Consumers’ Attitudes towards Mobile Banking in Bangladesh
Mohammad Majedul Islam1
and Md. Enayet Hossain2
1 – Lecturer, Department of Marketing, University of Rajshahi, Rajshahi, Bangladesh
2 – Professor, Department of Marketing, University of Rajshahi, Rajshahi, Bangladesh
ABSTRACT
The aim of this study is to investigate the
factors influencing the consumer acceptance of
mobile banking in Bangladesh. The
demographic, attitudinal, and behavioural
characteristics of mobile bank users were
examined. 292 respondents from seven major
mobile financial service users of different
mobile network operators participated in the
consumer survey. Infrastructural facility, self-
control, social influence, perceived risk, ease
of use, need for interaction, perceived
usefulness, and customer service were found
to influence consumer attitudes towards
mobile banking services. The infrastructural
facility of updated user friendly technology
and its availability was found to be the most
important factor that motivated consumers’
attitudes in Bangladesh towards mobile
banking. The sample size was not necessarily
representative of the Bangladeshi population
as a whole as it ignored large rural population.
This study identified two additional factors i.e.
infrastructural facility and customer service
relevant to mobile banking that were absent in
previous researches. By addressing the
concerns of and benefits sought by the
consumers, marketers can create positive
attractions and policy makers can set
regulations for the expansion of mobile
banking services in Bangladesh. This study
offers an insight into mobile banking in
Bangladesh focusing influencing factors,
which has not previously been investigated.
KEYWORDS
Mobile Phone, Mobile Banking, Consumer
Attitude, Influencing Factors, and Bangladesh
Paper type Research paper
1. INTRODUCTION
Mobile banking is a system that allows
customers of mobile financial institution
(MFI) to offering banking services of
make deposits, withdraw, and to send or
receive funds from a mobile account
through a mobile device such as a mobile
phone or personal digital assistant. Mobile
banking offers services of banking like
account information; payments, deposits,
withdrawals, and transfers; investments;
ATM support; and content services.
Bangladesh Bank has introduced
permissions for mobile banking on July
2011 to promote market development.
Initially five banks have responded
positively to establish active deployments
where three largest of these were launched
immediately at the time of launching and
others in early 2012. By the end of the first
quarter of 2012 the fastest early expansion
has come from bKash (Brac Bank) and
Dutch Bangla Bank Limited (DBBL).
Most retail banks in Bangladesh is
providing online banking as add-on
services to the existing branch activities
while mobile banking is in the initial stage
of implementation. This service is enabled
here by the use of bank agents that allow
mobile account holders to transact at
independent agents locations outside of the
bank branches. This involves a sequenced
set of activities includes finding and
training agents, marketing to bring
attention to the service, and acquiring
customers using know-your-customer
(KYC) and account opening processes
while at the same time helping new
customers to begin to transact.
There are 55.6 million Bank accounts are
operating through branch banking in July
2012 which is only 36% of total
population. The maximum portion of the
population is outside from banking sector.
It is certainly shows a positive sign to
intensification of the capital flows by the
introduction of mobile banking. Within
two years of operation mobile banking
customers proliferated at 7.21 million in
September 2013 [43]. Though the
increasing rate is little fast mobile banking
customers are very low considering mobile
phone subscribers’ penetration rate or
coverage of rural population. The mobile
phone subscribers in Bangladesh are
109.35 million [46] and 71.9% people are
living in low banking coverage are in rural
[51]. So, enormous opportunities are
waiting for the banking industry of
Bangladesh in the platform of mobile
banking service.
The existing features are primarily
beneficial for the consumers. But all the
banks are not so much aggressive to attract
their respective customers. This research
aims to investigate the factors influencing
the consumer acceptance of mobile
banking so that MFIs can improve their
facilities and make people aware for the
development of banking sector in
Bangladesh.
2. LITERATURE REVIEW
2.1 Mobile Phone Banking
M-banking involves conducting account
balance and transaction history inquiries,
funds transfers, bill payments, stock
trades, portfolio management, as well as
insurance ordering, via a mobile device
[47]. An emerging component of M-
services that could become a significant
revenue source to both banks and telecom
service providers is M-banking [34]. It
provides value for consumers, above other
banking channels, through ubiquitous
access, time convenience, and mobility [4,
29]. The degree of interest and the
willingness to pay vary for individual
services; it seems to be necessary to design
specific services taking the needs and
wishes of relevant target groups into
consideration. Banks ought to therefore
employ mobile channels with a clear
business- focus [48]. The proliferation of
mobile phone adoption, together with
advances in mobile technology, has
accelerated the development of M-services
[45, 49]. Despite its many advantages, the
use of mobile phones in banking services
is still in its and Internet banking retains its
position as the leading channel in
electronic banking [11, 25]. The
emergence of mobile banking underscores
how, occasionally, innovations emerge
from unexpected places and have the
capability of reconfiguring the significance
of a technology to its users, offering a way
to lower the costs of moving money from
place to place and opening a way to bring
more users into contact with formal
financial [6]. There appears to be no set of
clearly identifiable variables that serve as a
basis for success and that those necessary
conditions for the replication of m-
banking models identified by the existing
literature to other countries around the
world do not guarantee results. Moreover,
we find that some of these conditions are
not present in countries where m-banking
models have been successful [16].
