Critical ATM adoption

www.theinternationaljournal.org > RJSSM: Volume: 03, Number: 04, August-2013 Page 91
Abstract—The paper examines factors that most importantly affect customer adoption of ATMs in
Ghanaian banking industry. The study was a cross-sectional survey that employed the use self-
administered questionnaire to collect data from a sample of 256 respondents through personal contact.
Through confirmatory factor analysis approach using AMOS 18.0, the findings indicatethat,two items
of perceived ease of use, four items of perceived benefits and two items of perceived barriers critically
affect the adoption of ATMs in the research context. Given that the research model is theoretically
grounded and indicateshigh goodness-of-fit indices, factor loadings, validity and reliability, it offers
practitioners the basis for developing effective customer driven strategies for delivering ATM services.
In spite of the limitations of the study, the findings also confirm and further our understanding of
factors affecting consumer adoption of technology in electronic banking.
Index Terms—banking industry, Automated Teller Machine, Ghana, perceived benefits,
perceived ease of use, perceived, barriers, self-service, TAM, Confirmatory factor analysis.
I. INTRODUCTION
Information and communications technologies (ICTs) are now used in business to bring in new
products, service market opportunities and developing more information system that is business
oriented and supports management processes such as planning, controlling and co-ordination [1]. In
recent times, the impact of ICTs in the banking industry has been greatly felt as most banks in
developed and developing parts of the world are now offering internet banking services with various
levels of sophistication as a competitive strategy [2], [3].
Since banking started in Ghana in 1894, the deployment of ICTs in the banking industry has grown
from one level of complexity to another.The government of Ghana established an ICT framework to
facilitate the development of ICT in all sectors of the economy (ICT4AD, 2003) and the e-zwich
electronic payment platform that was initiated in 2008 to facilitate business, competition and better
delivery of services in the economy [4]. Many of the commercial banks in Ghana now offer many
kinds of electronic banking services platform and a wide range of electronic products and transactions,
some of which allow customers to receive their monthly bank statements via e-mail, online checking
of accounts balance, online transfer of funds, the use of electronic cash systems, and for
communicating to customers on regarding bank statements, other banks use internet banking services
to allow business customers to make inter-bank financial transactions and information sharing [5]- [7].
One of the electronic banking tools that has gain the attention of banking management and scholars
alike is the use of the Automated Teller Machine (ATM) services. As competition in the Ghanaian
banking industry becomes keener with over 25 banks and other non-bank financial institutions,
industry players continue to find strategic ways of becoming relevant and competitive in order to
survive in the banking market. Banking firms that attempt to provide superior service quality to
customers with the help of ATM services as a means of raising the level of customer satisfaction and
overall experience of banking services in order to generate loyalty in customers [8]-[10].
Existing literature on the use of ATM and its services in African countries are generally scanty, and
Simon Gyasi Nimako,
Department of Management Studies Education, University of Education, Winneba, and
Accra Institute of Technology Business School, Accra – Ghana, West Africa.
E-mail: sim.ekomerce@gmail.com
Nana Kwame Gyamfi
Department of Computer Science, Kumasi Polytechnic, Kumasi – Ghana,
West Africa.
E-mail:emeritusbrains@gmail.com
Critical ATM Adoption Factors in Ghanaian Banking Industry: CFA approach

those that exist seem to be very limited in scope and methodology. First, research on the use of ATMs
in Sub-Sahara Africa (SSA) is limited in general as there are few papers that have contributed
knowledge on the use of ATMs in Sub-Sahara Africa. These include studies such as reference [11] in
Bostwana, reference [12]-[16] in Nigeriaand an initial exploration in Ghana [17]. Second, most of
these previous studies have included either small sample size or customers from one or two banking
institutions, giving very limited results within each country. Third, these previous studies used mostly
descriptive statistics and multiple regression analysis to describe important factors that affect ATM
adoption in the Sub-Sahara Africa. Apart from a few such as [13], much of the previous studies did not
attempted to study the phenomenon of ATM adoption using methodology and data analysis techniques
such as Confirmatory Factor Analysis (CFA) or Structural Equation Modelling (SEM) that have been
recommended over multiple regression and descriptive analysis in terms of their robustness [18].
