User Perceptions of Mobile Banking Apps in Tanzania: Impact of Information Systems (IS) Factors and Customer Personality Traits

Authors

DOI:

https://doi.org/10.23962/10539/32214

Keywords:

Mobile banking apps, Adoption, Personality traits, Information systems (IS), IS success model, Tanzania

Abstract

This study probes the roles that information systems (IS) success factors and user personality traits play in Tanzanian users’ perceptions of their experiences with mobile banking apps. Based on a survey of 249 mobile banking customers, the study finds that users are being positively influenced by the apps’ system quality and system service, but not by the apps’ information quality. The study also finds that, with respect to user personality traits, openness, agreeableness, conscientiousness and extraversion are all traits that have a positive impact on customers’ use of, and satisfaction with, mobile banking apps. The findings suggest that developers of mobile banking apps for the Tanzanian market need to both improve the quality of the information in the apps and continue to target a range of personality traits.

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AL Athmay, A. A. A., Fantazy, K., & Kumar, V. (2016). E-government adoption and user’s satisfaction: An empirical investigation. EuroMed Journal of Business, 11(1), 57–83. https://doi.org/10.1108/EMJB-05-2014-0016

Alavi, S., & Ahuja, V. (2016). An empirical segmentation of users of mobile banking apps. Journal of Internet Commerce, 15(4), 390–407. https://doi.org/10.1080/15332861.2016.1252653

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modelling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411

Ashraf, H. (2019). Factors that Influence the use of Mobile Banking in Lebanon: Integration of UTAUT2 and 3M Model. Universidade de Santiago de Compostela.

Barnett, T., Allison, W., Pearson, R., & Kellermanns, F. W. (2014). Five-factor model personality traits as predictors of perceived and actual usage of technology. European Journal of Information Systems, 24(4), 374–390. https://doi.org/10.1057/ejis.2014.10

Bennett, J., & Perrewé, P. L. (2002). An empirical examination of individual traits as antecedents to computer anxiety and computer self-efficacy. MIS Quarterly, 26(4), 381–396. https://doi.org/10.2307/4132314

Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921

Bond, M. H. (1983). Linking person perception dimensions to behavioral intention dimensions: The Chinese connection. Journal of Cross-Cultural Psychology, 14(1), 41–63. https://doi.org/10.1177/0022002183014001004

Bond, M. H., & Forgas, J. P. (1984). Linking person perception to behavior intention across cultures: The role of cultural collectivism. Journal of Cross-Cultural Psychology, 15(3), 337–352. https://doi.org/10.1177/0022002184015003006

Byrne, B. M. (2009). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). Routledge.

Byun, D. H., & Finnie, G. (2011). Evaluating usability, user satisfaction and intention to revisit for successful e-government websites. Electronic Government, 8(1), 1–19. https://doi.org/10.1504/EG.2011.037694

Camadan, F., Reisoglu, I., Faruk, U. Ö., & Mcilroy, D. (2018). How teachers[’] personality affect on their behavioral intention to use tablet PC. The International Journal of Information and Learning Technology Article Information, 35(1), 12–28. https://doi.org/10.1108/IJILT-06-2017-0055

Chang, L., Connelly, B. S., & Geeza, A. A. (2012). Separating method factors and higher order traits of the big five: A meta-analytic multitrait-multimethod approach. Journal of Personality and Social Psychology, 102(2), 408–427. https://doi.org/10.1037/a0025559

Chiu, P. S., Chao, I. C., Kao, C. C., Pu, Y. H., & Huang, Y. M. (2016). Implementation and evaluation of mobile e-books in a cloud bookcase using the information system success model. Library Hi Tech, 34(2), 207–223. https://doi.org/10.1108/LHT-12-2015-0113

Chmielarz, W., & Łuczak, K. (2015). Mobile banking in the opinion of users of banking applications in Poland. Applied Mechanics and Materials, 795, 31–38. https://doi.org/10.4028/www.scientific.net/AMM.795.31

Clickpesa. (2019). An overview of Consumer Financial Apps in Tanzania. https://clickpesa.com/financial-apps-tanzania/

Cochran, W. (1977). Sampling techniques (3rd ed.). John Wiley & Sons.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale.

DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748

Devaraj, S., Easley, R. F., & Crant, J. M. (2008). How does personality matter? Relating the five-factor model to technology acceptance and use. Information Systems Research, 19(1), 93–105. https://doi.org/10.1287/isre.1070.0153

Digman, J. M. (1990). Personality structure: Emergence of the five-factor model. Annual Review of Psychology, 41(1), 417–440. https://doi.org/10.1146/annurev.ps.41.020190.002221

Donnellan, M. B., Oswald, F. L., Baird, B. M., & Lucas, R. E. (2006). The mini-IPIP scales: Tiny-yet-effective measures of the big five factors of personality. Psychological Assessment, 18(2), 192–203. https://doi.org/10.1037/1040-3590.18.2.192

Dudley, N. M., Orvis, K. A., Lebiecki, J. E., & Cortina, J. M. (2006). A meta-analytic investigation of conscientiousness in the prediction of job performance: Examining the intercorrelations and the incremental validity of narrow traits. Journal of Applied Psychology, 91(1), 40–57. https://doi.org/10.1037/0021-9010.91.1.40

Dukic, Z., Chiu, D., & Lo, P. (2015). How useful are smartphones for learning? Perceptions and practices of Library and Information Science students from Hong Kong and Japan. Library Hi Tech, 33(4), 545–561. https://doi.org/10.1108/LHT-02-2015-0015

Fife, E., & Orjuela, J. (2012). The privacy calculus: Mobile apps and user perceptions of privacy and security regular paper. International Journal of Engineering Business, 4(11), 1–10. https://doi.org/10.5772/51645

Floh, A., & Treiblmaier, H. (2006). What keeps the e-banking customer loyal? A multigroup analysis of the moderating role of consumer characteristics on e-loyalty in the financial service industry. Journal of Electronic Commerce Research, 7(2), 97–110. https://doi.org/10.2139/ssrn.2585491

Fornell, C., & Larcker, D. (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

Franque, F. B., Oliveira, T., & Tam, C. (2021). Understanding the factors of mobile payment continuance intention: empirical test in an African context. Heliyon, 7(8), 1–12.

Freeze, R. D., Lane, P. L., & Wen, H. J. (2019). IS success model in e-learning context based on students’ perceptions. Journal of Information Systems Education, 21(2), 173–185.

Gaardboe, R., Nyvang, T., & Sandalgaard, N. (2017). Business intelligence success applied to healthcare information systems. Procedia Computer Science, 121, 483–490. https://doi.org/10.1016/j.procs.2017.11.065

Gao, L., & Park, A. T. (2017). Understanding sustained participation in virtual travel communities from the perspectives of IS success model and flow theory. Journal of Hospitality and Tourism Research, 41(4), 475–509. https://doi.org/10.1177/1096348014563397

Gatian, A. W. (1994). Is user satisfaction a valid measure of system effectiveness? Information & Management, 26(3), 119–131. https://doi.org/10.1016/0378-7206(94)90036-1

Gelderman, M. (1998). The relation between user satisfaction, usage of information systems and performance. Information & Management, 34(1), 11–18. https://doi.org/10.1016/S0378-7206(98)00044-5

Gilbert, P., Cox, L. P., Chun, B.-G., & Jung, J. (2011). Vision: Automated security validation of mobile apps at app markets. In Proceedings of the Second International Workshop on Mobile Cloud Computing and Services (pp. 21–26). https://doi.org/10.1145/1999732.1999740

Godwin-Jones, R. (2011). Emerging technologies mobile apps for language learning. Language Learning & Technology, 15(2), 2–11.

Goldberg, L. (1999). A broad-bandwidth, public-domain, personality inventory measuring the lower-level facets of several five-factor models. In I. Mervielde, I. Deary, F. De Fruyt, & F. Ostendorf (Eds.), Personality psychology in Europe (Vol. 7) (pp. 7-28). Tilburg University Press.

Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual. MIS Quarterly, 19(2), 213–236. https://doi.org/10.2307/249689

Graziano, W. G., & Eisenberg, N. (1997). Agreeableness: A dimension of personality. In R. Hogan, J. Johnson, & S. Briggs (Eds.), Handbook of personality psychology (pp. 795–824). Elsevier. https://doi.org/10.1016/B978-012134645-4/50031-7

GSMA. (2021). The mobile economy 2021. https://www.gsma.com/mobileeconomy/wp-content/uploads/2021/07/GSMA_MobileEconomy2021_3.pdf

Hair, J., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Prentice-Hall.

Halko, S., & Kientz, J. A. (2010). Personality and persuasive technology: An exploratory study on health-promoting mobile applications. In T. Ploug, P. Hasle, & H. Oinas-Kukkonen (Eds.), Persuasive technology: 5th International Conference, PERSUASIVE 2010, Copenhagen, Denmark, June 7-10, 2010: Proceedings (pp. 150–161). https://doi.org/10.1007/978-3-642-13226-1_16

Hepola, J., Karjaluoto, H., & Shaikh, A. A. (2016). Consumer engagement and behavioral intention toward continuous use of innovative mobile banking applications—A case study of Finland. In Thirty Seventh International Conference on Information Systems, Dublin (pp. 1–20).

Hong, W., Thong, J. Y. L., & Wai-Man Wong, K.-Y. T. (2002). Determinants of user acceptance of digital libraries: An empirical examination of individual differences and system characteristics. Journal of Management Information Systems, 18(3), 97–124. https://doi.org/10.1080/07421222.2002.11045692

Hu, P.-H. (2003). Evaluating telemedicine systems success: A revised model. In 36th Annual Hawaii International Conference on System Sciences, 2003. https://doi.org/10.1109/HICSS.2003.1174379

Inukollu, V. N., Keshamoni, D. D., Kang, T., & Inukollu, M. (2014). Factors influencing quality of mobile apps: Role of mobile app development life cycle. International Journal of Software Engineering & Applications (IJSEA), 5(5), 15–34. https://doi.org/10.5121/ijsea.2014.5502

Isaac, O., Abdullah, Z., Ramayah, T., & Mutahar, A. M. (2017). Internet usage, user satisfaction, task-technology fit, and performance impact among public sector employees in Yemen. The International Journal of Information and Learning Technology, 34(3), 210–241. https://doi.org/10.1108/IJILT-11-2016-0051

Jain, A. K., & Shanbhag, D. (2012). Addressing security and privacy risks in mobile applications. IT Professional, 14(5), 28–33. https://doi.org/10.1109/MITP.2012.72

Joreskog, K., & Sorbom, D. (1984). LISREL VI user’s guide (3rd ed.). Scientific Software. Keyes, D. (2019, July 2). WhatsApp Pay is on the verge of launching in India. Business Insider. https://www.businessinsider.com/whatsapp-pay-ready-for-india-launch-2019-7?IR=T

Khan, A. N., Xiongfei, C. & Pitafi, H. (2019). Personality traits as predictor of m-payment systems: A SEM-neural networks approach. Journal of Organizational and End User Computing, 31(4), 89–110. https://doi.org/10.4018/JOEUC.2019100105

Kim, M., Chang, Y., Park, M., & Lee, J. (2015). The effects of quality on the satisfaction and the loyalty of smartphone users. Telematics and Informatics, 32(4), 949–960. https://doi.org/10.1016/j.tele.2015.05.003

Kim, Y., & Jeong, J. S. (2015). Personality predictors for the use of multiple internet functions. Internet Research, 25(3), 399–415. https://doi.org/10.1108/IntR-11-2013-0250

Krishnan, S., Lim, V. K. G., & Tao, T. S. H. (2010). How does personality matter? Investigating the impact of big-five personality traits on cyberloafing. In International Conference on Information Systems (pp. 1–16). https://scholarbank.nus.edu.sg/handle/10635/44246

Kumar, R. R., Israel, D., & Malik, G. (2018). Explaining customer’s continuance intention to use mobile banking apps with an integrative perspective of ECT and self-determination theory. Pacific Asia Journal of the Association for Information Systems, 10(2). https://doi.org/10.17705/1pais.10204