2.2 Consumer Attitude, Adoption,
Information, Environmental Influence
of Mobile Banking
The wide use of geographic, demographic,
socio-economic and psychographic
variables have not always been accepted as
good predictors in predicting buying
behaviour in financial services by past and
recent studies, which claimed that, the
benefits customers seek for in banking
services and/or the product attributes
should be identified instead [28, 30, 32].
Consumers’ motives also predetermine
consumers’ attitudes and behaviours
towards different banking technologies [7].
The findings increase the understanding of
customer-perceived value and value
creation on the basis of attributes of
mobile services and customer-perceived
disadvantages of mobile phones in
electronic banking context [23]. Perceived
usefulness, perceived risk, cost and
compatibility were found to affect
consumer acceptance of M-banking. The
results also support a mediation model,
whereby attitude transfers the effects of the
consumers’ perceptions to their intention
to use M-banking [50]. Usefulness, social
norms and social risk, in this order, are the
factors that influence the intention to adopt
mobile banking services the most. Ease of
use has a stronger influence on female
respondents than male, whereas relative
advantage has a stronger effect on
perception of usefulness on male
respondents. Social norms or the
importance of others in the decision, also
influence adoption more strongly among
female respondents than male [41]. The
information and guidance offered by a
bank has the most significant effect on
decreasing the usage barrier, followed by
image, value and risk barriers respectively.
The information and guidance showed no
effect on the tradition barrier [26].
Compatibility, perceived usefulness, and
risk are significant indicators for the
adoption of m-banking services.
Compatibility not only had a strong direct
effect but was also identified as an
important antecedent for perceived ease of
use, perceived usefulness and credibility.
Trust and credibility are crucial in
reducing the overall perceived risk of m-
banking [20]. Customer value perceptions
in banking actions differ between internet
and mobile channels. It suggests that
efficiency, convenience and safety are
salient in determining the differences in
customer value perceptions between
internet and mobile banking [25]. The
framework offers an integrated view,
taking into account more predictors than
other studies on the adoption of
innovations. It was also observed that the
predictors’ influence over the criterion
variable was different for each group of
mobile banking users and non-users [40].
It was found that perceived usefulness,
perceived social risk, perceived
performance risk and perceived benefit
directly affect attitudes towards mobile
banking, and that attitude is the major
determinant of mobile banking adoption
intention [2].
2.3 M-banking in Emerging Markets
Chinese online and mobile bank users
were predominantly males, not necessarily
young and highly educated, in contrast
with the electronic bank users in the West.
The issue of security was found to be the
most important factor that motivated
Chinese consumer adoption of online
banking. Main barriers to online banking
were the perception of risks, computer and
technological skills and Chinese traditional
cash-carry banking culture. The barriers to
mobile banking adoption were lack of
awareness and understanding of the
benefits provided by mobile banking [22].
In Africa, m- banking is now being added
on to the services offered to existing
customers by a number of retail banks and
this is likely to continue. However,
genuinely transformational models of m-
banking are few today; and they face
numerous obstacles. These include the
standard uncertainties about the pace and
scale of customer adoption, exacerbated by
the fact that low end models require higher
volumes of transactions to be viable [39].
Perception of cost, risk, low perceived
relative advantage and complexity were
revealed to be the main reasons behind the
reluctance to use the service. The influence
of other background factors is less evident
[11]. The residents of the study site use
mobile money for a variety of transactions
related to the personal and professional
lives in Bangladesh [1]. M-banking has the
potential to bring basic banking and
electronic transactions services to
unbanked consumers in developing
markets. But in enabling two-sided
markets, m-banking solutions also provide
specific questions for telecommunications
industry regulators [5]. The unbanked
require efficient utilization of varying
sources of cash inflows. Living off a cash‐
based economy, they receive irregular
income from occasional jobs, farm
produce, and “welfare”. Their limited
access to established financial channels
exposes them to financial risks and less
secure transactions [3]. To develop a good
distribution network, Vietnam Mobile
Services should build four elements into
its channel management execution
strategy: (i) engaging intermediaries to
help manage the individual stores; (ii)
ensuring that outlets were sufficiently
incentivized to actively promote the
service; (iii) maintaining tight control over
the customer experience; and (iv)
developing several different methods for
stores to re-balance their stocks [33]. In
Bangladesh, around 54% respondents
opinioned that this system is less costly
and time saving and 63% respondents felt
trust to this service. 83% respondents think
it is easier to access but this service is not
available for interbank transaction, as well
as the absence of regulatory framework
may lead to money laundering activities
[17].
