Re-Thinking a Structural Model for M-Phone Paying among South African Consumers
Keywords:
Mobile, m-phone paying, consumers, South Africa
Abstract
Contemporary payment systems have transformed global businesses extensively. Nevertheless, despite its vast prospects, the widespread utilisation of mobile phone technology for payment transactions (m-phone paying) and reproduction of pecuniary structures has only been hemmed in among a small number of markets. The proliferated reliance on mobile payment services has not been witnessed universally, suggesting that even success stories are still ambivalent and as a result, cannot be easily replicated. This paper is intended to address this issue by evaluating the determining factors towards the continued use of m-phone payment services by existing South African customers. The research model was tested using SMART PLS 3, upon examining the antecedents of users’ intentions toward embracing the emerging mobile phone in commercial transactions. A cross-sectional study was performed on a sample of 474 consumers, wherein security and usefulness were validated as having significant and direct effects on consumers’ attitude towards m-phone paying, of which the latter influences future intentions. The relevance of customers’ future intentions towards m-phone paying was established, thereby sanctioning the idea to include the variable as a proxy for actual usage in technology adoption research. This study provides sound reason for cumulative research that seeks to refine novel models of technology acceptance even further. For marketers and m-phone technologists, understanding the key determinants is vital towards the upgrade and implementation of m-phone payment services. In lieu of this, delivering m-phone applications and payment services that achieve high usage, value and consumer laudation will be an inevitable boon.
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References
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Chin, W. W. (1998). Issues and opinion on structural equation modelling. Management Information Systems Quarterly, 22(1), 7-16.
Choi, J., Lee, A. & Ok, C. (2014). The effects of consumer perceived risk and benefit on attitude and behavioural intention: a study of street food. Journal of Travel and Tourism, 30(1), 222-237.
Churchill, G. A., Brown, T. J. &Suter, T. A. (2010). Basic marketing research, (7thed), Canada: South Western, Cengage Learning.
Dahlberg, T., Mallat, N., Ondrus, J. & Zmijewska, A. (2008). Past, present and future of mobile payments research: a literature review. Journal ofElectronic Commerce Research and Applications, 7(2), 165-181.
Davis, F. D., Bagozzi, R. P. &Warshaw, P. R. (1989). User acceptance of computer technology: comparisons of two theoretical models. Journal of Management Science, 35(8), 982-1003.
Diniz, E. H., Cernev, A. K. & Albuquerque, J. P. D. (2011). Mobile money and payment: a literature review based on academic and practitioner-oriented publications (2001–2011). In Proceedings of the 4th Annual Workshop ICT in Global Development - Workshop of the International Conference on Information Systems ICIS 2011, Shangai (pp. 1-35).
Dlodlo, N. (2015). The use of m-payment services in South Africa: a value based perception approach. International Business and Economics Research Journal, 14(1), 159-178.
Donner, J. & Tellez, C. A. (2008). Mobile banking and economic development: linking adoption, impact and use. Asian Journal of Communication, 18(4), 318-322.
Duane, A., O'Reilly, P. & Andreev, P. (2014). Realising m-payments: modelling consumers' willingness to m-pay using smart phones. Behaviour and Information Technology, 33(4), 318-334. Erasmus, E., Rothmann, S. & Van Eeden, C. (2015). A structural model of technology acceptance. South African Journal of Industrial Psychology, 41(1), 1-12.
Field, A. (2009). Discovering Statistics Using SPSS, (3rd ed.), London: Sage.
Fishbein, M. &Ajzen, I. (1975). Belief, Attitude, Intention and Behaviour: an Introduction to Theory and Research, Reading, MA: Addison-Wesley.
Fishbein, M. (1963). An investigation of the relationships between beliefs about an object and the attitude toward that object. Human Relations, 16(3), 233-240.
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gartner Group. (2012). Forecast: Mobile payment, worldwide, 2009-2016, [Online] Available at: http://www.gartner.com/resId¼2010515. Accessed 15/05/2016.
Ghezzi, A., Renga, F., Balocco, R. &Pescetto, P. (2010). Mobile payment applications: offer state of the art in the Italian market. Information, 12(5), 3-22.
Grubb, L. (2012). How ready is Africa for mobile payments? [Online] Available at: http://www.technologybanker.com/news-analysis/how-ready-is-africa-for-mobile-payments.U8kyuvmSw1y. Accessed 18/07/ 2016. Hair, J. F., Ringle, C. M. & Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, 18(2), 139-152. Henseler, J., Ringle, C. M. & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of Marketing Science, 43(1), 115-135. Höck, M. & Ringle, C. M. (2010). Local strategic networks in the software industry: An empirical analysis of the value continuum. International Journal of Knowledge and Management Studies, 4(1), 132-151.