Kumar, S., & Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services : An empirical investigation. International Journal of Information Management, 44, 65–75. https://doi.org/10.1016/j.ijinfomgt.2018.09.013

Landers, R. N., & Lounsbury, J. W. (2006). An investigation of big five and narrow personality traits in relation to internet usage. Computers in Human Behavior, 22(2), 283–293. https://doi.org/10.1016/j.chb.2004.06.001

Leonidas, H., Misirlis, N., Arnhem, H., Boutsouki, C., & Vlachopoulou, M. (2019). Understanding the role of personality traits on Facebook intensity. International Journal of Internet Marketing and Advertising, 13(2), 99–119. https://doi.org/10.1504/IJIMA.2019.099494

Lissitsa, S., & Kol, O. (2021). Four generational cohorts and hedonic m-shopping: association between personality traits and purchase intention. Electronic Commerce Research, 21(2), 545–570.

Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198–1202. https://doi.org/10.1080/01621459.1988.10478722

Loiacono, E. T. (2015). Self-disclosure behavior on social networking web sites. International Journal of Electronic Commerce, 19(2), 66–94.

Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems, 49, 222–234. https://doi.org/10.1016/j.dss.2010.02.008

Maddi, S. R. (1996). Personality theories: A comparative analysis. Brooks/Cole.

Manuel, J., & Veríssimo, C. (2016). Enablers and restrictors of mobile banking app use: A fuzzy set qualitative comparative analysis (fsQCA). Journal of Business Research, 69(11), 5456–5460. https://doi.org/10.1016/j.jbusres.2016.04.155

McCrae, R. R. (1993). Openness to experience as a basic dimension of personality. Imagination, Cognition and Personality, 13(1), 39–55.

https://doi.org/10.2190/H8H6-QYKR-KEU8-GAQ0

McCrae, R. R., & Terracciano, A. (2005). Universal features of personality traits from the observer’s perspective: Data from 50 cultures. Journal of Personality and Social Psychology, 88(3), 547. https://doi.org/10.1037/0022-3514.88.3.547

McElroy, J. C., Hendrickson, A. R., Townsend, A. M., & DeMarie, S. M. (2007). Dispositional factors in internet use: Personality versus cognitive style. MIS Quarterly, 31(4), 809–820. https://doi.org/10.2307/25148821

Melone, N. P. (1990). A theoretical assessment of the user-satisfaction construct in information systems research. Management Science, 36(1), 76–91. https://doi.org/10.1287/mnsc.36.1.76

Mohammadi, H. (2015). Investigating users’ perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45, 359–374. https://doi.org/10.1016/j.chb.2014.07.044

Moslehpour, M., Thi Thanh, H. Le, & Van Kien, P. (2018). Technology perception, personality traits and online purchase intention of Taiwanese consumers. In International Conference of the Thailand Econometrics Society (pp. 392–407). https://doi.org/10.1007/978-3-319-70942-0_28

Muñoz-Leiva, F., Climent-Climent, S., & Liébana-Cabanillas, F. (2017). Determinants of intention to use the mobile banking apps: An extension of the classic TAM model. Spanish Journal of Marketing, 21(1), 25–38. https://doi.org/10.1016/j.sjme.2016.12.001

Njoroge, C. N., & Koloseni, D. (2015). Adoption of social media as full-fledged banking channel: An analysis of retail banking customers in Kenya. International Journal of Information and Communication Technology Research, 5(2), 1–12.

Nunnally, J. C., & Bernstein, I. (1994). Psychometric theory. McGraw-Hill.

Ones, D. S., & Viswesvaran, C. (1996). Bandwidth–fidelity dilemma in personality measurement for personnel selection. Journal of Organizational Behavior, 17(6), 609–626.https://doi.org/10.1002/(SICI)1099-1379(199611)17:6<609::AIDJOB1828>3.0.CO;2-K

Panda, A., & Jain, N. K. (2018). Compulsive smartphone usage and users’ ill-being among young Indians: Does personality matter? Telematics and Informatics, 35(5), 1355–1372. https://doi.org/10.1016/j.tele.2018.03.006

Pituch, K. A., & Lee, Y. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47, 222–244. https://doi.org/10.1016/j.compedu.2004.10.007

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569. https://doi.org/10.1146/annurev-psych-120710-100452

Ramayah, T., Wai, J., & Lee, C. (2012). System characteristics, satisfaction and e-learning usage: A structural equation model. The Turkish Online Journal of Educational Technology, 11(2), 26–28.

