Acceptance and use of digital payments by consumers: an empirical analysis in Italy




consumer behavior, UTAUT2, Italy, government incentives, digital payments


Frame of the research: Digital payments have gained popularity over the last decade. Several governments have introduced policies to foster the usage of digital payments by consumers, with the goal of curbing tax evasion. Nevertheless, cash is still predominant. This raises questions about the factors that can promote the usage of digital payments by consumers.

Purpose of the paper: This paper aims at investigating the factors affecting the adoption of digital payments by Italian consumers, extending the unified theory of acceptance and use of technology in a consumer context (UTAUT2) with three constructs that are relevant when analyzing this topic, namely the role of government incentives, the concerns related to privacy, and the degree of aversion towards tax evasion.

Methodology: To empirically assess the proposed research model, we gathered data in Italy through a web-based survey and analyzed them using Partial Least Squares-Structural Equation Modeling.

Results: Findings confirm the UTAUT2 model, except for price value, which is found to be insignificant. Government incentives and tax evasion aversion have a significant positive impact on the behavioral intention to adopt digital payments, whereas privacy concerns have a significant negative effect.

Research limitations: The main limitation of this study concerns data gathering, as it was conducted using the Computer-Assisted Web Interviewing (CAWI) methodology, which targets consumers that are already familiar with digital instruments.

Practical implications: The paper highlights the factors that both digital payment providers and public institutions may leverage to foster the adoption of digital payments by consumers.

Originality of the study: To the best of our knowledge, this study is unique as it examines the adoption of digital payments by Italian consumers, extending the framework to prepaid, credit, and debit cards, instead of considering mobile payments alone.


AJZEN, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

AL-OKAILY, M., LUTFI, A., ALSAAD, A., TAAMNEH, A., & ALSYOUF, A. (2020). The determinants of digital payment systems’ acceptance under cultural orientation differences: The case of uncertainty avoidance. Technology in Society, 63(August).

BANDURA, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice Hall.

DAVIS, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation, Massachusetts Institute of Technology.

DAVIS, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3).

DAVIS, F. D., BAGOZZI, R. P., & WARSHAW, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.

DAVIS, F. D., BAGOZZI, R. P., & WARSHAW, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132.

DINEV, T., & HART, P. (2005). Internet privacy concerns and social awareness as determinants of intention to transact. International Journal of Electronic Commerce, 10(2), 7–29.

EUROPEAN CENTRAL BANK. (2020). Study on the Payment Attitudes of Consumers in the Euro Area (SPACE) (Issue December 2020).

EUROPEAN CENTRAL BANK. (2021). Payments statistics (Issue July 2021).

EUROPEAN CENTRAL BANK. (2022). Study on the Payment Attitudes of Consumers in the Euro Area (SPACE) (Issue December 2022).

FISHBEIN, M., & AJZEN, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley, Readin, MA.

FORNELL, C., & LARCKER, D. F. (1981). Evaluating Structural Equation Models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39.

GOMEZ-HERRERA, E., MARTENS, B., & TURLEA, G. (2014). The drivers and impediments for cross-border e-commerce in the EU. Information Economics and Policy, 28(1), 83–96.

HAIR, J. F., HULT, G. T. M., RINGLE, C. M., & SARSTEDT, M. (2017). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications,Inc.

HAIR, J. F., RINGLE, C. M., & SARSTEDT, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.

HAMDOLLAH, R., & PURYA, B. (2016). Partial Least Squares Structural Equation Modeling with R. Journal of Marketing Theory and Practice, 21(11).

IMMORDINO, G., & RUSSO, F. F. (2018). Cashless payments and tax evasion. European Journal of Political Economy, 55(June 2017), 36–43.

INTERNATIONAL CHAMBER OF COMMERCE. (2020). WTO Plurilateral Negotiations on Trade-related Aspects of Electronic Commerce. ICC issues brief n° 4.

KRUGMANN, P. (2020). Understanding incentives in economics: 5 common types of economic incentives. Masterclass Articles.

