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Effect of consumers’ online shopping on their investment in money market funds on ecommerce platforms

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Abstract

Along with the rapid growth of online and mobile shopping, a recent interesting phenomenon is the introduction of money market funds by many ecommerce platforms. The goal might be to provide consumers the one-stop convenience of both shopping and short-term investment. So far, little rigorous work has examined the relationship between online shopping and investment in ecommerce money market funds (eMMFs). In this study, we examine how consumers’ online-shopping expenditure affects their eMMF investment amounts using data from the China Household Finance Survey (CHFS) dataset. We find that consumers’ online-shopping expenditure increases their eMMF investment amounts, holding other variables constant. This effect is significant and positive even after we consider the potential endogeneity issues with seemingly unrelated regression estimation. Further, analyzing whether consumers’ risky-market experience could moderate this effect, we find the coefficient of the moderating term to be significant after we consider the potential endogeneity issues. These findings suggest that consumers’ eMMF investments is largely affected by their online-shopping experience, and this effect is even stronger for those with risky-market participation.

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References

  • Adner R, Chen J, Zhu F (2020) Frenemies in platform markets: heterogeneous profit foci as drivers of compatibility decisions. Manag Sci 66(6):2432–2451

    Article  Google Scholar 

  • Arnold Z (1962) An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. J Am Statistical Assoc 57(298):348–368

    Article  Google Scholar 

  • Bilgihan A (2016) Gen Y consumer loyalty in online shopping: an integrated model of trust, user experience and branding. Comput Hum Behav 61:103–113

    Article  Google Scholar 

  • Campbell JY (2006) Household Finance. J Finance 61:1553–1604

    Article  Google Scholar 

  • CBInsights (2018) Everything you need to know about what Amazon is doing in financial services. https://www.cbinsights.com/research/report/amazon-across-financial-services-fintech/

  • Chakraborty R, Lee J, Sen SB, Upadhyaya S, Rao HR (2016) Online shopping intention in the context of data breach in online retail stores: an examination of older and younger adults. Decis Support Syst 83:47–56

    Article  Google Scholar 

  • Chen J, Fan M, Li M (2016) Advertising versus brokerage model for online trading platforms. MIS Q 40(3):575–596

    Article  Google Scholar 

  • Chinese academy of financial inclusion (2018) Growing with pain: digital financial inclusion in China. Report, Chinese Academy of Financial Inclusion, Beijing. http://www.ruralfinanceandinvestment.org/sites/default/files/growing_with_pain_digital_financial_inclusion_in_china_cafi_report.pdf

  • Crockett J, Friend I (1967) Consumer investment behavior. In: Ferber R (Ed) Determinants of investment behavior. National Bureau of Economic Research. pp 15–127. http://www.nber.org/books/ferb67-1. ISBN 0-87014-309-3

  • Cronqvist H, Siegel S, Yu F (2015) Value versus growth investing: why do different investors have different styles? J Financ Econ 117:333–349

    Article  Google Scholar 

  • Erdem T, Sun B (2002) An empirical investigation of the spillover effects of advertising and sales promotions in umbrella branding. J Mark Res 39(4):408–420

    Article  Google Scholar 

  • Gan L, Yin Z, Jia N, Xu S, Ma S, Zhen L (2013) Data you need to know about China: research report of China household finance survey 2012. Springer, New york

    Google Scholar 

  • Gao H, Mao S, Huang W, Yang X (2018) Applying probabilistic model checking to financial production risk evaluation and control: a case study of Alibaba’s Yu’e Bao. IEEE Trans Comput Soc Syst 5(3):785–795

    Article  Google Scholar 

  • Grable JE (1997) Investor risk tolerance: testing the efficacy of demographics as differentiating and classifying factors. Dissertation, Virginia Polytechnic Institute and State University

  • Hashim A, Ghani EK, Said J (2009) Does consumers’ demographic profile influence online shopping? an examination using Fishbein’s theory. Can Soc Sci 5(6):19–31

    Google Scholar 

  • Hoffman DL, Novak TP, Peralta M (1999) Building consumer trust online. Commun ACM 42(4):80–85

    Article  Google Scholar 

  • iResearch (2020) The era of industrial payment 2020: China’s third-party payment industry report. http://www.iresearchchina.com/content/details8_62751.html

  • James T (1958) Estimation of relationships for limited dependent variables. Econometrica 26(1):24–36

    Article  Google Scholar 

  • Jarvenpaa SL, Tractinsky N, Vitale M (2000) Consumer trust in an internet store. Inf Technol Manag 1(12):45–71

    Article  Google Scholar 

  • Jason R (2001) From the sociology of trust towards a sociology of ‘E-trust.’ Int J New Prod Dev Innovation Manag 2(4):385–399

