B C Y. Advertising Effectiveness in Social Networking Sites: Social Ties, Expertise, and Product Type[J]. IEEE Transactions on Engineering Management, 2012, 59(4): 634-643.
doi: 10.1109/TEM.2011.2177665
[65] Kuang L N, Huang N, Hong Y L, et al. Spillover Effects of Financial Incentives on Non-Incentivized User Engagement: Evidence from an Online Knowledge Exchange Platform[J]. Journal of Management Information Systems, 2019, 36(1): 289-320.
doi: 10.1080/07421222.2018.1550564
[66] Kim S, Oh S. Users’ Relevance Criteria for Evaluating Answers in a Social Q&A Site[J]. Journal of the American Society for Information Science and Technology, 2009, 60(4): 716-727.
doi: 10.1002/asi.v60:4
[67] Jin Y, Huang J H, Wang X Y. What Influences Content Popularity? An Empirical Investigation of Voting in Social Q&A Communities [C]//Proceedings of the 21st Pacific Asia Conference on Information Systems (PACIS). 2017: 161.
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