A Systematic Review and Weight Analysis of Mobile Financial Services Adoption Literature from 2011 to 2021


  • Komlan Gbongli University of Miskolc




Mobile banking, mobile payment, mobile money, mobile wallet, mobile financial services, systematic literature review


The global extent and use of the internet and mobile have increased the importance of mobile financial services (MFS) and payments. However, only limited numbers of review studies are accessible on the topic. Therefore, this paper aims to offer a systematic literature review (SLR) methodology and perform a weight analysis of articles published between 2011 and 2021. By reviewing 61 studies, the results indicate that the unified theory of acceptance and usage of technology (UTAUT) followed by the technology of acceptance model (TAM) are the main conceptual frameworks and models adopted. It reveals that attitude, perceived ease of use, performance expectancy, habit, social norms, and perceived usefulness are the best behavioral intention predictors. The critical technological factors of using MFS were provided, followed by future research opportunities.

Author Biography

Komlan Gbongli, University of Miskolc



AL-JABRI, I. M. & SOHAIL, M. S. (2012). Mobile banking adoption: application of diffusion of innovation theory. Journal of Electronic Commerce Research, 13(4), 379–391.

AL KHASAWNEH, M. H. (2015). An Empirical Examination of Consumer Adoption of Mobile Banking (M-Banking) in Jordan. Journal of Internet Commerce, 14(3), 341–362. https://doi.org/10.1080/15332861.2015.1045288

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

ALALWAN, A. A., DWIVEDI, Y. K., RANA, N. P. P. & WILLIAMS, M. D. (2016). Consumer adoption of mobile banking in Jordan. Journal of Enterprise Information Management, 29(1), 118–139. https://doi.org/10.1108/JEIM-04-2015-0035

ALHASSAN, A., LI, L., REDDY, K. & DUPPATI, G. (2020). Consumer acceptance and continuance of mobile money. Australasian Journal of Information Systems, 24. https://doi.org/10.3127/ajis.v24i0.2579

ALI, F., RASOOLIMANESH, S. M., SARSTEDT, M., RINGLE, C. M. & RYU, K. (2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, 30(1), 514–538. https://doi.org/10.1108/IJCHM-10-2016-0568

ASTRACHAN, C. B., PATEL, V. K. & WANZENRIED, G. (2014). A comparative study of CB-SEM and PLS-SEM for theory development in family firm research. Journal of Family Business Strategy, 5(1), 116–128. https://doi.org/10.1016/j.jfbs.2013.12.002

BAABDULLAH, A. M., ALALWAN, A. A., RANA, N. P., PATIL, P. & DWIVEDI, Y. K. (2019). An integrated model for m-banking adoption in Saudi Arabia. International Journal of Bank Marketing, 37(2), 452–478. https://doi.org/10.1108/IJBM-07-2018-0183

BAILEY, A. A., PENTINA, I., MISHRA, A. S. & BEN MIMOUN, M. S. (2017). Mobile payments adoption by US consumers: an extended TAM. International Journal of Retail & Distribution Management, 45(6), 626–640. https://doi.org/10.1108/IJRDM-08-2016-0144

BAPTISTA, GONCALO & OLIVEIRA, T. (2017). Why so serious? Gamification impact in the acceptance of mobile banking services. Internet Research, 27(1), 118–139. https://doi.org/10.1108/IntR-10-2015-0295

BAPTISTA, GONÇALO & OLIVEIRA, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2015.04.024

BEHERA, R. K., BALA, P. K. & DHIR, A. (2019). The emerging role of cognitive computing in healthcare: A systematic literature review. International Journal of Medical Informatics, 129, 154–166. https://doi.org/10.1016/j.ijmedinf.2019.04.024

BOOTH, A., SUTTON, A. & PAPAIOANNOU, D. (2016). Taking a systematic approach to your literature review. In Systematic approaches to a successful literature review.

