对自身经济状况的不满意和投资推广信息是如何影响 P2P 网贷投资意愿的?来自稀缺思维理论与错误管理理论的解释 (How Financial Dissatisfaction and Investment Promotion Information Affect the Investment Intention in P2P Lending? An Explanation From Scarcity Mind-Set and Error Management Theory)

21 Pages Posted: 27 May 2019

See all articles by Shichang Deng

Shichang Deng

Shanghai University of International Business and Economics

Qianqian Huang

Shanghai University of International Business and Economics

Yazhou He

Shanghai University of International Business and Economics

Date Written: April 29, 2019

Abstract

Chinese Abstract: 在社区公益活动中,我们观察到对自身经济状况不满意的人群更有可能被投资机构的推广信息所影响,出现较高的P2P网贷投资意愿。虽然该现象非常普遍,然而这其中的机制却缺乏研究。在本研究中,我们通过稀缺思维理论 (Shah, Shafir, & Mullainathan, 2015) 和错误管理理论 (Haselton & Buss, 2009) 对这一现象的形成机制进行了分析。通过两个实验,我们取得了三项研究发现。首先,经济状况满意程度对P2P网贷投资意愿有着显著影响,对自身经济状况不满意的个体表现出了显著更高的P2P网贷投资意愿。其次,这一现象的形成原因是因为对自身经济状况不满意的个体会显著高估P2P网贷中的投资利益,显著低估投资中的风险,使得其在面对P2P网贷投资产品时更倾向于选择II类错误(即冒着风险进行投资的取伪错误)。最后,鼓励网贷投资的推广信息在经济状况满意程度对P2P网贷投资意愿的影响中起了显著的正向调节作用,暴露于网贷投资推广信息增强了对自身经济状况不满意的个体在面对P2P网贷投资时的感知利益上升、感知风险下降和投资意愿升高的倾向。基于这些发现,我们一方面建议未来的互联网金融投资应该设立一定的投资门槛以防范盲目投资,另一方面建议应该加强对网贷投资推广信息的监管。

English Abstract: In our community charity activities, we observed that people who are dissatisfied with their financial situation are more likely to be affected by the promotion information from online investment institutions, resulting in higher P2P lending investment intention. Although this phenomenon is very common, the mechanism is lacking in research. In this study, we explored the mechanism of this phenomenon through scarcity mind-set theory (Shah, Shafir, & Mullainathan, 2015) and error management theory (Haselton & Buss, 2009). Through two experiments, we have made three research findings. Firstly, the degree of financial satisfaction has a significant impact on P2P lending investment intention. Individuals who are relatively financial dissatisfied have shown a significantly higher intention in investing in P2P lending. Secondly, the mechanism of the above phenomenon is that individuals in financial dissatisfaction were significantly overestimated the investment benefits in P2P lending, and significantly underestimated the risks in that investment, making them more inclined to choose a type II error (the false negative error, i.e., investing in risk) in P2P lending investment. Finally, the promotion information which encouraging online investment has played as a significant positive moderator between financial dissatisfaction and P2P lending investment intention. After being exposed to investment promotion information, individuals in financial dissatisfaction shown an increasing tendency in overestimate investment benefits and underestimate investment risks, and the intention to invest in P2P lending were much stronger. Based on these findings, we suggest that online financial investment firms should set a certain investment threshold to prevent irrational investment. Moreover, we suggest strengthening the supervision of online investment promotion information.

Note: Downloadable document is in Chinese.

Keywords: 经济状况不满意, financial dissatisfaction, 推广信息, promotion information, P2P网贷投资, P2P lending investment, 稀缺思维, scarcity mind-set, 错误管理, error management theory

JEL Classification: C92, G40

Suggested Citation

Deng, Shichang and Huang, Qianqian and He, Yazhou, 对自身经济状况的不满意和投资推广信息是如何影响 P2P 网贷投资意愿的?来自稀缺思维理论与错误管理理论的解释 (How Financial Dissatisfaction and Investment Promotion Information Affect the Investment Intention in P2P Lending? An Explanation From Scarcity Mind-Set and Error Management Theory) (April 29, 2019). Available at SSRN: https://ssrn.com/abstract=3379768 or http://dx.doi.org/10.2139/ssrn.3379768

Shichang Deng (Contact Author)

Shanghai University of International Business and Economics ( email )

No. 1900, Wenxiang Road
Shanghai, 201620
China

Qianqian Huang

Shanghai University of International Business and Economics ( email )

No. 1900, Wenxiang Road
Shanghai, 201620
China

Yazhou He

Shanghai University of International Business and Economics ( email )

No. 1900, Wenxiang Road
Shanghai, 201620
China

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