Research Article I
Usage of
Presented
at the American Marketing Association Summer Marketing Educators’ Conference,
Conference
Proceedings Vol. 14, pp. 179-187.
Usage of
from a Bank Customer Survey
Abstract
Technological
advancement has challenged the providers of financial services; the very nature
of selling and buying financial services has changed. The paradigm shift, from traditional branch
banking to electronic banking and the newly emerged wireless delivery channel
are the motivators of this study in which the focus is on studying usage of
mobile services.
In consequence we are
able to state what is the influence of demographic characteristics of the
customers on the adoption and usage of mobile services. A quantitative survey
sheds more light on this researched issue. The data was collected in
Keywords:
1. Introduction
Rapid changes in the financial services
environment; increased competition by new players from non-banking sector,
product innovations, globalization and technological advancement, have led to a
market situation where battle of customers is intense. As a consequence
financial services providers have started to offer services through various
delivery channels. Developing innovative service products, offering wider
service range and delivering multi-channel services aim at increased customer
satisfaction and efficiency. Offering financial services also through
electronic delivery channels is one step in achieving that goal. Besides
reducing costs and improving effectiveness, employing multi-channel
distribution strategy contributes to retaining the existing customer base and
attracting new customers. Today’s knowledgeable consumers demand up-to-date,
innovative services, thus the pressures banks face are twofold stemming from
the competitive market environment and from customers’ needs (Polatoglu & Ekin 2001;
Thornton & White 2001). Impacts of technological advancement can be seen in
almost every industry, technology has become an increasingly vital element in
the competitive landscape of the financial service industry too. The recent
developments have created totally new service concept and service environment (Bitner et al. 2000). Technology has changed the very nature
of selling and buying financial services.
Innovations in
telecommunications have led to usage of mobile devices in banking services.
Mobile banking is among the newest electronic delivery channels to be offered
by banks. As using the term electronic banking we refer to a definition, which
explains it as the provision of information and services by a bank to its
customers via electronic wired or wireless channels, for example Internet,
telephone, mobile phone or interactive television (Daniel 1999). Currently,
conducting account balance and transaction history inquires, funds transfer,
bill payments, stock trades and quotes, portfolio management as well as
insurance ordering are technologically enabled via a mobile device. Even though
technology and applications for these services are available, the usage rates
internationally have been fairly low and, in fact, in most developed countries
financial institutions have only recently begun to offer mobile services to
customers. Mobile banking service market is still in its infancies (Mattila and Pento 2002; Durlacher Report 2002).
Adoption of tele-banking (e.g. Al-Ashban & Burney 2001) as well as Internet banking (e.g.
Bradley & Steward 2002; Black et al. 2001; Mattila
2001) has received research attention in recent years. Much of the existing
research in electronic banking services has adopted an organisational
perspective (e.g. Daniel 1999) or a distribution channel perspective (e.g.
Black et al. 2002; Thornton and White 2001; Mols
2001). Consumers using these
services have been focus in a large body of current research, nevertheless
customer behavior in mobile banking context have remained rather uncharted
territory. This paper aims at filling that gap by shedding light on the general
usage of mobile services and in particular on influence of demographic
characteristics on usage. The survey was conducted among Finnish bank
customers. The paradigm shift, from traditional branch banking to electronic
banking; the newly emerged channels; rapidly increasing penetration rates of
mobile phones are among other the motivators of this study. The approach we
employ is practical and provides insights drawn from the quantitative empirical
survey.
The paper is
organised as follows: it begins with a brief review on theoretical background
of the study followed by reviews on mobile service market and mobile banking in
order to provide research rationale for the study. Thereafter, the methodology
and data collection are described and the relevant empirical implications of
the survey presented. The paper concludes with a discussion of the findings and
development of practical guidelines applicable to this case.
2.
Theoretical Background
The newly
emerged mobile banking services represent an innovation where both intangible
service and an innovative medium of service delivery employing high technology
are present. Within this research area one of the most often cited work is that
of Everett M. Rogers (e.g. Moore and Benbasat 1991)
which originally dates back to 1962. In
the search to understand adoption of technology, and when research has focused
on the consumer perspective,
Traditionally, the Rogers’
adoption continuum recognizes five categories of consumers that differ in terms
of adoption rate and, as the findings of this study reveal, in terms of certain
socioeconomic characteristics. The common extrapolation characterizes adopter
categories as follows. Innovators who are the first adopters, interested in
technology itself with positive technology attitudes; early adopters who are
also interested in technology and willing to take risk; early majority who can
be considered pragmatist and process oriented; late majority who are more or
less skeptical with negative technology attitudes; laggards who have extremely
negative technology attitudes and hence never adopt technology among the main
stream. Earlier adopters of technological innovations are often stated to be
relative young, have higher income, more education, and higher social status
(professional, technical and managerial) occupations.
3. Mobile Service Environment
The market penetration of mobile phones is
rapidly increasing around the world and the role of mobile phones is changing.
From having been a luxury product in the late 1980s today the mobile phone is
merely a mass product in most develop countries. Until recently, Europe had the
highest total number of wireless subscribers in the world, although the
Asia-Pacific region has now surpassed it. Last year penetration rate in Western
Europe was 75.2 % (eMarketer 2003). According to
calculations by Morgan Stanley and eMarketer over the
next tree years the US will take the lead over Europe and Asia in terms of
total number of wireless subscribers on advanced 2.5G and 3G networks; by 2004
114.7 million subscribers in 2.5G and 3G in US and 35.8 million in Europe. Exceptionally
fast diffusion of mobile subscribers and the growth of generic mobile services
such as Short Messaging Systems do not overcome the fact that the adoption of
many so called value-added services has not been successful.
Consequently, we cannot make a
straightforward conclusion that popularity of mobile devices is a clear
indication of popularity of all mobile services. Several surveys have tried to
capture the factors hindering the adoption of mobile services (e.g. Anckar and D’Incau 2002), whereby
the answer has often been technical problems, contradicting experiences from
flop of Wireless Application Protocol services and lack of appropriate enabled
devices. Yet, it is still widely predicted in Western world and shown by the
success of iMode in Japan that the mobile terminal
will finally be the access point for
all sorts of services. Though, we do not believe that the success strategies
from Japan can be directly implemented, for example in Finnish market. Admittedly, the expected improvements for the mobile service
and application space arriving with 2.5G and 3G networks can act as a trigger
for acceptance. These include ability of mobile devices to provide
location-specific information, new ways of personalization, enhanced
availability and immediacy of service. Particularly the last mentioned feature
can contribute to the predicted shift from wired Internet connections to
wireless mobile services in banking too (Wah
1999). The immediacy of information access will be enhanced by the always-on functionality,
which supports the provision of time-critical information conducting high value
transactions, such as participating in mobile auctions and executing mobile
stock trading deals. These type of value-added mobile services will without
doubt become some of the most interesting, revenue-generating services simply
because of the economic value attached to them (Durlacher
Report 2001).
Availability, 24/7 access,
independence of time and place and portability are key benefits and selling
points of the mobile services. Purpose of the wireless device is to facilitate
an individual’s connectivity to necessary information and services at any
location, whether on –site, down the street or thousand miles away (Jonason and Eliasson, 2001).
According to Keen and Mackintosh (2001), the key value proposition of mobility
is creation of choice or new freedom for customers. If mobility aspect will be
the most valued feature by customers in the future, the wireless connections
gain advantage over wired connections in banking. Customers in Finland
are familiar with conducting their banking over Internet, over 85 % of all
payment transactions by Finnish banks are already made in digital form (The
Finnish Bankers’ Association 2002). Mobile phone penetration amounted to 94 %
in year 2002 (Statistics Finland 2002). The structures of Finnish society
comprising information infrastructure have developed over years to be
favourable for adopting technology-based products and services.
2.1 Mobile Banking
Northern European countries are among the
most advanced ones in the adoption to and use of different new mobile and
technological appliances and these countries have extended the implementation
of technological advancement in banking services (Finland Statistics 2002). In
Finland payments and account management products over mobile GSM phones as SMS
service have been available over one decade, exactly since 1992,
television-based banking since 1998 and banking via mobile Internet WAP since
1999 (Mattila and Pento
2002). Finnish customers conduct their routine banking mainly via Internet,
over 70 % of the customers visit a branch office less than twice a year. The
number of branches in Finland has been shrinking in rhythm with increased
Internet banking usage (The Finnish Bankers’ Association 2002). At the moment
Internet is also the leading electronic banking channel elsewhere where the
electronic delivery channels have been introduced, although telephone banking
seemed to have toehold on the British financial services market (Howcroft et al. 2001).
As we argued above the landscape
of wireless services is presently changing and the expected improvements in
2.5G and 3G devices and networks will encourage the uptake of mobile banking.
Although the densities of fixed and mobile connections are high in all the
Nordic countries, the number of most advanced Internet-enabled mobile phones is
still fairly low; in Finland 20 % of population has Internet-enabled device. Access to
advanced model is slightly more common to men than to women. In addition
younger people have advanced mobile phones more often than older people, in
fact in the age group 60 years or over as well as among retired persons the
access rate is only 3-9 %. Those with tertiary education have more often an
Internet enabled mobile phone, but the effect is not as strong as that of age
(Statistics Finland 2002). One issue driving future mobile banking is the cost
efficiency pressures from supply side. Payment transaction costs vary: manually
in a branch from $2.60 to $4.40, with automatic teller machine $0.44 and less
than three cents via mobile phone. Quite often wireless capability is built
into financial institution’s software platform, leaving maintenance and
upgrades as the only added costs (Mattila and Pento 2002; McCall 2002). European IT consultants
International Data Corp. expect mobile banking to be the fastest growing sector
of total information technology spending on electronic banking, with a 1999 to
2003 compound annual growth rate of 129% (West 2001). Adding digital channels such as mobile and
developing more and more commoditized products will clearly help to shift
further tasks towards the customer through self-provisioning and thus, will
help cutting additional costs (Durlacher Report
2001). Today’s banking is thereby not just online and wireless but also
interactive.
In
the next chapters we will further discuss mobile services in an empirical
setting and provide insights for research findings drawn from the quantitative
survey as well as highlight factors proven to be indicators of a certain
consumer behavior in this context.
4.