BUZETA, C., DE PELSMACKER, P. & DENS, N. (2020). Motivations to Use Different Social Media Types and Their Impact on Consumers’ Online Brand-Related Activities (COBRAs). Journal of Interactive Marketing, 52, 79–98. https://doi.org/10.1016/j.intmar.2020.04.004

CHANGCHIT, C., KLAUS, T., LONKANI, R. & SAMPET, J. (2020). A Cultural Comparative Study of Mobile Banking Adoption Factors. Journal of Computer Information Systems, 60(5), 484–494. https://doi.org/10.1080/08874417.2018.1541724

CHANGCHIT, C., LONKANI, R. & SAMPET, J. (2017). Mobile banking: Exploring determinants of its adoption. Journal of Organizational Computing and Electronic Commerce, 27(3), 239–261. https://doi.org/10.1080/10919392.2017.1332145

CHAWLA, D. & JOSHI, H. (2021). Importance-performance map analysis to enhance the performance of attitude towards mobile wallet adoption among Indian consumer segments. Aslib Journal of Information Management, 73(6), 946–966. https://doi.org/10.1108/AJIM-03-2021-0085

CHEN, L. & NATH, R. (2008). Determinants of mobile payments: an empirical analysis. Journal of International Technology and Information, 17(1), 9–20.

CHIN, W., CHEAH, J.-H., LIU, Y., TING, H., LIM, X.-J. & CHAM, T. H. (2020). Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research. Industrial Management & Data Systems, 120(12), 2161–2209. https://doi.org/10.1108/IMDS-10-2019-0529

CIPRIANI, A. & GEDDES, J. (2003). Comparison of systematic and narrative reviews: the example of the atypical antipsychotics. Epidemiologia e Psichiatria Sociale, 12(3), 146–153. https://doi.org/10.1017/S1121189X00002918

DEB, M. & AGRAWAL, A. (2017). Factors impacting the adoption of m-banking: understanding brand India’s potential for financial inclusion. Journal of Asia Business Studies, 11(1), 22–40. https://doi.org/10.1108/JABS-11-2015-0191

DI PIETRO, L., GUGLIELMETTI MUGION, R., MATTIA, G., RENZI, M. F. & TONI, M. (2015). The Integrated Model on Mobile Payment Acceptance (IMMPA): An empirical application to public transport. Transportation Research Part C: Emerging Technologies, 56, 463–479. https://doi.org/10.1016/j.trc.2015.05.001

DINIZ, E. H., CERNEV, A. K. & DE ALBUQUERQUE, J. P. (2011). Mobile Money and Payment : a literature review based on academic and practitioner - oriented publications ( 2001 - 2011 ) Mobile Money and Payment : GlobDev - Proceedings Annual Workshop of the AIS Special Interest Group for ICT in Global Development.

ERIKSSON, T. (2014). Processes, antecedents and outcomes of dynamic capabilities. Scandinavian Journal of Management, 30(1), 65–82. https://doi.org/10.1016/j.scaman.2013.05.001

FARAH, M. F., HASNI, M. J. S. & ABBAS, A. K. (2018). Mobile-banking adoption: empirical evidence from the banking sector in Pakistan. International Journal of Bank Marketing, 36(7), 1386–1413. https://doi.org/10.1108/IJBM-10-2017-0215

FARROKHI, F. & MAHMOUDI-HAMIDABAD, A. (2012). Rethinking Convenience Sampling: Defining Quality Criteria. Theory and Practice in Language Studies, 2(4). https://doi.org/10.4304/tpls.2.4.784-792

FINK, A. (2014). Conducting Research Literature Reviews: From the Internet to Paper Fourth Edition. In SAGE Open Medicine.

FIRPO, J. (2009). E-Money–Mobile Money–Mobile Banking–What’s the Diference? https://blogs.worldbank.org/psd/e-money-mobile-money-mobile-banking-what-s-the-difference

FRADET, L. (2013). Quelle approche de synthèse des connaissances adopter pour faire un état des lieux de la recherche-action participative en santé et services sociaux au Québec francophone? Nouvelles Pratiques Sociales, 25(2), 219–230. https://doi.org/10.7202/1020831ar

FRIMPONG, K., SHURIDAH, O., WILSON, A. & SARPONG, F. (2020). A cross‐national investigation of trait antecedents of mobile‐banking adoption. Thunderbird International Business Review, 62(4), 411–424. https://doi.org/10.1002/tie.22132

GBONGLI, K., CSORDAS, T. & KISSI MIREKU, K. (2017). Impact of consumer multidimensional online trust-risk in adopting Togolese mobile money transfer services: structural equation modelling approach. Journal of Economics, Management and Trade, 19(2), 1–17.

