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The moderating role of income on consumers’ preferences and usage for online and offline payment methods

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Abstract

In this paper we examine consumer attitudes towards a payment method, which is a key factor affecting the probability of completing a transaction offline and online. More specifically, we constructed a model that surveyed the offline and online usage of prepaid e-cash, debit cards, credit cards and cash. User perceptions of the attractiveness of e-cash and various traditional payment means were also empirically assessed. Consumer attitudes towards a payment technology were found to be influential on users’ perceptions in both online and offline environments. User perceptions of offline purchases with a payment technology had significant and positive effects on the corresponding online usage perceptions. The effects of our research model are contingent on the income level of users. Our findings have significant implications, as they could help shed light on why consumers abandon their shopping carts and do not complete their transactions, which could potentially play a significant role when it comes to designing applications targeting sspecific consumer segments.

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Notes

  1. The \(\chi ^{2}\) statistic is the traditional fit measure for evaluating the hypothesis \(\hbox {H}_{0}:\Sigma =\Sigma (\uptheta )\) where \(\Sigma \) is the population covariance structure and \(\Sigma (\uptheta )\) is the covariance structure approximated by the model. We would like to accept this hypothesis, so small values of the \(\chi ^{2}\) statistic are preferred. One idiosyncrasy of this statistic is that it tends to be sensitive to, and to increase with, departures from multivariate normality (particularly excessive kurtosis). The fact that our data were ordinals from 1 to 7 implies a skewness which will tend to increase the value of this particular statistic, even with optimal fit.

  2. RMSEA provides an indication of the size of error of approximation of \(\Sigma \), the population covariance structure, by \(\Sigma (\uptheta )\), that of the model, but per degree of freedom, thus taking model complexity into account. Ideally this would be zero, and larger values indicate an inappropriate model; values less than 0.05 reflect a good fit; between 0.05 and 0.08 a mediocre fit; and those above 0.08 reflect a poor fit. Again, skewed distributions will tend to raise this value.

References

  1. Auh, S., Shih, E., & Yoon, Y. (2007). Aligning benefits with payments in a consumer financing context. A test of the pattern alignment hypothesis. SSRN eLibrary.

  2. Borzekowski, R., Kiser, E., & Ahmed, S. (2008). Consumers’ use of debit cards: Patterns, preferences, and price response. Journal of Money, Credit and Banking, 40(1), 149–172.

    Article  Google Scholar 

  3. Carow, K. A., & Staten, M. E. (1999). Debit, credit, or cash: Survey evidence on gasoline purchases. Journal of Economics and Business, 51(5), 409–421.

    Article  Google Scholar 

  4. Chakravorti, S., & Lubasi, V. (2006). Payment instrument choice: The case of prepaid cards. Economic Perspectives, Federal Reserve Bank of Chicago, 2nd Quarter, 29–43.

  5. Cheung, C. M. K., Chan, G. W. W., & Limayem, M. (2005). A critical review of online consumer behavior: Empirical research. Journal of Electronic Commerce in Organizations, 3(4), 1–19.

    Article  Google Scholar 

  6. Chong, S., Bagnall, J., & Smith, K. E. (2011). Australian consumer payment behaviour and preferences. JASSA, 2(4), 20–29.

    Google Scholar 

  7. Close, A. G., & Kukar-Kinney, M. (2010). Beyond buying: Motivations behind consumers’ online shopping cart use. Journal of Business Research, 63(9–10), 986–992.

    Article  Google Scholar 

  8. Davis, F., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.

    Article  Google Scholar 

  9. Eastin, M. (2002). Diffusion of e-commerce: An analysis of the adoption of four e-commerce activities. Telematics and Informatics, 19(3), 251–267.

    Article  Google Scholar 

  10. Fenech, T. (2002). Antecedents to web cart abandonment. Paper presented at the Australian and New Zealand Marketing Academy (ANZMAC) Conference, Melbourne.

  11. Foscht, T., Maloles, C. I., Swoboda, B., & Chia, S. (2010). Debit and credit card usage and satisfaction who uses which and why—evidence from Austria. International Journal of Bank Marketing, 28(2), 150–165.

    Article  Google Scholar 

  12. Garcia-Murillo, M. (2004). Institutions and the adoption of electronic commerce in Mexico. Electronic Commerce Research, 4, 201–219.

    Article  Google Scholar 

  13. Global Millennia Marketing. (2002). Shopping Cart Abandonment. Retrieved May 3, 2010 from http://www.globalmillenniamarketing.com/press_release_mar_12_02.htm.