While these previous studies have provided us with a preliminary findings, more empirical studies
that incorporate robust methodologies are needed to further our understanding on the factors that affect
the adoption of ATMs in banking industry that are critical to specific research context. This paper is an
attempt to fill this void in the electronic banking literature by employing Confirmatory Factor Analysis
(CFA) to study ATM adoption factors, especially in the SSA, which is a region in dire need of ICT
development and probably one with the greatest need of research attention in e-banking.
The findings of this study would also provide empirical knowledge to management of e-banking
systems, and in particular ATMs to understand the critical ATM factors that should be used to develop
successful banking strategy. In view of this, the main purpose of this paper is to determine the most
important factors that influence the adoption of ATM services among customers in the Ghanaian
banking industry (GBI) through CFA approach. Specifically, the study sought to address the following
objectives
1. To determine most important perceived benefits in consumer adoption of ATM services in
GBI.
2. To determine most important perceived barriers in consumer adoption of ATMs in GBI.
3. To determine most important factors that underlie perceived ease of use in consumer
adoption of ATMs in GBI
II. LITERATURE REVIEW AND RESEARCH MODEL
A. Self-service Delivery and Technology
ATMs are part of Self-service technologies (SSTs). In recent times the application of SST have been
prevalently in many industries, including airline, banking, travel, hotel, financial, and retailing since
the automated teller machines (ATMs) were introduced several decades ago. Today, SST have
produced great economic value [19], apart from its wide varieties of applications including automated
hotel checkout, flight ticket checkouts at kiosks or online, internet shopping, paying bills online,
banking via ATMs, and many others [20].
ATM is a computerised telecommunication device that provides the customers of Banks the facility of
accessing their accounts for dispensing cash and to carry out other financial transactions without the
need of actually visiting a Bank Branch. The ATM cards/debit cards that usually permit cash
withdrawal can be used at a Bank’s ATM for various transactions [21].The ATM like any SST enables
consumers to become service coproducers rather than only service receivers [22]. Not only do ATMs
shift a traditional service pattern that completely separates production and consumption, but also
change the role and the behavior of consumers. Consequently, it becomes essential to management and
scholars to study the adoption ATMs in specific industries and research contexts to determine which
factors affect the adoption of the technology.
B. Theory of Technology Acceptance
In the last three decades, the integration of ICT into business has received considerable attention of
scholars and practitioners in many areas of business [23]. As a result researchers have made many
attempts to develop and test models to help in predicting technology acceptance. Among these models,
the Technology Acceptance Model (TAM) developed by Davis, Bagozzi, &Warshaw[24] has provided
useful foundation for understanding the factors that drive technology acceptance, and has therefore

been one of the most widely adopted theoretical framework in understanding user acceptance of
technology [25].
The TAM came from Ajzen and Fishbein’s (1980) Theory of Reasoned Action (TRA) [26]. The
TRA presupposes that beliefs and attitudes are related to individuals’ intentions to perform. It holds
that attitude toward a behaviour is determined by behavioural beliefs about the consequences of the
behaviour and the affective evaluation of those consequences on the part of the individual. Based on
TRA, the TAM was developed to address the issue of how users come to accept and use a technology.
According to the TAM, perceived usefulness and perceived ease of use of the technology in question
are hypothesized to be fundamental determinants of user acceptance. The TAM posits that users’
actual or behavioural acceptance is principally determined by behavioural intentions to use the
technology in question. Behavioural intentions are in turn influenced by the user’s attitude towards
technology. Reference [24] stated that perceived usefulness and perceived ease of use are beliefs that
lead to favourable attitudes and intentions to accept and use technology. Figure 1 shows the
Technology Acceptance Model.
Fig. 1 Technology Acceptance Model (Adapted from Davis, Bagozzi, &Warshaw, 1989).
Note: INT – Intention to Use Technology, ATT- Computer Attitude, PEU – Perceived Ease of Use,
PUS – Perceived Usefulness, EXT – External Variables.