Howard, J. & Sheth, J. (1969). Thetheoryofbuyerbehaviour, New York: John Wiley.
Hsiao, W. H. & Chang, T. S. (2013). Understanding consumers’ continuance intention towards mobile advertising: a theoretical framework and empirical study. Journal of Behavioural Information technology, 33(7), 730-742.
Jeong, B. & Yoon, T. E. (2013). An empirical investigation on consumer acceptance of mobile banking services. Journal of Business Management Research, 2(1), 31-40.
Kim, Y. J., Chun, J., U. & Song, J. (2009). Investigating the role of attitude in technology acceptance from an attitude strength perspective. International Journal of Information Management, 29, 67-77.
Kim, C., Mirusmonov, M. & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behaviour, 26(3), 310-322.
Leong, L. Y., Hew, T. S., Tan, G. W. H. & Ooi, K. B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: a neural networks approach. Expert Systems with Applications, 40(2013), 5604-5620.
Liébana-Cabanillas, F., Sanchez-Fernandez, J. & Munoz-Leiva, F. (2014). Role of gender on acceptance of mobile payment. Journal of Industrial Management and Data Systems, 114(2), 220-240.
Lin, H. F. (2011). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. InternationalJournal of Information Management, 31(1), 252-260.
Liu, J., Kauffman, R. J. & Ma, D. (2015). Competition, cooperation, and regulation: understanding the evolution of the mobile payments technology ecosystem. Journal ofElectronic Commerce Research and Applications, 14(5), 372-391.
Lohmöller, J. B. (1989). Latent Variable Path Modeling With Partial Least Squares, Heidelberg: Physica-Verlag.
Malhotra, N. K. (2010). Marketing research: an applied orientation, (6th ed.), New Jersey: Prentice- Hall.
Malhotra, N. K. & Mccort, J. D. (2001). A cross-cultural comparison of behavioural intentions models. International Marketing Review, 18(3), 235-269.
Mallat, N. (2007). Exploring consumer adoption of mobile payments: a qualitative study. The Journal of Strategic Information Systems, 16(4), 413-432. McKechnie, S., Winklhofer, H. & Ennew, C. (2006). Applying the technology acceptance model to the online retailing of financial services. International Journal of Retail and Distribution Management, 34(4/5), 388-410.
Meharia, P. (2012). Assurance on the reliability of mobile payment system and its effects on it’s’ use: an empirical examination. Journal of Accounting and Management Information System, 11(1), 97-111.
Miltgen, C. L., Popovic, A. & Oliveira, T. (2013). Determinants of end-user acceptance of biometrics: integrating the Big 3 of technology acceptance with privacy context. Decision Support Systems, 56, 103-114.
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 Behaviour, 61(2016), 404-414.
Ondrus, J. & Pigneur, Y. (2007). Towards a holistic analysis of mobile payments: a multiple perspective approach. Journal ofElectronic Commerce Research and Applications, 5(3), 246-257.
O'Reilly, P., Duane, A. & Andreev, P. (2012). To m-pay or not to m-pay? Realising the potential of smart phones: conceptual modeling and empirical validation. Electronic Markets, 22(4), 229-241.
Overbr. (2014). MÃdiaCorporativa. São Paulo: Ãndice Global de PagamentosMóve is. [Online] Available at: http://overbr.com.br/midia-corporativa/indice-global-de-pagamentos-move. Accessed 5/01/2017.
Pallant, J. (2010). SPSS Survival Manual: a Step-By-Step Guide to Data Analysis Using SPSS for Windows, Buckingham: Open University Press.
Pham, T. T. T. & Ho, J. C. (2015). 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.
Rao, S. & Troshani, I. A. (2007). Conceptual framework and propositions for the acceptance of mobile services. Journal of Theoretical and Applied Electronic Commerce Research, 2(2), 61-73.
Revels, J., Tojib, D. & Tsarenko, Y. (2010). Understanding consumer intention to use mobile services. Journal of Australasian Marketing, 18, 74-80.
Schierz, P. G., Schilke, O. &Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services. Journal of Electronic Commerce Research and Applications, 9(1), 209-216.
