Os resultados apresentados por esta pesquisa nem sempre tiveram o poder de explicação pleno sobre determinados constructos que, à luz da revisão teórica preparatória à pesquisa, deveriam ter papel significativo na adoção e uso de mobile banking. Além do trabalho de Baptista & Oliveira (2015), entretanto, os referidos constructos não foram testados – especificamente e
estensivamente – quanto à aceitação e uso de mobile banking por outras pesquisas de forma profunda.
Influência Social é um desses constructos, que se considerarmos Kim & Park (2011) e o próprio Venkatesh et al. (2012), a expectativa era de que tivesse significância como antecedente de Intenção de Uso, mas os dados não mostraram isso. Embora o capítulo anterior apresente explicações de outros autores, sugere-se que sejam estudados especificamente para a realidade brasileira os motivos que levam a Influência Social a não ter peso na adoção e uso de mobile banking. O mesmo racional acontece para a dimensão Aversão à Incerteza, que é relacionada com confiança (trust) e risco (risk) na literatura, mas não encontrou abrigo nos dados da pesquisa. Entender por que isso acontece é recomendação de pesquisa futura.
Por fim, o entendimento de por que Idade e Gênero não se apresentam como variáveis moderadoras, conforme proposto por Venkatesh et al. (2012), é outra proposta de pesquisa futura, já que foram encontradas pesquisas que tratam Idade e Gênero como importantes fatores (Akturan & Tezcan, 2012; Chung & Holdsworth, 2012; Koenig-Lewis et al., 2010; Pascual-Miguel et al, 2015).
Além dos pontos acima, ao longo da pesquisa e da revisão teórica que embasou este trabalho, por vezes surgiram temas relacionados à adoção e ao uso de mobile banking que merecem a recomendação de pesquisas futuras. Estão listados a seguir.
Influência da Cultura sobre a Intenção de Uso
As dimensões de cultura nacional também podem ter influência sobre a intenção de uso e não somente sobre o Comportamento de uso (Nistor et al., 2014), por isso realizar testes considerando a influência sobre a intenção de uso é sugestão de pesquisa futura no Brasil. O trabalho de Choi et al. (2014) é um exemplo em que as dimensões culturais moderam a relação de variáveis independentes como Influência Social (enjoyment) e Atitude. Outros exemplos são Chung & Holdsworth (2012) e Hung & Chou (2013). Srite & Karahanna (2006) definem que as variáveis de dimensões culturais moderam a Intenção de Uso e não o Comportamento de Uso.
Estudo longitudinal, em vez de transversal, pode acompanhar a dinâmica das mudanças que acontecem na população pesquisada e ampliar o poder de resposta do estudo (Magsamen- Conrad et al., 2015).
Mobile Banking em Áreas Rurais e Carentes
Em outros países, os serviços de mobile banking são relativamente populares em áreas rurais (Oliveira et al., 2014) e carentes. Neste estudo não se analisa a aceitação e o uso em tais áreas (Tobbin, 2012), concentrando a pesquisa em consumidores das áreas urbanas brasileiras. A ubiquidade da tecnologia pode ter importante impactos em consumidores das referidas áreas.
REFERÊNCIAS
Referências criadas no padrão APA e usando o software Zotero.
AbuShanab, E., & Pearson, J. M. (2007). Internet banking in Jordan: The unified theory of acceptance and use of technology (UTAUT) perspective. Journal of Systems and Information Technology, 9(1), 78–97. http://doi.org/10.1108/13287260710817700 Ain, N., Kaur, K., & Waheed, M. (2015). The influence of learning value on learning
management system use: An extension of UTAUT2. Information Development, 1(16). http://doi.org/10.1177/0266666915597546
Ajzen, I. (1991). Theory of Planned Behavior. Retrieved February 1, 2016, from http://people.umass.edu/aizen/tpb.html
Akturan, U., & Tezcan, N. (2012). Mobile banking adoption of the youth market: Perceptions and intentions. Marketing Intelligence & Planning, 30(4), 444–459.
http://doi.org/10.1108/02634501211231928
Alafeef, M., Singh, D., & Ahmad, K. (2012). The Influence of Demographic Factors and User Interface on Mobile Banking Adoption: A Review. Journal of Applied Sciences, 12(20), 2082–2095. http://doi.org/10.3923/jas.2012.2082.2095
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.