Methodology and Data Collection
The methodological approach in this study is
descriptive, because we attempt to identify and explain the variables that
exist in a given situation, and to describe the relationship that exists between
these variables, the intention being to provide a picture of a particular
phenomenon rather than to ferret out cause-effect relationships (Churchill and Iacobucci 2002). The phenomenon to be studied, mobile
banking, is comparatively new in the field of academic research and for this
reason the study aims at increasing the understanding of the current consumer
behavior pattern in the electronic services era. The research data was
collected by means of a traditional postal survey. The pre-tested questionnaire
with a covering letter and a postage-paid return envelope was sent to a
cross-section of 3000 bank customers. The questionnaire was administered to a
stratified sample of Finnish bank customers, selected in terms of their banking
habits. The sampling frame from which the sample elements were drawn was a
customer database of one major Finnish bank. After two follow-up mailings 1303
responses were received, of which 1253 were usable. The usable response rate
amounted to 41.8 percent, which was really satisfactory and above the 20-30
percent rate considered acceptable in economics research. The objective was to
gather a highly representative sample that was also attained since the sample
represents geographically
TABLE 1
Profile of the respondents
Demographic Frequency Percentage Cumulative
Characteristics
percentage
Gender
Male 634 50.6 50.6
Female 590 47.1 97.7
Missing 29 2.3 100
Standard
deviation 0.499
Age
Under 18 4 0.3 0.3
18-24 years 226 18 18.3
25-34 years 418 33.4 51.7
35-49 years 370 29.5 81.2
50-64 years 212 16.9 98.1
65 years and over 17 1.4 99.5
Missing 6 0.5 100
Standard
deviation 1.026
Marital
status
Married 488 38.9 38.9
Cohabitation 337 26.9 65.8
Single 322 25.7 91.5
Widow 13 1 92.5
Divorced 75 6 98.5
Missing 18 1.5 100
Standard
deviation 1.113
Occupation
Executive 70 5.6 5.6
Worker 503 40.1 45.7
Not at work 84 6.7 52.4
White-collar worker 246 19.6 72
Student 132 10.5 82.5
Farmer 29 2.3 84.8
Pensioner 54 4.3 89.1
Entrepreneur 74 5.9 95
Public servant 49 3.9 98.9
Other 5 0.5 99.4
Missing 7 0.6 100
Standard deviation 2.183
Household
income
Under 10.000 euros 109 8.7 8.7
10.001-20.000 euros 191 15.2 23.9
20.001-30.000 euros 239 19.1 43
30.001-40.000 euros 195 15.6 58.6
40.001-50.000 euros 181 14.4 73
50.001-60.000 euros 130 10.4 83.4
60.001-70.000 euros 67 5.3 88.7
70.001-80-000 euros 34 2.7 91.4
Over 80.001 euros 33 2.7 94.1
Missing 74 5.9 100
Standard deviation 1.988
3.1
The Profile
of a Typical
Academic research has been interested in examining
socio-economical factors (demographics, psychographics) of consumers adopting
new technologies. According to Polatoglu and Ekin (2001) and Howcroft et al.
(2001) demographic factors that describe typical electronic banking customers
include young, affluent and highly educated. In earlier Finnish studies
findings of the typical Internet banking user were somewhat similar and in some
respect contradictory. A Finnish study (Mattila 2001)
states Internet banking user is middle aged, relative wealthy and highly
educated. Interestingly, results from this study indicate that the average
mobile banking user’s socio-economical factors differ from that of Internet
banking user. Gender seemed to have slightly impact on mobile service usage;
there were 10 % more men in regular users’ group. A user of mobile banking
belonged most often to age group 25 to 34 years old. Majority of the so called
regular users (43.6 %) were 25 to 34 years old as well as majority (36.8 %) of
occasional users, whereas non-users were relatively older compared to the two
other groups. Every third of non-users (31.7%) belonged to age group 35 to 49
years old and 25.9 % to 50 to 64 years old.
38.9
% of respondent were married. Majority of the all respondents were workers
(40.1%), the second largest occupation group was white-collar workers (19.6 %)
and the third students (10.5 %). The result is compatible with the result of
background education of the respondents, which was in most cases (25.2 %)
secondary level vocational school. These results differ from the earlier
finding of electronic (Internet) banking users, who have traditionally had
university level education and higher professions (e.g. Jayawardhena
et al. 2000). Majority of the respondents (19.1 %) belonged to household income
category of 20.001-30.000 euros/year which matches with the average year income
of two persons in
5. Usage of
While studying usage of different
technology-based services and products the question about consumers’ perception
of technology in general is often raised in academic literature. Several well
know behavioral models explain and predict the adoption and usage of
technology-based products e.g. Theory of Planned Behavior (Ajzen
1991), Technology Acceptance Model (Davies 1989), Theory of Reasoned Action (Fishbein and Ajzen 1975). Those
all propose that beliefs and attitude of the individual towards a certain behavior
are determinants of the individual’s intention towards the adoption of that
behavior, e.g. using mobile service. Empirical surveys (e.g. Mattila 2001; Tan and Teo 2000)
suggest that technology experience and technology perceptions have an impact on
usage of Internet banking and in particular beliefs towards computer and
Internet. Following that reasoning Table 2 outlines the results of respondents’
technology perceptions. It seems that technology perceptions in general were
positive, only electronic ID-card had negative means within all target groups.
Not surprisingly among the regulars users the most liked technology-based
product was mobile phone (mean 1.85), whereas among occasional (1.86) and
non-users (1.97) it was Internet.
TABLE 2 Technology perceptions. Consumer
beliefs ranging from like
Regular users Occasional users Non-users
Mean Stand.dev. Mean Stand.dev. Mean Stand.dev.
Mobile phone 1.85 1.359 1.63 1.495 1.03 1.741
Computer 1.51 1.648 1.71 1.566 1.82 1.296
Bank and
credit cards 0.99 1.820 1.09 1.806 1.19 1.679
Cable television 0.52 2.244 0.54 2.260 0.19 2.265
E-mail 1.23 1.997 1.76 1.695 1.81 1.495
Internet 1.54 1.741 1.86 1.533 1.97 1.265
Personal
service 1.43 1.645 1.55 1.649 1.51 1.576
Text television 1.42 1.622 1.16. 1.778 1.13 1.681
ATM 0.49 2.000 0.35 1.969 0.32 1.967
Electronic ID-card -0.25 2.540 -0.17 2.498 -0.09 2.481
Cronbach’s alpha α=0.7788
In order to gain more insight
into influence of demographics on usage of certain mobile services ANOVA tests
were conducted. ANOVA results by age are presented herein in table form (see
Table 3) and the rest discussed. Public opinion is that younger consumers use
more mobile services. According to our findings this holds true. ANOVA results
yielded some statistically significant differences in means between the age
groups. Only in ordering parking payments via mobile phone and reserving tickets
age was not statistically significant. Consequently, age seems to have no
impact on usage of these mobile services. In usage of other services younger
respondents are likely to use more of service. In case of ordering logos
(F=89.743) and ringing tones (F=76.438) differences in using services vary more
between the age groups than within an age group. As investigating another
demographic variable, household income, ANOVA results for using eCards (F=1.278 p=.277), parking payments (F=1.308 p=.265)
and receiving offers (F=2.339 p=.053) were not significant, within all the
other mobile services income level have impact on usage. Statistical
significant differences in means between marital status were found only for
ordering logos (F=14.403 p=.000), ringing tones (F=15.214 p=.000) and offers
(F=3.400 p=.009); herein marital status had impact on usage. Whereas
occupational group affected usage of all these mobile service, differences were
statistically significant, except receiving offers (F=1.551 p=.125).
TABLE 3 ANOVA by age
Ordering or using N Means Mean square F
value Sig.
the service by mobile phone between groups
1. eCards 1.487 4.784 .003
18-24 228 3.66
25-34 416 3.65
35-49 363 3.77
50-65- 217 3.78
Total 1224 3.71
2. SMS Chat 13.980 9.027 .000
18-24 228 3.63
25-34 414 3.31
35-49 363 3.11
50-65- 216 3.16
Total 1221 3.29
3. Logos 39.748 89.742 .000
18-24 228 2.80
25-34 415 2.88
35-49 363 3.34
50-65- 219 3.62
Total 1225 3.13
4. Ringing tones 37.634 76.438 .000
18-24 229 2.75
25-34 417 2.80
35-49 364 3.27
50-65- 218 3.53
Total 1228 3.06
5. News services 5.150 9.178 .000
18-24 228 3.55
25-34 417 3.47
35-49 363 3.63
50-65- 219 3.78
Total 1227 3.59
6. Weather forecast 3.000 5.674 .001
18-24 228 3.54
25-34 416 3.44
35-49 364 3.62
50-65- 219 3.65
Total 1227 3.55
7. Parking payments 0.509 2.059 .104
18-24 228 3.79
25-34 416 3.77
35-49 364 3.86
50-65- 219 3.79
Total 1227 3.80
8. Ticket reservations 0.582 1.777 .150
18-24 228 3.67
25-34 417 3.66
35-49 364 3.74
50-65- 218 3.73
Total 1227 3.7
9. Offers to mobile phone 2.527 6.731 .000
18-24 228 3.62
25-34 417 3.68
35-49 364 3.81
50-65- 219 3.80
Total 1228 3.73
Scale ranging from 0 (daily)
1 (weekly) 2 (monthly) 3 (less frequently) 4 (never)
To develop further understanding
in interdependency of the above mentioned mobile services (indicated by the
number) and demographics we formed correlation coefficients matrix (Table 4).
Even thought there seems be correlation among many variables, only correlations
between age and ordering logos (r =.425) and ringing tones (r =.399)
were significant (0.3 < r < 0.7). Although the large size of sample
increases the significance of other correlations too. Interpretation of table
means younger are more likely to use SMS chat (r=-.107); all the other services
are positively correlated with age. Household income is positively correlated
with ordering logos (r=.076) and offers to mobile phone (r=.073). Wealthier
customers are likely to use those services. Gender is positively correlated
with news and weather services, parking payments and ticket reservations. That
is, females are more likely to use these services. Marital status is negatively
correlated with logos (r=-.110), ringing tones (r=-.144) and offers (r= -.08); herein
service users are more likely to be married. Occupation is positively
correlated with logos, ringing tones, new and weather services and ticket
reservation. On the basis of this, the better occupational level the consumer
has the more likely she is to use these services.
TABLE 4
Correlations between demographic characteristics and mobile service usage
Variables 1 2 3 4 5 6 7 8
9
Gender M=0 F=1 -.027 .053 -.052 -.013 .167** .200** .107** .077**
.003
Age .117** -.107** .425**
.399** .136** .103** .065* .075** .149**
Marital status -.056
.018 -.110** -.144** -.029 -.016 -.018 -.039 .080**
M=0 not M=1
Occupation -.016 .007
.124** .113** .077**
.083** .056
.060*
.042
Household income .000 -.084**
.076** .057 -.059* -.100** -.031 -.035 .073*
Notes: ** Correlation is
significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05
level (2-tailed)
(measured
by using Pearson’s
6. Conclusions
As we are gradually starting to gain an
understanding of the unique characteristics of the Internet, a new medium has
emerged, the wireless service delivery channel, which raises many of the same
questions in a new context (Anckar and D’Incau 2002). This paper
contributed to answering these questions by shedding light on the fairly
unexamined and ‘unknown territory’ of mobile services and banking in context of
demographic characteristics. A small excursion in investigating bank customers’
technology perceptions was taken too.
Technology perceptions in this study proved to be positive. Mahajan et al. (1990) argues
adoption of complex products depends on adopter’s ability to develop new
knowledge and new patterns of experience and ability can be enhanced by the
knowledge gained from related, technological products. Little research has been
conducted to identify the primary target groups for mobile services of
different types even with regards to basic demographic variables, although the
understanding of the impact of such factors is crucial for a marketing point of
view. Previous research has suggested and verified e.g. gender and age to be
relevant factors in terms of technology adoption and usage (Venkatesh
and Morris 2000). Results of this survey proved the influencing power of
demographics too.
On the basis of the findings we are
suggesting that services providers should be aware of the demographics of their
customer base using mobile services. This kind of data has its value when
designing new services and products or implementing marketing communications.
In addition, information gained from experience with Internet banking and other
modes of electronic banking cannot be straightforward implemented to mobile
banking service customers. As the findings reveled customer bases are
socio-economically different. Given the increased competition and pressures to
cut expenses financial institutions have to be able to make informed decisions
on resource allocation. Thus, research of this kind is of critical importance.