Despite the fact that the TAM has been criticized of having attracted a lot of modifications and
extensions, suggesting that the model is inadequate to explain technology acceptance in many research
context [25], it continues to be empirically proven for its ability to predict about 40% of a system use
[23], and has received praise for its parsimony and predictive powers over the years, The
TAM.Therefore, could become an important reference theory in understanding the critical dimensions
of ATM adoption in the research context.
C. The Research Model
The conceptual framework for this study (Figure 2) is based on the information systems literature and
preliminary focus group interview conducted by the researchers in the research context. Apart from,
perceived usefulness and perceived ease of use, another factor that came up in the focus group
interview was some perceived challenges or barriers.
1. Perceived usefulness (PU). PU is defined as the degree to which a person believes that using a
particular technology will enhance his or her job performance [24], or personal and/or the adopting
organization’s well-being. In the research context, the perceived usefulness of ATM services
refers to the extent to which customers believe that using ATM would be beneficial to them. In this
study it was described as Perceived benefit (PBE). The preliminary focus group interviews for this
study lend support to previous qualitative research findings in the Sub-Sahara Africa. These studies
found that customers often cited the following benefits that they derive for using ATM services
[11]-[17]: ability to cash money without wasting too much time, for balance enquiry, easy access
to mini bank statement of services, overall convenience of ATM servuces, personalized self-
services, privacy issues, having access to account every time, 24/7.
2. Perceived ease of use (PEU).PEU refers to the degree to which a person believes that using a
particular technology will be free of effort [24]. It is possible that while users may believe that
computers are useful, they may be, at the same time, too difficult to use and that the performance
benefits of usage are outweighed by the effort of using the application [24]. In the context of ATM
INT
PUS
EXT
PEU
ATT

adoption perceived ease of use includes items such as the proximity of ATM location, simple ATM
instructions, convenience in using ATM, among others [11]-[17].
3. Perceived Barriers/Challenges (PBA). The use and therefore the adoption of ATMs come with
barriers which could influence customers’ level of ATM adoption. Many previous studies in the
Sub-Sahara Africa have identified, through qualitative research, a number of factors that are
usually perceived by customers as challenging or barrier in the adoption of ATMs [11]-[17], [28].
These factors include: unavailability of transaction receipt, long queue at the ATM location,
breakdown or non-functioning of ATM, fear of criminals getting access to customer’s ATM
code(Security risk issues), inadequate number of ATMs, ATMs not being user friendly, among
others.
Fig. 2 Research Model. It depicts the proposed underlying factors affecting ATM adoption in GBI
used in the CFA.
III. METHODOLOGY
A. Population
The target population consists of banking customers of five banks, Ghana Commercial Bank Ltd.,
United Bank for Africa, Ecobank Ghana,Barclays Bank Ghana and AMA Bank Ltd.These banks were
chosen as they are part of the key players in the GBI with respect to electronic banking services.
B. Sampling
The convenient sample size of 400 banking customers were sampledfrom the five chosen
banksrespondents, 80 from each sub-group. In selecting the 200 respondents, a purposive sampling
method was used to consciously select customers who meet the criteria of having used ATM services
of these banks for the past twelve months.
C. Data Collection Instrument
A self-administered structured questionnaires was developed based on focus group interview and
literature review to gain insight into the critical benefits and barriers that are latent in the consumer
adoption of ATM in GBI. A preliminary focus group interview was conducted to gain insight into
PEU, PUS, and PBA aspects of the adoption of ATMs in GBI. The outcome was combined with
findings from existing empirical studies to develop the questionnaire. The questionnaire contained
included two sections. Section one contained bio data of respondents – gender, age, education, income
and marital status. Section two focused on the three constructs PBA, PBE and PEU, which together
had 19 items, three for PEU, ten for PBE and six for PBA (See Table 1). Respondents were asked to
respond tothe measurement items on a five-point Likert scale ranging fromStrongly Disagree,

Disagreed, neutral, Agree, and Strongly agree, coded from 1 to 5 respectively. The initial reliability of
the instrument for all the 19 items was assessed through the Cronbach alpha; it produced a value of
0.773 which is a little above the recommended alpha of 0.70 [18].
