Mobile Payment Adoption: An Empirical Investigation of Alipay

Published Online:https://doi.org/10.1287/isre.2021.0156

References

  • Aral S, Muchnik L, Sundararajan A (2009) Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks. Proc. Natl. Acad. Sci. USA 106(51):21544–21549.CrossrefGoogle Scholar
  • Austin PC, Small DS (2014) The use of bootstrapping when using propensity-score matching without replacement: A simulation study. Statist. Medicine 33(24):4306–4319.CrossrefGoogle Scholar
  • Avery J, Steenburgh TJ, Deighton J, Caravella M (2012) Adding bricks to clicks: Predicting the patterns of cross-channel elasticities over time. J. Marketing 76(3):96–111.CrossrefGoogle Scholar
  • Bang Y, Lee D-J, Han K, Hwang M, Ahn J-H (2013) Channel capabilities, product characteristics, and the impacts of mobile channel introduction. J. Management Inform. Systems 30(2):101–126.CrossrefGoogle Scholar
  • Bellman S, Potter RF, Treleaven-Hassard S, Robinson JA, Varan D (2011) The effectiveness of branded mobile phone apps. J. Interactive Marketing 25(4):191–200.CrossrefGoogle Scholar
  • Bertrand M, Duflo E, Mullainathan S (2004) How much should we trust differences-in-differences estimates? Quart. J. Econom. 119(1):249–275.CrossrefGoogle Scholar
  • Brynjolfsson E, Hu Y, Rahman MS (2009) Battle of the retail channels: How product selection and geography drive cross-channel competition. Management Sci. 55(11):1755–1765.LinkGoogle Scholar
  • Caliendo M, Kopeinig S (2008) Some practical guidance for the implementation of propensity score matching. J. Econom. Surveys 22(1):31–72.CrossrefGoogle Scholar
  • Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, Newey W, Robins J (2018) Double/debiased machine learning for treatment and structural parameters. Econom. J. 21(1):C1–C68.CrossrefGoogle Scholar
  • Coase RH (1937) The nature of the firm. Economica (N.S.) 4(16):386–405.CrossrefGoogle Scholar
  • Dube A, Jacobs J, Naidu S, Suri S (2020) Monopsony in online labor markets. Amer. Econom. Rev. Insights 2(1):33–46.CrossrefGoogle Scholar
  • Einav L, Levin J, Popov I, Sundaresan N (2014) Growth, adoption, and use of mobile e-commerce. Amer. Econom. Rev. 104(5):489–494.CrossrefGoogle Scholar
  • Gao F, Su X (2017) Online and offline information for omnichannel retailing. Manufacturing Service Oper. Management 19(1):84–98.LinkGoogle Scholar
  • Ghose A (2018) TAP: Unlocking the Mobile Economy (MIT Press, Cambridge, MA).Google Scholar
  • Ghose A, Han SP (2014) Estimating demand for mobile applications in the new economy. Management Sci. 60(6):1470–1488.LinkGoogle Scholar
  • Ghose A, Goldfarb A, Han SP (2012) How is the mobile internet different? Search costs and local activities. Inform. Systems Res. 24(3):613–631.LinkGoogle Scholar
  • Gu Z, Bapna R, Chan J, Gupta A (2022) Measuring the impact of crowdsourcing features on mobile app user engagement and retention: A randomized field experiment. Management Sci. 68(2):1297–1329.LinkGoogle Scholar
  • Han B, Sun T, Chu L, Wu L (2023) Connecting customers and merchants offline: Experimental evidence from the commercialization of last-mile stations at Alibaba. Management Inform. Systems Quart. Forthcoming.Google Scholar
  • Han SP, Park S, Oh W (2016) Mobile app analytics. Management Inform. Systems Quart. 40(4):983–1008.CrossrefGoogle Scholar
  • Haviland A, Nagin D, Rosenbaum P (2007) Combining propensity score matching and group-based trajectory analysis in an observational study. Psych. Methods 12(3):247–267.CrossrefGoogle Scholar
  • Heckman J, Ichimura H, Todd P (1998) Matching as an econometric evaluation estimator. Rev. Econom. Stud. 65(2):261–294.CrossrefGoogle Scholar
  • Jung J, Bapna R, Ramaprasad J, Umyarov A (2019) Love unshackled: Identifying the effect of mobile app adoption in online dating. Management Inform. Systems Quart. 43(1):47–72.CrossrefGoogle Scholar