As Wah (1999) already five years ago pointed out,
electronic banking as well as any other service of this type does not
necessarily have to be on computer screen. It can be on the tiny screen of the
mobile phone or any other wireless device. Limitations of this study arise from
the pretty narrow scope in research focus; we mainly discussed certain
demographic variables and a limited number of mobile service products. In the
sample majority of the respondents was technologically oriented. These issues
may have an effect on the validity and reliability of the results.
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Thornton, Jennifer and White,
Lesley (2001), “Customer Orientations and Usage of Financial Distribution Channels,”
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Research Article II
Modelling Mobile
Banking Adoption: An Empirical Investigation
Earlier
version of the paper presented at the European Marketing Academy Conference,
Glasgow 20-23 May 2003, and published in Conference Proceedings (CD-ROM), pp.
28. The present paper is under review for publication in International Journal
of Innovation Management
MODELLING
AN EMPIRICAL INVESTIGATION
Abstract
Innovation adoption literature suggests that
the perceived innovation attributes are the most important determinants of
consumers’ adoption decision. This paper focuses on defining the factors
affecting mobile banking adoption and aims at forming a model describing
consumer behaviour pattern. Mobile banking services
can be seen as an innovation in the financial services industry, introduction
of these services was enabled by the recent advances in telecommunications. A
quantitative survey sheds more light on this researched issue. The data were
collected in
Keywords: Mobile banking, innovation adoption,
innovation attributes,
modelling consumer behaviour
Introduction
Rapid changes in the financial services
environment - increased competition by new players from non-banking sector,
product innovations, globalisation and technological
advancement - have led to a market situation where battle of customers is
intense. In order to rise to the challenges service providers are even more
interested to enhance their understanding of consumer behaviour
patterns. As more and more advanced technologies enter the household domain, it
becomes increasingly important to understand consumer response to these new
technologies. This paper examines factors influencing the adoption of mobile
banking services. Adoption is understood in the paper as acceptance and
continued use of a product, service or an idea.
Recent research in electronic delivery of
financial services has largely been conducted in the context of Internet
banking, the present study contributes to this research area by exploring
wireless delivery channel and services used via mobile devices. In using the
term electronic banking we refer to a definition, which explains it as the
provision of information and services by a bank to its customers via electronic
wired or wireless channels, for example Internet, telephone, mobile phone or
interactive television (Daniel 1999). In other words electronic banking is a
high-order construct consisting of several delivery platforms of which mobile
handsets are an example and hence mobile banking is a sub-set of the electronic
banking construct. Marketing implications that can be drawn from the findings
will assist service providers in understanding consumers better and in making
justified marketing decisions. Research findings make a contribution to the
theoretical consumer behaviour modelling
by extending a traditional theory to a new application area that may give new
insights into the theory. Thus, the study contributes both to practice and
theory.
The paper is organised
as follows: it begins with a brief literature review in order to provide
theoretical background for the study. Thereafter, the methodology and data
collection are described and the empirical implications of the survey
explained. The paper concludes with a discussion of the findings and
development of a model applicable to this case.
Theoretical Background
The newly emerged mobile banking services
represent an innovation where both intangible service and an innovative medium
of service delivery employing high technology are present. Thus, concepts of
innovation and diffusion of innovation are even more intricate as technology
and service aspects have an effect on the characteristics of mobile banking
services (Mohr 2001). Traditionally research relating to the consumer adoption
of innovation has tended to concentrate on socio-demographic and psychographic
attributes of potential adopters. Even though these kind of personal
characteristics of a consumer have found to be predictors of adoption (e.g. Al-Ashban and Burney 2001), an increasing body of research has
demonstrated that it is the perceived attributes of innovation itself rather
than the personal characteristics that are the stronger predictors of the
adoption decision (Black et al. 2001). In the search to understand consumers’
adoption of innovation, and where research has focused on the consumer
perspective, Rogers’ diffusion model, which originally dates back to 1962, has
often been employed (Howcroft et al. 2002; Black et
al. 2001). Within financial services innovation research i.a.
Black et al. (2001), Polatoglu and Ekin (2001), Tan and Teo (2000)
have applied Rogers’ model to Internet banking.
According to Rogers (1995) the perceived
innovation characteristics are supposed to provide the framework how potential
adopters perceive an innovation. Research that has investigated the product
characteristics of innovation has generally endorsed evaluating the innovation
along the product characteristics that involve five constructs: relative
advantage, compatibility, complexity, trialability
and observability (Moore and Benbasat
1991). Concept of perceived risk is often included as augmented by Bauer
(1960). Particularly in banking services the perceived risk associated with the
financial product itself as well as with electronic delivery channel is higher
than in basic consumer goods, and hence increases the importance of this
attribute of innovation (Harrison 2000). Ensuring security and confidentiality
is the fundamental prerequisite before any banking activity involving sensitive
information can take place (Jayawardhena and Foley
2000). Relative advantage, compatibility, trialability
and observability are positively related to adoption
of an innovation and the remaining two, complexity and perceived risk,
negatively related (Rogers 1995). These innovation attributes and their
influence on adoption of mobile banking services are detailed under empirical
implications.
The issue of acceptance of different service
delivery mediums and managing the customers in different delivery channels in
the financial services industry has received growing attention in the academic
and professional literature since it has been hailed as an increasingly
important factor in determining whether a company competes effectively in
markets (e.g. Mattila 2002). And as Black et al.
(2001) stated given the attributes of innovation, often also called product or
service attributes, are under control of marketers, then arguably an
understanding of impact of these attributes on the adoption of an innovation
becomes highly interesting and valuable for research question. Adoption of tele-banking (e.g. Al-Ashban and
Burney 2001) as well as Internet banking (e.g. Bradley and Stewart 2002) has
received research attention in recent years. Much of the existing research in
electronic banking services has adopted an organisational
perspective (e.g. Daniel 1999) or a distribution channel perspective (e.g.
Black et al. 2002), notwithstanding these slightly different approaches similar
patterns have emerged within financial services innovations that include
convenience, flexibility, access, security, control etc. (Black et al.
2001).
Methodology and Data Collection
The methodological approach in this study is
descriptive, because we attempt to identify and explain the variables that
exist in a given situation and to describe the relationship that exists between
these variables, the intention being to provide a picture of a particular
phenomenon rather than to ferret out cause-effect relationships (Churchill and Iacobucci 2002). The phenomenon to be studied, mobile
banking, is comparatively new in the field of academic research and for that
reason study aims at increasing the understanding of the current consumer behaviour pattern in the electronic services era. The
research data were collected by means of a traditional postal survey. The
pre-tested questionnaire with a covering letter and a postage-paid return
envelope was sent to a cross-section of 3000 bank customers. The questionnaire
was administered to a stratified sample of Finnish bank customers, selected in
terms of their banking habits. The sampling frame from which the sample
elements were drawn was a customer database of one major Finnish bank, OKO Bank
Group. After two follow-up mailings 1303 responses were received, of which 1253
were usable. The usable response rate amounted to 41.8 percent, which was
really satisfactory and above the 20-30 percent rate considered acceptable in
economics research.
The objective was to gather a highly
representative sample which was also attained as the sample represents
geographically Finland and the respondents were chosen in terms of their
banking habits. The survey sample consisted of three equal-sized segments that
were selected according to mobile banking usage experience and density. The
non-users (38.8 percent of the respondents) had never used permanently any form
of mobile banking services, the occasional users (33.2 percent of the
respondents) had started to use some form of mobile services and the regular
users (28 percent of the respondents) had been using the services for a longer
period of time. The questionnaires were also partly tailored respectively. Most
of the questions were multichotomous questions; only
the questionnaire designed for the regular users included some open-ended
questions. Respondents were asked to complete a five to seven point Likert scale on each question or proposition. The scales
for measuring each of the beliefs and attitudes were developed based on
existing scales discussed in the relevant methodological literature and in
surveys in the research area (e.g. Fishbein and Ajzen 1975; Bahia and Nantel 2000). This data form the basis of the whole
research of which this paper is one part. Only the selected sections of the
survey data will be used in the present paper. In accordance with the chosen
methodological research approach the quantitative data were analysed
using statistical methods such as mean, standard deviation, ANOVA, correlation
coefficients, exploratory factor analysis by SPSS-program.
Empirical Implications
One of the aims of the research was to identify
the extent to which established approaches and models that have been used to
study the adoption of new service innovations may prove relevant in consumer
decisions to adopt a major service innovation. In next chapters each innovation
attribute is defined and investigated based on the survey findings in the
domain of mobile banking.
Relative advantage
Relative advantage is concerned with the
degree to which an innovation is perceived as being better than the idea it
supersedes. The degree of relative advantage is often expressed as economic
profitability, social prestige, savings in time and
effort, immediacy of the reward or as decrease of discomfort (
Place here: FIGURE 1 Reasons for adopting
mobile banking services
Compatibility
The degree to which an innovative channel
such as mobile devices as a channel is compatible with the individual’s past
experiences and values appears to have a significant impact on willingness to
adopt (Rogers 1995). Respondents were asked about their attitudes towards
technology-based products and services which gave us an idea of respondents’
perceptions in general (see Table 1). Every target segment informed with
positive mean scores (scale used ranged from -3 dislike to 3 like) i.a. to mobile phone and services, Internet, personal
computer, cable television, e-mail that they were pretty enthusiastic about
using technology (mean scores 0.19 – 1.97), except of electronic ID-card (mean
scores -0.2 - -0.09). In their Internet
banking study Tan and Teo (2000) stated that Internet
banking has been viewed as a delivery channel that is compatible with the
profile of the modern day banking customer, who is likely to be technologically
savvy meaning computer-literate and familiar with Internet. Following that
reasoning innovation attribute compatibility can be viewed against the
background information that Finland has close to 90 percent mobile phone
penetration and Finns are in general very well used to use mobile devices,
mainly in person-to-person communication but increasingly in using different
kind of value added services too (Statistics Finland 2002). Positive technology
perceptions will certainly affect adoption of mobile banking services. We have
to also keep in mind that 82 percent of the respondents had an Internet
connection in use. These results are consistent with
Place here: TABLE 1
Technology perceptions. Consumer beliefs ranging from like
Complexity
The perception of complexity involved when
conducting financial transactions via mobile channel is often inversely related
to a consumer’s experience with technology in general. Gatignon and
Robertson (1985) argued adoption of complex products depends on adopter’s
ability to develop new knowledge and new patterns of experience and ability can
be enhanced by the knowledge gained from related, technological products. Additionally,
they made an interesting finding on the basis of their review of adoption
research. Within adoption framework of technology-based product innovation,
where no prior data of totally new product or service concept exists, some
conclusion can be drawn from adoption experiences of other products within the
product class. However, there are some significant differences between services
offered in wireless or wired line environment. Innovation attribute complexity
has thereby some similar determinants than the above discussed compatibility.
In
Place
here: FIGURE 2
Problems faced while using mobile banking services
Observability
Observability of an innovation describes the extent to
which an innovation is visible to other members of a social system, and how
easily the benefits can be observed, imagined and communicated to potential
customers (Rogers 1995). Earlier the branch network helped to overcome intangibility
problems by providing tangible evidence of the organisation
as well as was a convenient location for the customers to visit and become
involved in the service production process (Devlin 1995). The lack of physical
domain in service products may present some problems, even though in this case
the service delivery medium, mobile phone itself, may enhance physical evidence
of the innovation. In the survey respondents mentioned they had gained
information about mobile banking services from banks’ personnel (occasional
users 46.7 %, non-users 19.5 %) through personal selling activities, and
secondly from marketing communication activities, such as advertisements
(occasional users 15.7 %, non-users 36.4 %) and mailings (occasional users 16.4
%, non-users 26.1 %). These results are illustrated in Figure 3.