3. RESEARCH OBJECTIVES
In Bangladesh, mobile banking has
introduced newly in the banking sector
targeting unbanked people for the essential
money transactions. The service is
growing with increasing rate as it seems
less costly and time saving. But it has
some technological difficulties for most of
the unbanked people. Therefore, the
objectives of the study were:
to figure out the demographic
characteristics of mobile banking
users; and
to ascertain the factors influence
consumer attitudes towards mobile
banking
4. METHODOLOGY
The questions in the questionnaire were
based on review of literatures and the
specific characteristics of Bangladeshi
people & market context. The specific
characteristics represented different
services and facilities provided by the
MFS institutions and expected by the MFS
consumers of Bangladesh. The
questionnaire was translated into Bengali
language to make clear and simple to
understand by every respondent. The items
in the questionnaire were constructed
based on the consumer attitude and
acceptance of mobile banking focusing:
Consumers’ attitudes and reactions
to mobile banking services
Consumers’ perceptions of mobile
banking service attributes
Consumers’ expectations and
major concerns of mobile banking
Demographic factors,
psychological factors, social factors, and
infrastructural factors
The constructs/factors have been adopted
from existing literatures and field survey.
Among eight factors six were espoused
from existing literatures those are
Perceived Usefulness [2, 11, 13, 14, 19,
20, 21, 22, 27, 31, 36, 41, 50, 53],
Perceived Risk [2, 8, 9, 10, 11, 12, 14, 15,
18, 20, 22, 24, 26, 27, 29, 37, 38, 41, 42,
44, 50, 52], Self-Control [22], Perceived
Ease of Use [2, 11, 13, 14, 41, 50], Need
for Interaction [12, 14, 41, 50], and Social
Influence [2, 14, 18, 41]. Along with the
six factors field survey had found another
two factors named Infrastructure Facility
(22% Respondents), and Customer Service
(17% Respondents).
The field study was carried out in June
2013 using empirical data. The sample size
decisions were primarily based on cost
considerations and in line with studies on
consumer attitude and acceptance of
mobile banking, where sample sizes used
were between 114 to 1,167 respondents. A
total 292 respondents from six divisions of
Bangladesh, including capital city, Dhaka,
were collected randomly at the time of
transaction from MFS agent stores through
interview. Respondents verbally replied to
a structured questionnaire and their
answers were recorded accordingly by the
interviewers.
The analysis was performed using eight
factors to rank their relative significance
and to describe their influences consumer
acceptance on MFS of the respondents.
Likert scale was used ranging from 1 to 6
response categories where 1 denotes don’t
know, 2 = not good, 3 = not so good, 4 =
good, 5 = very good, and 6 = excellent. As
far as scale-based variables were
concerned, principal factor analysis was
performed. In this study, the correlation
matrix was used to obtain Eigen values. To
facilitate the interpretation of factor
loading, VARIMAX rotation was
performed. SPSS software version 18 was
used for analysing the data.
5. DATA ANALYSIS AND RESULTS
5.1 Descriptive Statistics
Demographic characteristics of the study
were investigated in regards to the
respondents’ gender, age, occupation,
income, residence region, mobile financial
services (MFS) account, mobile network
operator (MNO) subscription, reason for
MFS account, monthly MFS transaction,
and purpose of MFS transactions. Missing
values, outliers, and distribution of all the
measured items were conducted to avoid
the error of the estimates and also to purify
the data. The demographic profile and
mobile banking history of the respondents
are summarized in Table 1. Most of the
respondents were at 18 to 25 years age
range (62.7%), which implies that mostly
students (55.1%) are using MFS for
mobile banking. Male and female ratio of
the respondents was 84.6% and 15.4%
respectively.
It indicates female respondents are less to
operate mobile banking directly. Income
range of the respondents is less than BDT
10,000 and they are covering most of the
regions of Bangladesh except Barisal
(2.1%). Mobile banking users are having
mostly Dutch Bangla Bank Ltd. (DBBL)
and bkash account for using MFS which is
45.9% and 46.9% respectively where they
are favouring Grameen Phone (GP) at
66.1% as MNO subscription. Respondents
have opened mobile banking account
mostly for easy money transfer (82.2%)
for personal need (83.6%) of money
receive or payment, and doing maximum
five transaction (65.8%) in a month.
In Table 2 the descriptive statistics of
different individual items has been
presented with factor coefficients of
selected eight factors. The factor loadings
indicate the highest correlations between
variables and corresponding factors.
Table1. Demographic profile and mobile banking history of the respondents.