Allen, M., & Preiss, R. (1993). Replication and Meta-Analysis: A Necessary Connection. Journal of Social Behavior and Personality, 8(6), 9–20.
Alwahaishi, S., & Snasel, V. (2013). Consumers’ Acceptance and Use of Information and Communications Technology: A UTAUT and Flow Based Theoretical Model. Journal of
Technology Management & Innovation, 8(2), 61–73. http://doi.org/10.4067/S0718- 27242013000200005
Anderson, J. (2010). M‐ banking in developing markets: competitive and regulatory implications. Info, 12(1), 18–25. http://doi.org/10.1108/14636691011015358
Arpaci, I. (2015). A comparative study of the effects of cultural differences on the adoption of mobile learning. British Journal of Educational Technology, 46(4), 699–712.
http://doi.org/10.1111/bjet.12160
Ashraf, A. R., Thongpapanl, N., & Auh, S. (2014). The Application of the Technology Acceptance Model Under Different Cultural Contexts: The Case of Online Shopping Adoption. Journal of International Marketing, 22(3), 68–93.
http://doi.org/10.1509/jim.14.0065
Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418–430. http://doi.org/10.1016/j.chb.2015.04.024
Barnes, S. J., & Corbitt, B. (2003). Mobile banking: Concept and potential. INTERNATIONAL JOURNAL OF MOBILE COMMUNICATIONS, 1(3), 273–288.
http://doi.org/10.1504/IJMC.2003.003494
Barry III, H. (2014). Proximity of Paired Nations Reveals Correlation of Masculinity With Individualism. Journal of Cross-Cultural Psychology, 0022022114557480.
http://doi.org/10.1177/0022022114557480
Bearden, W. O., Money, R. B., & Nevins, J. L. (2006). A measure of long-term orientation: Development and validation. Journal of the Academy of Marketing Science, 34(3), 456– 467. http://doi.org/10.1177/0092070306286706
Berger, E., & Nakata, C. (2013). Implementing Technologies for Financial Service Innovations in Base of the Pyramid Markets. Journal of Product Innovation Management, 30(6), 1199– 1211. http://doi.org/10.1111/jpim.12054
Bickman, L., & Rog, D. J. (1998). Handbook of Applied Social Research Methods. SAGE. Board of Governors of the Federal Reserve System. (2015). Consumers and Mobile Financial
Services.
Bouwman, H., De Vos, H., & Haaker, T. (2008). Mobile Service Innovation and Business Models. Berlin: Springer Berlin Heidelberg.
Brown, S. A., & Venkatesh, V. (2005). Model of Adoption of Technology in Households: A Baseline Model Test and Extension Incorporating Household Life Cycle. MIS Quarterly, 29(3), 399–426.
Bryson, D., Atwal, G., Chaudhuri, H., & Dave, K. (2015). Understanding the Antecedents of Intention to Use Mobile Internet Banking in India: Opportunities for Microfinance Institutions. Strategic Change, 24(3), 207–224. http://doi.org/10.1002/jsc.2005 Chaouali, W., Yahia, I. B., & Souiden, N. (2016). The interplay of counter-conformity
motivation, social influence, and trust in customers’ intention to adopt Internet banking services: The case of an emerging country. Journal of Retailing and Consumer Services, 28, 209–218. http://doi.org/10.1016/j.jretconser.2015.10.007
Chauhan, S. (2015). Acceptance of mobile money by poor citizens of India: integrating trust into the technology acceptance model. Info, 17(3), 58–68. http://doi.org/10.1108/info-02- 2015-0018
ChauShen Chen. (2013). Perceived risk, usage frequency of mobile banking services. Managing Service Quality: An International Journal, 23(5), 410–436. http://doi.org/10.1108/MSQ- 10-2012-0137
Chemingui, H., & Lallouna, H. B. (2013). Resistance, motivations, trust and intention to use mobile financial services. International Journal of Bank Marketing, 31(7), 574–592. http://doi.org/10.1108/IJBM-12-2012-0124
Chen, K., & Chan, A. H. S. (2014). Predictors of gerontechnology acceptance by older Hong Kong Chinese. Technovation, 34(2), 126–135.
