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A STUDY ON FACTORS INFLUENCING ADOPTION OF MOBILE BANKING IN SINGAPORE The Researchers - Group 15 Devkant Shacksaria A.V.  Nagarjun Parul Oberai
Agenda Introduction Research Model Data Collection Analysis Implications Limitations & Future Research
Interesting Statistics Source:  http://mobithinking.com/mobile-marketing-tools/latest-mobile-stats#mobilemoney http://www.ida.gov.sg/Publications/20110209152802.aspx
AdoptedFramework
Perceived Usefulness Degree to which a person believes that using mobile banking would enhance his job performance. H1: Perceived Usefulness has  positive effect on the behavioural intention to adopt mobile banking.
Perceived Ease of Use The degree to which a person believes that using a particular system would be free from effort. H2: Perceived ease of use has the positive effect on the behavioural intention to adopt mobile banking.
Perceived Credibility The extent to which a person believes that using mobile banking will be free of security and privacy threats. H3: Perceived Credibility has the positive effect on the behavioural intention to adopt mobile banking.
Self Efficacy The judgement of one’s ability to use mobile service. H4: Self efficacy has the positive effect on the behavioural intention to adopt mobile banking.
Perceived Financial cost The extent to which a person believes that he has the financial resources needed to use mobile banking. H5: Perceived financial cost has the negative effect on the behavioural intention to adopt mobile banking.
Online survey Likert scale Total 18 questions Pilot study 165 RESULTS
Descriptive Statistics 80% < 35yrs &  20% > 35 yrs 68% MALE   32% FEMALE
M – Banking Usage
Overall Analysis
Analysis for Adopters of M-Banking
Analysis for Non-Adopters of M-Banking
Implications for Overall Group Trust Factor, Simple Traceability System, Handset Manufacturers & Banks Should Collaborate
Implications for Adopters Speed, SMS Banking, Accessibility, Band Width Bigger Screen size, Easy texting Mechanism, Convenient Keypad, Handset Makers & Banks should collaborate
Implications for Non-Adopters Speed, SMS Banking, Accessibility, Band Width Initiate Awareness camps, More advertisements,
Limitations & Future Research Contemporary Framework Inter-relation between Factors Re-validate at Regular Intervals
THANK YOU…
Multiple Regression results
T-test results
References Central Intelligence Agency (2011) The World Factbook, [online] Available at: https://www.cia.gov/library/publications/the-world-factbook/rankorder/2151rank.html [Accessed: 10th July 2011]. Marketing Charts (2011) Mobile Banking, [online] Available at: http://www.marketingcharts.com/direct/mobile-banking-grows-in-popularity-15102/nielsen-mobile-banking-household-nov-2010jpg/ [Accessed: 10th July 2011]. Berg Insight (2011) Mobile money users in emerging markets, [online] Available at: http://www.berginsight.com/News.aspx?m_m=6&amp;s_m=1 [Accessed: 10th July 2011]. PR Web (2010) Global Mobile Banking Customer Base to Reach 1.1 Billion by 2015, According to New Report by Global Industry Analysts, Inc., [online] Available at: http://www.prweb.com/releases/2010/02/prweb3553494.htm [Accessed: 10th July 2011]. Mattila, M. (2002) Factors Affecting The Adoption Of Mobile Banking Services, Journal of Internet Banking and Commerce, 7(3). Vatanprast, R. and Z. Qadim, H. (2009) A Cross-Cultural Study on Mobile Internet Usage, International Journal of Mobile Marketing, 4(2), p.14-17. Bhatti, T. (2007) Exploring Factors Influencing Adoption of Mobile Commerce, Journal of Internet Banking and Commerce, 12(3).
