Exploring factors influencing US millennial consumers’ use of tap-and-go payment technology

References

• Agrebi, S., and J. Jallais. 2015. “Explain the Intention to Use Smartphones for Mobile Shopping.” Journal of Retailing & Consumer Services 22 (January): 16–23. doi:10.1016/j.jretconser.2014.09.003.
   Google Scholar
• Ajzen, I. 1991. “The Theory Of Planned Behavior.” Organizational Behavior and Human Decision Processes 50 (2): 179-211. doi:10.1016/0749-5978(91)90020-T.
   Web of Science ®Google Scholar
• Amato-McCoy, D. M. 2018. “In-Store Shoppers Want to Be Left Alone—But Only until a Certain Point.” https://www.chainstoreage.com/technology/in-store-shoppers-want-to-be-left-alone-but-only-until-a-certain-point/
   Google Scholar
• Antón, C., C. Camarero, and J. Rodríguez. 2013. “Usefulness, Enjoyment, and Self-Image Congruence: The Adoption of e-Book Readers.” Psychology & Marketing 30 (4): 372–384. doi:10.1002/mar.20612.
   Web of Science ®Google Scholar
• Arora, S., and S. Sahney. 2018. “Antecedents to Consumers’ Showrooming Behavior: An Integrated TAM-TPB Framework.” Journal of Consumer Marketing 35 (4): 438–450. doi:10.1108/JCM-07-2016-1885.
   Web of Science ®Google Scholar
• Ashraf, A. R., N. Thongpapanl, and S. Auh. 2014. “The Application of the Technology Acceptance Model under Different Cultural Contexts: The Case of Online Shopping Adoption.” Journal of International Marketing 22 (3): 68–93. doi:10.1509/jim.14.0065.
   Web of Science ®Google Scholar
• Browne, M. W., and R. Cudeck. 1993. “Alternative Ways of Assessing Model Fit.” In Testing Structural Equation Models, ed. K. A. Bollen, 136–162. Newbury Park, CA: Sage.
   Google Scholar
• Chadha, R. 2018. “Four Mobile Payment Trends to Watch for in 2019.” https://retail.emarketer.com/article/four-mobile-payment-trends-watch-2019
   Google Scholar
• Chen, L.-D. 2008. “A Model of Consumer Acceptance of Mobile Payment.” International Journal of Mobile Communications 6 (1): 32–52. doi:10.1504/IJMC.2008.015997.
   Web of Science ®Google Scholar
• Chi, T. 2018. “Understanding Chinese Consumer Adoption of Apparel Mobile Commerce: An Extended TAM Approach.” Journal of Retailing & Consumer Services 44 (September): 274–284. doi:10.1016/j.jretconser.2018.07.019.
   Google Scholar
• Cho, J. 2004. “Likelihood to Abort an Online Transaction: Influences from Cognitive Evaluations, Attitudes, and Behavioral Variables.” Information & Management 41 (7): 827-838. doi:10.1016/j.im.2003.08.013.
   Web of Science ®Google Scholar
• Cocosila, M., and H. Trabelsi. 2016. “An Integrated Value-Risk Investigation of Contactless Mobile Payments Adoption.” Electronic Commerce Research & Applications 20: 159–170. doi:10.1016/j.elerap.2016.10.006.
   Web of Science ®Google Scholar
• Dabholkar, P. A., and R. P. Bagozzi. 2002. “An Attitudinal Model of Technology-Based Self-Service: Moderating Effects of Consumer Traits and Situational Factors.” Journal of the Academy of Marketing Science 30 (3): 184–202. doi:10.1177/0092070302303001.
   Web of Science ®Google Scholar
• Davis, F. D., R. P. Bagozzi, and P. R. Warshaw. 1989. “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models.” Management Science 35 (8): 982–1004. doi:10.1287/mnsc.35.8.982.
   Web of Science ®Google Scholar
• de Kerviler, G., N. T. M. Demoulin, and P. Zidda. 2016. “Adoption of In-Store Mobile Payment: Are Perceived Risk and Convenience the Only Drivers?” Journal of Retailing & Consumer Services 31 (July): 334–344. doi:10.1016/j.jretconser.2016.04.011.
   Google Scholar
• Dinev, T., and P. Hart. 2004. “Internet Privacy Concerns and Their Antecedents - Measurement Validity and a Regression Model.” Behaviour & Information Technology 23 (6): 413–22. doi:10.1080/01449290410001715723.