Schiffman, L. G. Kanuk, L. L. &Wisenblit, J. (2010). Consumer behaviour, (10th ed.), New Jersey: Prentice-Hall.
Slade, E., Williams, M., Dwivedi, Y. & Piercy, N. (2014). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 1-15.
Solomon, M., Bamossy, G., Askegaard, S. & Hogg, M. K. (2006). Consumer Behaviour: a European Perspective, (3rd ed.), Edinburg: Prentice-Hall.
Statistica Corporation. (2015). Mobile payment transaction volume 2010-2017. The Statistics Portal. Available at: http://www.statista.com/statistics/226530/mobile-paymenttransaction-volume-forecast/. Accessed 01/09/16.
Tan, G., Ooi, K. B, Chong, S. C. & Hew, T. S. (2014). NFC mobile credit card: the next frontier of mobile payment? Telematics and Informatics, 31(2), 292-307. Teo, T., Luan, W. S. & Sing, C. C. (2008). A cross-cultural examination of the intention to use technology between Singaporean and Malaysian pre-service teachers: an application of the Technology Acceptance Model (TAM). Educational Technology and Society, 11(4), 265-280.
Teo, A. C., Tan, G. W. H., Ooi, K. B., Hew, T. S. & Yew, K. T. (2015). The effects of convenience and speed in m-payment. Industrial Management and Data Systems, 115(2), 311-331. Venkatesh, V. & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence and their role in technology acceptance and usage behavior. Management Information Systems Quarterly, 24(1), 115-139.
Wang, H. M. &Idertsog, B. (2015). A study on user’s intention of using mobile payments. International Journal of Sciences: Basic and Applied Research, 24(6), 433-449.
Wang, Y. S., Wang, Y. M., Lin, H. H. & Tang, T. I. (2003). Determinants of user acceptance of Internet banking: an empirical study. International Journal of Service Industry Management, 14(5), 501-519.
Yousafzai, S., Pallister, J. &Foxall, G. (2009). Multi-dimensional role of trust in Internet banking adoption. Journal of the Service Industries, 29(5), 591-605.
Yu, C. S. (2012). Factors affecting individuals to adopt mobile banking: empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2), 104-121.
Zhong, J. (2009). A comparison of mobile payment procedures in Finnish and Chinese markets. 22nd BLED e-conference e-enablement: facilitating an open, effective and representative e-society.
Accenture. (2014). Driving the adoption of mobile payments-what SA consumers want. [Online] Available at: http// www.cas-ag.eu/SiteCollectionDocuments/Local_South_Africa/pdf/Accenture-Driving-Adoption-for-Mobile-Payments-What-do-consumers-South-Africa-want.pdf. Accessed 18/08/2014.
Ajzen, I. (1989). Attitude Structure and Behaviour. In Pratkanis, A.R., Beckler, S.J. & Greenwald A.G. (Eds.), Attitude Structure and Function (pp. 241-274),Hillsdale, NJ: Erlbaum. Armstrong, J. S. & Overton, T. S. (1977). Estimating non-response bias in mail surveys. Journal of Marketing Research, 14(3), 396-402.
Cernev, A. K. (2010). Mobile banking in Brazil: critical events, trajectory and expected scenarios. PhD thesis, Sao Paulo: Getulio Vargas Foundation. 378 p. [Online] Available at: http://bibliotecadigital.fgv.br/dspace/handle/10438/ 8167. Accessed 16/02/2016.
Chin, W. W. (1998). Issues and opinion on structural equation modelling. Management Information Systems Quarterly, 22(1), 7-16.
Choi, J., Lee, A. & Ok, C. (2014). The effects of consumer perceived risk and benefit on attitude and behavioural intention: a study of street food. Journal of Travel and Tourism, 30(1), 222-237.
Churchill, G. A., Brown, T. J. &Suter, T. A. (2010). Basic marketing research, (7thed), Canada: South Western, Cengage Learning.
Dahlberg, T., Mallat, N., Ondrus, J. & Zmijewska, A. (2008). Past, present and future of mobile payments research: a literature review. Journal ofElectronic Commerce Research and Applications, 7(2), 165-181.
Davis, F. D., Bagozzi, R. P. &Warshaw, P. R. (1989). User acceptance of computer technology: comparisons of two theoretical models. Journal of Management Science, 35(8), 982-1003.
Diniz, E. H., Cernev, A. K. & Albuquerque, J. P. D. (2011). Mobile money and payment: a literature review based on academic and practitioner-oriented publications (2001–2011). In Proceedings of the 4th Annual Workshop ICT in Global Development - Workshop of the International Conference on Information Systems ICIS 2011, Shangai (pp. 1-35).
