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THE EFFECTS OF INNOVATION CHARACTERISTICS ON MOBILE BANKING
ADOPTION
ULUN AKTURAN
Asst.Prof.Dr.
Galatasaray University
Faculty of Economics and Administrative Sciences
Ciragan Cad. No: 36
Ortakoy/ISTANBUL
Phone: 00 90 532 374 77 45, Fax: 00 90 212 258 22 83
E-mail: uakturan@yahoo.com
NURAY TEZCAN
Asst.Prof.Dr.
Halic University
Faculty of Management
Emekyemez Mah. Okçu Musa Cad.
Mektep Sok. No: 21
Sishane/İSTANBUL
Phone: 00 90 532 700 81 46 , Fax: 00 90 212 297 31 44
E-mail: tezcan_nuray@yahoo.com
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THE EFFECTS OF INNOVATION CHARACTERISTICS ON MOBILE BANKING
ADOPTION
Asst.Prof.Dr. Ulun Akturan, Galatasaray University, Turkey
Asst.Prof.Dr. Nuray Tezcan, Halic University, Turkey
ABSTRACT
This study aims to determine the effect of innovation characteristics on mobile
banking adoption intention. In the study, the eight characteristics of innovation- relative
advantage, compatibility, complexity, image, result demonstrability, visibility, trialability, and
voluntariness- are portrayed and their combined effect on adoption intention was searched.
The data was collected from 311 college students- who are described as young prospects- and
the research hypothesis tested by SEM. The results provide support for the theoretical
relationship between the relative advantage and compatibility, and mobile banking adoption.
However, no relationship was found between image, result demonstrability, complexity,
trialability, and adoption intention.
INTRODUCTION
The business of banking has changed by the developments in technology. The
increasing use of information technologies enabled banking applications to be transformed to
electronic and even mobile devices. Electronic banking has become very successful as a retail
distribution channel for banks. Since the introduction of e-banking service in 1995, the
number of consumers using e-banking has grown steadily. Gan et al. (2006) predicted that ebanking is necessary for banks to stay profitable in the future.
Today, mobile banking is emerging as a new channel. The innovations in
telecommunications have led the use of mobile devices in banking services (Suoranta and
Mattila, 2004). Mobile banking is defined as the “a type of execution of financial services in
the course of which- within an electronic procedure- the consumer uses mobile
communication techniques in conjunction with mobile devices” (Pousttchi and Schurig, 2004:
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1). With their cell phone, consumers can access their accounts and check account balances,
pay bills, and perform other banking transactions (Brown et al., 2003). Mobile banking is an
important application of mobile commerce since it is an additional source of revenue to both
banks and telecom services.
In 2000s, mobile banking has been described as the most important distribution
channel for retail banking. However, the adoption of mobile banking has not been as rapid as
the new mobile devices. This slow start is partly resulted from the poor technology of the
mobile handsets. But the new generation of mobile phones and the reduced costs accelerated
its usage (Riivari, 2005). Therefore it is still growing and there are opportunities for mobile
banking applications to expand. The worldwide number of users of mobile banking and
related services is forecasted to grow from 55 million users in 2009 to reach 894 million users
in 2015 (Berg Insight, 2010: Mobile Banking and Payments Report).
Mobile banking services represent an innovation as an intangible service and a medium of
service delivery employing high technology (Suoranta and Mattila, 2004). Since it is an
innovative application, it is important to understand the perception of mobile banking as
innovation. Besides in the literature it was revealed that the perception of innovation
characteristics has an important influence on acceptance behavior (Agarwal and Prasad, 1997;
Van Slyke et al., 2002; Moore and Benbasat, 1991).
In the literature, the mobile banking usage intention was explained in relation with the
TAM (Technology Acceptance Model) (Luarn and Lin, 2005), and trust and firm reputation
(Kim et al., 2009). Brown et al. (2003) investigated the effects of some of the innovation
characteristics (relative advantage, perceived compatibility, perceived complexity and
trialability), along with experience, perceived risk, banking needs and self efficacy on the
usage intention.
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This study aims is to determine the perceived characteristics of innovation (PCI) of
mobile banking applications and its effect on the adoption intention. In the study, the
combined effect of PCI was searched
Mobile Banking Applications
M-commerce
embodies
business
transactions
conducted
thorough
mobile
communication networks or the internet (Kim et al., 2009). The distinctive values of mcommerce are convenience, ubiquity, flexibility and contextuality (Lee and Benbasat, 2003;
Venkatesh et al., 2003). Mobile banking enables customers to execute conventional and more
advanced financial transactions and provide the wireless and mobile values of m-commerce.