Demographic
Characteristics Frequency % Valid %
Cumulative
%
Gender Male 247 84.6 84.6 84.6
Female 45 15.4 15.4 100
Age
< 18 Yr 23 7.9 7.9 7.9
18-25 Yr 183 62.7 62.7 70.5
26-30 Yr 49 16.8 16.8 87.3
> 30 Yr 37 12.7 12.7 100
Occupation
Student 161 55.1 55.1 55.1
Business 50 17.1 17.1 72.3
Service 67 22.9 22.9 95.2
Agriculture 14 4.8 4.8 100
Monthly
Income
(BDT, 1$=78 BDT)
< 10K 185 63.4 63.4 63.4
10-20K 59 20.2 20.2 83.6
21-30K 36 12.3 12.3 95.9
>30K 12 4.1 4.1 100
Residence
Region
Barisal 6 2.1 2.1 2.1
Chittagong 48 16.4 16.4 18.5
Dhaka 47 16.1 16.1 34.6
Khulna 61 20.9 20.9 55.5
Rajshahi 81 27.7 27.7 83.2
Rangpur 49 16.8 16.8 100
MFS Account
DBBL 134 45.9 45.9 45.9
bKash 137 46.9 46.9 92.8
TRUST 5 1.7 1.7 94.5
MERCENTILE 2 0.7 0.7 95.2
PRIME 6 2.1 2.1 97.3
NCC 2 0.7 0.7 97.9
ISLAMI 6 2.1 2.1 100
Mobile Network
Operator
Grameen Phone 193 66.1 66.1 66.1
ROBI 48 16.4 16.4 82.5
AIRTEL 17 5.8 5.8 88.4
Bangla Link 27 9.2 9.2 97.6
Tele Talk 4 1.4 1.4 99
City Cell 3 1 1 100
Reasons Behind
MFS A/C
No Bank A/C 32 11 11 11
Easy Money
Transfer 240 82.2 82.2 93.2
No Bank
at Locality 12 4.1 4.1 97.3
Purchase through
Mobile 2 0.7 0.7 97.9
Low Charge than Bank 6 2.1 2.1 100
Number of Monthly
Transaction
< 1 47 16.1 16.1 16.1
1 -- 5 192 65.8 65.8 81.8
6 -- 10 36 12.3 12.3 94.2
> 10 17 5.8 5.8 100
Purpose of
Transaction
Business 48 16.4 16.4 16.4
Personal 244 83.6 83.6 100
The greater the coefficients, the more the
variable are pure measures of factor. For
instance, VGN, SAE, ACS, NPN, and
EAM show the highest correlations with
Infrastructural Facility (IF). Thus, these
variables were considered as group. As all
of these variables were related to network
& basic mobile banking platform, this
group named as “Infrastructural Facility”
Table2. Descriptive statistics of the variables.
Factors Item Item Name Mean Std.
Deviation
Factor
Loading
Cronbach's
Alpha
IF
(Infrastructural
Facility)
VGN Very Good Network 3.90 1.080 0.789
0.746
SAE Service Available in Everywhere 3.98 1.460 0.746
ACS Available ATM and Customer Service 3.92 1.311 0.655
NPN No Problem in Network 3.91 1.144 0.608
EAM No Difficulty in Account Manage 4.78 1.069 0.471
SC (Self-
Control)
IU Independently Use 3.87 1.525 0.820
0.762 USM Use Self Mobile Phone 3.64 1.555 0.737
CDO Can do like others 4.14 1.304 0.690
PF Purchase Facility 3.64 1.579 0.564
SI (Social
Influence)
AMB Lot of Advertisement for MBanking 4.26 1.337 0.761
0.754
CAI Customer Agent Influence for MBanking 3.88 1.298 0.694
PIU Profession Influence to Use MBanking 4.19 1.429 0.667
FNFI FNF Influence to Use Mobile Banking 4.10 1.272 0.608
MPU Many People Use Mobile Banking 4.27 1.341 0.527
PR (Perceived
Risk)
NAM Not Available Money at Customer Agent 4.20 1.355 0.766
0.721
NMD Network Most time Down 4.01 1.349 0.690
ECA Extra Charge taking by Customer Agent 4.17 1.388 0.679
MSC More Service Charge 4.2 1.485 0.636
NSR No Service in Remote Areas 4.16 1.404 0.647
EoU (Ease of
Use)
FMT Fast Money Transfer 5.31 0.868 0.555
0.549 ATM ATM Use without Bank Account 4.22 1.638 0.552
EAO Easy Account Opening 5.08 0.981 0.518
ATB Anytime Banking 5.09 0.945 0.406
NFI (Need for
Interaction)
WPO Wants to Purchase like others 4.56 1.259 0.697
0.558 WUO Wants to Use like others 4.92 1.064 0.694
FNFS Available Support from FNF 4.44 1.030 0.456
PU (Perceived
Usefulness)
AAT Any Amount Transfer 4.39 1.315 0.746 0.409
AWB Anywhere Banking 4.68 1.059 0.687
CS (Customer
Service)
ICS Immediate Support Available from CS 3.73 2.249 0.745 0.417
ETS Easy to Solve Wrong Transaction 3.44 1.455 0.688
Similarly, IU, USM, CDO, and PF show
highest correlations with Self-Control;
AMB, CAI, PIU, FNFI, and MPU with
Social Influence (SI); NAM, NMD, ECA,
MSC, and NSR with Perceived Risk (PR);
FMT, ATM, EAO, and ATB with Ease of
Use (EoU); WPO, WUO, and FNFS with
Need for Interaction (NFI); AAT and
AWB with Perceived Usefulness (PU);
and ICS and ETS have highest correlation
with Customer Service (CS).
5.2 Measures of Sampling Adequacy
This study has used KMO and Bartlett’s
Test to examine the accuracy of sample.
The result of Kaiser-Meyer-Olkin Measure
shows that the current sample is adequate
for factor analysis. Table 3 shows the
current data yield about 78.7% accuracy at
1% level of significant for the said
analysis.
Table3. KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of
Sampling Adequacy. 0.787
Bartlett's Test of
Sphericity
Approx. Chi-
Square 2512.336
df 435
Sig. .000
5.3 Scale Reliability
There are thirty items have been
considered for the study. Multi-item scales
(Six Point Likert Scale) response format
has been used to operationalize each
individual item of the questionnaire. The
overall measurement for contextually
formatted items is described in Table 4.
