INBCT 4.1
Mari Suoranta
Minna
Mattila
TECHNOLOGY-BASED SERVICE PRODUCTS – A STUDY ON THE
DRIVERS AND INHIBITORS OF MOBILE BANKING
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 influencing 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 Finland during May-July 2002 and
includes 1253 survey responses.
Keywords:
Electronic banking diffusion, mobile banking, technology-based services
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; market
uncertainty, technology uncertainty and competitive volatility. 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 (Bradley and Steward
2002; Daniel 1997).
Possibilities to exploit
advanced technologies among other in service delivery have created challenges
to financial services developers; competitive advantage can be gained in form
of costs reduction or customer satisfaction increase or lost in investing wrong
technologies. In order to rise to the challenges service provider are even more
interested to enhance their understanding of consumer behaviour patterns. This
paper examines factors influencing 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. 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).
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
Finland (Karjaluoto et al. 2002). Thereupon rapidly
changing technology has reshaped behavioral pattern how consumers interact with
their financial institutions. Consumers are also more technologically savvy
than ever, reducing their uneasiness involving technological innovation.
The infusion of new technologies in the services
sector is ubiquitous and continues to increase. Recently emerged wireless
delivery channel using mobile phones, Internet-enabled mobile phones and PDAs for banking services is one step along that path. The starting point
in investigating drivers and inhibitors of mobile banking adoption is to give
some insights into the mobile technology development in recent years. In
Western Europe the presence of a common GSM standard and the high penetration
rates of mobile phones have raised the expectations in mobile communication
development. And those high hopes came true; mobile technologies are growing hyperbolically.
Mobile devices have become the fastest adopted consumer product to data (Dholokia et al. 2003).
Especially
Northern European countries are among the most advanced ones in the adoption to
and use of different new mobile and technological appliances (Statistics
Finland 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). 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 has received academic research attention in
recent years (see e.g. Daniel 1999; Polatoglu and Ekin 2001; Karjaluoto et al.
2002). However, mobile phones have characteristics in use that differ sharply
from wired line devices: they are truly portable, seldom used by other, 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
(Gilbert and Kendall 2002). Even though, Internet banking as well as mobile
services research can act as a valuable starting point as suggested by Pedersen and
Ling (2003).
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 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 development of a model applicable to this
case.
50 %
■
30 %
■
■
10 % ■
∙■
0 %
90 91
92 93 94
95 96 97
98 99 2000
FIGURE 1 Penetration
of electronic banking (on-line agreements/ population %)
and introduction of certain electronic
delivery channels in Finland (Mattila and Pento 2002)
2. FACTORS INFLUNCING THE
TECHNOLOGY-BASED SERVICES ADOPTION
In the search to understand
consumers’ adoption of innovation, and where research has focused on the
consumer perspective, Rogers’ synthesis of diffusion studies, which originally
dates back to 1962, has often been employed (Howcroft
et al. 2002; Black et al. 2001). In their article Mahajan
et al. (1990) give a pretty comprehensive overview to facilitating the mapping
of diffusion patterns in different contexts. Academic literature has identified
factors that encourage diffusion of an innovation in general terms. These
include i.a. achievement of competitive advantage,
reducing costs, protecting an organisation’s strategic position in the markets.
Adoptions happen due to changes in organisation’s internal and external
environment variables (Bradley and Steward 2002; Gallouj
1998).
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. Following Rogers’ suggestion
that explanation for different diffusion paths can be found in attributes of
innovations being adopted, those studies have generally endorsed
evaluating the innovation along the product characteristics involving 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 service product itself as well as with electronic delivery channel is
higher than in basic consumer goods, and hence increasing the importance of
this attribute of innovation (Harrison 2000). Ensuring security and
confidentiality are the fundamental prerequisites before any banking activity
involving sensitive information can take place (Jayawardhena
and Foley 2000). 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.
At a fundamental level the
adoption decisions of a customer is governed by supply and demand side factors,
meaning there has to be consumer demand for new electronic banking modes and
the available supply of new technology 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. Meuter et al.
2002; Lee and Allaway 2002) provide a relevant
reference point in investigating service offerings employing technology.
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 (2001), 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, instant connectivity. However, all these features are valid differently for different mobile services and customers (Turban et al. 2002; Anckar and D’Incau 2002). 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.
Within
Internet banking adoption literature researchers have identified industry and
banking specific drivers of electronic banking adoption. These include
protection of reputation, intense competition, cost savings, mass
customization, enhancement of marketing and communication activities, and
retention and attraction of customers (Bradley and Steward 2002; Mols 2001). And contrary to these motivating factors,
security concerns have often been highlighted as the most important issue
delaying the diffusion. Furthermore, lack of user-friendly technology and
consumer 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 banks’ point of view (Daniel 1999). Gatignon
and Robertson (1985) 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 category. Similarly, Hirschman (1980) 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 behaviour pattern in electronic services
era, and particularly in mobile banking (Churchill and Iacobucci
2002). The research data was collected by means of a traditional postal survey.
The pre-tested questionnaire was sent to a gross section of 3000 bank customers
in Finland. This resulted to 1303 responses of which 1253 were usable i.e.
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 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 have not ever 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 services for a longer
period of time. The questionnaires were also partly tailored respectively. This
data forms 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 (Nunnally
1978).
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 was analysed 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 express that which is common among the original variables
(Steward 1981). 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 (Malhorta 1999). Varimax rotation facilitated interpretability. In addition,
Gronbach’s alpha was counted; the scores were above
accepted level (Nunnally 1978). 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 value proposition of the
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 taken for granted. Independent usage of mobile banking services
seems to be valued by the respondents. Previous studies (e.g. Tan and Teo 2000) 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. Advantage in mobile banking is gained also in
saving 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. 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.(1991), do not
reach an adequate level. In addition, emphasizing technology 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. Technologically enabled electronic delivery channel do not constitute
service offering and create value alone, but service content (e.g. funds transfer
or stock trades and quotes) have 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, not to be
designed for this type of services, for example keyboard is relatively small,
which facilitates possibilities of errors 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 the 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 accounted to the secondly highest
importance mean (mean 3.74, standard deviation 2.49). Surprisingly, the third
attribute mentioned to boost to 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. These results reflect the fact that
mobile banking services are in relative early state in a 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 (Mohr
2001).
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; high-technology services launched in
considerably early stage of the product development phase. 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
Key code list xxx 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
Saving 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 AND
CONCLUSIONS
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 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. The adoption process of mobile banking services seems to be
most substantially inhibited by functional-specific factors of a mobile phone.
The brackets imply whether the part of the model is more internal or external
to the service providing institution. 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.
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 (Bitner et al. 2000; Meuter 2000). In this research we have defined several
factors that act as a driver or as an inhibitor for mobile banking adoption. The
paper presents a model that is usable by practitioners investigating the
acceptability and potential diffusion rate of these kind new services. The
model aims at conceptualizing different influencing factors in electronic
banking environment and delivering potential to generalize it to introduction
of future products along this line that are not yet being marketed.
DRIVERS INHIBITORS
external
internal
FIGURE 2 Model for underlying
factors of mobile banking adoption
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