In order to use the service, a cell phone equipped with a built-in chipset or WAP (Wireless
Access Protocol) and an activation of the banking service is needed.
There are customer requirements to mobile banking applications that the banks should
pay attention. These are grouped under four categories as technical, usability, design and
security requirements (Pousttchi and Schurig, 2004: 3-4): As technically; the usage should be
possible with both kinds of available mobile devices. The application should adapt to the
conditions of the mobile device automatically. The usage must be possible for customers of
any MNO. And the amount of transmitted data should be s small as possible. For the
usability; it must be possible to work offline with the application. There should be a
simplified method of data input. The application should allow the user to resume his usage
and the information should be available with just a few “clicks”.
For the design; the
application should be personalized. The user should easily switch to a version of the
application a wider range of functions. The application should provide push functionality.
There should be a wide range of functionality, similar to the one in the electronic banking. For
the security; the transmission of the data has to be encrypted. Before usage, access to the data
must be authorized and the authorization has to be simple.
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Mobile banking application creates value not only for the customers but also for the
banks. Mobile banking improves customer services, reduces costs, increase the reactivity of
the company, increase market share and reinforce brand image (Riivari, 2005).
Innovation Characteristics
Innovation has been described as “an idea, material, or artifact perceived to be new by
the relevant unit of adoption” (Agarwal and Prasad, 1997: 560). Innovation exists to the
extent that the potential adopter finds it new or unlike any other products (Garcia and
Calantone, 2002). Some innovations perceived as minor while some are perceived as great.
The characteristics of an innovation influence the consumer’s impression of the product.
Diffusion is “the process by which an innovation is communicated through certain
channels over time among the members of a social system (Rogers, 1995: 5). The
characteristics of an innovation affect the likelihood and speed of purchase (Holak and
Lehmann, 1990). Rogers (1995: 15-16) defined five major innovation characteristics:
 Relative advantage, “is the degree to which an innovation is perceived as better
than the idea it supersedes. The greater the perceived relative advantage, the
more rapid its rate of adoption will be”.
 Compatibility, is the degree to which an innovation is perceived as being
consistent with the existing values, past experiences, and needs of potential
adopter. The adoption of an incompatible innovation requires the prior
adoption of a new value system which is a relatively slow process”.
 Complexity, is the degree to which an innovation is perceived as difficult to
understand and use. The innovations that are simpler to understand are
adopted more rapidly than the innovations that require the adopter to develop
new skills and understandings.
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 Trialability, is the degree to which an innovation may be experimented with on
a limited basis. An innovation that is trialable represents less uncertainty to the
adopter”.
 Observability, “is the degree to which the results of an innovation are visible to
others. The innovations that are relatively less observable diffuse more
slowly”.
Moore and Benbasat (1991: 195-203) identified three additional characteristics as:
 Image, “the degree to which use of an innovation is perceived to enhance one’s image
or status in one’s special system. The desire to gain social status is an important
motivation for someone to adopt an innovation”.
 Voluntariness of use, “the degree to which use of an innovation is perceived as being
voluntary or of free will. When an innovation is mandatory, the freedom of choice of
adoption. The behavior is influenced by the perception of voluntariness much more
than the actual voluntariness”.
 Result demonstrability, “the tangible of the results of using an innovation. The greater
the perceived result demonstrability, the more rapid its rate of adoption will be”.
RESEARCH METHODOLOGY
Research Model
The research model of the study derived from the literature is given in Figure 1. Consistent
with the theory, the model embodies eight PCI instruments and adoption intention of mobile
banking. The main research hypothesis is stated as below:
H1: The perceived characteristics of innovation in relation with mobile banking influence the
adoption intention.
<Figure 1>
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Measures and Data Collection
The questionnaire was formed as including multi- item measures of the perceived
characteristics of innovation and adoption intention. All the scales were five-point Likert type
scales. To measure perceived characteristics of innovation PCI scale adapted by Gounaris and
Koritos (2008) and to measure adoption intention the scale developed by Kim et al. (2007)
were used. Gounaris and Koritos (2008) adapted the PCI scale developed by Moore and
Benbasat (1991) to the internet banking. The scales are given in the Appendix.
The data used in the research was collected by face-to-face interviews. The subjects in
this study are undergraduate and graduate students. The sample exhibits the characteristics of
being a potential customer of mobile banking. Moreover, earlier adopters of technological
innovations are often described as being relatively young, better educated, having higher
income and having higher occupations (Suoranta and Mattila 2003). Therefore the sample
consisted of future prospects for the mobile banking. Besides, the subjects in the sample were
the non-user of the mobile banking applications. The soci-demographics of the sample is
given in Table 1.