Result shows that scales used for the data
collection are reliable with highly
recommended alpha score (a0.825) which
is within the range of good scale reliability
[35].
Table4. Reliability statistics of items
Cronbach's
Alpha
Cronbach's Alpha
Based on
Standardized Items
N of
Items
0.825 0.835 30
5.4 Extraction communalities
This study has examined communalities of
each variable accounted for the research.
Initially 34 items were approached for this
test. This study did not find absolute
commonalities score for all items. Hence,
four items (scored less than 0.5) have been
dropped from the data set. But, two items
ATB and FMT have scored 0.454 and
0.364 respectively those were kept as these
are basic attributes of mobile banking
service. The score was low due to
introduction stage of the services in
Bangladesh. The other 28 items having 0.5
or more commonalities score have been
accepted for further analysis. Since data
have been collected from field survey,
author has considered current score level
for 30 items included in eight factors.
5.5 Scree Plot
In this study examines the optimal number
of items using scree plot. This
demonstrates the distribution of variance
among the components. For each principal
component, the corresponding Eigenvalue
is plotted on the y-axis. The Eigenvalue of
each item in the initial solution is plotted
in the figure below. Figure shows that the
variance of each component is less than
the proceeding one. The sharp fall is
marked till fifth principle component and
last big drop occurs between third and
fourth components. It is known that
components on the shallow slope
contribute little to the solution. Thus, it can
choice first four five principal components
for understanding consumer attitude
towards mobile banking in Bangladesh.
Figure 1. Scree plot
5.6 Variance
The study identifies 30 items from initially
approached 34 items that are important to
measuring consumer attitudes towards mobile
banking in Bangladesh. All 30 items are
selected based on Eigenvalue - value 1 or
above includes into the list of items.
Statistically 30 items construct eight factors
which can explain 58.14% of the field. So, this
study considers these factors are important for
the study. Factor-1 explains 19.087% having
Eigenvalue of 5.726 and Factor-8 explains
3.612% with Eigenvalue 1.084 as lowest
(Table 5). Hence, factor-1 is the most
important in the current study which is related
to the infrastructural development of mobile
financial services in Bangladesh.
Table5. Eigen value and variability of the retained factors.
Factors IF SC SI PR EoU NFI PU CS
Eigen values 5.726 2.616 2.16 1.723 1.514 1.339 1.278 1.084
Variability 19.087 8.722 7.201 5.744 5.048 4.465 4.259 3.612
Cumulative % 19.087 27.809 35.009 40.753 45.801 50.266 54.525 58.137
Pearson correlation coefficients of all factors
represents in Table 6. Here, considerable
numbers of correlation coefficients among
factors are significant (p ≤ 0.01 or p ≤ 0.05).
Table 6. Pearson correlation coefficients among all factors
Factors IF SC SI PR EoU NFI PU CS
IF 1
SC .308** 1
SI .329** .446** 1
PR -0.011 .121* 0.053 1
EoU .329** .444** .323** .147* 1
NFI .277** .342** .440** 0.082 .269** 1
PU .250** .202** .184** 0.007 .347** 0.097 1
CS .211** .202** 0.1 0.027 .226** .133* .170** 1
Notes: **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-
tailed).
5.7 Exploratory Factor Analysis
As result shows in Table 2, eight factors were
initially formed considering 30 variables to
influence consumer attitudes towards mobile
banking in Bangladesh. Factor analysis was
conducted to know the underlying factor
associated with all 30 variables. This study
exposes that consumer attitudes towards mobile
banking in Bangladesh is highly influence by
four factors i.e. infrastructural facility, self-
control, social influence, and perceived risk and
other four factors (ease of use, need for
interaction perceived usefulness and customer
service)have less alpha score than significant
level. But this study considers also the factors
having less Cronbach’s alpha score as these have
high factor loading score. Again, the mobile
banking services are newly introduced in
Bangladesh and most consumers are not well
known about all measures. The eight factors are
briefly discussing in following paragraphs:
Infrastructural Facility: This study has
identified that infrastructural facility has high
influence on mobile banking attitude in
Bangladesh. This factor constitute with five
items - Very Good Network, Service Available
in Everywhere, Available ATM and Customer
Service, No Problem in Network, and No
Difficulty in Account Manage. This factor’s
Cronbach’s Alpha 0.746 is quite satisfactory
within acceptable level (0.70 or above)[35].
However, the factor loading score for each item
is within the acceptable level (from 0.471 to
0.789).
Self-Control: Mobile banking influence by the
self-control on mobile technology of the
consumers in Bangladesh. This factor constitutes
with four variables with good factor loading
score range from 0.564 to 0.820. The Cronbach’s
Alpha 0.762 is within the acceptable level.
Social Influence: Consumers using mobile
banking services in Bangladesh are highly
influenced by interpersonal & external forces of
the society. This study identified five variables to
construct social influence for forcing mobile
banking services use. The factor loading score
for all five items are range from 0.537 to 0.761
and Cronbach’s Alpha 0.754 is at acceptable
level.