Place here:
FIGURE
3 Information sources of mobile banking
services
Trialability
Place here: FIGURE 4 NATU Model ( adapted from Mattila
and Pento 2002b)
In the beginning, all customers are not
aware of the new channel and are in the group N of the model. After awareness, it is not possible to become
not aware (this is illustrated as a continuous line in the figure), and the
only possibilities for a person is either to remain at A, or to try the new channel, which places her to
the group T. Again, there are two possibilities: either the person did not like
the service and remains in T, or she liked it and becomes a regular
Perceived risk
Perceived risk as a construct was not
included in the original
Place here:
FIGURE
5 Importance of different factors for
channel choice. Scale ranging from agree 3 to – 3 disagree
Discussion and Model Development
The research draws its theoretical
underpinnings from the adoption and diffusion of innovation literature, where
attributes of an innovation and individuals’ perceptions about using an
innovation are posited to influence adoption behaviour.
Based on the above discussed findings of the survey and the reviewed literature,
the model summarises the influential dimensions (see
Figure 6).
The dimensions on the right hand side are
the pertinent construct in adoption research, even though they are not the core
of the present paper but investigated in the scope of the whole study. The diffusion of an innovation takes place
in a social system, which is a physical, social and cultural environment with
its own values and norms which are likely to influence the acceptance or
rejection (
Place
here: FIGURE
6 A model of the factors affecting
the adoption of mobile banking services
Conclusions
Analysing how the innovation attributes are formed in
domain of mobile banking innovation and in consequence being able to define the
certain factors affecting the adoption constituted the broad motivation for
this paper. Several theoretical and practical implications followed. We found
support for the usage of these six innovation
attributes as lenses in investigating these kind of innovations. The model
formed based on
Mattila (2002) adduced an important managerial
question about how adoption process can be better managed and in this paper we
were able offer some solutions. When planning an introduction of a new idea, in
this case new delivery channel for financial services, practitioners would like
to be able to predict whether the new system will be acceptable to users,
diagnose the reasons why a planned system may not be fully acceptable to users,
and to take corrective action to increase the acceptability and as a result
adoption of an innovation. The present research is relevant to all of these
concerns. Diffusion of mobile banking services is still in an early phase that
is why it is relevant to study what are in general the factors affecting the
channels choice, or what are the service features that have caused problems. We
saw that many of the factors influencing the mobile banking adoption are under
the direct influence of managers, even tough there are some factors that remain
to be in the inherent personality and background of the individuals and their
environment such as the ones discussed in context of compatibility. Since
results of this study in comparison with other research in electronic banking
showed that consumer preferences vary with service attributes, this information
indicates how important it is to investigate a phenomenon in its own context
and not just rely on information gained from wired line environment.
Issues like how consumers perceive the
advantages of a new innovation, how are the preceding innovations accepted, or
how well are potential adopters informed about the service and its benefits, or
are the services difficult to use, is there a possibility for trial use, are
often overlooked. And yet, actions taken by financial
services practitioners in appropriately addressing these critical issues will
determinate the success of mobile banking too. The findings have
implications for facilitating the design of new service features or allocation
resources on marketing communication. Financial service providers need to
establish what is behind customer responses to service characteristics before
proceeding to implement different inducements to enhance the adoption.
We have illustrated that
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FIGURE 1 Reasons for adopting mobile banking services
TABLE 1 Technology perceptions. Consumer beliefs
ranging from like
Regular users Occasional users Non-users
Mean Stand.dev. Mean Stand.dev. Mean
Stand.dev.
Mobile phone 1.85 1.359 1.63 1.495 1.03 1.741
Computer 1.51 1.648 1.71 1.566 1.82 1.296
Bank and credit cards 0.99 1.820 1.09 1.806 1.19 1.679
Cable
television 0.52 2.244 0.54 2.260 0.19 2.265
E-mail 1.23 1.997 1.76 1.695 1.81 1.495
Internet 1.54 1.741 1.86 1.533 1.97 1.265
Personal service 1.43 1.645 1.55 1.649 1.51 1.576
Text television 1.42 1.622 1.16. 1.778 1.13 1.681
ATM 0.49 2.000 0.35 1.969 0.32 1.967
Electronic ID-card -0.25 2.540 -0.17 2.498 -0.09 2.481
Cronbach’s alpha α=0.7788
FIGURE 2
Problems faced while using mobile banking services
FIGURE
3 Information sources of mobile banking
services
User U
Tried T T
Aware A
Not aware
FIGURE
4 NATU Model ( adapted from Mattila
and Pento 2002b)
FIGURE 5
Importance of different factors for channel choice. Scale ranging from
agree 3 to – 3 disagree
Social
System
Communication
Time
Demographics
FIGURE
6 Model of the factors affecting the
adoption of mobile banking services
Research Article III
Technology-based Service Products – a Study on
the Drivers and Inhibitors of
Earlier
version of the paper presented at the m>Business Conference, Vienna 23-24
June 2003, and published in Conference Proceedings, Band 169, pp. 187-199. The
present paper is under review for publication in Special Issue of International
Journal of Mobile Communications
Technology-based Service Products – A Study on
the Drivers and Inhibitors of
Abstract
The paradigm shift from traditional branch
banking to electronic banking; the newly emerged service delivery channels and
rapidly increasing penetration rates of mobile phones are the motivators of
this study. Technology has become an increasingly vital element in the
competitive landscape of the financial services industry. Innovations in
telecommunications have led to usage of mobile devices in banking. This paper reviews recent
technological advances in banking and forces that will drive or inhibit mobile
banking services adoption.
Drawing on the relevant literature and
empirical implications of the study, the paper proposes a model that
conceptualizes different affecting factors in electronic banking environment,
and particularly in mobile banking. A quantitative survey sheds more light on
this researched issue. The data was collected in
Keywords:
1.
Introduction
Today’s banking industry is, to large
extent, driven by technological innovations, the industry shares the common
characteristics of high-technology industry, most notably; competitive
volatility, market uncertainty, and technology uncertainty. Impact of
information technology revolution upon banking has been widely discussed.
Banking industry has formed suitable grounds to apply technological innovation
because banking activities are easily digitized and automated [1, 2].
Possibilities to exploit advanced
technologies among other in service delivery have created challenges to
developers of financial services; competitive advantage can be gained in form
of costs reduction or customer satisfaction increase, or lost investing in
wrong technologies. In order to rise to the challenges service providers are
even more interested to enhance their understanding of consumer behavior
patterns. This paper examines factors affecting the adoption of mobile banking
services. Electronic banking, in its diversified forms, represents an
innovation in which both intangible service and an innovative medium of service
delivery employing high technology convergence. In using the term electronic
banking we refer to a definition, which explains it as the provision of
information and services by a bank to its customers via electronic wired or
wireless channels, for example Internet, telephone, mobile phone or interactive
television [3].
The move away from traditional branch
banking has also been encouraged by the current enthusiasm for banking
technologies. Emergence of the Internet had a significant impact on the
diffusion of electronic banking. Along with Internet diffusion the first
Internet-based banking service system was launched in 1996 in
Especially Northern European countries are
among the most advanced ones in the adoption to and use of different new mobile
and technological appliances [6]. In Finland payments and account management
products over mobile GSM phones as SMS service have been available over one
decade, exactly since 1992, television-based banking since 1998 and banking via
mobile Internet WAP since 1999 [7]. And furthermore, mobile phone penetration
amounted to 94 % in year 2002. On that grounds diffusion of mobile banking in
Finland seems to have a bright future (see Figure 1). Currently, mobile banking
services such as conducting account balance and transaction history inquires,
funds transfer, bill payments, stock trades and quotes, portfolio management as
well as insurance ordering are technologically enabled via a mobile device.
Diffusion and adoption of Internet banking
have received academic research attention in recent years [3; 4; 8]. However,
mobile phones have characteristics in use that differ sharply from wired line
devices. They are truly portable, seldom used by others, and increasingly, constantly
connected to an always on network. Mobile phone inhabits also far more intimate
space in our daily lives than television or personal computer. Thus, few of the
marketing and consumer behavior patterns applied in wired line environment are
directly applicable to wireless services [9]. Admittedly, research on Internet
banking as well as on mobile services can act as a valuable starting point as
suggested by Pedersen and Ling [10].
As the technology has become increasingly
more vital element of service delivery, managerial interest in understanding
the adoption processes, preferences and needs of different customers has led to
calls for more academic research. This paper aims at answering that call by
shedding light on the factors influencing the adoption of mobile banking
services. The survey was conducted among Finnish bank customers. The approach
we employ is practical and provides insights drawn from the quantitative
empirical survey. The paper is organized as follows: it begins with a brief
literature review in order to provide theoretical background for the study.
Thereafter, the methodology and data collection are described and the empirical
implications of the survey explained. The paper concludes with a development of
a model applicable to this case.
Figure
1 Penetration of electronic banking (on-line
agreements/ population%)
and
introduction of certain electronic delivery channels in
50 %
■
30 %
■
■
10 % ■
∙■
0 %
90 91 92
93 94 95
96 97 98
99 2000
2. Factors influencing the technology-based
services adoption
In the search to understand consumers’
adoption of innovation, and where research has focused on the consumer
perspective, Rogers’ [14] synthesis of diffusion studies, which originally
dates back to 1962, has often been employed [11; 12]. In their article Mahajan et al. [13] give a pretty comprehensive overview to
facilitating the mapping of diffusion patterns in different contexts.
Theoretical framework of this paper follows this traditional innovation
diffusion research. Although our approach is practically oriented contributing
to the research area by applying existing knowledge and research to a new context.
Academic literature has identified factors
that encourage diffusion of an innovation in general terms. From an
organization’s point of view the factors include i.a.
achievement of competitive advantage, reducing costs, protecting an organization’s
strategic position in the market. As a service supplier banks are also forced
to response to the changes in organization’s internal and external environment
variables [1; 15]. From consumer’s point of view factors influencing adoption
of a certain innovation are often perceived as benefits and costs relating to
the usage. Availability, 24/7 access, independence of time and place and
portability are often mentioned as key benefits and selling points of the
mobile applications. According to Keen and Mackintosh [25], the key value
proposition of mobility is creation of choice or new freedom for customers.
Similarly, words commonly used to describe main value-adding features of mobile
communication include flexibility, convenience, ubiquity, localization, personalization
and instant connectivity. However, all these features are valid differently for
different mobile services and customers [23]. If mobility aspect will be the
most valued feature by customers in the future, the wireless connections gain
advantage over wired connections in banking too.
At a fundamental level the adoption decision
of a consumer is governed by supply and demand side factors, meaning there has
to be customer demand for new electronic banking modes and the available supply
of new technology-based services provided by financial institutions. It is
apparent that most financial services providers have no other option than to
jump onto the bandwagon of electronic banking, for example due to competitive
and cots-efficiency pressures, and provide services also via these new delivery
channels. This has resulted to the introduction of automated or digitalized
service delivery systems, or self-service technologies from customer point of
view. In other words, supply and demand side factors are often to some extent
given by the marketplace situation. Literature on self-service technology
innovations and adoption [see e.g. 21, 22] provide a relevant reference point
in investigating service offerings employing technology.
