Understanding Factors Affecting UPI Adoption among Low-Income Consumers in India

Authors

  •   Rosin C. Jacob Assistant Professor, St. Joseph’s College of Engineering and Technology, Palai - 686 579, Kerala
  •   Mishel Elizabeth Jacob Assistant Professor (Corresponding Author), Baselius College, Kottayam - 686 001, Kerala
  •   Johney Johnson Professor, School of Management and Business Studies, Mahatma Gandhi University, Kottayam - 686 560, Kerala

DOI:

https://doi.org/10.17010/ijf/2024/v18i7/174032

Keywords:

behavioral intention to use UPI

, unified payment interface (UPI), perceived risk, facilitating conditions.

JEL Classification Codes

, G2, G5, G59, O30

Paper Submission Date

, August 20, 2023, Paper sent back for Revision, March 15, 2024, Paper Acceptance Date, April 10, Paper Published Online, July 15, 2024

Abstract

Purpose : The study investigated the factors influencing the behavioral intention to use Unified Payment Interface (UPI) apps among low-income Indian consumers. It examined how consumers’ behavioral intention to use UPI apps was influenced by their perceptions of the technology’s performance (performance expectancy), ease of use (effort expectancy), presence of facilitating conditions (FC), social influence (SI), and perceived risks (PR).

Design/Methodology/Approach : An empirical study using a causal research design was conducted. The sampling unit consisted of Indian citizens with monthly household incomes below ₹ 20,000. Data were collected using questionnaires from 351 respondents and analyzed using structural equation modeling with AMOS 21.

Findings : The findings demonstrated that performance expectancy, effort expectancy, and facilitating conditions positively impacted the behavioral intention to use UPI apps. A negative relationship was found between PR and behavioral intention. SI showed no impact on the usage intention among low-income consumers.

Practical Implications : Understanding the adoption of UPI apps among low-income consumers can help policymakers and app developers promote financial inclusion by developing strategies to bridge the digital divide in India.

Originality/Value : The study is unique as it extended the unified theory of acceptance and use of the technology model by including the PR construct in the context of UPI app adoption among the low-income population of India. Understanding this demographic is important to attaining financial inclusion.

Downloads

Download data is not yet available.

Published

2024-07-01

How to Cite

Jacob, R. C., Jacob, M. E., & Johnson, J. (2024). Understanding Factors Affecting UPI Adoption among Low-Income Consumers in India. Indian Journal of Finance, 18(7), 44–59. https://doi.org/10.17010/ijf/2024/v18i7/174032

Issue

Section

Articles

References

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002

Amnas, M. B., Selvam, M., & Parayitam, S. (2024). FinTech and financial inclusion: Exploring the mediating role of digital financial literacy and the moderating influence of perceived regulatory support. Journal of Risk and Financial Management, 17(3), 108. https://doi.org/10.3390/jrfm17030108

Bartlett, M. S. (1954). A note on the multiplying factors for various χ 2 approximations. Journal of the Royal Statistical Society. Series B (Methodological), 16(2), 296–298. https://doi.org/10.1111/j.2517-6161.1954.tb00174.x

Bentler, P. M., & Dudgeon, P. (1996). Covariance structure analysis: Statistical practice, theory, and directions. Annual Review of Psychology, 47, 563–592. https://doi.org/10.1146/annurev.psych.47.1.563

Bhat, R., & Chauhan, S. S. (2023). Exploring Unified Payments Interface's (UPI) adoption factors and trust variables: Insights from retailers and consumers across low and middle-income communities. Available at SSRN. https://doi.org/10.2139/ssrn.4624379

Chawla, D., & Joshi, H. (2019). Consumer attitude and intention to adopt mobile wallet in India – An empirical study. International Journal of Bank Marketing, 37(7), 1590–1618. https://doi.org/10.1108/IJBM-09-2018-0256

de Luna, I. R., Liébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2019). Mobile payment is not all the same: The adoption of mobile payment systems depending on the technology applied. Technological Forecasting and Social Change, 146, 931–944. https://doi.org/10.1016/j.techfore.2018.09.018

de Sena Abrahão, R., Moriguchi, S. N., & Andrade, D. F. (2016). Intention of adoption of mobile payment: An analysis in the light of the unified theory of acceptance and use of technology (UTAUT). Administration and Innovation Magazine, 13(3), 221–230. https://doi.org/10.1016/j.rai.2016.06.003