Wang, Y. et al. (2006) Predicting consumer intention to use mobile service, Information Systems Journal, 6(2), p.157-179. Cheong, J.H. & Park, M.-C., 2008. Mobile Payment Adoption in Korea: Switching from Credit Card. In 15th International Telecommunication SocietyEurope Regional Conference. pp. 1-22. Sripalawat, J. et al. (2011) M-Banking in Metropolitan Bangkok and a comparison with other countries, Computer Information Systems, 51(3), p.67-76. Yu, S. (2009) Factor influencing the use of Mobile Banking: The case of SMS-based Mobile Banking, Computing and Mathematical Sciences, p.33-66. Crabbe, M. et al. (2009) An adoption model for mobile banking in Ghana, International Journal of Mobile Communications, 7(5), p.515-541. Wu, J. and Wang, S. (2005) What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model, Information and Management, 42(5), p.719-729. C. C. Yang, K. (2005) Exploring factors affecting the adoption of mobile commerce in Singapore, Telematics and Informatics, 22(1), p.257-277. Laurn, P. and Lin, H. (2005) Towards an understanding of the behavioral intention to use mobile banking, Computers in Human Behavior, 21(6), p.873-891.
Mobile Life - Global Telecom Insights (2011) MOBILE BANKING SURGES AS EMERGING MARKETS EMBRACE MOBILE FINANCE, [online] Available at: http://discovermobilelife.com/wpcontent/uploads/2011/05/Mobile_Finance_Press_Release.pdf [Accessed: 17th Sep 2011]. Riquelme, H. and Rios, R. (2010) The moderating effect of gender in the adoption of mobile banking, Internaitonal Journal of Bank, 28(5), p.328-341. Ajzen, I. (1991) The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50(2), p.179-211. Ajzen, I. (1986) Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control, Journal of Experimental Social Psychology, 22(5), p.453-474. Gefen, D. (2003) Trust and TAM in online shopping: An integrated model, MIS Quarterly,27(1), p.51-90. Laukkanen, T. (2007) Internet vs mobile banking: comparing customer value perceptions, Business Process Management Journal, 13(6), p.788-797. Pederson, P. (2005) Adoption of Mobile Internet Services: An Exploratory Study of Mobile Commerce Early Adopters, JOURNAL OF ORGANIZATIONAL COMPUTING AND ELECTRONIC COMMERCE, 15(2), p.203-222.

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Factors Influencing Adoption of Mobile Banking in Singapore

  • 1.
  • 2. A STUDY ON FACTORS INFLUENCING ADOPTION OF MOBILE BANKING IN SINGAPORE The Researchers - Group 15 Devkant Shacksaria A.V. Nagarjun Parul Oberai
  • 3. Agenda Introduction Research Model Data Collection Analysis Implications Limitations & Future Research
  • 4. Interesting Statistics Source: http://mobithinking.com/mobile-marketing-tools/latest-mobile-stats#mobilemoney http://www.ida.gov.sg/Publications/20110209152802.aspx
  • 5.
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  • 7.
  • 9.
  • 10. Perceived Usefulness Degree to which a person believes that using mobile banking would enhance his job performance. H1: Perceived Usefulness has positive effect on the behavioural intention to adopt mobile banking.
  • 11. Perceived Ease of Use The degree to which a person believes that using a particular system would be free from effort. H2: Perceived ease of use has the positive effect on the behavioural intention to adopt mobile banking.
  • 12. Perceived Credibility The extent to which a person believes that using mobile banking will be free of security and privacy threats. H3: Perceived Credibility has the positive effect on the behavioural intention to adopt mobile banking.
  • 13. Self Efficacy The judgement of one’s ability to use mobile service. H4: Self efficacy has the positive effect on the behavioural intention to adopt mobile banking.
  • 14. Perceived Financial cost The extent to which a person believes that he has the financial resources needed to use mobile banking. H5: Perceived financial cost has the negative effect on the behavioural intention to adopt mobile banking.
  • 15. Online survey Likert scale Total 18 questions Pilot study 165 RESULTS
  • 16. Descriptive Statistics 80% < 35yrs & 20% > 35 yrs 68% MALE 32% FEMALE
  • 17. M – Banking Usage
  • 19. Analysis for Adopters of M-Banking
  • 21. Implications for Overall Group Trust Factor, Simple Traceability System, Handset Manufacturers & Banks Should Collaborate
  • 22. Implications for Adopters Speed, SMS Banking, Accessibility, Band Width Bigger Screen size, Easy texting Mechanism, Convenient Keypad, Handset Makers & Banks should collaborate
  • 23. Implications for Non-Adopters Speed, SMS Banking, Accessibility, Band Width Initiate Awareness camps, More advertisements,
  • 24. Limitations & Future Research Contemporary Framework Inter-relation between Factors Re-validate at Regular Intervals
  • 26.
