Determinants of intention to use the mobile banking appsan extension of the classic TAM model

  1. F. Muñoz Leiva
  2. S. Climent Climent 1
  3. F. Liébana Cabanillas
  1. 1 Universidad de Granada
    info

    Universidad de Granada

    Granada, España

    ROR https://ror.org/04njjy449

Revista:
Spanish journal of marketing-ESIC

ISSN: 2444-9695 2444-9709

Año de publicación: 2017

Volumen: 21

Número: 1

Páginas: 25-38

Tipo: Artículo

DOI: 10.1016/J.SJME.2016.12.001 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Spanish journal of marketing-ESIC

Objetivos de desarrollo sostenible

Resumen

For financial institutions mobile banking has represented a breakthrough in terms of remote banking services. However, many customers remain uncertain due to its security. This study develops a technology acceptance model that integrates the innovation diffusion theory, perceived risk and trust in the classic TAM model in order to shed light on what factors determine user acceptance of mobile banking applications. The participants had to examine a mobile application of the largest European bank. In the proposed model, an approach to external influences was included, theoretically and originally stated by Davis et al. (1989). The proposed model was empirically tested using data collected from an online survey applying structural equation modeling (SEM). The results obtained in this study demonstrate how attitude determine mainly the intended use of mobile apps, discarding usefulness and risk as factors that directly improve its use. Finally, the study shows the main management implications and identifies certain strategies to reinforce this new business in the context of new technological advances.

Información de financiación

This study has been conducted with financial support received from Excellence Research Project P12-SEJ-1980 of the Andalusia Regional Government and Project ECO2012- 39576 of Spanish Ministry of Economy and Competitiveness.