http://doi.org/10.1016/j.technovation.2013.09.010
Chian-Son Yu. (2014). Consumer Switching Behavior from Online Banking to Mobile Banking. International Journal of Cyber Society & Education, 7(1), 1–28.
http://doi.org/10.7903/ijcse.1108
Chin, W. (1998). Issues and Opinion on Structural Equation Modeling. Management Information Systems Quarterly, 22(1). Retrieved from http://aisel.aisnet.org/misq/vol22/iss1/3
Choe, J. (2004). The Consideration of Cultural Differences in the Design of Information Systems. Inf. Manage., 41(5), 669–684. http://doi.org/10.1016/j.im.2003.08.003
Choi, J., Lee, H. J., Sajjad, F., & Lee, H. (2014). The influence of national culture on the attitude towards mobile recommender systems. Technological Forecasting and Social Change, 86, 65–79. http://doi.org/10.1016/j.techfore.2013.08.012
Chung, K., & Holdsworth, D. K. (2012). Culture and behavioural intent to adopt mobile
commerce among the Y Generation: comparative analyses between Kazakhstan, Morocco and Singapore. Young Consumers, 13(3), 224–241.
Cohen, J., Bancilhon, J.-M., & Jones, M. (2013). South African physicians’ acceptance of e- prescribing technology: an empirical test of a modified UTAUT model. South African Computer Journal, 50(1). http://doi.org/10.18489/sacj.v50i1.175
Compeau, D., Higgins, C. A., & Huff, S. (1999). Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study. MIS Quarterly, 23(2), 145– 158. http://doi.org/10.2307/249749
comScore, Inc. (2011). Mobile Usage Behaviours and Trends: The who, what, when, why & how of mobile consumers. Retrieved from www.comscore.com
comScore Inc. (2015). comScore / IMS Mobile in LatAm Study. Conecta. (2016). Retrieved from http://conecta-i.com/
COOPER, D., & Schindler, P. S. (2003). Metodos de Pesquisa Em Administracao. Bookman Companhia Ed.
Corrar, L. J., Paulo, E., & Dias Filho, J.M. (Eds.). (2014). Análise Multivariada para os Cursos de Administração, Ciências Contábeis e Economia. São Paulo: Atlas.
preference on future online banking services. Information Systems, 53, 1–15. http://doi.org/10.1016/j.is.2015.04.006
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Q., 13(3), 319–340. http://doi.org/10.2307/249008 Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of
Davis, F. D., Bagozzi, R., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1. Journal of Applied Social Psychology, 22(14), 1111–1132. http://doi.org/10.1111/j.1559-1816.1992.tb00945.x
Dictionary.com. (2015). Retrieved May 12, 2015, from http://dictionary.reference.com/ Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of Price, Brand, and Store
Information on Buyers’ Product Evaluations. Journal of Marketing Research, 28(3), 307– 319. http://doi.org/10.2307/3172866
Dwivedi, Y. K., Rana, N. P., Chen, H., & Williams, M. D. (2011). A Meta-analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT). In Governance and Sustainability in Information Systems. Managing the Transfer and Diffusion of IT (pp. 155–170). Springer Berlin Heidelberg. Retrieved from
http://link.springer.com/chapter/10.1007/978-3-642-24148-2_10
Dwivedi, Y. K., Shareef, M. A., Simintiras, A. C., Lal, B., & Weerakkody, V. (2015).