Furthermore, within Internet banking
adoption literature researchers have identified industry and banking specific
drivers of electronic banking. These include protection of reputation, intense
competition, cost savings, mass customization, enhancement of marketing and communication
activities, and retention and attraction of customers [14; 24]. And contrary to
these motivating factors, security concerns have often been highlighted as the
most important issue delaying the diffusion. Lack of user-friendly technology
and customer demand, high initial set-up costs, redundancy of existing high
cost legacy systems and lack of suitable skills have acted as inhibiting
factors of Internet banking from a bank’s point of view [3]. Gatignon and Robertson [26] made an interesting finding on
the basis of their review of adoption research. Within adoption framework of
technology-based product innovation, where no prior data of a totally new
product or service concept exists, some conclusion can be drawn from adoption
experiences of other products within the product category. Similarly, Hirschman
[27] has suggested that prior experience with a product category (e.g. Internet
banking) may lead to greater acceptability of new products (e.g. mobile
banking), hence increasing likelihood they will be adopted. Yet, the above
discussed differences between wireless and wired line environment have to be
kept in mind.
3. Methodology and data collection
The methodological approach in this study is
descriptive, the phenomenon to be studied is comparatively new in the field of
academic research and thereby study aims at increasing the understanding of the
current consumer behavior pattern in the electronic services era, and
particularly in mobile banking [28]. The pre-tested questionnaires with a covering
letter from
The survey sample consisted of three
equal-sized segments that were selected according to mobile banking usage
experience and density. The non-users had never used permanently any form of
mobile banking services, the occasional users had started to use some form of
mobile services and the regular users had been using the services for a longer
period of time. The questionnaires were also partly tailored respectively. This
data form the basis of the whole research of which this paper is one part. In
the whole study the Cronbach’s alpha varied from
0.6209 to 0.9538, which is considered acceptable for exploratory research [29].
Only the selected sections of the survey data will be used in the present
paper. The consumer perspective was the focus in the whole study whereby we
examined i.a. demographic variables as indicators of
certain consumer behavior, presented a profile of typical mobile banking user
and described the relationships that exist between variables such as technology
perceptions and usage. Furthermore, applicability of
According to the chosen methodological
research approach the quantitative data were analyzed using statistical methods
by SPSS-program. Statistical methods such as means, standard deviations and
rotated factor analysis were found to be suitable for the data, of which the
main body consists of interval scale variables on a seven-point Likert attitude scale. In general exploratory factor
analysis is appropriate in cases where the underlying dimensions of the data
set are not known in advance, and in an effort to find a new set of variables,
fewer in number than the original variables, which expresses that which is
common among the original variables [30]. The demographic profile of the
respondents is summarized in Table 1.
Table 1
Demographic
profile of the respondents
Demographic Frequency Percentage Cumulative
Characteristics
percentage
Gender
Male 634 50.6 50.6
Female 590 47.1 97.7
Missing 29 2.3 100
Standard deviation 0.499
Age
Under 18 4 0.3 0.3
18-24 years 226 18 18.3
25-34 years 418 33.4 51.7
35-49 years 370 29.5 81.2
50-64 years 212 16.9 98.1
65 years and over 17 1.4 99.5
Missing 6 0.5 100
Standard deviation 1.026
Marital status
Married 488 38.9 38.9
Cohabitation 337 26.9 65.8
Single 322 25.7 91.5
Widow 13 1 92.5
Divorced 75 6 98.5
Missing 18 1.5 100
Standard deviation 1.113
Occupation
Executive 70 5.6 5.6
Worker 503 40.1 45.7
Not at work 84 6.7 52.4
White-collar worker 246 19.6 72
Student 132 10.5 82.5
Farmer 29 2.3 84.8
Pensioner 54 4.3 89.1
Entrepreneur 74 5.9 95
Public servant 49 3.9 98.9
Other 5 0.5 99.4
Missing 7 0.6 100
Standard deviation 2.183
Household income
Under 10.000 euros 109 8.7 8.7
10.001-20.000 euros 191 15.2 23.9
20.001-30.000 euros 239 19.1 43
30.001-40.000 euros 195 15.6 58.6
40.001-50.000 euros 181 14.4 73
50.001-60.000 euros 130 10.4 83.4
60.001-70.000 euros 67 5.3 88.7
70.001-80-000 euros 34 2.7 91.4
Over 80.001 euros 33 2.7 94.1
Missing 74 5.9 100
Standard deviation 1.988
4. Research findings
4.1 Factor analysis
Exploratory factor analysis was used in
order to identify underlying constructs and investigate relationships among key
survey interval-scaled questions regarding reasons for adopting and not
adopting mobile banking services. Principal axis factoring was carried out,
followed by varimax rotation with Kaiser
Normalization. The Kaiser-Meyer-Olkin (KMO) measures
of sampling adequacy (0.86 and 0.93) were well above the 0.5 recommendation
level, and Bartlett’s test of sphericity (p=0.0 and
p=0.0) provided as well support for the validity of the factor analysis of the
data set [31]. Varimax rotation facilitated herein
interpretability. In addition, Gronbach’s alphas were
counted; the scores were above accepted level [29]. Hence, the data set can be
defined as reliable. Deciding the number of factors to retain is difficult, but
initial runs based on a scree plot and eigenvalues showed support for two factors. The criterion
for assignment of reasons to a certain factor was a minimum factor loading of
0.5. The two-factor solution identified explained 59.5 % of the total variance
within the first question and 66.3 % of the total variance within the second
question.
Examination of the factor analysis for
drivers of mobile banking (Table 2) suggests that the first factor, which we
labeled “access”, accounts for 48.4 % of the total variance and is defined by
four variables with factor loadings. Factor one appears to represent variables
that constitute the value proposition of a wireless delivery channel and nature
of a handheld device. Mobile banking allows customers to access their accounts
from any location, at any time of the day. Today mobile phone is more often
carried always in a pocket and familiarity with the device is taken for
granted. Independent usage of mobile banking services seems to be valued by the
respondents. Previous studies [e.g. 16] have stated likewise that electronic
banking gives customers greater control over managing the finances. The second
factor accounts 11.1 % of the total variance and exhibits loadings for three
variables. We call here factor two “accelerating pace of development, positive
effect”, as the variable pace of development in mobile banking accounted
highest loadings (0.772). Technology has infused to the service encounters of
financial institutions. Knowledgeable and demanding customers assume that
banking service providers acting in technology driven environment will continue
to keep up with the development: apply technological innovation further in
service offerings and consequently ease up the everyday lives of the customers.
Enthusiasm with technological development itself is obviously a driver for
adoption of mobile banking. Thus, this is the manifestation of the factor
accelerating pace of development. Advantage in mobile banking is gained also in
savings in time and effort.
Factor 1: Access
Factor 2: Accelerating pace of development,
positive effect
Table 2 Drivers: Factor analysis
Reasons for using mobile banking services
Factor 1 Factor 2
Mobile phone is anyway a familiar device 0.540
Mobile phone is always with me 0.711
Using mobile banking is independent 0.794
Service quality does not change, it is routinized 0.645
Sufficient guidance in using mobile phone for
banking 0.546
Conducting banking is fast and effortless 0.634
Pace of development in mobile banking services is
fast 0.722
Initial eigenvalue 4.35 1.00
Total variance explained % 48.4 11.1
Extraction method: Principal Axis Factoring
Rotation method: Varimax
Cronbach’s alpha α = 0.8603
Factor analysis for inhibitors of mobile
banking (Table 3) suggests that the first factor accounts for 57.7 % of the
total variance and is defined by six variables. Factor one appears to be
defined by a mix of items that are reflections of problems in supplier side of
the services, for example too slow data transmission speed (0.692) or
complicated user interface (0.787). The negative effect of accelerating pace of
development is manifested in services that are launched in too early stage of
development process due to competitive and cost pressures. As a consequence
competence of service quality, as defined by Zeithaml
et al. [32], does not reach an adequate level, consumers feel that services are
not responding to their needs. An example of that is the support for the item
services are not enough versatile (0.832). In addition, emphasizing technology
in service offering may result in ignoring certain fundamental prerequisites
required for acceptance. Technology is enabler; way to build up a new delivery
channel, but communicating only technological features elides other elements of
service such as service content. Technology-based electronic delivery medium
does not constitute service offering and create value alone, but service content
(e.g. funds transfer or stock trades and quotes) has to function properly and
ways of usage have to be known. Factor two accounts for 8.57 % of total
variance. There the main impediment seems to be functionality of a mobile phone
as delivery medium for banking services. Mobile phone can be considered, to
some extent, as not being designed for this type of services, for example
keyboard is relatively small, which facilitates possibility of error in
typing.
Factor 1: Accelerating pace of development,
negative effect
Factor 2: Functional issues
Table 3 Inhibitors: Factor Analysis
Reasons for not using mobile banking services
Factor
1 Factor 2
Mobile banking services are
expensive 0.546
Insufficient guidance 0.588
Use has been a
disappointment 0.683
Too slow data transmission 0.692
Use is complicated 0.787
Mobile banking services are
not enough versatile 0.832
Possibility of errors
higher than in Internet banking 0.533
Using key code list with mobile
phone complicated 0.538
I do not want to use mobile
phone in banking 0.669
Mobile phone is an
unpractical device for banking 0.683
Initial eigenvalue 5.77 1.22
Total variance explained %
57.7 8.57
Extraction method: Principal Axis Factoring
Rotation method: Varimax
Cronbach’s alpha α = 0.6204
4.2 Importance measures
In addition to the factoring, further
descriptive findings were analyzed to provide a better understanding of
customers’ attitudes to various characteristics of mobile banking presented as
attributes in Tables 4 and 5. The most important attribute in encouraging the
use of mobile banking was related to the costs of conducting banking (mean
4.38, standard deviation 2.15). Wish of faster data transmission amounted to
secondly highest importance mean (mean 3.74, standard deviation 2.49).
Surprisingly, the third attribute mentioned to boost the mobile banking
adoption was authentication with mobile phone to Internet bank (mean 3.67,
standard deviation 2.60). Admittedly, the response pattern along different attributes
was pretty homogenous. The distinctly most important reason for the trial of
mobile banking was the possibility to conduct banking truly regardless of time
and place (mean 5.09, standard deviation 1.62). As secondly important was
mentioned to be novelty and curiosity towards using the services. This result
reflects the fact that mobile banking services are in relative early stage in
the diffusion path. Often the first adopters of an innovation are motivated by
just to get their hands on the latest and greatest innovation, on anything that
is truly brand-new [33].
As evidenced by importance means for
adoption impediments presented in Table 5, the highest scored importance means
relate to the above discussed problem with accelerating pace of development,
which leads to launching high-technology services in considerable early stage
of the product development phase, often too early. Consequence is that
consumers’ experiences with the service may end up being negative. In the end,
it should be noticed that overall ranging scores to these attributes were
relatively slow. The respondents have not had very significant problems with
mobile banking services.