GBONGLI, K., PENG, Y. & ACKAH, O. (2016). Selection and ranking of perceived risk associated with mobile banking in West Africa: An AHP Approach from customers’ perspective. International Journal of Scientific & Engineering Research, 7(1), 80–86.

GBONGLI, K., XU, Y. & AMEDJONEKOU, K. M. (2019). Extended Technology Acceptance Model to Predict Mobile-Based Money Acceptance and Sustainability: A Multi-Analytical Structural Equation Modeling and Neural Network Approach. Sustainability, 11(13), 3639. https://doi.org/10.3390/su11133639

GBONGLI, K., XU, Y., AMEDJONEKOU, K. M. & KOVÁCS, L. (2020). Evaluation and Classification of Mobile Financial Services Sustainability Using Structural Equation Modeling and Multiple Criteria Decision-Making Methods. Sustainability, 12(4), 1288. https://doi.org/10.3390/su12041288

GIOVANIS, A., ATHANASOPOULOU, P., ASSIMAKOPOULOS, C. & SARMANIOTIS, C. (2019). Adoption of mobile banking services. International Journal of Bank Marketing, 37(5), 1165–1189. https://doi.org/10.1108/IJBM-08-2018-0200

GIOVANIS, A., RIZOMYLIOTIS, I., KONSTANTOULAKI, K. & MAGRIZOS, S. (2021). Mining the hidden seam of proximity m-payment adoption: A hybrid PLS-artificial neural network analytical approach. European Management Journal. https://doi.org/10.1016/j.emj.2021.09.007

GOH, T.-T. & SUN, S. (2014). Exploring gender differences in Islamic mobile banking acceptance. Electronic Commerce Research, 14(4), 435–458. https://doi.org/10.1007/s10660-014-9150-7

GSMA. (2021). State of the industry report on mobile money in 2021. https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2021/03/GSMA_State-of-the-Industry-Report-on-Mobile-Money-2021_Full-report.pdf

GUPTA, A. & ARORA, N. (2017). Consumer adoption of m-banking: a behavioral reasoning theory perspective. International Journal of Bank Marketing, 35(4), 733–747. https://doi.org/10.1108/IJBM-11-2016-0162

HAIR, J. F., RINGLE, C. M. & SARSTEDT, M. (2014). Corrigendum to “Editorial Partial Least Squares Structural Equation Modeling: Rigorous Applications, Better Results and Higher Acceptance” [LRP 46/1-2 (2013) 1–12]. Long Range Planning, 47(6), 392. https://doi.org/10.1016/j.lrp.2013.08.016

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

ISMAGILOVA, E., SLADE, E. L., RANA, N. P. & DWIVEDI, Y. K. (2020). The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis. Information Systems Frontiers, 22(5), 1203–1226. https://doi.org/10.1007/s10796-019-09924-y

JADIL, Y., RANA, N. P. & DWIVEDI, Y. K. (2021). A meta-analysis of the UTAUT model in the mobile banking literature: The moderating role of sample size and culture. Journal of Business Research, 132, 354–372. https://doi.org/10.1016/j.jbusres.2021.04.052

JEYARAJ, A., ROTTMAN, J. W. & LACITY, M. C. (2006). A review of the predictors, linkages, and biases in IT innovation adoption research. In Journal of Information Technology. https://doi.org/10.1057/palgrave.jit.2000056

JOHNSON, V. L., KISER, A., WASHINGTON, R. & TORRES, R. (2018). Limitations to the rapid adoption of M-payment services: Understanding the impact of privacy risk on M-Payment services. Computers in Human Behavior, 79, 111–122. https://doi.org/10.1016/j.chb.2017.10.035