Rana, N., Dwivedi, Y., Williams, M., & Weerakkody, V. (2015). Investigating success of an e-government initiative: Validation of an integrated IS success model. Information Systems Frontiers, 17(1), 127–142. https://doi.org/10.1007/s10796-014-9504-7

Rosen, P. A., & Kluemper, D. H. (2008). The impact of the big five personality traits on the acceptance of social networking website. In AMCIS 2008 Proceedings (pp. 1–10). https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.909.2632&rep=rep1&-type=pdf

Sampaio, C. H., Ladeira, W. J., & Santini, F. D. O. (2017). Apps for mobile banking and customer satisfaction: A cross-cultural study. International Journal of Bank Marketing, 35(7), 1133–1153. https://doi.org/10.1108/IJBM-09-2015-0146

Sangar, A. B., & Rastari, S. (2015). A model for increasing usability of mobile banking apps on smart phones. Indian Journal of Science and Technology, 8(30), 1–9. https://doi.org/10.17485/ijst/2015/v8i30/85690

Shambare, N. (2013). Examining the influence of personality traits on intranet portal adoption by faculty in higher education. PhD dissertation, Northcentral University, San Diego, CA.

Shim, M., & Jo, H. S. (2020). What quality factors matter in enhancing the perceived benefits of online health information sites? Application of the updated DeLone and McLean information systems success model. International Journal of Medical Informatics, 137. https://doi.org/10.1016/j.ijmedinf.2020.104093

Svendsen, G. B., Johnsen, J. A. K., Almås-Sørensen, L., & Vittersø, J. (2013). Personality and technology acceptance: The influence of personality factors on the core constructs of the technology acceptance model. Behaviour and Information Technology, 32(4), 323–334. https://doi.org/10.1080/0144929X.2011.553740

Tam, C., & Oliveira, T. (2016). 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

Tuten, T., & Bosnjak, M. (2001). Understanding differences in web usage: The role of need for cognition and the five factor model of personality. Social Behaviour and Personality, 29(4), 391–398. https://doi.org/10.2224/sbp.2001.29.4.391

Urbach, N., & Ahlemann, F. (2010). Structural Equation Modeling in Information Systems Research Using Partial Least Squares. JITTA: Journal of Information Technology Theory and Application, 11(2), 5.

Vedadi, A., & Warkentin, M. (2016). Continuance intention on using mobile banking applications – A replication study of information systems continuance model. AIS Transactions on Replication Research, 2, 1–11. https://doi.org/10.17705/1atrr.00014

Veeramootoo, N., Nunkoo, R., & Dwivedi, Y. K. (2018). What determines success of an e-government service? Validation of an integrative model of e-filing continuance usage. Government Information Quarterly, 35(2), 161–174. https://doi.org/10.1016/j.giq.2018.03.004

Were, M., Odongo, M., & Israel, C. (2021). Gender disparities in financial inclusion in Tanzania. World Institute for Development Economic Research (UNU-WIDER).

Yang, H. C. (2013). Bon appétit for apps: Young American consumers’ acceptance of mobile applications. Journal of Computer Information Systems, 53(3), 85–96. https://doi.org/10.1080/08874417.2013.11645635

Zwass, V. (2003). Electronic commerce and organizational innovation: Aspects and opportunities. International Journal of Electronic Commerce, 7(3), 7–37. https://doi.org/10.1080/10864415.2003.11044273

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06-12-2021

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Koloseni, D. N. (2021) “User Perceptions of Mobile Banking Apps in Tanzania: Impact of Information Systems (IS) Factors and Customer Personality Traits”, The African Journal of Information and Communication. South Africa, 28. doi: 10.23962/10539/32214.

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