Dlodlo, N. (2015). The use of m-payment services in South Africa: a value based perception approach. International Business and Economics Research Journal, 14(1), 159-178.
Donner, J. & Tellez, C. A. (2008). Mobile banking and economic development: linking adoption, impact and use. Asian Journal of Communication, 18(4), 318-322.
Duane, A., O'Reilly, P. & Andreev, P. (2014). Realising m-payments: modelling consumers' willingness to m-pay using smart phones. Behaviour and Information Technology, 33(4), 318-334. Erasmus, E., Rothmann, S. & Van Eeden, C. (2015). A structural model of technology acceptance. South African Journal of Industrial Psychology, 41(1), 1-12.
Field, A. (2009). Discovering Statistics Using SPSS, (3rd ed.), London: Sage.
Fishbein, M. &Ajzen, I. (1975). Belief, Attitude, Intention and Behaviour: an Introduction to Theory and Research, Reading, MA: Addison-Wesley.
Fishbein, M. (1963). An investigation of the relationships between beliefs about an object and the attitude toward that object. Human Relations, 16(3), 233-240.
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gartner Group. (2012). Forecast: Mobile payment, worldwide, 2009-2016, [Online] Available at: http://www.gartner.com/resId¼2010515. Accessed 15/05/2016.
Ghezzi, A., Renga, F., Balocco, R. &Pescetto, P. (2010). Mobile payment applications: offer state of the art in the Italian market. Information, 12(5), 3-22.
Grubb, L. (2012). How ready is Africa for mobile payments? [Online] Available at: http://www.technologybanker.com/news-analysis/how-ready-is-africa-for-mobile-payments.U8kyuvmSw1y. Accessed 18/07/ 2016. Hair, J. F., Ringle, C. M. & Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, 18(2), 139-152. Henseler, J., Ringle, C. M. & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of Marketing Science, 43(1), 115-135. Höck, M. & Ringle, C. M. (2010). Local strategic networks in the software industry: An empirical analysis of the value continuum. International Journal of Knowledge and Management Studies, 4(1), 132-151.
Howard, J. & Sheth, J. (1969). Thetheoryofbuyerbehaviour, New York: John Wiley.
Hsiao, W. H. & Chang, T. S. (2013). Understanding consumers’ continuance intention towards mobile advertising: a theoretical framework and empirical study. Journal of Behavioural Information technology, 33(7), 730-742.
Jeong, B. & Yoon, T. E. (2013). An empirical investigation on consumer acceptance of mobile banking services. Journal of Business Management Research, 2(1), 31-40.
Kim, Y. J., Chun, J., U. & Song, J. (2009). Investigating the role of attitude in technology acceptance from an attitude strength perspective. International Journal of Information Management, 29, 67-77.
Kim, C., Mirusmonov, M. & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behaviour, 26(3), 310-322.
Leong, L. Y., Hew, T. S., Tan, G. W. H. & Ooi, K. B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: a neural networks approach. Expert Systems with Applications, 40(2013), 5604-5620.
Liébana-Cabanillas, F., Sanchez-Fernandez, J. & Munoz-Leiva, F. (2014). Role of gender on acceptance of mobile payment. Journal of Industrial Management and Data Systems, 114(2), 220-240.
Lin, H. F. (2011). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. InternationalJournal of Information Management, 31(1), 252-260.
Liu, J., Kauffman, R. J. & Ma, D. (2015). Competition, cooperation, and regulation: understanding the evolution of the mobile payments technology ecosystem. Journal ofElectronic Commerce Research and Applications, 14(5), 372-391.
Lohmöller, J. B. (1989). Latent Variable Path Modeling With Partial Least Squares, Heidelberg: Physica-Verlag.
Malhotra, N. K. (2010). Marketing research: an applied orientation, (6th ed.), New Jersey: Prentice- Hall.
Malhotra, N. K. & Mccort, J. D. (2001). A cross-cultural comparison of behavioural intentions models. International Marketing Review, 18(3), 235-269.
Mallat, N. (2007). Exploring consumer adoption of mobile payments: a qualitative study. The Journal of Strategic Information Systems, 16(4), 413-432. McKechnie, S., Winklhofer, H. & Ennew, C. (2006). Applying the technology acceptance model to the online retailing of financial services. International Journal of Retail and Distribution Management, 34(4/5), 388-410.