    Google Scholar 

  • Keller KL (1987) Memory factors in advertising: the effect of advertising retrieval cues on brand evaluations. J Consumer Res 14(3):316–333

    Article  Google Scholar 

  • Krishna A, Rajan U (2009) Cause marketing: spillover effects of cause-related products in a product portfolio. Manag Sci 55(9):1469–1485

    Article  Google Scholar 

  • Lam SY, Vandenbosch M, Hulland J, Pearce M (2001) Evaluating promotions in shopping environments: decomposing sales response into attraction, conversion, and spending effects. Mark Sci 20(2):194–215

    Article  Google Scholar 

  • Lewis R, Nguyen D (2015) Display advertising’s competitive spillovers to consumer search. Quantitative Mark Econ 13(2):93–115

    Article  Google Scholar 

  • Liu Q, Zhang F, Mao M, Xue B, Lin Z (2018) An empirical study on factors affecting continuance intention of using Yu’e Bao. Technical Gazette 25(5):1414–1420

    Google Scholar 

  • Martey E, Al-Hassan RM, Kuwornu JKM (2012) Commercialization of smallholder agriculture in Ghana: a Tobit regression analysis. Afr J Agric Res 7(14):2131–2141

    Google Scholar 

  • McLoughlin K, Meredith J (2017) The rise of Chinese money market funds. RBA bulletin (print copy discontinued), Reserve Bank of Australia, 75–84

  • Miyazaki AD, Fernandez A (2001) Consumer perceptions of privacy and security risks for online shopping. J Consumer Aff 35(1):27–44

    Article  Google Scholar 

  • Phelps J, Nowak G, Ferrell E (2000) Privacy concerns and consumer willingness to provide personal information. J Public Policy Mark 19(1):27–41

    Article  Google Scholar 

  • Poterba JM, Samwick AA (2003) Taxation and household portfolio composition: US evidence from the 1980s and 1990s. J Public Econ 87(1):5–38

    Article  Google Scholar 

  • Ren J, Sun H (2017) Acceptance behavior of internet wealth management based on user risk perception: the case of Alibaba’s Yu’e Bao. 2017 International conference on management engineering, software engineering and service sciences(ICMSS 2017), Wuhan China, China. https://dl.acm.org/doi/proceedings/https://doi.org/10.1145/3034950

  • Sahni NS (2016) Advertising spillovers: evidence from online field experiments and implications for returns on advertising. J Mark Res 53(4):459–478

    Article  Google Scholar 

  • Song W, Chen J, Li W (2020) Spillover effect of consumer awareness on third parties’ selling strategies and retailers’ platforms openness, Information Systems Research, forthcoming

  • Strzelecki A, Rizun M (2020) Consumers’ security and trust for online shopping after GDPR: examples from Poland and Ukraine. Digital Policy, Regulation and Governance (forthcoming)

    Google Scholar 

  • Weber M, Weber EU, Nosić A (2013) Who takes risks when and why: determinants of changes in investor risk taking. Rev Finance 17(3):847–883

    Article  Google Scholar 

  • Xu H, Chen J, Whinston AB (2018) Identity management and tradable reputation. MIS Q 42(2):577–593

    Article  Google Scholar 

  • Yousafzai SY, Pallister JG, Foxall GR (2003) A proposed model of e-trust for electronic banking. Technovation 23:847–860

    Article  Google Scholar 

  • Zetzsche DA, Buckley RP, Arner DW, Barberis JN (2017) From FinTech to TechFin: the regulatory challenges of data-driven finance. Working Paper, European Banking Institute, Frankfurt

  • Zhou L, Dai L, Zhang D (2007) Online shopping acceptance model—a critical survey of consumer factors in online shopping. J Electron Commer Res 8(1):41–62

    Google Scholar 

  • Zhou W, Tsiga Z, Li B, Zheng S, Jiang S (2018) What influence users’ e-finance continuance intention? The moderating role of trust. Industrial Manag Data Syst 118(8):1647–1670

    Article  Google Scholar 

  • Zhu F, Zhang Y, Palepu KG, Woo AK, and Dai NH (2017) Ant financial. Harvard business school case 617–060 (Revised March 2019)

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  1. School of Management, Zhejiang University, Zhejiang, China

    Zheren Wang & Shenglin Ben

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  1. Zheren Wang
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  2. Shenglin Ben
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Correspondence to Shenglin Ben.

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Wang, Z., Ben, S. Effect of consumers’ online shopping on their investment in money market funds on ecommerce platforms. Inf Syst E-Bus Manage 20, 325–346 (2022). https://doi.org/10.1007/s10257-021-00516-5

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  • DOI: https://doi.org/10.1007/s10257-021-00516-5

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