IV. DATA ANALYSIS
A. Data Analysis Methods
Data was analysedusing SPSS version 16.0 for descriptive statistics and Cronbach alpha reliability
test, and AMOS version 18.0 to perform Confirmatory Factor Analysis (CFA) of the constructs and
their respective indicatorsin proposed measurement model (Figure 1). CFA is a confirmatory
technique that involves testing whether a hypothesized measurement model is valid and reliable. It
tests the relationship between a latent construct and its proposed measures [18]. In CFA, the proposed
measurement model is implied from previous empirical findings and theoretically validated constructs.
Thus, while CFA is driven by theory, exploratory factor analysis is derived from statistical results of a
population sample [18].The following are some useful guidelines and steps involved in CFA [18],
[27]:
1. Define individual constructs based on theory;
2. Develop the overall measurement model to ensure that each construct has at least two or three
indicators for unidimensionality, are congeneric, are identified as formative or reflective
appropriately;
3. Design a study to produce empirical results by ensuring adequate sample size (minimum of 200
cases), using appropriate estimation method, checking for errors in specification of measurement
model; and
4. Assess measurement model validity by assessing the model fit using several fit indices with
recommended benchmarks [18, see Table 2]; ensuring a minimum of 0.50 standardized
regression estimates for each indictor, conducting diagnostic tests using path estimates,
modification indices and standardized residuals.
The following sections describe the procedures and results of the CFA using AMOS 18.0 for
Windows. It begins with results on background information about respondents in the study.
B. Respondents’ Characteristics
The study involved respondents with varied background characteristics. In terms of gender, 70.3% of
the respondents were males and 29.7% were females. 25.8% of the respondents were below 25 years
and 51.6% were between 25 and 35 years, and 19.5% between 36 and 45 years respectively, while
3.1% were between 46 and 55 years. This implies that majority of them were in the economically
active population (25 – 45 years). All respondents were educated with majority of them, 87.1% having
tertiary education, while 10.9% had Senior High School (SHS) and 7% had post-SHS education. In
terms of monthly income, few of them, 10.9% earned below GH¢100, 56.2% earned between GH¢101
to ¢500, while 19.5% and 10.2% earned between GH¢501 to GH¢1000 and GH¢1001 – 1500
respectively. 3.1% of them earned above GH¢1500. 60.9% of the respondents were operating savings
accounts, 33.6% operated current accounts and 5.5% held other banking accounts with their banks.
TABLE 1
CONSTRUCTS AND INDICATORS
Code Item FL
Perceived Barrier to Adoption
PBA1 Charges for the ATM are expensive 0.450
PBA2 Information on the ATM are secured 0.345
PBA3 ATM gets damaged or destroys easily 0.561
PBA4 ATM gets lost easily 0.322

PBA5 Replacing of lost card takes a long process 0.544
PBA6 ATM breaks down and not always available 0.536
Perceived Ease of Use
PEU1 ATM has simple instructions to follow for its use. 0.663
PEU2 ATM is convenient to use 0.841
PEU3 ATM easy to locate for use -0.143
Perceived Benefits
PBE1 Helps me to cash and access money quickly 0.685
PBE2 Helps me to check my balance quickly 0.611
PBE3 Gives me privacy for information on my accounts when checking my
balance
0.685
PBE4 Helps me cash money without anybody seeing me 0.432
PBE5 Helps me reduce the time needed for banking services 0.664
PBE6 Gives me enough freedom to serve myself 0.651
PBE7 Helps me to learn the usage of modern banking technology 0.616
PBE8 Always available for me to access banking services anytime 0.425
PBE9 Gives me a sense of personalised services 0.666
PBE10 Gives me recognition that i am a customer of the bank 0.508
Note: Table 1 shows the measurement constructs, their indicators and their respective initial Factor
Loadings (FL).
C. Procedures inConfirmatory Factor Analysis
First, as demonstrated in the literature review, all the constructs were based on theory and empirical
findings [24], [12]-[17]. Second, all the constructs in the proposed model are typically reflective in that
each of the variables in the proposed model are manifestations of the constructs they represent [18],
[27]. Together the constructs reflect factors that underpin user adoption of ATM in the research
context. Since each construct has more than two measurement items in the original model as shown in
the questionnaire (see Table 1) and at least two indicators in the final model, they can be said to be
unidimensional and congeneric. The study involved a cross-sectional survey that resulted in a useable
sample size of 256 which satisfies the sample size requirement for CFA.
