Cash in the Trash? An Austrian Perspective on Mobile Payment Adoption


Despite offering many benefits to consumers, merchants, banks, and other providers, mobile payment still has not found widespread acceptance in Austria, for example, in 2015, 15% of Austrian consumers used the Internet or a mobile device for payments and 16% made contactless payments at least once a week. This study sheds light on this issue by taking a consumer perspective and investigating the factors that foster or hinder mobile payment adoption. Three popular user acceptance models were compared and in the end, a unified theory of acceptance and use of technologybased model (UTAUT2) was chosen. The developed model was composed of 12 factors (behavioral intention, utilitarian performance expectancy, hedonic performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, perceived security, privacy concerns, trust, cost, personal innovativeness) and three moderators (age, gender, experience). The proposed model was tested using data from 158 Austrian consumers and analyzed with partial least squares structural equation modeling (PLS-SEM). The results showed that 68% of consumers’ intention to use mobile payments could be explained, making it a promising model in the mobile payment research area based on the baseline data. Perceived risk and hedonic performance expectancy are the greatest drivers with psychological risk (a lack of fit with one’s self-image) as the most important risk dimension. The results suggest that mobile payment possesses lifestyle characteristics and its usage needs to be fun in order for consumers to prefer it to cash and cards.

Keywords: mobile payment adoption, unified theory of acceptance and use of technology, user acceptance models, partial least squares structural equation modeling

[1] Dahlberg T, Guo J, Ondrus J. A critical review of mobile payment research. Electronic Commerce Research and Applications. 2015;14(5):265–284.

[2] Tan G, Ooi K, Chong S, Hew T-S. NFC mobile credit card: The next frontier of mobile payment? undefined 2014. Telematics Informatics. 2014;31:292–307.

[3] Dahlberg T, Öörni A. Understanding changes in consumer payment habits - Do mobile payments and electronic invoices attract consumers? Understanding changes in consumer payment habits - Do mobile payments and electronic invoices attract consumers? Waikola, Hawai; 2007.

[4] Innopay BV. Mobile payments 2012. My mobile, my wallet? Innopay; 2012 [cited 2018 June 6]. Available from: 2012-Innopay-v1.01.pdf

[5] MasterCard. The Mobile Payments Readiness Index: A global market assessement. MasterCard; 2012 [cited 2018 June 5]. Available from:

[6] ING Bank N.V. Immer mehr Lust auf Mobile Shopping. 2016 [cited 2018 July 3]. Available from: presse/pressemeldungen/2016/immer-mehr-lust-auf-mobile-shopping

[7] Zmijewska A, Lawrence E, Steele R. Towards understanding of factors influencing user acceptance of mobile payment systems. Towards Understanding of Factors Influencing User Acceptance of Mobile Payment Systems. Madrid, Spain; 2004. p. 270–277.

[8] Magnier-Watanabe R. An institutional perspective of mobile payment adoption: The case of Japan. An Institutional Perspective of Mobile Payment Adoption: The Case of Japan. Waikola, Hawai; 2014. p. 1043–1052.

[9] Ondrus J, Pigneur Y. Cross-industry preferences for development of mobile payments in Switzerland. Electronic Markets. 2007;17(2):142–152.

[10] Ooi K-B, Tan GW-H. Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card. Expert Systems With Applications. 2016;59:33–46.

[11] Dahlberg T, Mallat N, Ondrus J, Zmijewska A. Past, present and future of mobile payments research: A literature review. Electronic Commerce Research and Applications. 2008;7(2):165–181.

[12] Ghezzi A, Renga F, Balocco R, Pescetto P. Mobile payment applications: Offer state of the art in the Italian market. Info. 2010;12(5):3–22.

[13] Mallat N. Exploring consumer adoption of mobile payments – A qualitative study. The Journal of Strategic Information Systems. 2007;16(4):413–432.

[14] Chen L. A theoretical model of consumer acceptance of mPayment. A Theoretical Model of Consumer Acceptance of mPayment. Acapulco, Mexico; 2006. Paper 247.

[15] Gerpott TJ, Meinert P. Who signs up for NFC mobile payment services? Mobile network operator subscribers in Germany. Electronic Commerce Research and Applications. 2017;23:1–13.