Generalised adoption model for services: A cross-country comparison of mobile health (m-health). Government Information Quarterly. Retrieved from
http://dx.doi.org/10.1016/j.giq.2015.06.003
Easley, R. W., & Madden, C. S. (2013). Replication revisited: Introduction to the special section on replication in business research. Journal of Business Research, 66(9), 1375–1376. http://doi.org/10.1016/j.jbusres.2012.05.001
Easley, R. W., Madden, C. S., & Dunn, M. G. (2000). Conducting Marketing Science: The Role of Replication in the Research Process. Journal of Business Research, 48(1), 83–92. http://doi.org/10.1016/S0148-2963(98)00079-4
Evanschitzky, H., Baumgarth, C., Hubbard, R., & Armstrong, J. S. (2007). Replication research’s disturbing trend. Journal of Business Research, 60(4), 411–415.
http://doi.org/10.1016/j.jbusres.2006.12.003
Faqih, K. M. S. (2016). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter? Journal of Retailing and Consumer Services, 30, 140–164.
Faul, F., Erdfelder, E., Buchner, A.-G., & Lang, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191.
FEBRABAN. (2013). Pesquisa FEBRABAN de Tecnologia Bancária 2013. Retrieved from www.febraban.org.br
FEBRABAN. (2014). Pesquisa FEBRABAN de Tecnologia Bancária.
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley. Retrieved from
http://people.umass.edu/aizen/f&a1975.html
Fornell, C., & Larker, D. F. (1981). Evaluating Structural Equation Models With Unobservable Variable Sand Measurement Error. Journal of Marketing Research, 18(1), 39–50. http://doi.org/10.2307/3151312
Fosk, A. (2014, August). LATAM Digital Future in Focus 2014. Presented at the 2014 Latin America & U.S. Hispanic Digital Summit.
Francisco Javier Rondan-Cataluña, Jorge Arenas-Gaitán, & Patricio Esteban Ramírez-Correa. (2015). A comparison of the different versions of popular technology acceptance models. Kybernetes, 44(5), 788–805. http://doi.org/10.1108/K-09-2014-0184
Gao, Y., Li, H., & Luo, Y. (2015). An empirical study of wearable technology acceptance in healthcare. Industrial Management & Data Systems, 115(9), 1704–1723.
Giovanis, A. N., Binioris, S., & Polychronopoulos, G. (2012). An extension of TAM model with IDT and security/privacy risk in the adoption of internet banking services in Greece. EuroMed Journal of Business, 7(1), 24–53. http://doi.org/10.1108/14502191211225365 Google Scholar. (2015). Retrieved from https://scholar.google.com.br/
Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2009). Análise Multivariada de Dados (6th ed.). Porto Alegre: Bookman Companhia Editora.
Hair, J. F., Celsi, M. W., Ortinau, D. J., & Bush, R. P. (2013). Fundamentos de Pesquisa de Marketing (3rd ed.). AMGH Editora.
Hanafizadeh, P., Keating, B. W., & Khedmatgozar, H. R. (2014). A systematic review of Internet banking adoption. Telematics and Informatics, 31(3), 492–510.
http://doi.org/10.1016/j.tele.2013.04.003
Harzing, A. W. (2007). Publish or Perish. Retrieved from www.harzing.com/pop.htm
Hassan, L. M., Shiu, E., & Walsh, G. (2011). A multi‐ country assessment of the long‐ term orientation scale. International Marketing Review, 28(1), 81–101.
http://doi.org/10.1108/02651331111107116
Hew, J.-J., Voon-Hsien, L., Keng-Boon, O., & June, W. (2015). What catalyses mobile apps usage intention: an empirical analysis. Industrial Management & Data Systems, 115(7), 1269–1291. http://doi.org/10.1108/IMDS-01-2015-0028
Hoehle, H., Scornavacca, E., & Huff, S. (2012). Three decades of research on consumer adoption and utilization of electronic banking channels: A literature analysis. Decision Support Systems, 54(1), 122–132. http://doi.org/10.1016/j.dss.2012.04.010
Hofstede, G. (1984). Culture’s Consequences: International Differences in Work-Related Values. SAGE.