   Web of Science ®Google Scholar
• eMarketer. 2017. “The National Retail Federation (NRF) Scaled Back Its Forecast for US Retail Sales for the Year, Citing Sales Trends as Well as Consumer Income and Spending Data.” https://retail.emarketer.com/article/nrf-scales-back-expectations-2017-retail-sales/59b16e55ebd4000a7823aafa
   Google Scholar
• Falk, T., W. H. Kunz, J. J. Schepers, and A. J. Mrozek. 2016. “How Mobile Payment Influences the Overall Store Price Image.” Journal of Business Research 69 (7): 2417–2423. doi:10.1016/j.jbusres.2016.01.011.
   Web of Science ®Google Scholar
• Faqih, K. M., and M. M. Jaradat. 2015. “Assessing the Moderating Effect of Gender Differences and Individualism-Collectivism at Individual-Level on the Adoption of Mobile Commerce Technology: TAM3 Perspective.” Journal of Retailing & Consumer Services 22 (2015): 37–52. doi:10.1016/j.jretconser.2014.09.006.
   Google Scholar
• Federal Reserve. 2014. Consumers and mobile financial services 2014. Available at: www.federalreserve.gov/econresdata/consumers-and-mobile-financial-services-report-201403.pdf.Accessed October 14, 2019.
   Google Scholar
• Fishbein, M., and I. Ajzen. 1975. Beliefs, Attitude, Intention, and Behavior. Reading, MA: Addison-Wesley.
   Google Scholar
• Fornell, C., and D. F. Larcker. 1981. “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error.” Journal of Marketing Research 8 (1): 39–50. doi:10.1177/002224378101800104.
   Google Scholar
• Gefen, David, Elena Karahanna, and Detmar W. Straub.. 2003. “Trust and Tam in Online Shopping: An Integrated Model.” MIS Quarterly 27 (1): 51–90.
   Web of Science ®Google Scholar
• Gefen, D., E. Karahanna, and D. W. Straub. 2003a. “Trust and TAM in Online Shopping: An Integrated Model.” MIS Quarterly 27 (1): 51–90. doi:10.2307/30036519.
   Web of Science ®Google Scholar
• Gefen, D., E. Karahanna, and D. W. Straub. 2003b. “Inexperience and Experience with Online Stores: The Importance of TAM and Trust.” IEEE Transactions on Engineering Management 50 (3): 307–321. doi:10.1109/TEM.2003.817277.
   Web of Science ®Google Scholar
• Groß, M. 2015. “Exploring the Acceptance of Technology for Mobile Shopping: An Empirical Investigation among Smartphone Users.” International Review of Retail, Distribution and Consumer Research 25 (3): 215–235.
   Web of Science ®Google Scholar
• Im, H., and Y. Ha. 2013. “Enablers and Inhibitors of Permission-Based Marketing: A Case of Mobile Coupons.” Journal of Retailing & Consumer Services 20 (5): 495–503. doi:10.1016/j.jretconser.2013.05.002.
   Google Scholar
• Jahangir, N., and N. Begum. 2007. “Effect of Perceived Usefulness, Ease of Use, Security and Privacy on Customer Attitude and Adaptation in the Context of E-Banking.” Journal of Management Research (09725814) 7 (3): 147–57.
   Google Scholar
• Jones-Cooper, B. 2017. “These Countries Have Gone Mostly Cashless.” https://finance.yahoo.com/news/countries-gone-mostly-cashless-195953605.html
   Google Scholar
• Kalinic, Z., and V. Marinkovic. 2016. “Determinants of Users’ Intention to Adopt M-commerce: An Empirical Analysis.” Information Systems & E-Business Management 14 (2): 367–387. doi:10.1007/s10257-015-0287-2.
   Web of Science ®Google Scholar
• Karnouskos, S., and F. Fokus. 2004. “Mobile Payment: a Journey Through Existing Procedures and Standardization Initiatives.” Ieee Communications Surveys & Tutorials 6 (4): 44-66. doi:10.1109/COMST.2004.5342298.
   Web of Science ®Google Scholar
• Kaushik, A K., and Z. Rahman. 2015. “Innovation Adoption across Self-service Banking Technologies in India.” International Journal Of Bank Marketing 33 (2): 96–121. doi:10.1108/IJBM-01-2014-0006.