Demir, A., Pesqué-Cela, V., Altunbas, Y., & Murinde, V. (2022). Fintech, financial inclusion and income inequality: A quantile regression approach. The European Journal of Finance, 28(1), 86–107. https://doi.org/10.1080/1351847X.2020.1772335

Eriksson, N., Gökhan, A., & Stenius, M. (2021). A qualitative study of consumer resistance to mobile payments for in-store purchases. Procedia Computer Science, 181, 634–641. https://doi.org/10.1016/j.procs.2021.01.212

Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451– 474. https://doi.org/10.1016/S1071-5819(03)00111-3

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Gochhwal, R. (2017). Unified payment interface—An advancement in payment systems. American Journal of Industrial and Business Management, 7, 1174–1191. https://doi.org/10.4236/ajibm.2017.710084

Gupta, A., Yousaf, A., & Mishra, A. (2020). How pre-adoption expectancies shape post-adoption continuance intentions: An extended expectation-confirmation model. International Journal of Information Management, 52, 102094. https://doi.org/10.1016/j.ijinfomgt.2020.102094

Gupta, M., Taneja, S., Sharma, V., Singh, A., Rupeika-Apoga, R., & Jangir, K. (2023). Does previous experience with the unified payments interface (UPI) affect the usage of central bank digital currency (CBDC)? Journal of Risk and Financial Management, 16(6), 286. https://doi.org/10.3390/jrfm16060286

Gupta, S., Mittal, R., & Mittal, A. (2019). Modelling the intentions to adopt UPIs: A PLS-SEM approach. In 2019 6th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 246–250). IEEE.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson.

Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

Hussain, M., Mollik, A. T., Johns, R., & Rahman, M. S. (2019). M-payment adoption for bottom of pyramid segment: An empirical investigation. International Journal of Bank Marketing, 37(1), 362–381. https://doi.org/10.1108/IJBM-01-2018-0013

India leads global digital payments with 89.5 million transactions in 2022: MyGovIndia data. (2023, June 10). The Hindu. https://www.thehindu.com/business/Economy/india-leads-global-digital-payments-with-895-million-transactions-in-2022-mygovindia-data/article66953386.ece

Joseph, D., Girish, S., & Suresh, G. (2023). FinTech and financial capability, what do we know and what we do not know: A scoping review. Indian Journal of Finance, 17(12), 40–55. https://doi.org/10.17010/ijf/2023/v17i12/170910

Kalinic, Z., Marinkovic, V., Molinillo, S., & Liébana-Cabanillas, F. (2019). A multi-analytical approach to peer-to-peer mobile payment acceptance prediction. Journal of Retailing and Consumer Services, 49, 143–153. https://doi.org/10.1016/j.jretconser.2019.03.016

Kapoor, S., & Mohandas, V. (2023). Measuring financial inclusion in India: An approach. Indian Journal of Finance, 17(1), 27–46. https://doi.org/10.17010/ijf/2023/v17i1/172601

Kothari, S. (2023, October 2). UPI transactions cross 10 billion mark for second month in September. NDTV Profit. https://www.bqprime.com/business/upi-transactions-cross-10-billion-mark-for-second-month-in-september

Kumar, A., Adlakaha, A., & Mukherjee, K. (2018). The effect of perceived security and grievance redressal on continuance intention to use M-wallets in a developing country. International Journal of Bank Marketing, 36(7), 1170–1189. https://doi.org/10.1108/IJBM-04-2017-0077

Liébana-Cabanillas, F., Molinillo, S., & Ruiz-Montañez, M. (2019). To use or not to use, that is the question: Analysis of the determining factors for using NFC mobile payment systems in public transportation. Technological Forecasting and Social Change, 139, 266–276. https://doi.org/10.1016/j.techfore.2018.11.012

Ligon, E., Malick, B., Sheth, K., & Trachtman, C. (2019). What explains low adoption of digital payment technologies? Evidence from small-scale merchants in Jaipur, India. PLoS ONE, 14(7), e0219450. https://doi.org/10.1371/journal.pone.0219450