Table 4 Adoption triggers:
Summary of means
Attribute Importance
Standard deviation
means
I would use mobile bank if I could
Pay bills cheaper 4.38 2.15
Have faster data
transmission rate 3.74 2.49
Authenticate with mobile
phone to Internet bank 3.67 2.60
Use chip card of mobile
phone as bank and credit card 3.56 2.51
Have substantially more
versatile services 3.47 2.40
Use services via other
mobile device than mobile phone 3.27 2.81
Use services without key
code list 3.02 2.51
Control mobile services by
voice instead of typing 3.01 2.57
Have personal education 2.61 2.35
I tried mobile banking services because of
Possibility to conduct
banking regardless of time and place 5.09 1.62
Novelty and curiosity 3.51 2.24
Savings in time 3.44 2.48
Savings in bill payment costs 3.36 2.47
Bank personnel’s advice 2.15 2.39
Dissatisfaction with
Internet banking 1.35 2.44
Advertisement 1.83 2.22
Friends’ and relatives’
recommendation and usage 1.62 2.35
Importance of conducting
banking independently/
Avoiding the contact with
bank personnel 1.58 2.25
Prestige and status 0.95 1.97
Notes: Scale ranging from 0= not at all important
effect to 6 = very important effect
TABLE 5 Adoption inhibitors: Summary of means
Attribute Importance
Standard deviation
means
If I had problems with usage of mobile
banking
services they related to
Slow data transmission 2.01 2.47
Insufficient guidance 1.95 2.44
Malfunction of services 1.91 2.41
Lacking operating instructions 1.76 2.35
Poor user interface 1.44 2.31
Dexterity 1.42 2.28
Lack of time 1.43 2.28
General difficulties in using mobile phone 1.41 2.26
Notes: Scale ranging from
0= not at all important effect to 6 = very important effect
5. Model development
On the basis of the literature review and
the above discussed empirical implications, factor analysis as well as
importance means, we developed a multidimensional model that outlines the
factors encouraging (drivers) and discouraging (inhibitors) mobile banking
adoption. The model shown in Figure 2 depicts three main dimensions assigned to
drivers or to inhibitors or to the both constructs. Mobility-specific factors
were proven to be the most significant triggers for mobile banking adoption.
The construct accelerating pace of development entails both encouraging as well
as discouraging aspects for mobile banking adoption. On one hand customers like
the idea of being up-to-date in technological advancement and on the other hand
being the early adopter means that they have to tolerate possible initial
glitches and invest time and effort in learning. Functional-specific factors
are the main impediments of mobile banking adoption. The adoption process of
mobile banking services seems to be most substantially inhibited by
functionality of mobile phone as a device for conducting banking.
The brackets in the model imply whether the
part of the model is more internal or external to the service providing
institution. The underpinning rationale herein stems from a thought that
certain factors in mobile banking adoption are more under control of the
service provider, and that there are supply and demand side boosting factors as
discussed earlier. The proposed model is not intended to be fully comprehensive
or universally applicable, but rather it should be viewed as one of the first
insights into this fairly unexamined and unknown territory of mobile banking
adoption.
Figure 2 Model of the underlying factors in
mobile banking adoption
DRIVERS INHIBITORS
external
internal
6. Conclusions
The recent developments in banking industry
have created a totally new service concept and service environment. Technology
has changed the very nature of selling and buying financial services. The
changing marketplace has forced financial institutions to be adaptive.
Customers are increasingly given the option or are being asked to provide
services for themselves via electronic delivery channels [35; 21]. In this
research we have defined several factors that act as a driver or as an
inhibitor for mobile banking adoption. The survey findings both provided
support for previous research on electronic banking discussed in context of
theoretical foundations of the paper and brought out interesting new
information, such as the contradicting impact of accelerating pace of
development. The paper presents a model that is usable by practitioners
investigating the acceptability and potential diffusion rate of these kinds of
new services. The model aims at conceptualizing different influencing factors
in mobile banking environment and delivering potential to generalize it to
introduction of future products along this line that are not yet being
marketed.
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Research Article IV
Mobile Banking and Consumer Behaviour – New Insights
into the
Diffusion Pattern
Accepted for
publication in Journal of Financial Services Marketing Vol. 8
Mobile
Banking and Consumer Behaviour – New Insights
into the Diffusion Pattern
Abstract
Technological advancement has challenged the
providers of financial services; the very nature of selling and buying
financial services has changed. Mobile devices are among the newest channels to
conduct banking electronically. The present paper focuses on studying diffusion
and adopters of mobile banking services. Previous research has identified the
typical characteristics of a potential adopter in electronic services era; this
paper explores some contradicting empirical findings drawn from mobile banking
survey. The results provided an indication of the characteristics of a
potential next adopter of mobile banking, and of differences between user
segments.
Consequently, we are able to comment on the
influence of certain demographic characteristics and preferred communication
mode of customers on the adoption and future usage of mobile banking services.
The quantitative survey that sheds more light on this researched issue employed
a traditional method of postal questionnaire. The data was collected in
Keywords: Innovation diffusion, mobile banking, demographics,
communication, intentions
1.
Introduction
Today’s banking takes place
increasingly online, financial institutions deliver their services via various
electronic channels and importance of a traditional branch network has
declined. The newly emerged channels and rapidly increasing penetration rates
of mobile phones are the motivators of this study. Technology has become an
increasingly vital element in the competitive landscape of the financial
service industry. The recent developments have created a totally new service
concept and service environment [1]. Technology has changed the very nature of
selling and buying financial services. Innovations in telecommunications have
led to the usage of mobile devices in banking services. Mobile banking is among
the newest electronic delivery channels to be offered by banks. In using the
term electronic banking we refer to a definition, which explains it as the
provision of information and services by a bank to its customers via electronic
wired or wireless channels, for example Internet, telephone, mobile phone or
interactive television [2]. Electronic banking is a high-order construct
consisting of several distribution channels and hence mobile banking is a
sub-set of electronic banking which utilises mobile
phone technology. Currently, conducting account balance and transaction history
inquires, funds transfer, bill payments, stock trades and quotes, portfolio
management as well as insurance ordering are technologically enabled via a
mobile device. Even though technology and applications for these services are
available, the usage rates internationally have been fairly low and, in fact,
in most developed countries financial institutions have only recently begun to
offer mobile services to customers. The mobile banking service market is still
in its infancies [3, 4]. The newly emerged mobile banking services represent an
innovation where both intangible service and an innovative medium of service
delivery employing high technology are present. Thus, concepts of innovation
and diffusion of innovation are even more intricate as technology and service
aspects have an effect on the characteristics of mobile banking services [5].
As the technology has become an increasingly vital element of service delivery,
managerial interest in understanding the adoption processes and different
customers as adopters has led to calls for more academic research. This paper
aims at answering that call by shedding light on the consumer behaviour in mobile services era and in particular on
influence of certain demographic characteristics on adoption. The survey was
conducted among Finnish bank customers. The approach we employ is practical and
provides insights drawn from the quantitative empirical survey.
It is argued that because of the above
mentioned complexity of the service models in general and the convergence of
technologies and services, there are very little relevant research available to
help us understand the adoption of mobile banking services [6]. However,
adoption of basic mobile services as well as Internet services has received research
attention in recent years. Pedersen and Ling [7] suggest that this research is
highly relevant and can provide valuable starting points understanding more
complex end-user services. In banking context much of the existing research
cover tele-banking [e.g. 8,9]
or Internet banking [e.g. 10,11,12] perspectives. Nevertheless, a lack of
studies directly investigating the adoption and diffusion patterns of the
mobile banking services is to be expected due to newness of the services.
Customer behaviour in mobile banking context has
remained rather uncharted territory, which further raises the value of the
contribution of this study.
The paper is organised
as follows: it begins with a brief review on the traditional standpoint of the
diffusion and adoption research as well as on current state of mobile banking
usage in
2.
Diffusion of
Diffusion Research
Theoretical framework of this
paper is based on the traditional innovation diffusion research.
Consequently, in diffusion
research interest is in aggregates of individual users, typically identified as
user segments or as other aggregate communities of users. Diffusion research
mainly focuses on describing and explaining the adoption process as a process
of innovation diffusion at the aggregate level. Studies focusing on description
typically characterise user segments along the
diffusion process, such as early adopters, early majority users and laggards
using demographic and socioeconomic variables [7]. This is also our main
research interest. Valuable research avenue examples exist, e.g. Mattila et al. [15] studied Internet adoption among mature
customers or Wei [16] studied the socioeconomic
characteristics of mobile phone laggards. These studies do not concentrate on
explaining the observed segment differences.
Bass diffusion model assumes
that potential adopters of an innovation are influenced by two types of
communication channels: mass media (external influence) and interpersonal
worth-of-mouth (internal influence) channels, with the latter much more
important. Individuals adopting based on mass media messages occur continually
throughout the diffusion process, but are concentrated in the relatively early
time periods. Individuals adopting as a result of interpersonal messages about
the new idea expand in numbers during the first half of the diffusion process,
and thereafter decline in numbers per time period, creating the S-shaped
diffusion curve. Further Bass model assumes that the rate of adoption during
the first half of the diffusion process is symmetrical with that in the second
half, as necessary for a S-shaped diffusion curve [13,14].
Place
here: FIGURE 1 Adoptions due to external and internal influence in the Bass
model [20]
Traditionally, the
Adopter Category Differences
Research literature states that
information about technological innovations can travel through a variety of
communications sources and modes to members of a social system [13]. For example, the two-step model of communication posits that
information flows from mass media (e.g. commercial advertisements) to opinion
leaders (innovators), and that the less active members of the society
(imitators) are subsequently influenced by interpersonal communication with
these innovative consumers [21]. One of the basic assumptions is that
innovators tent to be heavier users of professional communication sources, such
as sellers, governments and other third parties, than imitators and
non-adopters. Thus, preferred information source may differ across different
adopter categories and individuals may have different propensities for relying
on marketer-provided information, independent third-party information, and
information from personal sources [22]. Lee et al. [21] have found that
communication factors are indeed significant predictors of consumer adoption of
electronic banking innovations too.
Voluminous research literature
has accumulated about variables, such as socioeconomic or personality
characteristics of the potential adopters, related to innovativeness [13].
Earlier adopters of technological innovations are often stated to be relative
young, have higher income, more education, and higher social status
(professional, technical and managerial) occupations. According to Polatoglu and Ekin [23] and Howcroft et al. [9] demographic factors that describe
typical electronic banking services adopter include young, affluent and highly
educated. In earlier Finnish studies findings of the typical Internet banking
user were somewhat similar and in some respect contradictory. A Finnish study
[12] reported Internet banking user is middle-aged, relative wealthy and highly
educated. Gatignon and Robertson [24] made an
interesting finding on the basis of their review of adoption research. New
product innovators in technology-based products are likely to be drawn from
heavy users of other products within the product category. Adopters who adopt
earlier than others are likely to have more gain from the use of the product
and hence have a greater usage propensity. Additionally, it is argued that
adoption of complex products depends on adopter’s ability to develop new
knowledge and new patterns of experience. This ability can be enhanced by the
knowledge gained from related products. In Finland usage of Internet banking
has already diffused to masses of banking customers, on that basis a conclusion
might be drawn that Internet banking services can serve as related service
products to mobile banking services and that innovators of mobile banking are
drawn from the heavy-users of Internet banking.
Mobile Banking in
Before discussing methodological
standpoints and the empirical evidences of the survey relating to above
discussed issues it is worthwhile to give some insights into the current state
of mobile banking activities in
3. Methodology and Data Collection
The methodological approach in
this study is descriptive, because we attempt to identify and explain the
variables that exist in a given situation and, to describe the relationship
that exists between these variables, the intention being to provide a picture
of a particular phenomenon, rather than to ferret out cause-effect
relationships [27]. The phenomenon to be studied, mobile banking, is
comparatively new in the field of academic research and thereby study aims at
increasing the understanding of the current consumer behaviour
pattern in the electronic services era. The research data were collected by
means of a traditional postal survey during the summer of 2002. The pre-tested
questionnaire with a covering letter and a postage-paid return envelope was
sent to a cross section of 3 000 bank customers. The questionnaire was
administered to a stratified sample of Finnish bank customers, selected in
terms of their banking habits. The sampling frame from which the sample
elements were drawn was a customer database of one major Finnish bank. After
two follow-ups 1303 responses of which 1253 were usable were received. The
usable response rate amounted to 41.8 percent, which was really satisfactory
and above the 20-30 percent rate considered acceptable in economics research.