Meharia, P. (2012). Assurance on the reliability of mobile payment system and its effects on it’s’ use: an empirical examination. Journal of Accounting and Management Information System, 11(1), 97-111.
Miltgen, C. L., Popovic, A. & Oliveira, T. (2013). Determinants of end-user acceptance of biometrics: integrating the Big 3 of technology acceptance with privacy context. Decision Support Systems, 56, 103-114.
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 Behaviour, 61(2016), 404-414.
Ondrus, J. & Pigneur, Y. (2007). Towards a holistic analysis of mobile payments: a multiple perspective approach. Journal ofElectronic Commerce Research and Applications, 5(3), 246-257.
O'Reilly, P., Duane, A. & Andreev, P. (2012). To m-pay or not to m-pay? Realising the potential of smart phones: conceptual modeling and empirical validation. Electronic Markets, 22(4), 229-241.
Overbr. (2014). MÃdiaCorporativa. São Paulo: Ãndice Global de PagamentosMóve is. [Online] Available at: http://overbr.com.br/midia-corporativa/indice-global-de-pagamentos-move. Accessed 5/01/2017.
Pallant, J. (2010). SPSS Survival Manual: a Step-By-Step Guide to Data Analysis Using SPSS for Windows, Buckingham: Open University Press.
Pham, T. T. T. & Ho, J. C. (2015). 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.
Rao, S. & Troshani, I. A. (2007). Conceptual framework and propositions for the acceptance of mobile services. Journal of Theoretical and Applied Electronic Commerce Research, 2(2), 61-73.
Revels, J., Tojib, D. & Tsarenko, Y. (2010). Understanding consumer intention to use mobile services. Journal of Australasian Marketing, 18, 74-80.
Schierz, P. G., Schilke, O. &Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services. Journal of Electronic Commerce Research and Applications, 9(1), 209-216.
Schiffman, L. G. Kanuk, L. L. &Wisenblit, J. (2010). Consumer behaviour, (10th ed.), New Jersey: Prentice-Hall.
Slade, E., Williams, M., Dwivedi, Y. & Piercy, N. (2014). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 1-15.
Solomon, M., Bamossy, G., Askegaard, S. & Hogg, M. K. (2006). Consumer Behaviour: a European Perspective, (3rd ed.), Edinburg: Prentice-Hall.
Statistica Corporation. (2015). Mobile payment transaction volume 2010-2017. The Statistics Portal. Available at: http://www.statista.com/statistics/226530/mobile-paymenttransaction-volume-forecast/. Accessed 01/09/16.
Tan, G., Ooi, K. B, Chong, S. C. & Hew, T. S. (2014). NFC mobile credit card: the next frontier of mobile payment? Telematics and Informatics, 31(2), 292-307. Teo, T., Luan, W. S. & Sing, C. C. (2008). A cross-cultural examination of the intention to use technology between Singaporean and Malaysian pre-service teachers: an application of the Technology Acceptance Model (TAM). Educational Technology and Society, 11(4), 265-280.
Teo, A. C., Tan, G. W. H., Ooi, K. B., Hew, T. S. & Yew, K. T. (2015). The effects of convenience and speed in m-payment. Industrial Management and Data Systems, 115(2), 311-331. Venkatesh, V. & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence and their role in technology acceptance and usage behavior. Management Information Systems Quarterly, 24(1), 115-139.
Wang, H. M. &Idertsog, B. (2015). A study on user’s intention of using mobile payments. International Journal of Sciences: Basic and Applied Research, 24(6), 433-449.
Wang, Y. S., Wang, Y. M., Lin, H. H. & Tang, T. I. (2003). Determinants of user acceptance of Internet banking: an empirical study. International Journal of Service Industry Management, 14(5), 501-519.
Yousafzai, S., Pallister, J. &Foxall, G. (2009). Multi-dimensional role of trust in Internet banking adoption. Journal of the Service Industries, 29(5), 591-605.
Yu, C. S. (2012). Factors affecting individuals to adopt mobile banking: empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2), 104-121.
Zhong, J. (2009). A comparison of mobile payment procedures in Finnish and Chinese markets. 22nd BLED e-conference e-enablement: facilitating an open, effective and representative e-society.
Published
2017-05-18
How to Cite
N., D. (2017). Re-Thinking a Structural Model for M-Phone Paying among South African Consumers. Journal of Economics and Behavioral Studies, 9(2(J), 114-130. https://doi.org/10.22610/jebs.v9i2(J).1655
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