Perceived Risk: The factor perceived risk
creating difficulties on mobile banking attitudes
of consumers in Bangladesh. It has constructed
by five items with very good factor loading score
ranging from 0.647 to 0.766. Again, the
Cronbach’s Alpha score 0.721 is positioning
within acceptable level.
Ease of Use: This study explores ease of use of
the technology for mobile banking has
influenced on consumer attitudes towards mobile
banking services in Bangladesh. This factor has
constructed by four items those have factor
loading score ranging from 0.406 to 0.555 and
the Cronbach’s Alpha value 0.549 is almost
acceptable level.
Need for Interaction: The factor need for
interaction influence consumers on positive
attitude towards mobile banking services in
Bangladesh. It has three variables having factor
loading score ranging from 0.456 to 0.697 and
Cronbach’s Alpha value 0.558 which is nearest
to acceptable level.
Perceived Usefulness: Perceived usefulness is
another factor to influence consumers’ attitudes
towards mobile banking services in Bangladesh.
This factor has only two variables with low
Cronbach’s Alpha 0.409 but high factor loading
scores of 0.687 and 0.746.
Customer Service: The last factor is customer
service is the specific factor to influence
Bangladeshi consumers’ to show positive or
negative attitudes towards mobile banking
services. This factor also has only two variables
with low Cronbach’s Alpha 0.417 but high factor
loading scores of 0.688 and 0.745.
6. GENERAL DISCUSSION
The primary theoretical contribution of this study
is the identification of factors that can be used to
enlighten and foretell consumers’ attitudes
towards mobile banking, particularly within the
Bangladesh context. This research also creates a
research interest on mobile banking for the
business researchers. Secondly, two additional
factors (infrastructural facility and customer
service) relevant to mobile banking that were
absent in previous researches were identified.
Finally, by investigating consumers’ attitudes
towards mobile banking within the Bangladesh
context, this study answers the call for additional
research to different fields of mobile banking
services.
This study found only 6.58% having mobile
banking account on mobile phone subscriptions
and 9.14% on rural population those are
relatively very low penetrations compare to other
emerging markets in the world. It indicates that
there is a huge scope of mobile banking in
Bangladesh and Banks and MNOs have massive
business opportunity. Again, the consumers of
this country are focusing highly on
infrastructural facility as a force to make their
intention to use mobile banking services. It is
suggested that along with others six factors
infrastructural facility is the most important
factor for Bangladeshi consumers and they also
concern on customer service facility of mobile
banking. Thus, by addressing the concerns of
and benefits sought by the consumers, marketers
can create positive attractions and policy makers
can set regulations for the expansion of mobile
banking services.
7. LIMITATION AND CONCLUSION
The sample size of this study was not necessarily
representative of the Bangladeshi population as a
whole as it ignored large rural population.
Secondly, the generalizability of this research
may be impacted by fact that the sample’s is
skewed towards males. This may be due to
general tendency of Bangladesh culture to do
outside tasks by maximum males. In addition,
this research only explores the factors to
influence motivators and inhibitors on behavioral
intentions. In terms of future research, a large
scale study with more representative sample
could be conducted to validate the factors of this
study and to enhance the generalizability of the
research conclusions.
Mobile banking services is very new to
Bangladeshi consumers and it is still at early
stages in Bangladesh. The current target market
for mobile banking is relatively small due to the
lack of updated user friendly infrastructural
facility. There is a good potential for introducing
mobile banking services. This research has
served to enhance the understanding of the
factors influencing consumers’ attitudes towards
mobile banking in the context of Bangladesh. It
has demonstrated that there were multiple factors
at work for influencing the consumers and that
some are more influential than others under
given circumstances. The knowledge gained by
this study into the motivators and inhibitors of
mobile banking is useful for practitioners who
aim to maximize consumer adoption of this self-
service banking service.
8. REFERENCE
[1] M. N. Abdullah, A. Rahman, and R. B. Tooheen,
“Mobile Money in Bangladesh,” European Journal of
Developing Country Studies, 2007, Vol. 4, pp. 24-30.
[2] U. Akturan, N. Tezcan, “Mobile banking adoption of
the youth market Perceptions and intentions,” Marketing
Intelligence & Planning, 2012, Vol. 30 No. 4, pp. 444-459.
DOI 10.1108/02634501211231928
[3] E. A. Alampay, “Mobile 2.0: m‐money for the BOP in
the Philippines,” International Development Research
Centre (IDRC), Canada and the Department for
International Development (DFID), UK, 2009. Retrieved
from http://ssrn.com/abstract=1618185
[4] B. Anckar, D. D’Incau, “Value creation in mobile
commerce: findings from a consumer survey,” Journal of
Information Technology Theory and Application, 2002,
Vol. 4 No. 1, pp. 43-64.
[5] J. Anderson, “M-banking in developing markets:
competitive and regulatory implications,” Info, 2009, Vol.
12 No. 1, pp. 18-25. DOI 10.1108/14636691011015358
[6] F. I. Anyasi, and P. A. Otubu, “Mobile Phone
Technology in Banking System: It’s Economic Effect,”
Research Journal of Information Technology, 2009, Vol. 1
No. 1, pp. 1-5.
[7] G. Barczak, P. S. Ellen, and B. K. Pilling, “Developing
typologies of consumer motives for use of technologically
based banking services,” Journal of Business Research,
1997, Vol. 38 No. 2, pp. 131-39.