  • 28.
  • 29.
  • 31. References Central Intelligence Agency (2011) The World Factbook, [online] Available at: https://www.cia.gov/library/publications/the-world-factbook/rankorder/2151rank.html [Accessed: 10th July 2011]. Marketing Charts (2011) Mobile Banking, [online] Available at: http://www.marketingcharts.com/direct/mobile-banking-grows-in-popularity-15102/nielsen-mobile-banking-household-nov-2010jpg/ [Accessed: 10th July 2011]. Berg Insight (2011) Mobile money users in emerging markets, [online] Available at: http://www.berginsight.com/News.aspx?m_m=6&amp;s_m=1 [Accessed: 10th July 2011]. PR Web (2010) Global Mobile Banking Customer Base to Reach 1.1 Billion by 2015, According to New Report by Global Industry Analysts, Inc., [online] Available at: http://www.prweb.com/releases/2010/02/prweb3553494.htm [Accessed: 10th July 2011]. Mattila, M. (2002) Factors Affecting The Adoption Of Mobile Banking Services, Journal of Internet Banking and Commerce, 7(3). Vatanprast, R. and Z. Qadim, H. (2009) A Cross-Cultural Study on Mobile Internet Usage, International Journal of Mobile Marketing, 4(2), p.14-17. Bhatti, T. (2007) Exploring Factors Influencing Adoption of Mobile Commerce, Journal of Internet Banking and Commerce, 12(3).
  • 32. Wang, Y. et al. (2006) Predicting consumer intention to use mobile service, Information Systems Journal, 6(2), p.157-179. Cheong, J.H. & Park, M.-C., 2008. Mobile Payment Adoption in Korea: Switching from Credit Card. In 15th International Telecommunication SocietyEurope Regional Conference. pp. 1-22. Sripalawat, J. et al. (2011) M-Banking in Metropolitan Bangkok and a comparison with other countries, Computer Information Systems, 51(3), p.67-76. Yu, S. (2009) Factor influencing the use of Mobile Banking: The case of SMS-based Mobile Banking, Computing and Mathematical Sciences, p.33-66. Crabbe, M. et al. (2009) An adoption model for mobile banking in Ghana, International Journal of Mobile Communications, 7(5), p.515-541. Wu, J. and Wang, S. (2005) What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model, Information and Management, 42(5), p.719-729. C. C. Yang, K. (2005) Exploring factors affecting the adoption of mobile commerce in Singapore, Telematics and Informatics, 22(1), p.257-277. Laurn, P. and Lin, H. (2005) Towards an understanding of the behavioral intention to use mobile banking, Computers in Human Behavior, 21(6), p.873-891.
  • 33. Mobile Life - Global Telecom Insights (2011) MOBILE BANKING SURGES AS EMERGING MARKETS EMBRACE MOBILE FINANCE, [online] Available at: http://discovermobilelife.com/wpcontent/uploads/2011/05/Mobile_Finance_Press_Release.pdf [Accessed: 17th Sep 2011]. Riquelme, H. and Rios, R. (2010) The moderating effect of gender in the adoption of mobile banking, Internaitonal Journal of Bank, 28(5), p.328-341. Ajzen, I. (1991) The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50(2), p.179-211. Ajzen, I. (1986) Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control, Journal of Experimental Social Psychology, 22(5), p.453-474. Gefen, D. (2003) Trust and TAM in online shopping: An integrated model, MIS Quarterly,27(1), p.51-90. Laukkanen, T. (2007) Internet vs mobile banking: comparing customer value perceptions, Business Process Management Journal, 13(6), p.788-797. Pederson, P. (2005) Adoption of Mobile Internet Services: An Exploratory Study of Mobile Commerce Early Adopters, JOURNAL OF ORGANIZATIONAL COMPUTING AND ELECTRONIC COMMERCE, 15(2), p.203-222.