[16] Chandra S, Srivastava SC, Theng YL. Evaluating the role of trust in consumer adoption of mobile payment systems: An empirical analysis. Communications of the Association for Information Systems. 2010;27:561–588.

[17] Zhou T. An empirical examination of continuance intention of mobile payment services. Decision Support Systems. 2013;54(2):1085–1091.

[18] Österreichische Nationalbank. Ergebnisse der OeNB Zahlungsmittelumfrage. 2015 [cited 2018 June 5]. Available from: com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0ahUKEwjEo- W827zbAhWEuhQKHcd4BjsQFggoMAA&url=https{%}3A{%}2F{%}2Fwww.oenb. at{%}2Fdam{%}2Fjcr{%}3A4e2c0617-d4b6-4df9-83ea-fdd727a85a51{%}2F2015-2- HJ-Zahlungsmittelumfrage_V3.pdf&usg=AOvVaw3QFKyfWgzw-ZrZE8J-viFh

[19] Statista Inc. Mobile payment usage in Austria 2016. Statista; 2016 [cited 2018 June 7]. Available from: in-austria/

[20] Rusu C, Stix H. Cash and card payments – Recent results of the Austrian payment diary survey. 2016 [cited 2018 June 7]. Available from: rja&uact=8&ved=0ahUKEwjlxZC94MHbAhVPLFAKHR_5Ak8QFgg9MAI&url= https{%}3A{%}2F{%}{%}2Fdam{%}2Fjcr{%}3Ad575fb1bf59c- 4a74-8652-1c6e05cd5ce7{%}2FCash-and-card-payments.pdf&usg= AOvVaw2Qt7bM7bTyvS5P0QEa18Q5

[21] Venkatesh V, Morris M, Davis G, Davis F. User acceptance of information technology: Toward a unified view. MIS Quarterly. 2003;27:425–478.

[22] Venkatesh V, Thong JY, Xu X. Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly. 2012;36(1):157–178.

[23] Khalilzadeh J, Ozturk AB, Bilgihan A. Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Computers in Human Behavior. 2017;70:460–474.

[24] Hair JF, Hult GTM, Ringle CM, Sarstedt M. A primer on Partial Least Squares Structural Equation Modeling. 2nd ed. Los Angeles: Sage Publications Ltd.; 2017.

[25] Hoyle RH. Introduction and overview. Handbook of Structural Equation Modeling. New York: Guilford Press; 2012.

[26] Hair JF, Ringle CM, Sarstedt M. PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice. 2011;19(2):139–152. 6679190202

[27] Porst R. Fragebogen: Ein Arbeitsbuch. 2nd ed. Wiesbaden: VS Verlag für Sozialwissenschaften; 2009.

[28] Küchenhoff H, Knieper T, Eichhorn W, Mathes H, editors. Statistik für Kommunikationswissenschaftler. 2., überarbeitete Auflage. Konstanz: UVK-Verlagsgesellschaft; 2006.

[29] Statistik Austria. Bevölkerung nach Alter und Geschlecht [Internet]. 2018 [cited 2018 June 5]. Available from: ung/bevoelkerungsstruktur/bevoelkerung_nach_alter_geschlecht/index.html

[30] Barclay D, Thompson R, Higgins C. The Partial Least Squares (PLS) approach to causal modeling: Personal computer use as an illustration. Technology Studies. 1995;2(2):285–309.

[31] Fricker RD, Schonlau M. Advantages and disadvantages of internet research surveys: Evidence from the literature. Field Methods. 2002;14(4):347–367.

[32] Hair JF, Sarstedt M, Ringle C, Gudergan SP. Advanced Issues in Partial Least Squares Structural Equation Modeling. Los Angeles: Sage Publications Ltd.; 2017.

[33] Koenig-Lewis N, Marquet M, Palmer A, Zhao AL. Enjoyment and social influence: Predicting mobile payment adoption. The Service Industries Journal. 2015;35(10):537–554

[34] Teo A-C, Tan GW-H, Ooi K-B, Hew T-S, Yew K-T. The effects of convenience and speed in m-payment. Industrial Management & Data Systems. 2015;115(2):311–331.

