互联网社交借贷用户接受行为影响因素研究

北京邮电大学学报(社科版) ›› 2016, Vol. 18 ›› Issue (5): 43-53.

互联网社交借贷用户接受行为影响因素研究

北京邮电大学经济管理学院，北京100876

收稿日期:2016-03-20 出版日期:2016-10-31

Determinants of Intentions to Use Internet Social Lending

School of Economics and Management, Beijing University of Posts and Telecommunications,
Beijing 100876, China

Received:2016-03-20 Online:2016-10-31

摘要/Abstract

摘要：

互联网社交借贷是新兴社交金融模式的典型代表，也是当下十分热门的P2P网络借贷的一个细分领域。相比传统P2P业务，社

交借贷具有征信成本低廉，违约风险较小，避免人情尴尬等诸多优点，并于2015年大规模兴起，在经济社会中产生重要影响，探究

互联网社交借贷用户的接受行为影响因素有着重要的理论和现实意义。基于TAM模型，构建了互联网社交借贷用户接受行为影响因

素模型，并通过调查数据对用户接受互联网社交借贷的影响因素进行了实证研究。结果表明：个体创新性、网络外部性等外部因素

对感知有用性、感知易用性有正向影响，兼容性对感知有用性有正向影响，感知有用性、感知易用性和网络外部性对用户使用意愿

有正向影响，感知风险对用户使用意愿有负向影响。

关键词: 互联网, 社交借贷, 用户接受, 金融模式

Abstract:

Internet social lending is a typical example of the emerging social finance and a product segmentation

of P2P lending. Compared with the traditional P2P lending, Internet social lending has a lower credit cost, a

lower default risk and can also avoid the embarrassment of borrowing money from your friends face to face.

Internet social lending is rising after 2015 and has had an important effect on our economy, so it is quite

meaningful to explore the determinants of user acceptance of Internet social lending. Based on technology

acceptance model (TAM), a model concerning the determinants of user acceptance of Internet social lending is

constructed and empirical research is made on factors influencing user selection of Internet social lending

through survey data. The results show that the external factors, such as personal innovation, network externality,

have a positive effect on perceived usefulness and perceived ease of use; the compatibility has a positive effect

on perceived usefulness; perceived usefulness, perceived ease of use and network externality have a positive

effect on use intention while perceived risk has a negative effect on use intention.

Key words: Internet, social lending, user acceptance；financial model

中图分类号:

F832.4
C912

赵保国，勾建康. 互联网社交借贷用户接受行为影响因素研究[J]. 北京邮电大学学报(社科版), 2016, 18(5): 43-53.

ZHAO Bao-guo, GOU Jian-kang. Determinants of Intentions to Use Internet Social Lending[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2016, 18(5): 43-53.

［1］周慧虹.熟人借贷须消除两大“软肋”［N］.上海金融报, 2015-08-25(A02).
［2］李耀东, 朱倩雯, 张筱玲.网络熟人借贷: 机会还是陷阱［J］.金融博览, 2015(10)： 60-61.
［3］林楠.做熟人间的借贷生意, “社交金融”能成功吗［J］.支点, 2015(8): 56-59.
［4］田君.好有钱: 掘金“熟人借贷”［J］.首席财务官, 2015(20): 62-64.
［5］施青华, 刘兰娟.互联网金融的用户选择行为实证研究［J］.上海财经大学学报（哲学社会科学版）, 2015, 17(6): 80-

89.
［6］傅婕.消费者互联网理财产品采纳意愿的影响因素及市政研究［D］.成都: 西南财经大学, 2014.
［7］刘志洋.消费者对互联网银行的可接受度问题研究［J］.浙江工商大学学报, 2015(2): 85-93.
［8］ Rogers E M. Diffusion of innovations: modifications of a model for telecommunications［C］//Die Diffusion

von Innovationen in der Telekommimikation. Berlin : Springer Berlin Heidelberg, 1995: 25-38.
［9］ Bauer R A. Consumer behavior as risk taking Dynamic marketing for a changing world［M］.Chicago: American

Marketing Association, 1960: 389-393.
［10］ Cox D F. Risk handling in consumer behavior-an intensive study of two cases［C］// Risk taking and

information handling in consumer behavior. Boston : Graduate School of Business Administration, Harvard

University, 1967: 34-81.
［11］ Jacoby J, Kaplan L B. The components of perceived risk［J］. Advances in consumer research, 1972, 3(3):

382-383.
［12］ Pagani M, Hofacker C. Use and participation in virtual social networks: a theoretical model ［J］.

International Journal of Virtual Communities and Social Networking (IJVCSN), 2010, 2(1): 1-17.
［13］ Stone R N, Gr0nhaug K. Perceived risk: further considerations for themarketing discipline［J］. European

Journal of marketing, 1993, 27(3): 39-50.
［14］ Rogers E M. Diffusion of preventive innovations ［J］. Addictive behaviors, 2002, 27(6): 989-993.
［15］ Chen L, Gillenson M L, Sherrell D L. Enticing online consumers: an extended technology acceptance

perspective［J］. Information & management, 2002, 39(8): 705-719.
［16］ Zhang Nan, Guo Xunhua, Chen Guoqing. DDT-TAM integrated model for IT adoption［J］.Tsinghua Science &

Technology, 2008, 13(3): 306-311.
［17］ Agarwal R, Prasad J. The antecedents and consequents of user perceptions in information technology adoption

［J］. Decision support systems, 1998, 22(1): 15-29.
［18］ Katz M L, Shapiro C. Technology adoption in the presence of network externalities［J］.The Journal of

Political E-conomy, 1986, 94(4): 822-841.
［19］ Wu J H, Wang S C. What drives mobile commerce? An empirical evaluation of the revised technology

acceptance model［J］. Information & Management, 2005, 42(5): 710-729.

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