  14. Gold, K. (2007). Tackling the Shopping Cart Abandonment Rate from http://www.searchmarketingstandard.com/tackling-the-shopping-cart-abandonment-rate.

  15. Holak, S., & Lehmann, D. (1990). Purchase intentions and the dimensions of innovation: An exploratory model. Journal of Product Innovation Management, 7(1), 59–73.

    Article  Google Scholar 

  16. Hussain, Z., Wallace, J., Tassabehji, R., & Khan, O. (2007). E-business in the developing world: An empirical study of payment methods and their implications. International Journal of Electronic Business, 5(3), 315–335.

    Article  Google Scholar 

  17. Isaac, J. T., Zeadally, S., & Cámara, J. S. (2012). A lightweight secure mobile payment protocol for vehicular ad-hoc networks (VANETs). Electronic Commerce Research, 12, 97–123.

    Article  Google Scholar 

  18. Jonker, N. (2007). Payment instruments as perceived by consumers. Results from a household survey. De Economist, 155(3), 271–303.

    Article  Google Scholar 

  19. Karahanna, E., Straub, D., & Chervany, N. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183–213.

    Article  Google Scholar 

  20. Kheng-Tan, W., & Tan, Y. (2009). From a retail-based e-micropayment program to a multi-purpose program: Which critical factors are needed for such a transformation? Paper presented at the IADIS International Conference e-Commerce 2009. Portugal: Algarve.

  21. Kindberg, T., Sellen, A., & Geelhoed, E. (2004). Security and trust in mobile interactions: A study of users’ perceptions and reasoning. Paper presented at the Ubiquitous Computing: 6th International Conference, Nottingham, UK.

  22. Knights, D., Noble, F., Vurdubakis, T., & Willmott, H. (2007). Electronic cash and the virtual marketplace: Reflections on a revolution postponed. Organization, 14(6), 747–776.

    Article  Google Scholar 

  23. Kukar-Kinney, M., & Close, A. (2010). The determinants of consumers’ online shopping cart abandonment. Journal of the Academy of Marketing Science, 38(2), 240–250.

    Article  Google Scholar 

  24. Lee, P.-M. (2002). Behavioral model of online purchasers in E-commerce environment. Electronic Commerce Research, 2(1–2), 75–85.

    Article  Google Scholar 

  25. Leung, L. (2001). College student motives for chatting on ICQ. New Media & Society, 3(4), 483–500.

    Article  Google Scholar 

  26. Liao, Z., & Cheung, M. (2001). Internet-based e-shopping and consumer attitudes: An empirical study. Information & Management, 38(5), 299–306.

    Article  Google Scholar 

  27. Lohse, G., Bellman, S., & Johnson, E. (2000). Consumer buying behavior on the Internet: Findings from panel data. Journal of Interactive Marketing, 14(1), 15–29.

    Article  Google Scholar 

  28. Moe, W. W., & Fader, P. S. (2001). Uncovering patterns in cybershopping. California Management Review, 43(4), 106–117.

    Article  Google Scholar 

  29. Moore, S., & Mathews, S. (2008). An exploration of online shopping cart abandonment syndrome: A matter of risk and reputation. Journal of Website Promotion, 2(1), 71–88.

    Google Scholar 

  30. Oliver, R. L., & Shor, M. (2003). Digital redemption of coupons: Satisfying and dissatisfying effects of promotion codes. Journal of Product & Brand Management, 12(2), 121–134.

    Article  Google Scholar 

  31. Park, C., & Jun, J. (2003). A cross-cultural comparison of internet buying behavior Effects of Internet usage, perceived risks, and innovativeness Cheol Park, Jong-Kun Jun the authors. International Marketing Review, 20(5), 534–553.

    Article  Google Scholar 

  32. Penz, E., Meier-Pesti, K., & Kirchler, E. (2004). It’s practical, but no more controllable: Social representations of the electronic purse in Austria. Journal of Economic Psychology, 25(6), 771–787.

    Article  Google Scholar 

  33. Phillips, D. J. (1998). The social construction of a secure, anonymous electronic payment system: Frame alignment and mobilization around Ecash. Journal of Information Technology, 13(4), 273–284.

    Article  Google Scholar 

  34. Rajamma, R. K., Paswan, A. K., & Hossain, M. M. (2009). Why do shoppers abandon shopping cart? Perceived waiting time, risk, and transaction inconvenience. Journal of Product & Brand Management, 18(3), 188–197.