[35] Determann L. Adequacy of data protection in the USA: Myths and facts. International Data Privacy Law. 2016;6(3):244–250.

[36] Pham T, Ho J. The effects of product-related, personal-related factors and attractiveness of alternatives on consumer adoption of NFC-based mobile payments. Technology in Society. 2015;43:159–172.

[37] Featherman MS, Pavlou PA. Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies. 2003;59(4):451–474.

[38] Morosan C, DeFranco A. It’s about time: Revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels. International Journal of Hospitality Management. 2016;53:17–29.

[39] Oliveira T, Thomas M, Baptista G, Campos F. Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior. 2016;61:404–414.

[40] Kim C, Mirusmonov M, Lee I. An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior. 2010;26(3):310– 322.

[41] Shin D-H. Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior. 2009;25(6):1343–1354.

[42] Liébana-Cabanillas F, Sánchez-Fernández J, Muñoz-Leiva F. The moderating effect of experience in the adoption of mobile payment tools in Virtual Social Networks: The m-Payment Acceptance Model in Virtual Social Networks (MPAM-VSN). International Journal of Information Management. 2014;34(2):151–66.

[43] Bailey AA, Pentina I, Mishra AS, Mimoun MSB. Mobile payments adoption by US consumers: An extended TAM. International Journal of Retail & Distribution Management. 2017;45(6):626–640.

[44] Johnson VL, Kiser A, Washington R, Torres R. Limitations to the rapid adoption of M-payment services: Understanding the impact of privacy risk on M-Payment services. Computers in Human Behavior. 2018;79:111–122.

[45] Abrahão RdS, Moriguchi SN, Andrade DF. Intention of adoption of mobile payment: An analysis in the light of the Unified Theory of Acceptance and Use of Technology (UTAUT). RAI Revista de Administração e Inovação. 2016;13(3):221– 230.

[46] Chen L, Nath R. Determinants of mobile payments: An empirical analysis. Journal of International Technology and Information Management. 2008;17(1):9–20.

[47] Ozturk AB, Bilgihan A, Salehi-Esfahani S, Hua N. Understanding the mobile payment technology acceptance based on valence theory: A case of restaurant transactions International Journal of Contemporary Hospitality Management. 2017;29(8):2027– 2049.

[48] Arvidsson N. Consumer attitudes on mobile payment services – Results from a proof of concept test. International Journal of Bank Marketing. 2014;32(2):150–170.

[49] Statista Inc. Anteil der genutzten Handy-Betriebssysteme in Österreich nach Geschlecht im Jahr 2016. Statista; 2018 [cited 2018 July 2]. Available from: in-oesterreich-nach-geschlecht/

[50] Liébana-Cabanillas F, Marinkovic V, Ramos de Luna I, Kalinic Z. Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach. Technological Forecasting and Social Change. 2017;April:117–130.

[51] Venkatesh V, Davis FD. A model of the antecedents of perceived ease of use: Development and test. Decision Sciences. 1996;27(3):451–481. 5915.1996.tb01822.x

[52] Secure Payment Technologies GmbH. Blue Code – Einfach bezahlen mit dem Smartphone & Handy. Blue Code; 2018 [cited 2018 June 6]. Available from:

[53] Google LLC. Google Pay - A better way to pay. 2018 [cited 2018 July 2]. Available from:

[54] Li H, Liu Y, Heikkilä J. Understanding the factors driving NFC-enabled mobile payment adoption: An empirical investigation. Chengdu, China; 2014.

[55] Kleijnen M, Wetzels M, Ruyter K de. Consumer acceptance of wireless finance. Journal of Financial Services Marketing. 2004;8(3):206–217.

[56] Leong L-Y, Hew T-S, Tan GW-H, Ooi K-B. Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. Expert Systems With Applications. 2013;14(40):5604–5620.

[57] Mobile Marketing Association Austria. Mobile Communication Report. 2017 [cited 2018 July 3]. Available from:

[58] ING Bank N.V. World on the move for mobile banking. Empowering personal finances anywhere, anytime. 2016.