[8] R. A. Bauer, “Consumer behaviour as risk taking in
Cox, D.F. (Ed.), Risk Taking and Information Handling in
Consumer Behaviour,” Harvard University Press,
Cambridge, MA, 1960, pp. 22-3.
[9] I. Brown, Z. Cajee, D. Davies, and S. Stroebel, “Cell
phone banking: predictors of adoption in South Africa – an
exploratory study,” International Journal of Information
Management, 2003, Vol. 23 No. 5, pp. 381-94.
[10] A. S. Cases, “Perceived risk and risk reduction
strategies in internet shopping,” The International Review
of Retail, Distribution and Consumer Research, 2002, Vol.
12 No. 4, pp. 375-94.
[11] P. Cruz, and T. Laukkanen Mobile banking rollout in
emerging markets: evidence from Brazil. International
Journal of Bank Marketing, 2010, Vol. 28 No. 5, pp. 342-
371. DOI 10.1108/02652321011064881
[12] J. M. Curran, and M. L. Meuter, “Self-service
technology adoption: comparing three technologies,”
Journal of Services Marketing, 2005, Vol. 19 No. 2, pp.
103-14.
[13] F. D. Davis, R. P. Bogazzi, and P. R. Warshaw, “User
acceptance of computer technology: a comparison of two
theoretical models,” Management Science, 1989, Vol. 35
No. 8, pp. 982-1003.
[14] S. M. Dewan, and A. M. Dewan, “Modelling Choice
of Mobile Technology for M-Banking,” International
Conference on Industrial Engineering and Operations
Management Dhaka, Bangladesh, January 9 – 10, 2010.
[15] U. M. Dholokia, “An investigation of the relationship
between perceived risk and product involvement,”
Advances in Consumer Research, 1997, Vol. 24 No. 1, pp.
159-67.
[16] E. M. Flores-Roux, J. Mariscal, “The Enigma of
Mobile Money Systems,” COMMUNICATIONS &
STRATEGIES, 2010, Vol. 79, pp. 41-62.
[17] M. S. Islam, “Mobile Banking: An Emerging Issue in
Bangladesh,” ASA University Review, 2013, Vol. 7 No. 1,
pp. 123-130.
[18] J. Jacoby, and L. B. Kaplan, “The components of
perceived risk in Venkatesan, M. (Ed.),” The Third Annual
Conference of The Association for Consumer Research,
Association for Consumer Research, Duluth, MN, 1972,
pp. 382-93.
[19] H. W. Kim, H. C. Chan, and S. Gupta, “Value-based
adoption of mobile internet: an empirical investigation,”
Decision Support Systems, 2007, Vol. 43 No. 1, pp. 111-
26.
[20] N. Koenig-Lewis, A. Palmer, and A. Moll,
“Predicting young consumers’ take up of mobile banking
services,” International Journal of Bank Marketing, 2010,
Vol. 28 No. 5, pp. 410-432. DOI
10.1108/02652321011064917
[21] P. Kotler, and G. Armstrong, “Principles of
Marketing, 10th ed.,” Pearson Education International,
Upper Saddle River, NJ, 2010.
[22] S. Laforet, X. Li, “Consumers’ attitudes towards
online and mobile banking in China,” International Journal
of Bank Marketing, 2005, Vol. 23 No. 5, pp. 362-380. DOI
10.1108/02652320510629250
[23] T. Laukkanen, and J. Lauronen, “Consumer value
creation in mobile banking services,” Int. J. Mobile
Communications, 2005, Vol. 3 No. 4, pp. 325-338.
[24] T. Laukkanen, S. Sinkkonen, M. Kivija¨rvi, and P.
Laukkanen, “Innovation resistance among mature
consumers,” The Journal of Consumer Marketing, 2007,
Vol. 24 No. 7, pp. 419-27.
[25] T. Laukkanen, “Internet vs mobile banking:
comparing customer value perceptions,” Business Process
Management Journal, 2007, Vol. 13 No. 6, pp. 788-797.
DOI: 10.1108/14637150710834550
[26] T. Laukkanen, and V. Kiviniemi, “The role of
information in mobile banking resistance,” International
Journal of Bank Marketing, 2010, Vol. 28 No. 5, pp. 372-
388. DOI 10.1108/02652321011064890
[27] M. S. Y. Lee, P. F. McGoldrick, K. A. Keeling, and J.
Doherty, “Using ZMET to explore barriers to the adoption
of 3G mobile banking services,” International Journal of
Retail & Distribution Management, 2003, Vol. 31 No. 6,
pp. 340-8.
[28] A. Lockett, and D. Littler, “The adoption of direct
banking services,” Journal of Marketing Management,
1997, Vol. 13 No. 8, pp. 791-811.
[29] P. Luarn, and H. Lin, “Toward an understanding of
the behavioural intention to use mobile banking,”
Computers in Human Behaviour, 2005, Vol. 21, pp. 873-
91.
[30] A. Machauer, S. Morgner, “Segmentation of bank
customers by expected benefits and attitudes,”
International Journal of Bank Marketing, 2001, Vol. 19
No. 1, pp. 6-17.