The survey sample consisted of three equal-sized groups that were selected
according to mobile banking usage experience and density. The non-users (38.8 percent
of the respondents) had never used permanently any form of mobile banking
services, the occasional users (33.2 percent of the respondents) had started to
use some form of mobile services and the regular users (28 percent of the
respondents) had been using services for a longer period of time. The
questionnaires were also partly tailored respectively. This data form the basis
of the whole research of which this paper is one part. Only the selected
sections of the survey data will be used in the present paper. According to the
chosen methodological research approach the quantitative data were analysed using statistical methods by SPSS-program. The
demographic profile of the respondents is summarised
in TABLE 1.
Place
here: TABLE 1 Demographic profile of the respondents
4. Empirical Implications
Information Sources
Referring to the Bass model of
diffusion we discuss the information sources (external and internal)
influencing and contributing to the adoption of mobile banking services. Based
on the information received from out empirical data, we know the respondents’
main sources of information about mobile banking services; and why the
customers tried mobile services in first place. The research results among so
called occasional users were consistent with Bass model arguments (FIGURE 2).
Most of the occasional users, 46.7 percent, had been exposed to interpersonal
influence, namely recommendations by bank’s personnel. Importance of mass media exposure was not equally
significant, 16.4 percent of respondents were influenced by bank’s direct
marketing activity (letter) and 15.7 percent by bank’s advertisement. In the
very beginning of the diffusion process it is typical that adoptions are more
due to external influence, i.e. mass media, and as the process continues
internal influences gain in importance. Occasional users of this survey may be characterised to consist of both innovator and imitators as
defined by Bass. In the group of so called non-users 36.3 percent of the
respondents had heard about mobile banking services through mass media, banks’
advertisements. And 26.1 percent of respondents have had bank’s letter as
information source and 19.5 percent bank’s personnel, in other words, the
results confirm the communication source and mode pattern presented in the
literature. Our findings are consistent with that of Lee’s et al. [21],
financial institutions are currently the most active diffusion agents for
customers as well as receiving written information from financial institutions
is likely to increase the probability of adopting electronic banking
innovations such as mobile banking services.
Place here: FIGURE 2 Information sources
Adopter Category Differences: Age and
Household Income
Following the rationale of
diffusion research, our interest focused on investigating intentions of
customers of different age and income category to begin the usage of mobile
services in the future, or intentions of customers who already use those
services to continue and increase their usage. In order to gain a realistic
picture of adoption intention it is worthwhile to discuss proportional
percentages of intentions in the age category of the user groups of
non-users/occasional users/regular users respectively. Proportional percentages
in the figures indicate the actual number of respondents who indicated a
positive intention response in relation to the number of respondents who fit
into each age or later income category. The FIGURE 3 depicts the results.
Place here: FIGURE
3 Intention to begin regular usage of mobile banking services presented
proportional among the user groups by age category
As it can be seen from the FIGURE 3 in the current non-users group the most
eager ones to begin the usage are the 50 years or over old customers. Two
of three respondents (30.2 percent in age group 50-64 years old and 35.5
percent in age group 65 years and over) stated that they will begin to use
mobile banking in the near future. Another very interesting implication from
the figure is that middle-aged are not very willing to begin usage of the
services. According to other Finnish studies [e.g. 12] on electronic banking
middle-aged customers are just the main users of Internet banking. In terms of age category, intentions of
occasional users to adopt mobile banking seem to follow the traditional way of
thinking in adoption and diffusion pattern research meaning younger customers
are more willing to adopt an innovation than older customers.
The
FIGURE 4 illustrates that among the
occasional users group customers who have annual household income level fewer
than 50.000 euros are more willing to begin usage, whereas customers
earning more have lower intention to use mobile delivery channel. The non-users
are in general willing to a lesser degree. Averagely half of the all customers
in each household income category are going to conduct their banking through
mobile channel.
Place here: FIGURE
4 Intention to begin regular usage of mobile banking services presented
proportional among the user groups by household income category
Our research interest included
also the current mobile delivery channel usage of so called regular users of
the survey and diffusion development among this user group. Even though regular
users can be considered to be the customers who have already made a favourable adoption decision, we cannot forget that
individual’s innovation decision is not only an instantaneous act but rather a
process consisting of a series of actions and decisions in which reversing a
previous decision may occur.
Place here: FIGURE
5 Intention to continue regular usage of mobile banking services presented
proportional among the user group by age category
The same trend of future usage intentions
among regular users can be seen in FIGURE 6, in terms of household income
category, approximately half of the customers are going to use mobile delivery
channel as their main banking service delivery channel. An interesting question
emerges: why are today’s mobile banking services users not more willing to
continue and increase their usage? And what are the underlying factors causing
that development? Answers to these questions of high importance have been
discussed and covered in the scope of the whole study, but are not touched in
detail in this paper. However, figures indicate indisputably that the mobile
banking services are not yet fully institutionalised
and routinised into the ongoing practice and way of
life of the adopters.
Place here: FIGURE
6 Intention to continue regular usage of mobile banking services presented
proportional among the user group by household income category
5. Conclusions
The paper provided new
interesting insights into the diffusion pattern of mobile banking services
adopters - and maybe not so surprisingly. As Pedersen and Ling [7] have noticed
within the research area of these new services, whereby technology, service as
well as human-interaction aspects convergence, traditional diffusion models
need to be extended and modified. In consequence, we are able to gain more
comprehensive understanding of value-added mobile services, such as mobile
banking, as well as draw conclusions that contribute not only to the theory but
also to practice of mobile service development.
In a management context, several
of our findings are apposite to financial services providers to better
understand diffusion of mobile banking services and characteristics of the
prospective adopters. Number of issues is worth mentioning. High hopes for the
diffusion of mobile services in banking are not completely unfound. With the
high market penetration of mobile phones and the optimally designed marketing
tactics of service providers, exposure to mobile technology increases which has
founded to be likely to facilitate the adoption [29]. Several differences among
the three user groups in relation to their adoption of mobile banking services
innovation were discussed and indicators therein included adopters’
communication source, age and household income. Managerial and practical
implications follow.
The way how financial services
providers disseminate information about new service products, meaning for
example how they allocate resources on training sales personnel or on
advertising campaigns, affects to which segment of customers (innovators or
imitators) the message comes across most. A bank’s communication style should
be compatible with the information processing styles of potential adopters.
According to the findings the more experienced customers, occasional users,
were more informed by interpersonal communication and less experienced,
non-users, by mass media. Applying the notion of segmentation is useful in this
context too; disseminating information through the right channel and the right
mode of communication for different consumer segments will likely increase each
segment’s probability to adopt technological innovations.
In literature it has been found
that age is a demographic variable that is a strong indicator of innovativeness.
The growing market segment, the elderly, has traditionally been considered
resistant to change and having negative attitudes towards technology [30].
Whereas
Internet banking surveys state
that wealthier customers are more willing to adopt and use technology-based
services. Traditional literature suggests that wealthier people are more likely
to adopt innovations earlier [13]. In this survey the clear indication was that
wealthier respondents were less willing to adopt the new mobile banking
services. The adoption framework that we were able to form in the survey
context implies that it is not just the paradigm of service environment that is
changing but also the typology of electronic service user. It seems that
typical Internet banking users will continue the usage of wired delivery
channel and the current users of bill payment automatic and branch offices will
more likely “leap” to usage of mobile banking.
Internet banking is obviously not the related service product category
in a way as suggested by Gatignon and Robertson [24].
Furthermore, new mobile banking innovators are not likely to be drawn from
heavy users of Internet banking services; they will more probably stick to
Internet. Drawing from that we argue it is more reasonable for banks not to
invest in convincing the regular Internet banking users to change from one
electronic channel to other but to try to inform and stimulate customers
outside this segment about advantages of mobile banking. The conclusion
provides further reasoning why Internet designed services and strategies cannot
directly be converted into mobile service environment: differentiation is
needed.
It should be noted that this study examined
mobile banking only in
Even though the sky of mobile
banking is now blue and clear the thunderclouds may arise if the questions we
pointed out in the end of empirical evidence section are not thoroughly
investigated. And this is the next research avenue we will step on.
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TABLE 1 Demographic profile of the
respondents
Demographic Frequency Percentage Cumulative
Characteristics
percentage
Gender
Male 634 50.6 50.6
Female 590 47.1 97.7
Missing 29 2.3 100
Standard deviation 0.499
Age
Under 18 4 0.3 0.3
18-24 years 226 18 18.3
25-34 years 418 33.4 51.7
35-49 years 370 29.5 81.2
50-64 years 212 16.9 98.1
65 years and over 17 1.4 99.5
Missing 6 0.5 100
Standard deviation 1.026
Marital status
Married 488 38.9 38.9
Cohabitation 337 26.9 65.8
Single 322 25.7 91.5
Widow 13 1 92.5
Divorced 75 6 98.5
Missing 18 1.5 100
Standard deviation 1.113
Occupation
Executive 70 5.6 5.6
Worker 503 40.1 45.7
Not at work 84 6.7 52.4
White-collar worker 246 19.6 72
Student 132 10.5 82.5
Farmer 29 2.3 84.8
Pensioner 54 4.3 89.1
Entrepreneur 74 5.9 95
Public servant 49 3.9 98.9
Other 5 0.5 99.4
Missing 7 0.6 100
Standard deviation 2.183
Household income
Under 10.000 euros 109 8.7 8.7
10.001-20.000 euros 191 15.2 23.9
20.001-30.000 euros 239 19.1 43
30.001-40.000 euros 195 15.6 58.6
40.001-50.000 euros 181 14.4 73
50.001-60.000 euros 130 10.4 83.4
60.001-70.000 euros 67 5.3 88.7
70.001-80-000 euros 34 2.7 91.4
Over 80.001 euros 33 2.7 94.1
Missing 74 5.9 100
Standard deviation 1.988
FIGURE 1 Adoptions due to
external and internal influences in the Bass Model [20]
FIGURE 2 Information sources
FIGURE 3 Intention to begin regular usage of
mobile banking services presented
proportional among the user group by age category
Χ2 = 91.13, p = .000 Cramer’s
V = .413
Note!
Under 18 years old represents only 0.3 % of all respondents
FIGURE 4 Intention to begin regular usage of
mobile banking services presented
proportional among the user groups by household income
category
Χ2 = 28.59, p = .433 Cramer’s V = .145
FIGURE 5 Intention to continue regular usage
of mobile banking services presented proportional among the user group by age
category
Χ2 = 28.59, p = .433 Cramer’s
V = .145
FIGURE 6 Intention to continue regular usage
of mobile banking services presented proportional among the user group by
household income category
Χ2 = 52.03, p = .626 Cramer’s
V = .153
YHTEENVETO (FINNISH
SUMMARY)
Mobiilipankkipalveluiden adoptio Suomessa
Nopeat muutokset pankkien
toimintaympäristössä - kilpailun kiristyminen uusien perinteisen
pankkiliiketoiminnan ulkopuolelta tulevien toimijoiden taholta,
tuoteinnovaatiot, pankkitoiminnan globalisaatio ja teknologinen kehitys - ovat
johtaneet siihen, että kilpailu asiakkaista on entistäkin kovempaa. Seurauksena
pankit ovatkin siirtyneet tarjoamaan palveluitaan yhä useampien jakelukanavien kautta.