Hofstede, G. (2016). Cultural Insights - Geert Hofstede. Retrieved January 9, 2016, from http://geert-hofstede.com/
Hofstede, G., & Bond, M. H. (1984). Hofstede’s Culture Dimensions: An Independent Validation Using Rokeach’s Value Survey. Journal of Cross-Cultural Psychology, 15(4), 417–433. http://doi.org/10.1177/0022002184015004003
Hofstede, G., Hilal, A. V. G., Malvezzi, S., Tanure, B., & Vinken, H. (2010). Comparing Regional Cultures Within a Country: Lessons From Brazil. Journal of Cross-Cultural Psychology, 41(3), 336–352. http://doi.org/10.1177/0022022109359696
Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and Organizations: Software of the Mind (3rd ed.). McGraw Hill Professional.
Holbrook, M. B., & Hirschman, E. C. (1982). The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun. Journal of Consumer Research, 9(2), 132–140. Hommels, A., Peters, P., & Bijker, W. E. (2007). Techno therapy or nurtured niches? Technology
studies and the evaluation of radical innovations. Research Policy, 36(7), 1088–1099. http://doi.org/10.1016/j.respol.2007.04.002
Hubbard, R., & Armstrong, J. S. (1994). Replications and extensions in marketing: Rarely published but quite contrary. International Journal of Research in Marketing, 11(3), 233– 248. http://doi.org/10.1016/0167-8116(94)90003-5
Hung, C., & Chou, J. C. (2013). Examining the cultural moderation on the acceptance of mobile commerce. International Journal of Innovation and Technology Management, 11(02), 1450010. http://doi.org/10.1142/S0219877014500102
IBGE. (2013). Pesquisa Nacional por Amostra de Domicílios: Acesso à Internet e à Televisão e Posse de Telefone Móvel Celular para Uso Pessoal.
Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information & Management, 48(1), 1–8.
http://doi.org/10.1016/j.im.2010.09.001
International Monetary Fund. (2015). World Economic Outlook: Adjusting to Lower Commodity Prices.
Internet Live Stats. (2015). Retrieved October 7, 2015, from http://www.internetlivestats.com/internet-users/#trend
Jack, W., & Suri, T. (2014). RISK SHARING AND TRANSACTION COSTS: EVIDENCE FROM KENYA’S MOBILE MONEY REVOLUTION. American Economic Revie, 104(1).
Kaur, G., & Quareshi, T. K. (2015). Factors obstructing intentions to trust and purchase products online. Asia Pacific Journal of Marketing and Logistics, 27(5), 758–783.
http://doi.org/10.1108/APJML-10-2014-0146
Kim, D., & Ammeter, T. (2014). Predicting personal information system adoption using an integrated diffusion model. Information & Management, 51(4), 451–464.
http://doi.org/10.1016/j.im.2014.02.011
Kim, H.-W., Chan, H. C., & Gupta, S. (2007). Value-based Adoption of Mobile Internet: An empirical investigation. Decision Support Systems, 43(1), 111–126.
Kim, S., & Park, H. J. (2011). Effects of social influence on consumers’ voluntary adoption of innovations prompted by others. Journal of Business Research, 64(11), 1190–1194. http://doi.org/10.1016/j.jbusres.2011.06.021
Kim, S. S., & Malhotra, N. K. (2005). A Longitudinal Model of Continued IS Use: An
Integrative View of Four Mechanisms Underlying Postadoption Phenomena. Management Science, 51(5), 741–755. http://doi.org/10.1287/mnsc.1040.0326
Koenig‐ Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers’ take up of mobile banking services. International Journal of Bank Marketing, 28(5), 410–432. http://doi.org/10.1108/02652321011064917
Krishnaraju, V., Mathew, S., & Sugumaran, V. (2013). Role of Web Personalization in Consumer Acceptance of E-Government Services. AMCIS 2013 Proceedings. Retrieved from
http://aisel.aisnet.org/amcis2013/eGovernment/GeneralPresentations/2
Ladhari, R., Souiden, N., & Choi, Y. (2015). Culture change and globalization: The unresolved debate between cross-national and cross-cultural classifications. Australasian Marketing Journal, 23, 235–245.