<Table 1>
RESEARCH FINDINGS
In the study, to test the research hypothesis Structural Equation Modeling (SEM) was
used. Before testing the hypothesis, because multi-item scales were used, reliability and
validity analysis were executed. Table 2 displays the results of the validity and reliability
analysis. To assure validity exploratory factor analysis was run, and to assure reliability
Cronbach’s Alpha was used.
<Table 2>
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As a result of the validity and reliability analysis eight variables eliminated from the
PCI scale and five factor solution was reached, while no variables were deleted from the
adoption intention scale. The innovation characteristics
“relative advantage” and
“compatibility” was found loaded on Factor 1, and “voluntariness” and “visibility” were
found as having low Cronbach’s Alpha values (,617 and ,570) and deleted from the scale.
These results are similar to the study of Agarwal and Prasad (1997).
<Figure 2>
After the reliability and validity analysis, the research hypothesis was tested by
Structural Equation Modeling (SEM). In Figure 2 the structured model can be seen. The
variables included in the model is displayed in Table 3.
<Table 3>
As it can be seen from the Table 3, the model includes 53 variables. 23 of them are
observed variables and 30 of them are unobserved variables. The unobserved variables
include 24 variables which are showing error and are identified as “e” and 6 latent variables.
The evaluation criteria and values related with the fitness of the data and the model are given
in Table 3 in details.
<Table 4>
As can be seen from Table 4, there are several criteria looked at while evaluating the
goodness-of-fit between the model and the data. The first measure is the likelihood ratio chisquare statistics. This value has a statistical significance (p=0.000). And 2/sd ratio, which
should be between 2 and 5, is 2.406. The other goodness of fit measures- GFI (0.878), NFI
(0.871), RFI (0.848), IFI (0.920), TLI (0.905) and CFI (0.920)- should be close to 1.0 and in
the study their values indicate the fitness between the model and the data. At last, in order to
determine the required minimum sample Hoelter .05 and Hoelter .01 indexes were used. To
test the hypothesis at %95 confidence interval level and 0.05 significance level, the required
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minimum sample size was determined as 150 and to test the hypothesis at %99 confidence
interval level and 0.01 significance level, the required minimum sample size was determined
as 160. The research sample (311) is much more than the minimum sample size.
<Table 5>
Table 5 displays the regression weights. As it is seen, only the “relative advantage &
compatibility” has a significant effect on mobile banking adoption intention. The other
innovation characteristics- trialability, image, result demonstrability and complexity- do not
significantly affect the mobile banking adoption. Therefore the research hypothesis was
partially accepted. In order to identify the explanatory power of the model, R2 values were
used. R2 values represent the explanatory power of the dependent variables and the overall
adequacy of the model and found in this study as 0,203. It means that relative advantage and
compatibility explains 20 % of the adoption intention of mobile banking. This is not a high
value but there are numerous other variables affecting mobile banking adoption intention and
in this study just innovation characteristics were examined. Hence the R2 value can be
acceptable.
DISCUSSION
Adoption is defined as “a decision to make full use of an innovation as the best course
of action available. Rejection is a decision not to adopt an innovation” (Rogers, 2003: 117).
Perceived attributes of an innovation is important in explaining the rate of adoption. This
study examines the effect of innovation characteristics on the mobile banking adoption
intention. From the underlying theory, the assumption was developed as there is a combined
effect of innovation characteristics. However it was found that not all innovation
characteristics emerged as predictor but relative advantage and compatibility.
Relative advantage is the perception of innovation as a better idea. It is cited as a
remarkable variable in the adoption intention and most commonly found significant.
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Perception of relative advantage is the outcome of the comparison made by the potential
adopters between the existing technology and the new technology. This study bring out that
when the prospects perceive that using mobile banking speeds up banking, improves the
quality of banking, makes banking easier, gives greater control in banking and enhances
banking activities their usage intention increases.
Compatibility, is the perception of innovation as being consistent with the existing
values, past experiences, and needs of potential adopter. It is related with how well the
innovation fits into the adopters’ existing social structure. When an innovation perceived as
compatible, it is perceived as consistent with an individual’s life situation. In this study
compatible was found as an important innovation characteristic that has a significant effect on
adoption intention. When the prospects perceive that using mobile banking is compatible with
all aspects of banking, is completely compatible with their current ways of banking and fits
well with the way they like to do banking, they tend to adopt it.
Moreover, it was found that image, trialability, result demonstrability and complexity
do not influence the adoption intention of mobile banking. Therefore the banks should focus
on communicating information that emphasizes the relative advantage of mobile banking
compared to other banking channels and its compatibility with the existing values, past
experiences and needs of the prospects.