Referencias bibliográficas

  • Aboelmaged, M., Gebba, T.R., Mobile banking adoption: An examination of technology acceptance model and theory of planned behavior. International Journal of Business Research and Development (IJBRD) 2:1 (2013), 719–729.
  • Agag, G., El-Masry, A.A., Understanding the determinants of hotel booking intentions and moderating role of habit. International Journal of Hospitality Management 54 (2016), 52–67.
  • Ajzen, I., Fishbein, M., Understanding attitudes and predicting social behavior. 1980, Prentice Hall International, London.
  • Alcántara, J.M., Modelización del comportamiento del consumidor online. El papel moderador de la cultura, el diseño web y el idioma. Tesis, 2012, Departamento de Comercialización e Investigación de Mercados, Universidad de Granada.
  • Aldás, J., Lassala, C., Ruiz, C., Sanz, S., Análisis de los factores determinantes de la lealtad hacia los servicios bancarios. Cuadernos de Economía y Dirección de la Empresa 14 (2011), 26–39.
  • Alsajjan, B., Dennis, C., Internet banking acceptance model: Cross-market examination. Journal of Business Research 63:9 (2010), 957–963.
  • Anderson, J.C., Gerbing, D.W., Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin 103:3 (1988), 411–423.
  • Bao, Y., Zhou, K.Z., Su, C., Face consciousness and risk aversion: Do they affect consumer decision-making. Psychology and Marketing 20:8 (2003), 733–755.
  • Bauer, R.A., Consumer behavior as risk-taking. Hancock, R.S., (eds.) Dynamic marketing for a changing world, 1960, American Marketing Association, Chicago, 389–398 Cited from D. F. Cox (Ed.), Risk-taking and information-handling in consumer behavior. Boston: Harvard University Press, 1967, pp. 23–33.
  • Bauer, R.A., Consumer behavior as risk taking. Cox, D.F., (eds.) Risk-taking and information-handling in consumer behavior, 1967, Harvard University Press, Boston, 23–33.
  • Bhatti, T., Exploring factors influencing the adoption of mobile commerce. Journal of Internet Banking and Commerce 12:3 (2007), 1–13.
  • Bollen, K.A., Overall fit in covariance structure models: Two types of sample size effects. Psychological Bulletin, 107(2), 1990, 256.
  • Bashir, I., Madhavaiah, C., Trust, social influence, self-efficacy, perceived risk and internet banking acceptance: An extension of technology acceptance model in indian context. Metamorphosis: A Journal of Management Research 14:1 (2015), 25–38.
  • Bounagui, M., Nel, J., Towards understanding intention to purchase online music downloads, Management Dynamics. Journal of the Southern African Institute for Management Scientists 18:1 (2009), 15–26.
  • Chang, M.L., Wu, W.Y., Revisiting perceived risk in the context of online shopping: An alternative perspective of decision-making styles. Psychology & Marketing 29:5 (2012), 378–400.
  • Chau, P.Y.K., Lai, V.S.K., An empirical investigation of the determinants of user acceptance of internet banking. Journal of Organizational Computing and Electronic Commerce 13:2 (2003), 123–145.
  • Chauhan, S., Acceptance of mobile money by poor citizens of India: Integrating trust into the technology acceptance model. Info 17:3 (2015), 58–68.
  • Chen, C., Perceived risk, usage frequency of mobile banking services. Managing Service Quality 23:5 (2013), 410–436.
  • Chong, A.Y.L., Ooi, K.B., Lin, B., Bao, H.J., An empirical analysis of the determinants of 3G adoption in China. Computers in Human Behavior 28 (2012), 360–369.
  • Crespo, A.H., del Bosque, I.R., The influence of the commercial features of the Internet on the adoption of e-commerce by consumers. Electronic Commerce Research and Applications 9:6 (2010), 562–575.
  • Davis, F.D., Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13:3 (1989), 319–340.
  • Davis, F.D., Bagozzi, R.P., Warshaw, P.R., User acceptance of computer technology: A comparison of two theoretical models. Management Science 35 (1989), 982–1003.
  • Del Barrio, S., Luque, T., Análisis de Ecuaciones Estructurales. In Luque, T. (coord.), Técnicas de Análisis de datos en investigación de mercados, 2012, Pirámide, Barcelona.
  • Dwyer, F.R., Schurr, P.H., Oh, S., Developing buyer–seller relationship. Journal of Marketing 51:2 (1987), 11–27.
  • Featherman, M.S., Pavlou, P.A., Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies 59 (2003), 451–474.
  • Finney, S.J., DiStefano, C., Nonnormal and categorical data in structural equation modeling. Hancock, G.R., Mueller, R.O., (eds.) Structural equations modeling: A second course, 1996, Information Age Publishing Inc., Greenwich, Connecticut, USA.
  • Fishbein, M., Ajzen, I., Belief, attitude, intention and behavior: An introduction to theory and research. 1975, Addison-Wesley, Reading, MA.
  • Flavián, C., Guinalíu, M., Gurrea, R., Análisis empírico de la influencia ejercida por la usabilidad percibida, la satisfacción y la confianza sobre la lealtad de un sitio web. XVI Encuentros de Profesores Universitarios de Marketing, 2004, ESIC, Madrid, 209–226.