KALINIĆ, Z., LIÉBANA-CABANILLAS, F. J., MUÑOZ-LEIVA, F. & MARINKOVIĆ, V. (2019). The moderating impact of gender on the acceptance of peer-to-peer mobile payment systems. International Journal of Bank Marketing, 38(1), 138–158. https://doi.org/10.1108/IJBM-01-2019-0012

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

KERAMATI, A., TAEB, R., LARIJANI, A. M. & MOJIR, N. (2012). A combinative model of behavioural and technical factors affecting ‘Mobile’-payment services adoption: an empirical study. The Service Industries Journal, 32(9), 1489–1504. https://doi.org/10.1080/02642069.2011.552716

KHALILZADEH, J., OZTURK, A. B. & BILGIHAN, A. (2017). Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460–474. https://doi.org/10.1016/j.chb.2017.01.001

KIM, M., ZOO, H., LEE, H. & KANG, J. (2018). Mobile financial services, financial inclusion, and development: A systematic review of academic literature. The Electronic Journal of Information Systems in Developing Countries, 84(5), e12044. https://doi.org/10.1002/isd2.12044

KOENIG-LEWIS, N., MARQUET, M., PALMER, A. & ZHAO, A. L. (2015). Enjoyment and social influence: predicting mobile payment adoption. The Service Industries Journal, 35(10), 537–554. https://doi.org/10.1080/02642069.2015.1043278

KUMAR, P., SINGH, S. K., PEREIRA, V. & LEONIDOU, E. (2020). Cause-related marketing and service innovation in emerging country healthcare. International Marketing Review, 37(5), 803–827. https://doi.org/10.1108/IMR-03-2019-0101

LEGUINA, A. (2015). A primer on partial least squares structural equation modeling (PLS-SEM). International Journal of Research & Method in Education, 38(2), 220–221. https://doi.org/10.1080/1743727X.2015.1005806

LIEBANA-CABANILLAS, F. & LARA-RUBIO, J. (2017). Predictive and explanatory modeling regarding adoption of mobile payment systems. Technological Forecasting and Social Change, 120, 32–40. https://doi.org/10.1016/j.techfore.2017.04.002

LIÉBANA-CABANILLAS, FRANCISCO, MARINKOVIC, V., RAMOS DE LUNA, I. & KALINIC, Z. (2018). Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach. Technological Forecasting and Social Change, 129, 117–130. https://doi.org/10.1016/j.techfore.2017.12.015

LIEBANA-CABANILLAS, FRANCISCO, RAMOS DE LUNA, I. & MONTORO-RIOS, F. J. (2015). User behaviour in QR mobile payment system: the QR Payment Acceptance Model. Technology Analysis & Strategic Management, 27(9), 1031–1049. https://doi.org/10.1080/09537325.2015.1047757

LIÉBANA-CABANILLAS, FRANCISCO, SÁNCHEZ-FERNÁNDEZ, J. & MUÑOZ-LEIVA, F. (2014). 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, 34(2), 151–166. https://doi.org/10.1016/j.ijinfomgt.2013.12.006

LIN, H.-F. (2011). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. International Journal of Information Management, 31(3), 252–260. https://doi.org/10.1016/j.ijinfomgt.2010.07.006

LU, M.-T., TZENG, G.-H., CHENG, H. & HSU, C.-C. (2015). Exploring mobile banking services for user behavior in intention adoption: using new hybrid MADM model. Service Business, 9(3), 541–565. https://doi.org/10.1007/s11628-014-0239-9

MADAN, K. & YADAV, R. (2016). Behavioural intention to adopt mobile wallet: a developing country perspective. Journal of Indian Business Research. https://doi.org/10.1108/JIBR-10-2015-0112

MERHI, M., HONE, K. & TARHINI, A. (2019). A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security, privacy and trust. Technology in Society, 59, 101151. https://doi.org/10.1016/j.techsoc.2019.101151

MOORTHY, K., CHUN T’ING, L., CHEA YEE, K., WEN HUEY, A., JOE IN, L., CHYI FENG, P. & JIA YI, T. (2020). What drives the adoption of mobile payment? A Malaysian perspective. International Journal of Finance & Economics, 25(3), 349–364. https://doi.org/10.1002/ijfe.1756