As a further research the adoption intention of mobile banking should be investigated
through other underlying variables and a more comprehensive model should be developed.
REFERENCES
Agarwal, R. & Prasad, J. (1997). The Role of Innovation Characteristics and Perceived
Voluntariness in The Acceptance of Information Technologies. Decision Sciences, Vol:28,
No:3, pp.557-582.
Brown, I., Zaheda, C., Davies, D. & Strobel, S. (2003). Cell Phone Banking: Predictors of
Adoption in South Africa- an Exploratory Study. International Journal of Information
Management, Vol:23, pp.381-394.
Gan, C., Clemens, M., Limsombunchai, V. & Weng, A. (2006). A logit analysis of electronic
banking in New Zealand. International Journal of Bank Marketing, Vol. 24 No. 6, pp. 360-83.
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Garcia R. & Calantone R. (2002). A Critical Look at Technological Innovation Typology and
Innovativeness Terminology: A Literature Review. Journal of Product Innovation
Management, Vol:19, pp.110–132.
Gounaris, S. & Koritos, C. (2008). Investigating the Drivers of Internat Banking Adoption
Decision A Comparison of Three Alternative Frameworks. International Journal of Bank
Marketing, Vol:26, No:5, pp.282-304.
Holak, S.L. & Lehmann, D.R. (1990). Purchase Intentions and the Dimensions of Innovation:
An Exploratory Model. Journal of Product Innovation Management, Vol:7, pp.59–73.
Kim, G., Shin, B. & Lee, H.G. (2009). Understanding Dynamics Between Initial Trust and
Usage Intentions of Mobile Banking. Information Systems Journal, Vol:19, pp.283-311.
Kim, H.W., Chan, H.C. & Gupta Sumeet (2007). Value-based Adption of Mobile Internet: An
Empirical Investigation. Decision Support Systems, Vol:43, pp.111-126.
Lee, Y. & Benbasat, I. (2003) Interface Design for Mobile Commerce. Communications of
the ACM, Vol: 46, pp.49–52.
Luarn, P. & Lin, H.H. (2005). Toward an Understanding of The Behavioral Intention to Use
Mobile Banking. Computers in Human Behavior, Vol:21, pp.873-891.
Moore, G.C. & Benbasat, I. (1991). Development of an Instrument To Measure The
Perceptions of Adopting an Information Technology Innovation. Information Systems
Research, Vol:21, No:3, pp.192-222.
Pousttchi, K. & Schurig, M. (2004). Assessments of Today’s Mobile Banking Applications
From the View of Customer Requirements. Proceedings of the Hawai’I International
Conference on System Sciences, January 5-8.
Riivari, J. (2005). Mobile Banking: A Powerful New Marketing and CRM Tool for Financial
Services Companies All Over Europe. Journal of Financial Services Marketing, Vol:20, No:1,
pp.11-20.
Rogers, E.M. (1995). The Diffusion of Innovations. 4th Edition, The Free Press, New York.
Rogers, E.M. (2003). The Diffusion of Innovations. 5th Edition, The Free Press, New York
Suoranta, M. & Mattila, M. (2004). Mobile Banking and Consumer Behaviour: New Insights
into the Diffusion Pattern. Journal of Financial Services Marketing. Vol:8, No:4, pp.354-366.
Van Slyke, C., Lou, H. & Day, J. (2002). The Impact of Perceived Innovation Characteristics
on Intention to use Groupware, Information Resources Management Journal, Vol:15, No:1,
pp. 5–12.
Venkatesh, V., Ramesh, V. & Massey, A.P. (2003) Understanding Usability in Mobile
Commerce. Communications of the ACM, Vol:46, pp.53–36.
Acknowledgments
The authors would like to thank to Galatasaray University Scientific Research Projects Commission for the
support provided (Research Project No. 09.102.009).