  • Fornell, C., Larcker, D.F., Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18:1 (1981), 39–50.
  • Frambach, R.T., Roest, H.C., Krishnan, T.V., The impact of consumer internet experience on channel preference and usage intentions across the different stages of the buying process. Journal of interactive marketing 21:2 (2007), 26–41.
  • Gefen, D., Rao, V., Tractinsky, N., Conceptualization of trust, risk and their relationship in electronic commerce: The need for clarifications. Proceedings of the 36th Hawaii international conference on IS, 2003.
  • Gefen, D., Karahanna, E., Straub, D.W., Inexperience and experience with online Stores: The importance of TAM and Trust. IEE Transactions on Engineering Management 50:3, agosto (2003), 307–321.
  • Gerrard, P., Cunningham, J., The diffusion of internet banking among Singapore consumers. International Journal of Bank Marketing 21:1 (2003), 16–28.
  • Goffman, E., Interaction ritual. 1967, Pantheon, New York.
  • Grandón, E.E., Nasco, S.A., Mykytyn, P.P., Comparing theories to explain e-commerce adoption. Journal of Business Research 64:3 (2011), 292–298.
  • Gu, J.C., Lee, S.C., Suh, Y.H., Determinants of behavioral intention to mobile banking. Expert Systems with Applications 36:9 (2009), 11605–11616.
  • Gupta, S., Kim, H.W., Value-driven Internet shopping: The mental accounting theory perspective. Psychology & Marketing 27:1 (2010), 13–35.
  • Ha, I., Yoon, Y., Choi, M., Determinants of adoption of mobile games under mobile broadband wireless access environment. Information & Management 44:3 (2007), 276–286.
  • Hair, J.F., Anderson, R.E., Tatham, R.L., William, C.B., Multivariate data analysis with readings. 1995, Prentice-Hall, Inc, New Jersey.
  • Harris, M.A., Brookshire, R., Chin, A.G., Identifying factors influencing consumers’ intent to install mobile applications. International Journal of Information Management 36:3 (2016), 441–450.
  • Harrison, D., Mobile banking acceptance among young consumers in Germany: An empirical analysis. (Doctoral dissertation, BI Norwegian Business School), 2015.
  • Hernández, J., Análisis y modelización del comportamiento de uso de las herramientas Travel 2.0. 2010, Departamento de Comercialización e Investigación de Mercados, Universidad de Granada.
  • Herrero, A., San Martín, H., Effects of the risk sources and user involvement on e-commerce adoption: Application to tourist services. Journal of Risk Research 15:7 (2012), 841–855.
  • Hew, J.J., Lee, V.H., Ooi, K.B., Wei, J., What catalyses mobile apps usage intention: An empirical analysis. Industrial Management & Data Systems 115:7 (2015), 1269–1291.
  • Hong, S.J., Tam, K.Y., Understanding the adoption of multipurpose information appliances: The case of mobile data services. Information Systems Research 17:2 (2006), 162–179.
  • Hsu, C.L., Lin, J.C.C., Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention. Technological Forecasting and Social Change 108 (2016), 42–53.
  • Hsu, C.L., Lu, H.P., Consumer behavior in online game communities: A motivational factor perspective. Computers in Human Behavior 23:3 (2007), 1642–1659.
  • Huang, Y.C., Tsay, W.D., Huan, C.H., Li, Y.H., Lai, M.C., The influence factors of electronic bill presentment and payment. In case study of mobile phone bill. IEEE, 2011, 4844–4847.
  • ING, Encuesta Internacional sobre el Empoderamiento Financiero en la Era Digital de ING. 2013 Retrieved from http://www.ingdirect.es/sobre-ing/prensa/prensa250713.html.
  • Jeong, B.K., Yoon, T.E., An empirical investigation on consumer acceptance of mobile banking services. Business and Management Research, 2(1), 2013, 31.
  • Jiang, G., Peng, L., Liu, R., Mobile game adoption in China: The role of TAM and perceived entertainment, cost, similarity and brand trust. International Journal of Hybrid Information Technology 8:4 (2015), 213–232.
  • Ko, E., Kim, E.Y., Lee, E.K., Modeling consumer adoption of mobile shopping for fashion products in Korea. Psychology & Marketing 26:7 (2009), 669–687.
  • KPMG, Informe Global de Banca Móvil. 2015 Retrieved from http://www.kpmg.com/ar/es/prensa/gacetillasdeprensa/paginas/informe-global-de-banca-movil-realizado-por-kpmg.aspx.
  • Krishanan, D., Khin, A.A., Teng, K.L.L., Chinna, K., Consumers’ perceived interactivity & intention to use mobile banking in structural equation modeling. International Review of Management and Marketing 6:4 (2016), 883–890.
  • Kulviwat, S., Bruner, I.I., Gordon, C., Kumar, A., Nasco, S.A., Clark, T., Toward a unified theory of consumer acceptance technology. Psychology& Marketing 24:12 (2007), 1059–1084.
  • Lai, J.Y., Li, D.H., Technology acceptance model for internet banking: An invariante analysis. Information & Management 42 (2005), 373–386.
  • Laukkanen, T., Internet vs mobile banking: Comparing customer value perceptions. Business Process Management Journal 13:6 (2007), 788–797.
  • Lee, M., McGoldrick, P.J., Keeling, K.A., Doherty, J., Using ZMET to explore barriers to the adoption of 3G mobile banking services. International Journal of Retail and Distribution Management 31 (2003), 340–348.