   Web of Science ®Google Scholar
• Kim, C., M. Mirusmonov, and I. Lee. 2010. “An Empirical Examination of Factors Influencing the Intention to Use Mobile Payment.” Computers in Human Behavior 26 (3): 310–322. doi:10.1016/j.chb.2009.10.013.
   Web of Science ®Google Scholar
• Kim, Gimun, BongSik Shin, and H G. Lee. 2009. “Understanding Dynamics between Initial Trust and Usage Intentions Of Mobile Banking.” Information Systems Journal 19 (3): 283–311. doi:10.1111/isj.2009.19.issue-3.
   Web of Science ®Google Scholar
• Koenig-Lewis, N., M. Marquet, A. Palmer, and A. L. Zhao. 2015. “Enjoyment and Social Influence: Predicting Mobile Payment Adoption.” Service Industries Journal 35 (10): 537–554. doi:10.1080/02642069.2015.1043278.
   Web of Science ®Google Scholar
• Korsgaard, M. A., and I. Roberson. 1995. “Procedural Justice in Performance Evaluation: The Role of Instrumental and Non-Instrumental Voice in Performance Appraisal Discussions.” Journal of Management 21 (4): 657–669. doi:10.1177/014920639502100404.
   Web of Science ®Google Scholar
• Köster, A., C. Matt, and T. Hess. 2016. “Carefully Choose Your (Payment) Partner: How Payment Provider Reputation Influences M-commerce Transactions.” Electronic Commerce Research & Applications 15 (1): 26–37. doi:10.1016/j.elerap.2015.11.002.
   Google Scholar
• Lee, K. C., and N. Chung. 2009. “Understanding Factors Affecting Trust in and Satisfaction with Mobile Banking in Korea: a Modified Delone and Mclean’s Model Perspective.” Interacting with Computers 21 (5–6): 385–392. doi:10.1016/j.intcom.2009.06.004.
   Web of Science ®Google Scholar
• López-Nicolás, C., and F Molina-Castillo. J., & Bouwman, H. 2008. An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models. Information & Management, 45(6), 359–364
   Google Scholar
• Mallat, N., M. Rossi, V K. Tuunainen, and A. Öörni. 2009. “The Impact Of Use Context on Mobile Services Acceptance: The case of Mobile Ticketing.” Information & Management 46 (3): 190–95. doi:10.1016/j.im.2008.11.008.
   Web of Science ®Google Scholar
• McCarthy, A. 2017. “Target’s Millennial Focus Gives It a Leg up for Mobile Payments.” https://www.emarketer.com/Article/Targets-Millennial-Focus-Gives-Leg-Up-Mobile-Payments/1015120?ecid=NL1014#sthash.LzgR9sYr.dpuf
   Google Scholar
• Mossholder, K. W., N. Bennett, E. R. Kemery, and M. A. Wesolowski. 1998. “Relationships between Bases of Power and Work Reactions: The Mediational Role of Procedural Justice.” Journal of Management 24 (4): 533–552. doi:10.1177/014920639802400404.
   Web of Science ®Google Scholar
• Murphy, B. 2013. “Benefits of Mobile Commerce in the Pay Parking Industry: How the Launch of the P$ Mobile Service Has Changed the Parking Experience in Montréal.” International Journal of Mobile Marketing 8 (1): 104–110.
   Google Scholar
• Muthén, L. K., and B. O. Muthén. 2014. Mplus: Statistical Analysis with Latent Variables (version 7.31). Los Angeles, CA: Muthén and Muthén.
   Google Scholar
• Narteh, B., M. A. Mahmoud, and S. Amoh. 2017. “Customer Behavioral Intentions Towards Mobile Money Services Adoption in Ghana.” Service Industries Journal 37 (7/8): 426–447. doi:10.1080/02642069.2017.1331435.
   Web of Science ®Google Scholar
• Natarajan, T., S. Balasubramanian, and D. Kasilingam. 2017. “Understanding the Intention to Use Mobile Shopping Applications and Its Influence on Price Sensitivity.” Journal of Retailing & Consumer Services 37 (July): 8–22. doi:10.1016/j.jretconser.2017.02.010.
   Google Scholar
• O’Cass, A., and T. Fenech. 2003. “Web Retailing Adoption: Exploring the Nature of Internet Users Web Retailing Behavior.” Journal of Retailing & Consumer Services 10 (2): 81–94. doi:10.1016/S0969-6989(02)00004-8.