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TABLES AND FIGURES
Perceived Characteristics of
Innovation- PCI
- relative advantage
- compatibility
- image
- ease of use
- result demonstrability
- visibility
- trialability
- voluntariness
ADOTION
INTENTION
Figure 1: The Research Model
Table 1: The Demographic Characteristics of The Sample
Age
18
19
20
21
22
23
24
25
Total
Family Income (USD)
2.000 USD or below
1.001-3.500 USD
3.501 USD and above
Total
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n
%
8
34
76
52
57
37
29
18
311
2.6
10.9
24.4
16.8
18.3
11.9
9.3
5,8
100.0
n
137
72
102
311
%
44
23.1
32.8
100.0
Monthly Expenditure (USD)
n
%
375 USD and below
376-750 USD
751-1.125 USD
1.126- 1.500 USD
1.501 USD and above
25
57
162
50
17
8
18.3
52.1
16.1
5.5
Total
311
100.0
Gender
n
%
Female
Male
173
138
55.6
44.4
Total
311
100.0
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Table 2: Results of Reliability and Validity Analysis
No.of
Cronbach’s
Scales
Items
Alpha
F1: Relative Advantage & Compatibility
8
,869
F2: Trialability
3
,856
F3: Image
3
,839
F4: Result Demonstrability
3
,813
F5: Complexity
3
,738
ADI: Adoption Intention
3
,941
1
Total Variance
Explained
,528
,782
,756
,726
,657
,894
v21
e8
1
v22
e7
1
v23
e6
1
v24
e5
1
F1
v25
e4
1
v26
e3
1
1
v27
e2
1
v28
e1
1
v42
e11
1
v43
e10
1
e28
1
1
F2
v44
e9
ADI
1
v49
v50
v51
1
v29
e14
1
e13
1
e12
1
e17
1
e16
1
e15
1
e20
1
e19
1
e18
v30
1
F3
v31
v35
v36
1
F4
v37
v32
v33
1
F5
v34
Figure 2: The Structured Research Model
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1
e25
1
e26
1
e27
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Table 3: The Variables in The Research Model
Number of variables in the model
53
Number of observed variables
23
Number of unobserved variables
30
Number of exogenous variables
29
Number of endogenous variables
24
Table 4: Goodness of Fit
Fit Measure
Discrepancy (2)
Degrees of freedom
P
Discrepancy / df (2/sd)
Goodness of Fit
Adjusted Goodness of Fit
Normed fit index
Relative fit index
Incremental fit index
Tucker-Lewis index
Comparative fit index
RMSEA
Hoelter ,05 index
Hoelter ,01 index
Default model
517,221
215
,000
2,406
,878
,843
,871
,848
,920
,905
,920
,067
150
160
Saturated
0.000
0
1.000
1.000
1.000
0,05<RMSEA<0,08
Abbreviations
CMIN
DF
P
CMINDF
GFI
AGFI
NFI
RFI
IFI
TLI
CFI
RMSEA
HFIVE
HONE
Table 5: Regression Weights
Estimate
Adoption Intention <-Adoption Intention
Adoption Intention
Adoption Intention
Adoption Intention
R2: ,203
<-<-<-<--
Relative Adv.&
Compatibility
Trialability
Image
Result Demonstrability
Complexity
S.E.
,178 4,241
***
-,048
,071
,168
,021
,096 -,494
,073 ,965
,116 1,453
,074 ,287
,621
,335
,146
,774
Perceived Characteristics of the Innovation
(PCI; Gounaris and Koritos, 2008- adapted from Moore and Benbasat, 1991)
Relative advantage
. Using mobile banking speeds up banking.
. Using mobile banking improves the quality of banking.
. Using mobile banking makes banking easier.
. Using mobile banking gives me greater control in banking.
. Using mobile banking enhances banking.
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Sig.
,754
Appendix
Complexity (Ease of use)
. Overall, I believe that mobile banking is easy to use.
. Learning to operate mobile banking is easy for me.
t
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. I believe that it is easy to get mobile banking to do what I want it to do.
Compatibility
. Using mobile banking is compatible with all aspects of banking.
. Using mobile banking is completely compatible with my current ways of banking.
. I think that using mobile banking fits well with the way I like to do banking.
Image
. People who use mobile banking have a high profile.
. People who use a mobile banking have more prestige than those who do not.
. Using mobile banking is a status symbol.
Result demonstrability
. I would have no difficulty telling others about the results of using mobile banking.
. I would have difficulty explaining why using mobile banking may or may not be beneficial.
. The results of using mobile banking are apparent to me.
Visibility
. I have not seen many others using mobile banking.
. I have seen what others do using mobile banking.
. It is easy for me to observe others using mobile banking.
Trialability
. Before deciding whether to use mobile banking, I can properly try it out.
. Mobile banking is available to me to adequately try it.
. It is permitted to use mobile banking on a trial basis long enough to see what it can do.
. I don’t really have adequate opportunities to try out different things on mobile banking.
Voluntariness
. My bank does not require me to use mobile banking.
. Although it was suggested by my bank, using mobile banking is certainly not compulsory.
. My use of mobile banking is voluntary.
Adoption Intention (Kim et al., 2007)
. I plan to use mobile banking in the future.
. I intend to use mobile banking in the future.
. I predict I would use mobile banking in the future.
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