  • Jung J, Umyarov A, Bapna R, Ramaprasad J (2014) Mobile as a channel: Evidence from online dating. 35th Internat. Conf. Inform. Systems (Association for Information Systems).Google Scholar
  • Kim SJ, Wang RJ, Malthouse EC (2015) The effects of adopting and using a brand’s mobile application on customers’ subsequent purchase behavior. J. Interactive Marketing 31:28–41.CrossrefGoogle Scholar
  • Kumar A, Mehra A, Kumar S (2019) Why do stores drive online sales? Evidence of underlying mechanisms from a multichannel retailer. Inform. Systems Res. 30(1):319–338.LinkGoogle Scholar
  • Lee J, Zhuang M, Kozlenkova I, Fang E (2016) The dark side of mobile channel expansion strategies. MSI Report.Google Scholar
  • Leong L, Hew T, Tan G, Ooi K (2013) Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. Expert Systems Appl. 40(14):5604–5620.CrossrefGoogle Scholar
  • Lewis M (2004) The influence of loyalty programs and short-term promotions on customer retention. J. Marketing Res. 41(3):281–292.CrossrefGoogle Scholar
  • Liébana-Cabanillas F, Muñoz-Leiva F, Sánchez-Fernández J (2015) Influence of age in the adoption of new mobile payment systems. Revista Brasileira Gestao Negócios 17(58):1390–1407.Google Scholar
  • Liu J (Jun), Abhishek V, Li B (2016) The impact of mobile adoption on customer omni-channel banking behavior. Working paper, Agency for Science, Technology and Research, Singapore Management University, Singapore.Google Scholar
  • Manchanda P, Packard G, Pattabhiramaiah A (2015) Social dollars: The economic impact of customer participation in a firm-sponsored online customer community. Marketing Sci. 34(3):367–387.LinkGoogle Scholar
  • Mehra A, Kumar S, Raju J (2018) Competitive strategies for brick-and-mortar stores to counter “showrooming.” Management Sci. 64(7):3076–3090.LinkGoogle Scholar
  • Meyer BD (1995) Natural and quasi-experiments in economics. J. Bus. Econom. Statist. 13(2):151–161.CrossrefGoogle Scholar
  • Miltgen CL, Popovič A, Oliveira T (2013) Determinants of end-user acceptance of biometrics: Integrating the “Big 3” of technology acceptance with privacy context. Decision Support Systems 56:103–114.CrossrefGoogle Scholar
  • Moulton B (1990) An illustration of a pitfall in estimating the effects of aggregate variables on micro units. Rev. Econom. Staist. 72(2):334–338.CrossrefGoogle Scholar
  • Mozur P (2017) In urban China, cash is rapidly becoming obsolete. The New York Times (July 16).Google Scholar
  • Napoli PM, Obar JA (2014) The emerging mobile internet underclass: A critique of mobile internet access. Inform. Soc. 30(5):323–334.CrossrefGoogle Scholar
  • Narang U, Shankar V (2019) Mobile app introduction and online and offline purchases and product returns. Marketing Sci. 38(5):756–772.LinkGoogle Scholar
  • Nykiel T (2014) Here’s why the biggest banks are pushing apple pay. Business Insider (September 26).Google Scholar
  • Oliveira T, Thomas M, Baptista G, Campos F (2016) Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Comput. Human Behav. 61:404–414.CrossrefGoogle Scholar
  • Overby E, Jap S (2009) Electronic and physical market channels: A multiyear investigation in a market for products of uncertain quality. Management Sci. 55(6):940–957.LinkGoogle Scholar
  • Pham TT, Ho J (2015) The effects of product-related, personal-related factors and attractiveness of alternatives on consumer adoption of NFC-based mobile payments. Tech. Soc. 43:159–172.CrossrefGoogle Scholar
  • Phang CW, Sutanto J, Kankanhalli A, Li Y, Tan BCY, Teo H-H (2006) Senior citizens’ acceptance of information systems: A study in the context of e-government services. IEEE Trans. Engrg. Management 53(4):555–569.CrossrefGoogle Scholar
  • Polasik M, Górka J, Wilczewski G, Kunkowski J, Przenajkowska K, Tetkowska N (2012) Time efficiency of point-of-sale payment methods: Empirical results for cash, cards and mobile payments. Internat. Conf. Enterprise Inform. Systems (Springer, New York), 306–320.Google Scholar