   Google Scholar
• Oliveira, T., M. Thomas, G. Baptista, and F. Campos. 2016. “Mobile Payment: Understanding the Determinants of Customer Adoption and Intention to Recommend the Technology.” Computers in Human Behavior 61 (August): 404–414. doi:10.1016/j.chb.2016.03.030.
   Google Scholar
• Ozturk, A. B. 2016. “Customer Acceptance of Cashless Payment Systems in the Hospitality Industry.” International Journal of Contemporary Hospitality Management 28 (4): 801–817. doi:10.1108/IJCHM-02-2015-0073.
   Web of Science ®Google Scholar
• Parker, C. M., and T. Castleman. 2009. “Small Firm e-Business Adoption: A Critical Analysis of Theory.” Journal of Enterprise Information Management 22 (1/2): 167–182. doi:10.1108/17410390910932812.
   Google Scholar
• Parry, T. (2015). 36% of Global Mobile Payments are Made on iPhone. MultiChannel Merchant. Available at http://multichannelmerchant.com/news/36-global-mobile-payments-made-iphone/. Accessed October 14, 2019
   Google Scholar
• Perry, A. 2016. “Consumers’ Acceptance of Smart Virtual Closets.” Journal of Retailing & Consumer Services 33 (November): 171–177. doi:10.1016/j.jretconser.2016.08.018.
   Google Scholar
• Reid, M., and Y. Levy. 2008. “Integrating Trust and Computer Self-efficacy with TAM: An Empirical Assessment of Customers’ Acceptance of Banking Information Systems (BIS) in Jamaica.” Journal of Internet Banking & Commerce 13 (3): 1–18.
   Google Scholar
• Reserve, F. 2016. “Consumers and Mobile Financial Services 2016.” https://www.federalreserve.gov/consumerscommunities/mobile_finance.htm
   Google Scholar
• Roy, S. K., M. S. Balaji, A. Quazi, and M. Quaddus. 2018. “Predictors of Customer Acceptance of and Resistance to Smart Technologies in the Retail Sector.” Journal of Retailing & Consumer Services 42 (May): 147–160. doi:10.1016/j.jretconser.2018.02.005.
   Google Scholar
• Schierz, P. G., O. Schilke, and B. Wirtz. 2010. “Understanding Consumer Acceptance of Mobile Payment Services: An Empirical Analysis.” Electronic Commerce Research and Applications 9 (3): 209–216. doi:10.1016/j.elerap.2009.07.005.
   Web of Science ®Google Scholar
• Schneider, J. 2015. “How to Market to the iGeneration.” Harvard Business Review. https://hbr.org/2015/05/how-to-market-to-the-igeneration
   Google Scholar
• Shin, D.-H. 2009. “Towards an Understanding of the Consumer Acceptance of Mobile Wallet.” Computers in Human Behaviour 25 (6): 1343–1354. doi:10.1016/j.chb.2009.06.001.
   Web of Science ®Google Scholar
• Slade, E., M. Williams, Y. Dwivedi, and N. C. Piercy. 2015b. “Exploring Consumer Adoption of Proximity Mobile Payments.” Journal of Strategic Marketing 23 (3): 209–223. doi:10.1080/0965254X.2014.914075.
   Web of Science ®Google Scholar
• Slade, E. L., Y. K. Dwivedi, N. C. Piercy, and M. D Williams. 2015. “Modeling Consumers’ Adoption Intentions Of Remote Mobile Payments in The United Kingdom: Extending Utaut with Innovativeness, Risk, and Trust.” Psychology & Marketing 32 (8): 860–873. doi:10.1002/mar.20823.
   Web of Science ®Google Scholar
• Slade, E. L., Y. K. Dwivedi, N. C. Piercy, and M. D. Williams. 2015a. “Modelling Consumers’ Adoption Intentions of Remote Mobile Payments in the United Kingdom: Extending UTAUT with Innovativeness, Risk, and Trust.” Psychology & Marketing 32 (8): 860–873. doi:10.1002/mar.20823.
   Web of Science ®Google Scholar
• Smith, J. S., M. R. Gleim, S. G. Robinson, W. J. Kettinger, and S.-H. Park. 2014. “Using an Old Dog for New Tricks: A Regulatory Focus Perspective on Consumer Acceptance of RFID Applications.” Journal of Service Research 17 (1): 85–101. doi:10.1177/1094670513501394.