[31] N. Mallat, M. Rossi, and V. K. Tuunainen, “Mobile
Banking Services,” COMMUNICATIONS OF THE
ACM, 2004, Vol. 47, No. 5, pp. 41 -46.
[32] R. Minhas, and E. Jacobs, “Benefit segmentation by
factor analysis: an improved method of targeting
customers for financial services,” International Journal of
Bank Marketing, 1996, Vol. 14 No. 3, pp. 3-13.
[33] T. T. T. Nga, “MOBILE MONEY BUSINESS
DEVELOPMENT AT VIETNAM MOBILE SERVICE
(VMS- MobiFone),” Vietnam National University, Hanoi,
2009.
[34] H. Nysveen, P. Pedersen, and H. Thornbjørnsen,
“Intentions to use mobile services: antecedents and cross-
service comparisons,” Journal of Academy of Marketing
Science, 2005, Vol. 33 No. 3, pp. 330-46.
[35] S. W. O’Leary-Kelly, and R. J. Vokurka, “The
empirical assessment of construct validity,” Journal of
Operation Management, 1998, Vol. 16 No. 4, pp. 387-405.
[36] P. Panurach, “Money in Electronic Commerce:
Digital Cash, Fund Transfers, and Ecash,”
COMMUNICATIONS OF THE ACM, 1996, Vol. 39, No.
6, pp. 45-50.
[37] P. A. Pavlou, “Consumer acceptance of electronic
commerce: integrating trust and risk with the technology
acceptance model,” International Journal of Electronic
Commerce, 2003, Vol. 7 No. 3, pp. 101-34.
[38] T. Pikkarainen, K. Pikkarainen, H. Karjaluoto, and S.
Pahnila, “Consumer acceptance of online banking: an
extension of the technology acceptance model,” Internet
Research, 2004, Vol. 14 No. 3, pp. 224-35.
[39] D. Porteous, “THE ENABLING ENVIRONMENT
FOR MOBILE BANKING IN AFRICA,” Commissioned
by Department for International Development (DFID),
Boston, USA, 2006.
[40] J, Pu¨schel, and J. A. Mazzon, “Mobile banking:
proposition of an integrated adoption intention
framework,” International Journal of Bank Marketing,
2010, Vol. 28 No. 5, pp. 389-409. DOI
10.1108/02652321011064908
[41] H. E. Riquelme, and R. E. Rios, “The moderating
effect of gender in the adoption of mobile banking,”
International Journal of Bank Marketing, 2010, Vo. 28 No.
5, pp. 328-341. DOI 10.1108/02652321011064872
[42] T. Roselius, “Consumer rankings of risk reduction
methods,” Journal of Marketing, 1971, Vol. 35, No. 1, pp.
56-61.
[43] S. Saha, “Bangladesh: a bright spot in m-banking,”
The Daily Star, October 6, 2013, retrieved from
http://www.thedailystar.net/beta2/news/bangladesh-a-
bright-spot-in-m-banking/
[44] R. N. Stone, and K. Gronhaug, “Perceived risk:
further considerations for the marketing discipline,”
European Journal of Marketing, 1993, Vol. 27 No. 3, pp.
39-50.
[45] G. Sullivan Mort, and J. Drennan, “Marketing m-
services: establishing a usage benefit typology related to
mobile user characteristics,” Journal of Database
Marketing &Customer Strategy Management, 2007, Vol.
12 No. 4, pp. 327-41.
[46] Subscribers Report. “Mobile Phone Subscribers,”
Bangladesh Telecommunication Regulatory Commission,
September, 2013, retrieved from http://www.btrc.gov.bd/
[47] M. Suoranta, and M. Mattila, “Mobile banking and
consumer behaviour: new insights into the diffusion
pattern,” Journal of Financial Services Marketing, 2004,
Vol. 8 No. 4, pp. 354-66.
[48] R. Tiwari, S. Buse, and C. Herstatt, “Mobile Banking
as Business Strategy: Impact of Mobile Technologies on
Customer Behaviour and Its Implications for Banks,”
Paper presented at the Portland International Conference
on Management of Engineering and Technology, Turkey.
July, 2006.
[49] Y. Wang, H. Lin, and P. Luarn, “Predicting consumer
intention to use mobile service,” Information Systems
Journal, 2006, Vol. 16, pp. 157-79.
[50] L. Wessels, and J. Drennan, “An investigation of
consumer acceptance of M-banking,” International Journal
of Bank Marketing, 2010, Vol. 28 No. 7, pp. 547-568. DOI
10.1108/02652321011085194
[51] World Bank Indicators, “RURAL POPULATION (%
OF TOTAL POPULATION) IN BANGLADESH,”
Trading Economics, 2010, retrieved from
http://www.tradingeconomics.com/bangladesh/rural-
population-percent-of-total-population-wb-data.html
[52] R. H. Walker, and L. W. Johnson, “Why consumers
use and do not use technology-enabled services,” Journal
of Services Marketing, 2006, Vol. 20 No. 2, pp. 125-35.
[53] P. Wright, “Consumer choice strategies: simplifying
vs optimization,” Journal of Marketing Research, 1975,
Vol. 12 No. 1, pp. 60-7.
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