  • Retana GF, Forman C, Wu DJ (2016) Proactive customer education, customer retention, and demand for technology support: Evidence from a field experiment. Manufacturing Service Oper. Management 18(1):34–50.LinkGoogle Scholar
  • Rosenbaum PR (2002) Observational Studies (Springer, New York).CrossrefGoogle Scholar
  • Samuel J, Zheng Z, Xie Y (2020) Value of local showrooms to online competitors. Management Inform. Systems Quart. 44(3):1073–1106.CrossrefGoogle Scholar
  • Schierz PG, Schilke O, Wirtz BW (2010) Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Res. Appl. 9(3):209–216.CrossrefGoogle Scholar
  • Silver L, Smith A, Johnson C, Jiang J, Anderson M, Rainie L (2019) Use of smartphones and social media is common across most emerging economies. Technical report, Pew Research Center, Washington, DC.Google Scholar
  • Slade E, Williams M, Dwivedi Y, Piercy N (2015) Exploring consumer adoption of proximity mobile payments. J. Strategic Marketing 23(3):209–223.CrossrefGoogle Scholar
  • Smirnov NV (1939) Estimate of deviation between empirical distribution functions in two independent samples. Bull. Moscow Univ. 2(2):3–16.Google Scholar
  • Son Y, Oh W, Han SP, Park S (2020) When loyalty goes mobile: Effects of mobile loyalty apps on purchase, redemption, and competition. Inform. Systems Res. 31(3):835–847.LinkGoogle Scholar
  • Soysal G, Zentner A, Zheng Z (2019) Physical stores in the digital age: How store closures affect consumer churn. Production Oper. Management 28(11):2778–2791.CrossrefGoogle Scholar
  • Sun T, Wei Y, Golden J (2024) Geographical pattern of online word-of-mouth: How offline environment influences online sharing. Inform. Systems Res. Forthcoming.Google Scholar
  • Sun T, Shi L, Viswanathan S, Zheleva E (2019) Motivating effective mobile app adoptions: Evidence from a large-scale randomized field experiment. Inform. Systems Res. 30(2):523–539.LinkGoogle Scholar
  • Tang Q, Lin M, Kim Y (2016) Showrooming vs. competing: The role of product assortment and price. Working paper, Singapore Management University, Singapore.Google Scholar
  • Teo A, Tan G, Ooi K, Hew T, Yew K (2015) The effects of convenience and speed in m-payment. Indust. Management Data Systems 115(2):311–331.CrossrefGoogle Scholar
  • Venkatesh V (2003) User acceptance of information technology: Toward a unified view. Management Inform. Systems Quest. 27(3):425–478.CrossrefGoogle Scholar
  • Venkatesh V, Thong JYL, Xu X (2012) Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. Management Inform. Systems Quart. 36(1):157–178.CrossrefGoogle Scholar
  • Wang K, Goldfarb A (2017) Can offline stores drive online sales? J. Marketing Res. 54(5):706–719.CrossrefGoogle Scholar
  • Wang P, Xiong G, Yang J (2019) Frontiers: Asymmetric effects of recreational cannabis legalization. Marketing Sci. 38(6):927–936.AbstractGoogle Scholar
  • Williamson OE (1989) Transaction cost economics. Handbook of Industrial Organization, 135–182.Google Scholar
  • Xu J, Forman C, Kim JB, Van Ittersum K (2014) News media channels: Complements or substitutes? Evidence from mobile phone usage. J. Marketing 78(4):97–112.CrossrefGoogle Scholar
  • Xu K, Chan J, Ghose A, Han S (2016) Battle of the channels: The impact of tablets on digital commerce. Management Sci. 63(5):1469–1492.LinkGoogle Scholar
  • Yan L, Tan G, Loh X, Hew J, Ooi K (2021) QR code and mobile payment: The disruptive forces in retail. J. Retailing Consumer Services 58:102300.CrossrefGoogle Scholar
  • Zellner A (1962) An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. J. Amer. Statist. Assoc. 57(298):348–368.CrossrefGoogle Scholar
  • Zhang X, Phan TQ, Yang AX (2019) Grandfather clause and customer loyalty: Evidence from a quasi-experiment. Working paper, National University of Singapore (NUS), Singapore.Google Scholar
  • Zheng J, Qi Z, Dou Y, Tan Y (2019) How mega is the mega? Exploring the spillover effects of WeChat using graphical model. Inform. Systems Res. 30(4):1107–1452.Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.