   Web of Science ®Google Scholar
• Sultan, F., A. J. Rohm, and T. Gao. 2009. “Factors Influencing Consumer Acceptance of Mobile Marketing: A Two-Country Study of Youth Markets.” Journal of Interactive Marketing 23 (4): 308–320. doi:10.1016/j.intmar.2009.07.003.
   Web of Science ®Google Scholar
• Tabachnick, B. G., and L. S. Fidell. 2013. Using Multivariate Statistics. Boston, MA: Allyn and Bacon.
   Google Scholar
• Teo, A.-C., G. W.-H. Tan, K.-B. Ooi, T.-S. Hew, and K.-T. Yew. 2015. “The Effects of Convenience and Speed in m-Payment.” Industrial Management & Data Systems 115 (2): 311–331. doi:10.1108/IMDS-08-2014-0231.
   Web of Science ®Google Scholar
• van der Heijden, H. 2003. “Factors Influencing the Usage of Websites: The Case of a Generic Portal in the Netherlands.” Information and Management 40 (6): 541–549. doi:10.1016/S0378-7206(02)00079-4.
   Web of Science ®Google Scholar
• Vance, A., C. Elie-Dit-Cosaque, and D. W. Straub. 2008. “Examining Trust in Information Technology Artifacts: The Effects of System Quality and Culture.” Journal of Management Information Systems 24 (4): 73–100. doi:10.2753/MIS0742-1222240403.
   Web of Science ®Google Scholar
• Venkatesh, V., and F. D. Davis. 2000. “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies.” Management Science 46 (2): 186–204. doi:10.1287/mnsc.46.2.186.11926.
   Web of Science ®Google Scholar
• Venkatesh, V., and H. Bala. 2008. “Technology Acceptance Model 3 and a Research Agenda on Interventions.” Decision Sciences 39 (2): 273–315. doi:10.1111/j.1540-5915.2008.00192.x.
   Web of Science ®Google Scholar
• Venkatesh, V., J. Y. L. Thong, and X. Xu. 2012. “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology.” MIS Quarterly 36 (1): 157–178. doi:10.2307/41410412.
   Web of Science ®Google Scholar
• Venkatesh, V., M. Morris, G. Davis, and F. Davis. 2003. “User Acceptance of Information Technology: Toward a Unified View.” MIS Quarterly 27 (3): 425–478. doi:10.2307/30036540.
   Web of Science ®Google Scholar
• Voropanova, E. 2015. “Exploring the Acceptance of Technology for Mobile Shopping: An Empirical Investigation among Smartphone Users.” The International Review of Retail, Distribution and Consumer Research 25 (3): 215–235.
   Web of Science ®Google Scholar
• Wu, J.-H., and S.-C. Wang. 2005. “What Drives Mobile Commerce? an Empirical Evaluation of the Revised Technology Acceptance Model.” Information and Management 42 (5): 719–729. doi:10.1016/j.im.2004.07.001.
   Web of Science ®Google Scholar
• Xin, H., A. A. Techatassanasoontorn, and F. B. Tan. 2015. “Antecedents of Consumer Trust in Mobile Payment Adoption.” Journal of Computer Information Systems 55 (4): 1–10. doi:10.1080/08874417.2015.11645781.
   Web of Science ®Google Scholar
• Yang, K. 2012. “Consumer Technology Traits in Determining Mobile Shopping Adoption: An Application of the Extended Theory of Planned Behavior.” Journal of Retailing & Consumer Services 19 (5): 484–491. doi:10.1016/j.jretconser.2012.06.003.
   Google Scholar
• Yang, K. C. C. 2005. “Exploring Factors Affecting the Adoption of Mobile Commerce in Singapore.” Telematics and Informatics 22 (3): 257–277. doi:10.1016/j.tele.2004.11.003.
   Google Scholar
• Zhou, T. 2011. “An Empirical Examination of Initial Trust in Mobile Banking.” Internet Research 21 (5): 527–540. doi:10.1108/10662241111176353.
   Web of Science ®Google Scholar
• Zhou, T. 2013. “An Empirical Examination of Continuance Intention of Mobile Payment Services.” Decision Support Systems 54 (2013): 1085–1091. doi:10.1016/j.dss.2012.10.034.
   Google Scholar