Given the above satisfactory conditions, and the fact that the data appears to be normally distributed,
Maximum Likelihood estimation methods was deemed appropriate. As a result the output of AMOS
18.0 programme identified the model as recursive and admissible with the initial corresponding factor
loadings (FL)for each of the 19 indicators presented in Table 1. An examination of the initial factor
loadings revealed that some six of them were below the recommended 0.50 as indicated with the
strike-through (PBA1, PBA2, PBA4, PEU3, PBE4 and PBE8), so they were removed from the
analysis. Furthermore, diagnostic tests were run on the remaining 13 items using the modification
indices and the standardized residuals of the variables to reveal problematic variables. The results
indicated that some of the 13 remainingindicators had high covariance above 4 and residuals above 2,
which are indications that their corresponding observed variables highly covaried or had entry
problems. Since there were no entry problems upon critical examination of the original dataset, it
became apparent that those problematic observed variables were redundant. The problematic variables
are PBA3, PBE2,PBE4, PBE6, PBE7, PBE9, and PBE10. Again following the recommendation for
dealing with such problematic variables [18], [27], the most appropriate option was to delete those
observed variables because their deletion will not render the construct invalid. After deleting those
redundant variables, the model goodness-of-fit indices were improved significantly as shown in Table
2.

D. Model Goodness-of-fit
In using CFA, the measurement model is expected to show a good model fit indices before
proceeding to examine the psychometric properties of the model. The usual method is the use of the
chi-square method or the ratio of the chi-square to its degree of freedom, with a value less than 3
indicating acceptable fit [18], [27]. However, due to the fact that the chi-square of the default model
could be affected by large sample size greater than 250, many researchers recommend a combination
of several fitness indices for judging fitness of a structural model [18]. Several benchmarks for good-
fit indices have been suggested by many scholars [18], [27], [29] as shown in Table 2. Reference [18]
advise that to provide strong evidence of good model fit, a combination of at least one absolute
goodness-of-fit measure, one absolute badness-of-fit index, one incremental fit measure and one
comparative fit index should be used.
In this study, as shown in Table 2, all the fit-indices are either very close to or better than their
corresponding recommended values. Though the Chi-square shows a significant value (p = 0.011), this
is probably due to the large sample size, the rest of the fit indices appear satisfactory: the Chi-square to
the degree of freedom (CMIN/Df = 2.213, GFI = 0.975, AGF = 0.935, RMR = 0.029, RMSEA =
0.069, NFI = 0.957, CFI = 0.975, IFI = 0.76, and PCGF = 0.511. Therefore, there is good fit for the
model. Thus, we proceed to examine the standardized co-efficient for the estimated measurement
model.
TABLE 2
MODEL GOODNESS-OF-FIT
Goodness-of-fit Indices, Bench-mark value
Absolute goodness of fit
Chi-square (CMIN) P >0.05 0.011
Chi-square/degree of freedom ≤ 3 2.213
Goodness-of-fit Index (GFI) ≥ 0.90 0.975
Adjusted Goodness-of-fit (AGF) ≥ 0.80 0.935
Absolute badness of fit
Root Mean Residual (RMR) ≤ 0.1 0.029
Root mean Square Error of Approximation (RMSEA) ≤ 0.08 0.069
Incremental fit measure
Normed Fit Index (NFI) ≥0.90 0.957
Incremental Fit Index (IFI) ≥0.90 0.976
Comparative Fit Index (CFI) ≥ 0.90 0.975
Parsimony fit measure
Parsimony Comparative Fit (PCGF) ≥ 0.50 0.511
Table 2 is the goodness of fit indices for the model after CFA
E. Reliability
Reliability refers to the extent to which a measuring instrument yields consistent results under
similar conditions [18]. It is judged by strong theoretical basis for all construct indicators, high factor
loadings greater than or equal to 0.5 and high composite reliability (CR) value greater than or equal to
0.7 [18]. As mentioned earlier, all items in the model are derived from the literature, construct item
reliability values are shown by the factor loadings (FL) presented in Table 3. After the refinement of
scale, the Cronbach alphas indicate values greater than 0.70 for each construct, implying acceptable
level of reliability for each construct, except PBA which was 0.60.