LEE, M. C. (2009). Understanding the behavioural intention to play online games: An extension of the theory of planned behaviour. Online Information Review, 33(5), 849–872.

MADZHAROVA, B. (2020). Traceable payments and VAT design: Effects on VAT performance. CESifo Economic Studies, 66(3), 221–247.

MIGLIORE, G., WAGNER, R., CECHELLA, F. S., & LIÉBANA-CABANILLAS, F. (2022). Antecedents to the adoption of mobile payment in China and Italy: An integration of UTAUT2 and Innovation Resistance Theory. Information Systems Frontiers.

MOORE, G. C., & BENBASAT, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.

MOROSAN, C., & DEFRANCO, A. (2016). It’s about time: Revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels. International Journal of Hospitality Management, 53, 17–29.

OECD. (2017). OECD Digital Economy Outlook 2017. In OECD Publishing, Paris.

OECD. (2020). OECD Digital Economy Outlook 2020. In OECD Publishing, Paris.

PATIL, P. P., DWIVEDI, Y. K., & RANA, N. P. (2017). Digital payments adoption: An analysis of literature. Digital Nations – Smart Cities, Innovation, and Sustainability, 61–70.

PATIL, P. P., RANA, N. P., & DWIVEDI, Y. K. (2018). Digital payments adoption research: A review of factors influencing consumer’s attitude, intention and usage. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Vol. 11195 LNCS. Springer International Publishing.

SANTOSA, A. D., TAUFIK, N., PRABOWO, F. H. E., & RAHMAWATI, M. (2021). Continuance intention of baby boomer and X generation as new users of digital payment during COVID-19 pandemic using UTAUT2. Journal of Financial Services Marketing, 26(4), 259–273.

SIVATHANU, B. (2019). Adoption of digital payment systems in the era of demonetization in India: An empirical study. Journal of Science and Technology Policy Management, 10(1), 143–171.

SLADE, E. L., WILLIAMS, M. D., & DWIVEDI, Y. K. (2014). Devising a research model to examine adoption of mobile payments: An extension of UTAUT2. The Marketing Review, 14(3), 310–335.

SOODAN, V., & RANA, A. (2020). Modeling customers’ intention to use e-wallet in a developing nation: Extending UTAUT2 with security, privacy and savings. Journal of Electronic Commerce in Organizations, 18(1), 89–114.

STEWART, K. A., & SEGARS, A. H. (2002). An empirical examination of the concern for information privacy instrument. Information Systems Research, 13(1), 36–49.

SUNG, M. J., AWASTHI, R., & LEE, H. C. (2017). Can tax incentives for electronic payments reduce the shadow economy. Korea’s Attempt to Reduce Underreporting in Retail Businesses. In Policy Research Working Paper (No. 7936; Equitable Growth, Finance and Institutions Global Practice Group, Vol. 32, Issue 2).

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

THOMPSON, R. L., HIGGINS, C. A., & HOWELL, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124–143.

VENKATESH, V., & DAVIS, F. D. (2000). Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204.

VENKATESH, V., & MORRIS, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly: Management Information Systems, 24(1), 115–136.

VENKATESH, V., MORRIS, M. G., DAVIS, G. B., & DAVIS, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.

VENKATESH, V., THONG, J. Y. L., & XU, X. (2012). Consumer acceptance and use of information technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157–178.

VENTURINI, S., & MEHMETOGLU, M. (2019). Plssem: A stata package for structural equation modeling with partial least squares. Journal of Statistical Software, 88(1).

YANG, S., LU, Y., GUPTA, S., CAO, Y., & ZHANG, R. (2012). Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computers in Human Behavior, 28(1), 129–142.

ZERBINI, C., AIOLFI, S., BELLINI, S., LUCERI, B., & VERGURA, D. T. (2022). Mobile shopping behavior: a bibliometric analysis. Sinergie Italian Journal of Management, 40(2), 233–256.

ZHANG, Y., ZHANG, G., LIU, L., DE RENZIS, T., & SCHMIEDEL, H. (2019). Retail payments and the real economy. Journal of Financial Stability, 44, 100690.