Innovatiivisten palvelutuotteiden, laajemman palveluvalikoiman ja useiden
jakelukanavavaihtoehtojen kehittämisen tavoitteena on ollut tyytyväisempi
asiakas ja parantunut tehokkuus. Elektronisten jakelukanavien luominen on ollut
osa kehitystä kohti tuota tavoitetta.
Tässä
tutkimuksessa keskitytään tutkimaan yhtä näistä elektronisista kanavista, mobiilin päätelaitteen välityksellä käytettäviä palveluita
ts. mobiili-pankkipalveluita. Tarkoituksena on
selvittää mobiilipalveluiden käyttämistä yleisesti,
pankkipalveluiden käyttämistä langattoman kanavan kautta, ja erityisesti palveluiden
käyttöönoton tai käyttämättömyyden syitä ja uskomuksia kuluttajakäyttäytymisen
taustalla. Mobiilipankkipalvelut
nähdään innovaationa pankkitoimialalla, siksi teoreettisena lähtökohtana
tutkimuksessa on käytetty perinteistä markkinoinnin tutkimusalaan kuuluvaa
innovaation diffuusion teoriaa ja toisaalta kuluttajanäkökulmasta tarkasteltuna
on kysymys innovaation omaksumisesta, adoptiosta. Tutkimuksen viitekehyksen
muodostamiseksi on tutustuttu aikaisempaan empiiriseen tutkimukseen koskien
teknologiapohjaisen palvelutuotteen erityispiirteitä, diffuusiota ja adoptiota,
sekä elektronista pankkitoimintaa, joka useimmiten on tarkoittanut
Internet-pankkia. Lähtö-kohdiltaan tutkimuksen kontribuutio on soveltaa näitä
teoreettisia näkökulmia täysin uudelle sovellusalueelle.
Mobiilipankkiliiketoimintaa
käsitteleviä tutkimustuloksia tai tieteellisiä selontekoja ei ole toistaiseksi
juurikaan julkaistu, mikä edelleen lisää tutkimusalueen kiinnostavuutta. Kansainvälisesti
mobiilipankkipalveluiden käyttäjämäärät ovat olleet
vielä vähäisiä. Kuitenkin kilpailulliset ja kustannus-tehokkuuspaineet, samoin
kuin langattoman tiedonsiirron nopeutuminen ja kolmannen sukupolven
matkapuhelinten käyttöönotto muuttavat mobiilia
toimintaympäristöä parhaillaan, ja siten tulevat lisäämään erilaisten mobiilipalveluiden käyttöä, niihin kohdistuvaa kiinnostusta
ja tutkimustulosten hyödyntämisen mahdollisuuksia. Metodologiselta taustaltaan
tutkimus luokitellaan positivistiseksi, kuvailevaksi tutkimukseksi, jolle on
tyypillistä, että tutkimusilmiötä pyritään selittämään ja ennustamaan; siitä
pyritään luomaan kuva tai malli, jossa eri tekijöiden väliset vaikutussuhteet
tulevat ilmi.
Tutkimusaineisto koottiin touko-heinäkuussa 2002
postikyselyn avulla, jonka yhteydessä lähetettiin 3000 kyselykaavaketta pankin
asiakkaille. Otos koostuu tasaisesti ympäri Suomea asuvista asiakkaista, eikä
otosta ollut rajoitettu demograafisten muuttujien suhteen. Sen sijaan otos oli
jaettu kolmeen yhtä-suureen osaan mobiilipankkipalveluiden
käytön suhteen (1000 kyselykaavaketta kullekin ryhmälle). Ns. ei-käyttäjät
eivät olleet koskaan hoitaneet pankkiasiointiaan mobiilikanavan
välityksellä, satunnaiset käyttäjät olivat aloittaneet mobiilipankkipalveluiden
käytön ja säännölliset käyttäjät olivat hoitaneet pankkiasiointiaan tätä
kanavaa käyttäen jo pidemmän aikaa. Kyselykaavake oli osittain räätälöity nämä
käyttäjäryhmät huomioiden. Vastauksia palautettiin yhteensä 1303 kappaletta,
joista 1253 hyväksyttiin analysoitavaksi tutkimusaineistoksi.
Vastausprosentiksi saatiin 41,8 prosenttia. Valitun tutkimusmetodologisen
lähestymistavan mukaisesti kvantitatiivista aineistoa analysoitiin
tilastotieteellisillä menetelmillä.
Tutkimuksessa
kehitetty mallia testattiin hypoteesien avulla, joiden mukaisesti mobiilipankkipalveluiden adoptioon vaikuttavia tekijöitä
ovat: omaksumisesta seuraava suhteellinen hyöty, innovaation monimutkaisuus,
innovaation yhteensopivuus kuluttajan arvojen ja aikaisempien kokemusten
kanssa, havainnollisuus, testattavuus ja adoptioon liitettävä havaittu riski.
Lisäksi palveluiden omaksumiseen vaikuttavat käytetyt kommunikaatiokanavat,
sekä kuluttajan ominaisuudet, kuten demografiset tekijät ja
teknologiasuhtautuminen.
Tutkimuksen
empirian tuloksista nousi esille mielenkiintoisia uusia näkökulmia
pankkipalveluihin liittyvään kuluttajakäyttäytymiseen. Keskeinen tavoite
tutkimuksessa oli määrittää mobiilipankkipalveluiden
käyttäjän tyypillinen profiili. Aineiston mukaan mobiilikanavaa
käyttävä henkilö on naimisissa oleva mies tai nainen, 25 – 34 –vuotias, keskiasteen koulutuksen
omaava, keskituloinen ja työskentelee työntekijänä palvelusektorilla.
Muuttujista iällä ja koulutustaustalla havaittiin olevan suuri merkitys mobiilikanavan kautta tapahtuvan pankkiasioinnin suhteen.
Tämä tulos poikkeaa aikaisemmista tutkimustuloksista, joiden mukaisesti
innovaatioiden, ja erityisesti mobiilipalveluiden,
omaksujat ovat korkeastikoulutettuja, suhteellisen
suurituloisia ja usein johtavassa asemassa olevia.
Näiden
tulosten perusteella voidaan tehdä eräs tutkimuksen mielen-kiintoisimmista
johtopäätöksistä. Yhä useampi mobiilipankkipalvelut
omaksuva kuluttaja ei otakaan ensin käyttöönsä Internet-pankkipalveluita ja
siirry sitten mobiilikanavan käyttäjäksi, kuten
adoptioteoriat olettavat, vaan he ikään kuin ”hyppäävät” tämän vaiheen ohi ja
siirtyvät suoraan mobiilipankkipalveluiden
käyttäjiksi. Kuluttajat, joilla ei ole minkäänlaista kokemusta pankin
elektronisista palvelukanavista, aikovat siis ottaa ensimmäisinä elektronisen
pankin kanavana käyttöönsä mobiilipalvelut. Sitä
vastoin vakiintuneet Internet-pankin käyttäjät ovat haluttomampia vaihtamaan
palvelukanavaa, he hoitavat pankkiasioitaan vain satunnaisesti
matkapuhelimella. Ikä ei näyttäsi olevan myöskään este palveluiden
käyttämiselle. Tämänhetkisistä ei-käyttäjistä innokkaimpia kokeilemaan mobiilipalveluita ovat yli 50-vuotiaat asiakkaat.
Mobiilipankkipalveluiden omaksumista vauhdittavia tekijöinä
esille nousivat mm. pankkiasioinnin nopeus
ja vaivattomuus, saatavuus ajasta ja paikasta riippumatta, itsenäisyys, säästöt
vaivassa ja rahallisissa kustannuksissa, sekä palveluiden jatkuva kehittäminen.
Näistä tekijöistä muodostuu hyöty kuluttajalle. Mobiilipankkipalvelut
koettiin yhteensopiviksi kuluttajien arvojen ja aikaisempien kokemuksien
kanssa. Osaltaan tähän tulokseen vaikuttaa se seikka, että
teknologiasuhtautuminen kaikissa eri käyttäjäryhmissä oli yleisellä tasolla
positiivinen ja suomalaiset pankkiasiakkaat ovat tottuneita matkapuhelimen
käyttäjiä. Innovaation monimutkaisuus ei osoittautunut merkittäväksi tekijäksi;
käyttäjät eivät muistaneet kohdanneensa huomattavia ongelmia palvelun
käyttöönottovaiheessa.
Mobiilipankkipalveluita ei käytetty mm. siitä syystä, että
niitä ei pidetty riittävän monipuolisina, niiden käyttäminen koettiin
hankalaksi ja matkapuhelin epäkäytännölliseksi pankkiasioinnin välineeksi.
Mahdollisuudesta käyttää pankkipalveluita mobiilikanavan
kautta vastaajat olivat kuulleet sekä massamedian että henkilöidenvälisten
kommunikaatiokanavien välityksellä, mikä vastaa esim. Bass’n
(1969) teorian olettamuksia. Tärkein informaationlähde satunnaisille
käyttäjille oli ollut pankin henkilökunta ja ei-käyttäjille mainokset. Sitä
vastoin vastaajat eivät kokeneet merkittävänä riskinä mobiilikanavaan
liittyviä turvallisuuskysymyksiä, vaan mobiilipankkipalvelut
nähtiin luotettavana tapana hoitaa pankkiasiointia. Rutiininomaiset,
yksinkertaiset pankkipalvelut, kuten saldo- ja tilitapahtumakysely ja laskunmaksu,
koettiin soveltuvimmiksi käyttää mobiilipankkipalveluina,
kun taas lainahakemukset, valuutan tilaus ja lainopilliset palvelut hoidetaan
mieluummin pankkikonttorissa. Pääsääntöisesti WAP- palveluita käyttävät
asiakkaat käyttävät lisäksi asiointikanavanaan Internet-pankkia ja pankin
tekstiviestipalveluita, SMS-asiakkaat puolestaan
sekakäyttävät Internet-pankkipalveluita, mutta eivät WAP-palveluita.
Tutkimuksessa
saatiin konkreettisia tuloksia mobiilipalveluiden
käyttämisestä yleisesti nyt ja tulevaisuudessa, sekä mobiilipankkipalveluiden
adoptioon positiivisesti että negatiivisesti vaikuttavista tekijöistä. Näiden
johtopäätösten perusteella voidaan tehdä päätöksiä siitä miten mobiili-pankkipalveluita tulisi kehittää, jotta ne paremmin
vastaisivat kuluttajan tarpeisiin. Tuloksia voidaan hyödyntää sekä uusien
kohderyhmien löytämisessä nykyisille palveluille, että mahdollisten uusien
tuotekonseptien ominaisuuksien määrittämisessä. Siten saadaan työkaluja
parempaan asiakkuuden hallintaan.
Tutkimuksen kuluessa uusia ajatuksia on
herännyt ja kysymyksiä noussut esille, joista voidaan muodostaa mahdollisia
lisätutkimusaiheita. Olisi mielenkiintoista nähdä, millaisia tuloksia
pitkittäistutkimuksen suorittaminen toisi esille tutkimusilmiöstä; eteneekö mobiilipankki-innovaation diffuusio näiden tutkimustulosten
perusteella tehtyjen olettamusten mukaisesti? Eräs jatkopohdiskelun kohde voisi
olla myös kansainvälisen aspektin lisääminen otokseen ja tutkimuksen
suorittaminen eri kulttuuritaustat ja teknologisen ympäristön omaavien
kuluttajien keskuudessa