Laukkanen, T., & Lauronen, J. (2005). Consumer value creation in mobile banking services. International Journal of Mobile Communications, 3(4), 325–338.
http://doi.org/10.1504/IJMC.2005.007021
Lee, H., Harindranath, G., Oh, S., & Kim, D.-J. (2015). Provision of mobile banking services from an actor–network perspective: Implications for convergence and standardization. Technological Forecasting and Social Change, 90, Part B, 551–561.
Lee, S.-G., Trimi, S., & Kim, C. (2013). The impact of cultural differences on technology adoption. Journal of World Business, 48(1), 20–29.
http://doi.org/10.1016/j.jwb.2012.06.003
Lee, S., Trimi, S., & Kim, C. (2013). Innovation and imitation effects’ dynamics in technology adoptionnull. Industrial Management & Data Systems, 113(6), 772–799.
http://doi.org/10.1108/IMDS-02-2013-0065
Lee, Y., Lee, J., & Hwang, Y. (2015). Relating motivation to information and communication technology acceptance: Self-determination theory perspective. Computers in Human Behavior, 51, Part A, 418–428. http://doi.org/10.1016/j.chb.2015.05.021
Lewis, C. C., Fretwell, C. E., Ryan, J., & Parham, J. B. (2013). Faculty Use of Established and Emerging Technologies in Higher Education: A Unified Theory of Acceptance and Use of Technology Perspective. International Journal of Higher Education, 2(2).
http://doi.org/10.5430/ijhe.v2n2p22
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance. MIS Q., 31(4), 705–737.
Lin, H. (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. http://doi.org/10.1016/j.ijinfomgt.2010.07.006
Lin, H.-F. (2013). Determining the relative importance of mobile banking quality factors. Computer Standards & Interfaces, 35(2), 195–204.
http://doi.org/10.1016/j.csi.2012.07.003
Liu, J., Kauffman, R. J., & Ma, D. (2015). Competition, cooperation, and regulation:
Understanding the evolution of the mobile payments technology ecosystem. Electronic Commerce Research and Applications. http://doi.org/10.1016/j.elerap.2015.03.003 Lu, J., Yao, J. E., & Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of
wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245–268. http://doi.org/10.1016/j.jsis.2005.07.003
Magsamen-Conrad, K., Upadhyaya, S., Joa, C. Y., & Dowd, J. (2015). Bridging the divide: Using UTAUT to predict multigenerational tablet adoption practices. Computers in Human Behavior, 50, 186–196. http://doi.org/10.1016/j.chb.2015.03.032
Malaquias, R., & Hwang, Y. (2016). An empirical study on trust in mobile banking: A developing country perspective. Computers in Human Behavior, 54, 453–461. http://doi.org/10.1016/j.chb.2015.08.039
Malhotra, N. K. (2010). Pesquisa de Marketing: uma Orientação Aplicada (6th ed.). Porto Alegre: Bookman.
Martins, C., Oliveira, T., & Popovic, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34.
Merkin, R. (2006). Uncertainty avoidance and facework: A test of the Hofstede model. International Journal of Intercultural Relations, 30(2), 213–228.
http://doi.org/10.1016/j.ijintrel.2005.08.001
Microsotf Excel for Mac. (2011). (Version 14.5.9). Microsoft.
Minkov, M., & Hofstede, G. (2011). The evolution of Hofstede’s doctrine. Cross Cultural Management: An International Journal, 18(1), 10–20.