  • Li, H., Liu, Y., Heikkilä, J., Understanding the factors driving NFC-enabled mobile payment adoption: An empirical investigation. PACIS, 2014, 231.
  • Liang, C.C., Subjective norms and customer adoption of mobile banking: Taiwan and Vietnam. 2016 49th Hawaii international conference on system sciences (HICSS), 2016, IEEE, 1577–1585.
  • Liébana Cabanillas, F.J., El papel de los sistemas de pago en lo nuevos entornos electrónicos. 2012, Universidad de Granada, Granada.
  • Liébana-Cabanillas, F., Muñoz-Leiva, F., Sánchez-Fernández, J., A global approach to the analysis of user behavior in mobile payment systems in the new electronic environment. Service Business, 2017 (in press).
  • Liébana-Cabanillas, F., Muñoz-Leiva, F., Rejón-Guardia, F., The determinants of satisfaction with e-banking. Industrial Management & Data Systems 113:5 (2013), 750–767.
  • Liébana-Cabanillas, F., Sánchez-Fernández, J., Muñoz-Leiva, F., Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Computers in Human Behaviour, 2014, 464–478.
  • 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. International Journal of Information Management, 2014, 151–166.
  • Lin, C.H., Shih, H.Y., Sher, P.J., Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing 24:7 (2007), 641–657.
  • Lin, C.P., Bhattacherjee, A., Extending technology usage models to interactive hedonic technologies: A theoretical model and empirical test. Information Systems Journal 20:2 (2010), 163–181.
  • Liu, Y., Li, H., Exploring the impact of use context on mobile hedonic services adoption: An empirical study on mobile gaming in China. Computers in Human Behavior 27:2 (2011), 890–898.
  • López-Nicolás, C., Molina-Castillo, F.J., Bouwman, H., An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models. Information & Management 45 (2008), 359–364.
  • Lu, J., Yao, J., Yu, C., Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems 14:3 (2005), 245–268.
  • Lu, Y., Yang, S., Chau, P., Cao, Y., Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information & Management 48 (2011), 393–403.
  • Luo, X., Li, H., Zhang, J., Shim, J.P., Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems 49:2 (2010), 222–234.
  • Luque, T., Investigación de marketing. Fundamentos. 1997, Ariel, Barcelona.
  • Malhotra, N.K., Investigación de Mercados. Un enfoque práctico 2ª Ed. 1997, Prentice Hall Hispanoamericana, México.
  • Moore, G.C., Benbasat, I., Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research 2:3 (1991), 192–222.
  • Muñoz, F., La adopción de una innovación basada en la Web. Tesis Doctoral, 2008, Departamento de Comercialización e Investigación de Mercados, Universidad de Granada.
  • Muñoz-Leiva, F., Hernández-Méndez, J., Sánchez-Fernández, J., Generalising user behaviour in online travel sites through the Travel 2.0 website acceptance model. Online Information Review 36:6 (2012), 879–902.
  • Muñoz-Leiva, F., Sánchez-Fernández, J., Luque-Martínez, T., How to improve trust toward electronic banking. Online Information Review 34:6 (2010), 907–934.
  • Niemelä-Nyrhinen, J., Baby boom consumers and technology: Shooting down stereotypes. Journal of Consumer Marketing 24:5 (2007), 305–312.
  • Nunnally, J.C., Psycometric theory. 2nd ed., 1978, McGraw-Hill, New York.
  • O'cass, A., Fenech, T., Web retailing adoption: Exploring the nature of internet users Web retailing behaviour. Journal of Retailing and Consumer Services 10:2 (2003), 81–94.
  • Oh, S.H., Kim, Y.M., Lee, C.W., Shim, G.Y., Park, M.S., Jung, H.S., Consumer adoption of virtual stores in Korea: Focusing on the role of trust and playfulness. Psychology & Marketing 26:7 (2009), 652–668.
  • Park, E., Baek, S., Ohm, J., Chang, H.J., Determinants of player acceptance of mobile social network games: An application of extended technology acceptance model. Telematics and Informatics 31:1 (2014), 3–15.
  • Park, S., Tussyadiah, I.P., Multidimensional facets of perceived risk in mobile travel booking. Journal of Travel Research, 2016, 10.1177/0047287516675062 First Online Published, October 27, 2016. Available in: http://journals.sagepub.com/doi/abs/10.1177/0047287516675062.
  • Pavlou, P.A., A theory of planned behavior perspective to the consumer adoption of electronic commerce. MIS Quarterly 30:1 (2002), 115–143.
  • Pavlou, P.A., Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal Electronic Commerce 7:3 (2003), 69–103.
  • Pham, T.T.T., Ho, J.C., The effects of product-related, personal-related factors and attractiveness of alternatives on consumer adoption of NFC-based mobile payments. Technology in Society 43 (2015), 159–172.
  • Phang, C.W., Sutanto, J., Kankanhalli, A., Li, Y., Tan, B.C., Teo, H.H., Senior citizens’ acceptance of information systems: A study in the context of e-government services. IEEE Transactions on Engineering Management 53:4 (2006), 555–569.