    Article  Google Scholar 

  35. Renaud, K., Cockshott, T., & Hair, M. (2009). Everyone Abandons—Eventually: Understanding the Online Shopping Experience. Paper presented at the Commerce and Enterprise Computing, 2009. CEC ’09. IEEE Conference.

  36. Roberts, H., & Gregor, S. (2005). Why Australian merchants aren’t adopting e-money. Journal of Research and Practice in Information Technology, 37(1), 11–25.

    Google Scholar 

  37. Rogers, E. (1995). Diffusion of innovations (4th ed.). New York: The Free Press.

    Google Scholar 

  38. Rossi, P., Wright, J., & Anderson, A. (1983). Handbook of survey research. New York: Academic Press.

    Google Scholar 

  39. See-To, E. W. K., Jaisingh, J., & Tam, K. Y. (2007). Analysis of electronic micro-payment market. Journal of Electronic Commerce Research, 8(1), 63–83.

    Google Scholar 

  40. Shy, O., & Tarkka, J. (2002). The market for electronic cash cards. Journal of Money, Credit, and Banking, 34(2), 299–314.

    Article  Google Scholar 

  41. Stalder, F. (2002). Failures and successes: Notes on the development of electronic cash. The Information Society: An International Journal, 18(3), 209–219.

    Article  Google Scholar 

  42. Tan, W. K., & Tan, Y. J. (2012). Transformation of smart-card-based single-purpose e-micropayment scheme to multi-purpose scheme: A case study. Expert Systems with Applications, 39(3), 2306–2313.

    Article  Google Scholar 

  43. Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(4), 561–570.

    Article  Google Scholar 

  44. Thompson, R., Higgins, C., & Howell, J. (1994). Influence of experience on personal computer utilization: Testing a conceptual model. Journal of Management Information Systems, 11(1), 167–187.

    Google Scholar 

  45. van Hove, L. (2004). Electronic purses in Euroland: Why do penetration and usage rates differ? Paper presented at the The European Money and Finance Forum.

  46. Venkatesh, V., Morris, M., Hall, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: Towards a unified view. MIS Quarterly, 27(3), 425–478.

    Google Scholar 

  47. Vincent, O. R., Folorunso, O., & Akinde, A. D. (2010). Improving e-payment security using elliptic curve cryptosystem. Electronic Commerce Research, 10(1), 27–41.

    Article  Google Scholar 

  48. Wang, C.-T., Chang, C.-C., & Lin, C.-H. (2002). A new micro-payment system using general payword chain. Electronic Commerce Research, 2(1–2), 159–168.

    Article  Google Scholar 

  49. Wang, H., Zhang, Y., & Cao, J. (2004). An electronic cash scheme and its management. Concurrent Engineering, 12(3), 247–257.

    Article  Google Scholar 

  50. Wansink, B. (1994). Advertising’s impact on category substitution. Journal of Marketing Research, 31(4), 505–515.

    Article  Google Scholar 

  51. Wansink, B., & Ray, M. (1996). Advertising strategies to increase usage frequency. Journal of Marketing Research, 60(1), 31–46.

    Article  Google Scholar 

  52. Westland, J. C. (2002). Preference ordering cash, near cash, and electronic cash. Journal of Organizational Computing and Electronic Commerce, 12(3), 223–242.

    Article  Google Scholar 

  53. Westland, J. C., Kwok, M., Shu, J., Kwok, T., & Ho, H. (1997). Electronic cash in Hong Kong. Electronic Markets, 7(2), 3–6.

    Article  Google Scholar 

  54. Worthington, S., Stewart, D., & Lu, X. (2007). The adoption and usage of credit cards by urban-affluent consumers in China. International Journal of Bank Marketing, 25(4), 238–252.

    Article  Google Scholar 

  55. Zhang, H., & Li, H. (2006). Factors affecting payment choices in online auctions: A study of eBay traders. Decision Support Systems, 42(2), 1076–1088.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Industrial & Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

    Eric W. K. See-To

  2. Newcastle University Business School, 5 Barrack Road, Newcastle upon Tyne , NE1 4SE, UK

    Savvas Papagiannidis

  3. Department of Information and Decision Sciences, University of Illinois at Chicago, 2400 University Hall, 601 South Morgan Street, MC 294, Chicago, IL , 60607-7124, USA

    J. Christopher Westland

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  1. Eric W. K. See-To
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Correspondence to Savvas Papagiannidis.

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See-To, E.W.K., Papagiannidis, S. & Westland, J.C. The moderating role of income on consumers’ preferences and usage for online and offline payment methods. Electron Commer Res 14, 189–213 (2014). https://doi.org/10.1007/s10660-014-9138-3

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