OKELLO CANDIYA BONGOMIN, G. & NTAYI, J. (2019). Trust: mediator between mobile money adoption and usage and financial inclusion. Social Responsibility Journal, 16(8), 1215–1237. https://doi.org/10.1108/SRJ-01-2019-0011

OLIVEIRA, T., FARIA, M., THOMAS, M. A. & POPOVIČ, A. (2014). Extending the understanding of mobile banking adoption: when UTAUT meets TTF and ITM. International Journal of Information Management, 34(5), 689–703. https://doi.org/10.1016/j.ijinfomgt.2014.06.004

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

OWUSU KWATENG, K., OSEI ATIEMO, K. A. & APPIAH, C. (2019). Acceptance and use of mobile banking: an application of UTAUT2. Journal of Enterprise Information Management, 32(1), 118–151. https://doi.org/10.1108/JEIM-03-2018-0055

PATIL, P., TAMILMANI, K., RANA, N. P. & RAGHAVAN, V. (2020). Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, 54, 102144. https://doi.org/10.1016/j.ijinfomgt.2020.102144

PENG, R., XIONG, L. & YANG, Z. (2012). Exploring Tourist Adoption of Tourism Mobile Payment: An Empirical Analysis. Journal of Theoretical and Applied Electronic Commerce Research, 7(1), 5–6. https://doi.org/10.4067/S0718-18762012000100003

PUROHIT, S. & ARORA, R. (2021). Adoption of mobile banking at the bottom of the pyramid: an emerging market perspective. International Journal of Emerging Markets. https://doi.org/10.1108/IJOEM-07-2020-0821

RAFDINAL, W. & SENALASARI, W. (2021). Predicting the adoption of mobile payment applications during the COVID-19 pandemic. International Journal of Bank Marketing, 39(6), 984–1002. https://doi.org/10.1108/IJBM-10-2020-0532

RAZA, S. A., SHAH, N. & ALI, M. (2019). Acceptance of mobile banking in Islamic banks: evidence from modified UTAUT model. Journal of Islamic Marketing, 10(1), 357–376. https://doi.org/10.1108/JIMA-04-2017-0038

RHAIEM, K. & AMARA, N. (2021). Learning from innovation failures: a systematic review of the literature and research agenda. Review of Managerial Science, 15(2), 189–234. https://doi.org/10.1007/s11846-019-00339-2

RHAIEM, M. (2017). Measurement and determinants of academic research efficiency: a systematic review of the evidence. Scientometrics, 110(2), 581–615. https://doi.org/10.1007/s11192-016-2173-1

RINGLE, C. M., SARSTEDT, M., MITCHELL, R. & GUDERGAN, S. P. (2020). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 31(12), 1617–1643. https://doi.org/10.1080/09585192.2017.1416655

SETH, H., TALWAR, S., BHATIA, A., SAXENA, A. & DHIR, A. (2020). Consumer resistance and inertia of retail investors: Development of the resistance adoption inertia continuance (RAIC) framework. Journal of Retailing and Consumer Services, 55, 102071. https://doi.org/10.1016/j.jretconser.2020.102071

SHAIKH, A. A. & KARJALUOTO, H. (2014). Mobile banking adoption: A literature review. In Telematics and Informatics (Vol. 32, Issue 1, pp. 129–142). https://doi.org/10.1016/j.tele.2014.05.003

SHARMA, S. K. (2019). Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling. Information Systems Frontiers, 21(4), 815–827. https://doi.org/10.1007/s10796-017-9775-x

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. (2020). An integrated model combining the ECM and the UTAUT to explain users’ post-adoption behaviour towards mobile payment systems. Australasian Journal of Information Systems. https://doi.org/10.3127/ajis.v24i0.2695

SLADE, E. L., DWIVEDI, Y. K., PIERCY, N. C. & WILLIAMS, M. D. (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. https://doi.org/10.1002/mar.20823

SLADE, E., WILLIAMS, M., DWIVEDI, Y. & PIERCY, N. (2015). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 209–223. https://doi.org/10.1080/0965254X.2014.914075