Min, Q., Ji, S., & Qu, G. (2008). Mobile Commerce User Acceptance Study in China: A Revised UTAUT Model. Tsinghua Science & Technology, 13(3), 257–264.
http://doi.org/10.1016/S1007-0214(08)70042-7
Mishra, V., & Singh Bisht, S. (2013). Mobile banking in a developing economy: A customer- centric model for policy formulation. Telecommunications Policy, 37(6–7), 503–514. http://doi.org/10.1016/j.telpol.2012.10.004
Montazemi, A. R., & Saremi, H. Q. (2014). Factors Affecting Adoption of Online Banking: A Meta-Analytic Structural Equation Modeling Study. Information & Management, 52(2). http://doi.org/10.1016/j.im.2014.11.002
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.
Morris, M. G., & Venkatesh, V. (2000). Age Differences in Technology Adoption Decisions: Implications for a Changing Work Force. Personnel Psychology, 53(2), 375–403. http://doi.org/10.1111/j.1744-6570.2000.tb00206.x
Mortimer, G., Neale, L., Hasan, S. F. E., & Dunphy, B. (2015). Investigating the factors influencing the adoption of m-banking: a cross cultural study. International Journal of Bank Marketing, 33(4), 545–570. http://doi.org/10.1108/IJBM-07-2014-0100
Moser, F. (2015). Mobile Banking: A fashionable concept or an institutionalized channel in future retail banking? Analyzing patterns in the practical and academic mobile banking literature. International Journal of Bank Marketing, 33(2), 162–177.
http://doi.org/10.1108/IJBM-08-2013-0082
Nair, P. K., Ali, F., & Leong, L. C. (2015). Factors affecting acceptance & use of ReWIND: Validating the extended unified theory of acceptance and use of technology. Interactive
Technology and Smart Education, 12(3), 183–201. http://doi.org/10.1108/ITSE-02-2015- 0001
Negahban, A., & Chung, C.-H. (2014). Discovering determinants of users perception of mobile device functionality fit. Computers in Human Behavior, 35, 75–84.
http://doi.org/10.1016/j.chb.2014.02.020
Niklas Arvidsson. (2014). Consumer attitudes on mobile payment services – results from a proof of concept test. International Journal of Bank Marketing, 32(2), 150–170.
http://doi.org/10.1108/IJBM-05-2013-0048
Nikou, S., & Mezei, J. (2013). Evaluation of mobile services and substantial adoption factors with Analytic Hierarchy Process (AHP). Telecommunications Policy, 37(10), 915–929. http://doi.org/10.1016/j.telpol.2012.09.007
Nistor, N., Göğüş, A., & Lerche, T. (2013). Educational technology acceptance across national and professional cultures: a European study. Educational Technology Research and Development, 61(4), 733–749. http://doi.org/10.1007/s11423-013-9292-7
Nistor, N., Lerche, T., Weinberger, A., Ceobanu, C., & Heymann, O. (2014). Towards the integration of culture into the Unified Theory of Acceptance and Use of Technology. British Journal of Educational Technology, 45(1), 36–55. http://doi.org/10.1111/j.1467- 8535.2012.01383.x
Nysveen, H. (2005). Intentions to Use Mobile Services: Antecedents and Cross-Service Comparisons. Journal of the Academy of Marketing Science, 33(3), 330–346. http://doi.org/10.1177/0092070305276149
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. http://doi.org/10.1016/j.ijinfomgt.2014.06.004
Oura, M. M. (2014). O IMPACTO DA CAPACIDADE DE INOVAÇÃO E DA EXPERIÊNCIA INTERNACIONAL NO DESEMPENHO EXPORTADOR DE PMES INDUSTRIAIS BRASILEIRAS. Universidade Nove de Julho, São Paulo.
Parameswaran, S., Kishore, R., & Li, P. (2015). Within-study measurement invariance of the UTAUT instrument: An assessment with user technology engagement variables. Information & Management, 52(3), 317–336. http://doi.org/10.1016/j.im.2014.12.007