ECL  >> Vol. 6 No. 3 (August 2017)

    Research on Influencing Factors of Users’ Continuance Intention toward Taobao Live Streaming

  • 全文下载: PDF(385KB) HTML   XML   PP.44-53   DOI: 10.12677/ECL.2017.63007  
  • 下载量: 698  浏览量: 1,882  



TAM淘宝直播感知成本使用态度持续使用意愿TAM Taobao Live Streaming Perceived Cost Behavior Intention Continuance Intention


目前各种电商直播层出不穷,但有关电商直播用户使用行为研究非常少。本文首先基于技术接受模型(Task Technology Model, TAM),增加了感知成本这一潜在变量,将直播平台特征、直播界面特点、直播主播特质和直播主播互动作为外部变量,提出研究假设,建立直播用户持续使用意愿影响因素的概念模型。接着,通过对淘宝直播用户问卷调查,收集了121份有效问卷,采用SPSS和AMOS进行数据分析,验证研究假设。实证研究结果表明:(1) 用户的感知有用性会显著正向影响其使用态度;(2) 用户的感知易用性会显著正向影响其感知有用性;(3) 用户的使用态度对其持续使用意愿有显著正向影响;(4) 直播平台特征对用户感知易用性和感知有用性均有显著正向影响;(5) 直播界面特点和直播主播特质对用户感知有用性有显著正向影响;(6) 但用户的感知有用性对持续使用意愿的影响不显著,感知易用性和感知成本对使用态度的影响均不显著,直播主播互动对用户感知有用性的影响不显著。

Currently the e-commerce live streaming develops quickly, however there is little research on the user behavior in such context. Firstly, based on the TAM (task technology acceptance model, TAM), we add the potential variable perceived cost to propose the concept model with research hypotheses, in which interface features of live streaming, characteristics of live anchors, live interaction and characteristics of the live streaming platform are used as external variables. Secondly, through questionnaire survey of Taobao live streaming, 121 valid questionnaires are collected and analyzed by SPSS and AMOS to test the proposed research hypotheses. The results show that (1) users’ perceived usefulness significantly affected users’ attitude towards use; (2) users’ perceived ease of use significantly affected users’ perceived usefulness; (3) users’ attitude significantly affected users’ continuance intention; (4) characteristics of Taobao live streaming platform have significantly positive impacts on users’ perceived ease of use and perceived usefulness; (5) the features of the live interface and anchor’s factors notably affect users’ perceived usefulness; (6) unexpectedly, the perceived usefulness had no significant effect on continuance intention, both the perceived ease of use and the perceived cost had no significant effect on the attitude toward use, and live interaction had no significant effect on the perceived usefulness.

吴冰, 周燕楠. 淘宝直播用户持续使用意愿的影响因素研究[J]. 电子商务评论, 2017, 6(3): 44-53.


[1] 钱智通, 孔刘柳. 互联网直播: 颠覆内容营销[J]. 企业管理, 2016(10): 113-115.
[2] Davis, F.D. (1989) Perceived Usefulness, Perceived Ease of Use, and User acceptance of information Technology. MIS Quarterly, 13, 318-340.
[3] Davis, F.D. (1993) User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts. International Journal of Man Machine Studies, 38, 475-487.
[4] 刘迎春. 基于TAM模型的消费者网络购物行为研究[J]. 中国商贸, 2010(8): 109-110.
[5] Butt, I., Tabassam, S., Chaudhry, N.G. and Nusair, K. (2016) Using Technology Acceptance Model to Study Adoption of Online Shopping in an Emerging Economy. Journal of Internet Banking and Commerce, 21, 1-18.
[6] Zeba, F. and Ganguli, S. (2016) Word-of-Mouth, Trust, and Perceived Risk in Online Shopping: An Extension of the Technology Acceptance Model. International Journal of Information Systems in the Service Sector, 8, 17-32.
[7] Lu, M. and Zhu, M. (2011) Customers’ Acceptance Behavior on Mobile Internet Service. Communication Technology and Application, 3, 20-25.
[8] Chang, S.C., Sun, C.C. and Pan, L.Y. (2015) An Extended TAM to Explore Behavioral Intention of Consumers to Use M-Commerce. Journal of Information& Knowledge Management, 14, 44-52.
[9] Hew, T.S., Leong, L. and Ooi, K.B. (2016) Predicting Drivers of Mobile Entertainment Adoption: A Two-Stage SEM- Artificial-Neural-Network Analysis. Journal of Computer Information Systems, 56, 352-370.
[10] Lin, C.W., Hsu, Y.C. and Lin, C.Y. (2017) User Perception, Intention, and Attitude on Mobile Advertising. International Journal of Mobile Communications, 15, 104-117.
[11] Wu, B. and Chen, X.H. (2017) Continuance Intention to Use MOOCs: Integrating the Technology Acceptance Model (TAM) and Task Technology Fit (TTF) Model. Computers in Human Behavior, 67, 221-232.
[12] Nikou, S.A. and Economides, A.A. (2017) Mobile-Based Assessment: Integrating Acceptance and Motivational Factors into a Combined Model of Self-Determination Theory and Technology Acceptance. Computers in Human Behavior, 68, 83-95.
[13] Bhattacherjee, A. (2001) Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25, 351-370.
[14] Yoon, H.S. and Occeña, L. (2014) Impacts of Customers’ Perceptions on Internet Banking Use with a Smart Phone. The Journal of Computer Information Systems, 54, 1-9.
[15] Chen, S.Y. (2016) Using the Sustainable Modified TAM and TPB to Analyze the Effects of Perceived Green Value on Loyalty to a Public Bike System. Transportation Research Part A—Policy and Practice, 88, 58-72.
[16] 李苓源. 基于用户心理需求的人机交互界面设计研究[J]. 电子技术与软件工程, 2015(21): 29-30.
[17] 张瑜. 网络意见领袖对女性消费者购买意愿的影响研究[D]: [硕士学位论文]. 上海: 上海外国语大学, 2014.
[18] Agag, G. and El-Masry, A.A. (2016) Understanding Consumer Intention to Participate in Online Travel Community and Effects on Consumer Intention to Purchase Travel Online and WOM: An Integration of Innovation Diffusion Theory and TAM with Trust. Computers in Human Behavior, 60, 97-111.
[19] Liaw, S.S. and Huang, H.M. (2013) Perceived Satisfaction, Perceived Usefulness and Interactive Learning Environments as Predictors to Self-Regulation in e-Learning Environments. Computers and Education, 60, 14-24.
[20] 吴明隆. 结构方程模型: Amos实务进阶[M]. 重庆: 重庆大学出版社, 2013.