A STUDY ON FACTORS INFLUENCING ADOPTION OF MOBILE BANKING IN

SINGAPORE

The Researchers - Group 15

Devkant Shacksaria

A.V. Nagarjun

Parul Oberai

AgendaIntroductionResearch ModelData CollectionAnalysisImplicationsLimitations & Future Research

Interesting Statistics

200 m to 1.1 b

Global M-

banking

users

5 billion Mobil

e phone users

Singapore Statistics 2011March April May June

Mobile populationpenetration rate

145.5%

146.1%

147.1%

148.5%

W/l broadband penetration rate

136.4%

138.3%

140.2%

142.4%

Source: http://mobithinking.com/mobile-marketing-tools/latest-mobile-stats#mobilemoneyhttp://www.ida.gov.sg/Publications/20110209152802.aspx

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 20150

20

40

60

80

100

120

140

160151.8

123.3116.0

DevelopedWorldDeveloping

Per 1

00 in

habi

tant

s

The developed/developing country classifications are based on the UN M49, see: http://www.itu.int/ITU-D/ict/definitions/regions/index.htmlSource: ITU World Telecommunication /ICT Indicators database

Mobile cellular subscriptions per 100 inhabitants, 2000-2010

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 20150

10

20

30

40

50

60

70

80

90

10092.2

53.144.0

Internet users per 100 inhabitants, 2000-2010

DevelopedWorldDeveloping

Per 1

00 in

habi

tant

s

The developed/developing country classifications are based on the UN M49, see: http://www.itu.int/ITU-D/ict/definitions/regions/index.htmlSource: ITU World Telecommunication /ICT Indicators database

Challenges• Handset Operability• Security• Scalability and Reliability• Application Distribution• Personalization

Benefits• Reduces operating cost• Saves time• Reduces Risk• Generates additional

revenue• Customer retention• Growth for service

providers

Name of the Research Paper

Place

Factors Considered

FrameworkRA

CX

CM

OB

TR

PR

SE

PFC

PU

PE

PC

FC

AL

IRPSC

CS

INPB

DM

SU

DB

SN

LI

Predicting consumer

intention to use mobile service.

Taiwan X X X X XExtended

TAM

M-banking in metropolitan

Bangkok and a comparison with other countries.

Bangkok X X X X X X X XExtended

TAM

Toward an understanding of the behavioural intention to use mobile banking

Taiwan X X X X XExtended

TAM

Factors affecting the adoption of

mobile commerce in Singapore

Singapore X X X X X TAM

The moderating effect of gender in

the adoption of mobile banking

Singapore X X X X X TAM

A study on Factors

influencing Adoption of

Mobile banking in Singapore

Singapore X X X X XExtended

TAM

Adopted Framework

Behavioural Intention

Perceived

Usefulness

Perceived Ease of Use

Perceived

Credibility Self

Efficacy

Perceived

Financial Cost

Technology Adoption

Model (TAM)

Theory of Planned

Behaviour (TPB)

Extended TAM

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.

Likert scale

165 RESULTS

Online survey

Pilot studyTotal 18

questions

Female32%

Male68%

Gender

68% MALE 32% FEMALE

18 - 25 25 - 35 35 - 50 Above 50

020406080

100120

Age group

Descriptive Statistics

80% < 35yrs & 20% > 35 yrs

M – Banking Usage

14%

21%

41%

25%

Very Often

Often

At times

RarelyA/c Balance

Investment management

Bill Payments

Notifications

0 50 100 150

Overall Analysis

Behavioural Intention

Perceived Usefulness(p – 0.000)

Perceived Ease of Use

(p – 0.0804)

Perceived Credibility

(p - 0.0453) Self Efficacy

(p – 0.0158)

Perceived Financial

Cost(p –

0.1152)

Analysis for Adopters of M-Banking

Behavioural Intention

Perceived Usefulnes

s(p –

0.000)

Perceived Ease of

Use(p –

0.0066)

Analysis for Non-Adopters of M-Banking

Behavioural Intention

Perceived Usefulness(p – 0.000)

Self Efficacy

(p – 0.0332)

Implications for Overall Group

Behavioral Intention

Perceived usefulness

Self Efficacy

Perceived Ease of Use

Perceived Credibility

Trust Factor, Simple

Traceability System, Handset

Manufacturers & Banks Should

Collaborate

Implications for Adopters

Behavioral Intention

Perceived Usefulness

Perceived Ease of Use

Speed, SMS Banking,

Accessibility, Band Width

Bigger Screen size, Easy

texting Mechanism, Convenient

Keypad, Handset Makers &

Banks should collaborate

Implications for Non-Adopters

Behavioral Intention

Perceived usefulness

Self Efficacy

Speed, SMS Banking,

Accessibility, Band Width

Initiate Awareness

camps, More advertisemen

ts,

Limitations & Future ResearchContemporary FrameworkInter-relation between FactorsRe-validate at Regular Intervals

THANK YOU…

Multiple Regression results

Regression Analysis of all respondents

Hypothesis Independent variable r-path coefficient t-value p-value

H1 Perceived Usefulness 0.6291 8.7668 0

H2 Perceived Ease of use 0.1497 1.7599 0.0804

H3 Perceived Credibility 0.1879 2.0181 0.0453

H4 Self-Efficacy 0.1788 2.4385 0.0158

H5 Perceived Financial cost 0.1 1.5841 0.1152

Regression analysis for mobile banking users

Hypothesis Independent variable r-path coefficient t-value p-value

H1 Perceived Usefulness 0.6205 2.7835 0

H2 Perceived Ease of use 0.2835 7.045 0.0066

H3 Perceived Credibility 0.1755 1.5468 0.1254

H4 Self-Efficacy 0.1075 1.0707 0.2872

H5 Perceived Financial cost 0.0598 0.6948 0.4889

Regression analysis for non-mobile banking users

Hypothesis Independent variable r-path

coefficient

t-value p-value

H1 Perceived Usefulness 0.6330 4.8856 0.0000

H2 Perceived Ease of use -0.1058 -0.7341 0.4656

H3 Perceived Credibility 0.2064 1.3458 0.1832

H4 Self-Efficacy 0.2375 2.1769 0.0332

H5 Perceived Financial cost 0.1013 1.0900 0.2799

T-test resultsIndependent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means

F Sig. TSig. (2-tailed)

Mean Difference

PFC Equal variances assumed

0.733 0.393

 

0.765 -0.03829-0.299

PU Equal variances assumed

0.401 0.528

 

0.217 -0.13358-1.238

PE Equal variances assumed

0.057 0.812

 

0.051 -0.17527

 

-1.966SE Equal variances

assumed0.009 0.926

 

0.368 -0.10764-0.903

PC Equal variances assumed

0.321 0.572

 

0.168 -0.11113-1.385

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.