Madan, K., & Yadav, R. (2016). Behavioural intention to adopt mobile wallet: A developing country perspective. Journal of Indian Business Research, 8(3), 227–244. https://doi.org/10.1108/JIBR-10-2015-0112

National Payments Corporation of India (NPCI). (n.d.). Unified Payments Interface (UPI) - Instant Mobile Payments. https://www.npci.org.in/what-we-do/upi/product-overview

Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior, 61, 404–414. https://doi.org/10.1016/j.chb.2016.03.030

Pahari, S., Manna, A., & Biswas, D. (2023). Pay with confidence: A thematic analysis of user intentions and perceptions on third-party and banking payment apps. Indian Journal of Finance, 17(5), 25–38. https://doi.org/10.17010/ijf/2023/v17i5/172735

Pal, A., Herath, T., De', R., & Rao, H. R. (2021). Why do people use mobile payment technologies and why would they continue? An examination and implications from India. Research Policy, 50(6), 104228. https://doi.org/10.1016/j.respol.2021.104228

Pal, D., Vanijja, V., & Papasratorn, B. (2015). An empirical analysis towards the adoption of NFC mobile payment system by the end user. Procedia Computer Science, 69, 13–25. https://doi.org/10.1016/j.procs.2015.10.002

Rastogi, S., Panse, C., Sharma, A., & Bhimavarapu, V. M. (2021). Unified payment interface (UPI): A digital innovation and its impact on financial inclusion and economic development. Universal Journal of Accounting and Finance, 9(3), 518–530. https://doi.org/10.13189/ujaf.2021.090326

Saikia, H., & Jacob, M. E. (2021). Unified payment interface (UPI)—A critical review of benefits and challenges of advanced payment systems. Webology, 18(6), 4386–4391.

Shaikh, A. A., Glavee-Geo, R., & Karjaluoto, H. (2018). How relevant are risk perceptions, effort, and performance expectancy in mobile banking adoption? International Journal of E-Business Research (IJEBR), 14(2), 39–60. https://doi.org/10.4018/IJEBR.2018040103

Sharma, M., Banerjee, S., & Paul, J. (2022). Role of social media on mobile banking adoption among consumers. Technological Forecasting and Social Change, 180, Article ID 121720. https://doi.org/10.1016/j.techfore.2022.121720

Singh, N., Sinha, N., & Liébana-Cabanillas, F. J. (2020). Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use and social influence. International Journal of Information Management, 50, 191–205. https://doi.org/10.1016/j.ijinfomgt.2019.05.022

Singh, S., Sahni, M. M., & Kovid, R. K. (2020). What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 58(8), 1675–1697. https://doi.org/10.1108/MD-09-2019-1318

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. https://doi.org/10.1108/JSTPM-07-2017-0033

Su, P., Wang, L., & Yan, J. (2018). How users' Internet experience affects the adoption of mobile payment: A mediation model. Technology Analysis & Strategic Management, 30(2), 186–197. https://doi.org/10.1080/09537325.2017.1297788

Tehseen, S., Ramayah, T., & Sajilan, S. (2017). Testing and controlling for common method variance: A review of available methods. Journal of Management Sciences, 4(2), 142–175. https://doi.org/10.20547/jms.2014.1704202

Thakur, R., & Srivastava, M. (2014). Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research, 24(3), 369–392. https://doi.org/10.1108/IntR-12-2012-0244

Vaghela, P. S., Kapadia, J. M., Patel, H. R., & Patil, A. G. (2023). Effect of financial literacy and attitude on financial behavior among university students. Indian Journal of Finance, 17(8), 43–57. https://doi.org/10.17010/ijf/2023/v17i8/173010

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. https://doi.org/10.2307/30036540

Venkatesh, V., Thong, J. Y., & 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. https://doi.org/10.2307/41410412

Williams, M., Rana, N., Dwivedi, Y., & Lal, B. (2011). Is UTAUT really used or just cited for the sake of it? A systematic review of citations of UTAUT'S originating article. Proceeding of European Conference on Information Systems (ECIS) 2011. Association for Information Systems Electronic Library (AISeL) https://aisel.aisnet.org/ecis2011/231