SOUIDEN, N., CHAOUALI, W. & BACCOUCHE, M. (2019). Consumers’ attitude and adoption of location-based coupons: The case of the retail fast food sector. Journal of Retailing and Consumer Services, 47, 116–132. https://doi.org/10.1016/j.jretconser.2018.11.009

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

SUHARTANTO, D., DEAN, D., ISMAIL, T. A. T. & SUNDARI, R. (2019). Mobile banking adoption in Islamic banks. Journal of Islamic Marketing, 11(6), 1405–1418. https://doi.org/10.1108/JIMA-05-2019-0096

TALWAR, S., DHIR, A., KHALIL, A., MOHAN, G. & ISLAM, A. K. M. N. (2020). Point of adoption and beyond. Initial trust and mobile-payment continuation intention. Journal of Retailing and Consumer Services, 55, 102086. https://doi.org/10.1016/j.jretconser.2020.102086

TAM, C. & OLIVEIRA, T. (2016a). Performance impact of mobile banking: using the task-technology fit (TTF) approach. International Journal of Bank Marketing, 34(4), 434–457. https://doi.org/10.1108/IJBM-11-2014-0169

TAM, C. & OLIVEIRA, T. (2016b). Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective. Computers in Human Behavior, 61, 233–244. https://doi.org/10.1016/j.chb.2016.03.016

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

THUSI, P. & MADUKU, D. K. (2020). South African millennials’ acceptance and use of retail mobile banking apps: An integrated perspective. Computers in Human Behavior, 111, 106405. https://doi.org/10.1016/j.chb.2020.106405

VERKIJIKA, S. F. (2020). An affective response model for understanding the acceptance of mobile payment systems. Electronic Commerce Research and Applications, 39, 100905. https://doi.org/10.1016/j.elerap.2019.100905

VOIGHT, M. L. & HOOGENBOOM, B. J. (2012). Publishing your work in a journal: understanding the peer review process. International Journal of Sports Physical Therapy, 7(5), 452–460.

WADDINGTON, H., WHITE, H., SNILSTVEIT, B., HOMBRADOS, J. G., VOJTKOVA, M., DAVIES, P., BHAVSAR, A., EYERS, J., KOEHLMOOS, T. P., PETTICREW, M., VALENTINE, J. C. & TUGWELL, P. (2012). How to do a good systematic review of effects in international development: a tool kit. Journal of Development Effectiveness, 4(3), 359–387. https://doi.org/10.1080/19439342.2012.711765

WEI, M.-F., LUH, Y.-H., HUANG, Y.-H. & CHANG, Y.-C. (2021). Young Generation’s Mobile Payment Adoption Behavior: Analysis Based on an Extended UTAUT Model. Journal of Theoretical and Applied Electronic Commerce Research, 16(4), 618–636. https://doi.org/10.3390/jtaer16040037

WU, R.-Z., LEE, J.-H. & TIAN, X.-F. (2021). Determinants of the Intention to Use Cross-Border Mobile Payments in Korea among Chinese Tourists: An Integrated Perspective of UTAUT2 with TTF and ITM. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1537–1556. https://doi.org/10.3390/jtaer16050086

YEN, Y.-S. & WU, F.-S. (2016). Predicting the adoption of mobile financial services: The impacts of perceived mobility and personal habit. Computers in Human Behavior, 65, 31–42. https://doi.org/10.1016/j.chb.2016.08.017

YU, C. S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the utaut model. Journal of Electronic Commerce Research.

ZHANG, J. & MAO, E. (2020). Cash, credit, or phone? An empirical study on the adoption of mobile payments in the United States. Psychology & Marketing, 37(1), 87–98. https://doi.org/10.1002/mar.21282

ZHOU, T. (2012). Examining mobile banking user adoption from the perspectives of trust and flow experience. Information Technology and Management, 13(1), 27–37. https://doi.org/10.1007/s10799-011-0111-8



How to Cite

Gbongli, K. (2022). A Systematic Review and Weight Analysis of Mobile Financial Services Adoption Literature from 2011 to 2021. Theory, Methodology, Practice - Review of Business and Management, 18(02), 23-49. https://doi.org/10.18096/TMP.2022.02.02