  • Price Waterhouse Coopers, Global insights and actions for Banks in the digital age. 2013 Retrieved from http://www.pwc.es/es/publicaciones/financiero-seguros/encuesta-mundial-banca-digital.jhtml.
  • Prodanova, J., San-Martín, S., Jiménez, N., El presente y el futuro de la banca por móvil según los usuarios españoles de banca. Universia Business Review 46 (2015), 94–117.
  • Reichheld, F.F., Schefter, P., E-loyalty: Your secret weapon on the web. Harvard Business Review 78:4 (2000), 105–113.
  • Rifon, N.J., LaRose, R., Choi, S.M., Your privacy is sealed: Effects of web privacy seals on trust and personal disclosures. The Journal of Consumer Affairs 39:2 (2005), 339–362.
  • Ristola, A., Insights into customers emerging interest in mobile services. 2010, University of Oulu, Department of Marketing.
  • Rogers, E.M., Diffusion of innovations. 5th ed., 2003, Free Press, New York, NY.
  • Rouibah, K., Abbas, H., Effect of personal innovativeness, attachement motivation and social norms on the acceptance of camera mobile phones: An empirial study in an Arab Country. International Journal of Handheld Computing Research 1:4 (2011), 41–62.
  • Rouibah, K., Lowry, P.B., Hwang, Y., The effects of perceived enjoyment and perceived risks on trust formation and intentions to use online payment systems: New perspectives from an Arab country. Electronic Commerce Research and Applications 19 (2016), 33–43.
  • Ruiz Mafé, C., Tronch García de los Ríos, J.E., Factores determinantes de la decisión de compra en Internet: un análisis de la formación a distancia. Estudios sobre Consumo, 2007 80 (2007), 49–60.
  • Saghafi, F., Moghaddam, E.N., Aslani, A., Examining effective factors in initial acceptance of high-tech localized technologies: Xamin Iranian localized operating system. Technological Forecasting and Social Change, 2016, 10.1016/j.techfore.2016.04.010 Online Publication, 1-May-2016.
  • Schierz, P.G., Schilke, O., Wirtz, B.W., Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications 9:3 (2010), 209–216.
  • Schurr, P.H., Ozanne, J.L., Influences on exchange processes: Buyers’ preconceptions of a seller's trustworthiness and bargaining toughness. Journal of Consumer Research 11 (1985, March), 939–953.
  • Sellitto, C., User intentions to adopt mobile payment services: A study of early adopters in Thailand. Journal of Internet Banking and Commerce 20:1 (2015), 1–29.
  • Slade, E.L., Dwivedi, Y.K., Piercy, N.C., Williams, M.D., Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: Extending UTAUT with innovativeness, risk, and trust. Psychology & Marketing 32:8 (2015), 860–873.
  • Shaikh, A.A., Karjaluoto, H., Mobile banking adoption: A literature review. Telematics and Informatics 32:1 (2015, February), 129–142.
  • Silva-Bidarra, S.H., Muñoz-Leiva, F., Liébana-Cabanillas, F., Analysis and modeling of the determinants of mobile banking acceptance. The International Journal of Management Science and Information Technology (IJMSIT), 2013, April–June, 1–27.
  • Stern, B.B., Royne, M.B., Stafford, T.F., Bienstock, C.C., Consumer acceptance of online auctions: An extension and revision of the TAM. Psychology & Marketing 25:7 (2008), 619–636.
  • Stewart, K., Trust transfer on the World Wide Web. Organization Science 14:1 (2003), 5–17.
  • Taylor, S., Todd, P., Understanding information technology usage: A test of competing models. Information Systems Research 6:2 (1995), 144–176.
  • Tecnocom Report, Tendencias en Medios de Pago 2012. 2012 Retrieved from http://www.afi.es/afi/libre/PDFS/Grupo/Documentos/Informe_Tecnocom12.pdf.
  • Venkatesh, V., Bala, H., Technology acceptance model 3 and a research agenda on interventions. Decision Sciences 39:2 (2008), 273–315.
  • Venkatesh, V., Davis, F.D., A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science 46:2 (2000), 186–204.
  • West, S.G., Finch, J.F., Curran, P.J., Structural equations models with nonnormal variables: Problems and remedies. Hoyle, R.H., (eds.) Structural equation model: Concepts, issues, and applications, 1995, Sage Publications, Newbury Park, CA, 57–75.
  • White, J.B., Tynan, R., Galinsky, A.D., Thompson, L., Face threat sensitivity in negotiation: Roadblock to agreement and joint gain. Organizational Behavior and Human Decision Processes 94:2 (2004), 102–124.
  • Wu, I.L., Chen, J.L., An extension of Trust and TAM model with TPB in the initial adoption of on-line tax: An empirical study. International Journal of Human-Computer Studies 62 (2005), 784–808.
  • Youtube, Nueva aplicación de Banco Santander para Iphone - Demo. 2012 Retrieved from https://www.youtube.com/watch?v=QXv45_cCNlE.
  • Zhang, A., Yue, X., Kong, Y., Exploring culture factors affecting the adoption of mobile payment. 10th international conference on mobile business, 2011, 263–267.
  • Zhang, J., Mao, E., Understanding the acceptance of mobile SMS advertising among young Chinese consumers. Psychology & Marketing 25:8 (2008), 787–805.
  • Zhou, T., Lu, Y., Wang, B., Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior 26:4 (2010), 760–767.