F. Construct Validity
Construct validity are assessed through convergent validity and discriminant validity [18].
Convergent validity could be assessed through item reliability, composite reliability, and the average
variance extracted (AVE) [18]. As already demonstrated for item reliability in Table 3, the factor

loadings of items to their respective constructs are strong providing evidence to support the convergent
validity of the items measured [27], [29]. The composite reliability, which is a measure of internal
consistency comparable to coefficient alpha [18], [27, [29]] are above 0.70, implying acceptable level
of reliability for each of constructs. Finally, convergent validity is judged to be adequate when AVE
equals or exceeds 0.50. As shown in Table 3, all the AVE values in the diagonal are greater than 0.5
and the composite reliability (CR) are all above the recommended 0.70. Therefore, taken together, the
evidence from the high composite reliability values, high factor loadings, combined with high AVE
estimates provide strong evidence in support of convergent validity.
G. Discriminant Validity
Discriminant validity refers to the extent to which the measure of a construct does not correlate with
measures of other constructs, and thus measures the extent to which constructs are different. At the
construct level, discriminant validity is considered adequate when the variance shared between a
construct and any other constructs in the model (covariance) is less than the variance which that
construct shares with its measures (AVE) [18], [29]. As indicated in Table 3, the AVE estimates in the
diagonal are greater than the covariance below the diagonal (inter-construct correlations), therefore,
discriminant validity appears satisfactory at the construct level in the case of all constructs. This
indicates that each construct shared more variance with its items than it does with other constructs.
Since the results show good discriminant validity for the constructs, the constructs in the proposed
research model are deemed to be adequate.
TABLE 3
FACTOR LOADINGS, RELIABILITY AND DESCRIPTIVES
Items FL α CR MEAN SD
PBA 0.601 0.793
Item 1 0.577 3.593 0.756
Item 2 0.683 4.156 0.834
PEU 0.707 0.861
Item 1 0.704 3.976 1.036
Item 2 0.779 3.914 0.962
PBE 0.752 0.844
Item 1 0.676 4.093 1.020
Item 2 0.629 3.976 1.028
Item 3 0.840 4.112 0.975
Note: FL –Factor Loading; α–Cronbach alpha; CR – Composite reliability; SD –Standard deviation;
X – Means;
TABLE 4
AVE AND INTERCONSTRUCT CORRELATIONS
Constructs PBA PEU PBE
PBA 0.573
PEU 0.230 0.728
PBE 0.170 0.613 0.856
Note: The covariance are below the diagonal, AVE estimates are in diagonal.
V. DISCUSSION AND IMPLICATIONS
A. Theoretical Implications
The main purpose of this paper is to determine the most important factors that influence the adoption
of ATM services among customers in the Ghanaian banking industry (GBI) through CFA approach.

After the proposed model was validated through CFA, seven factors were found to be critical factors
that affect the adoption of ATMs in GBI. These three constructs and their respective remaining
indicators are presented in Figure 2 and Table 5.
Fig. 2 It depicts the remaining seven measurement items of the three critical factors affecting the
adoption of ATM services in GBI.
TABLE 5
CONFIRMED CONSTRUCTS AND INDICATORS
Code Item FL
Perceived Barrier to Adoption
PBA5 Replacing of lost card takes a long process 0.577
PBA6 ATM breaks down and not always available 0.683
Perceived Ease of Use
PEU1 ATM has simple instructions to follow for its use. 0.704
PEU2 ATM is convenient to use 0.779
Perceived Benefits
PBE1 Helps me to cash and access money quickly 0.840
PBE3 Gives me privacy for information on my accounts when checking my
balance
0.629
PBE5 Helps me reduce the time needed for banking services 0.676
Table 5 shows the remaining measurement items and their respective constructs after the CFA.
From Figure 2 and Table 5, two of the seven remaining factors relate to Perceived barrier dimension,
being:
 Replacing of lost card takes a long process
 ATM breaks down and not always available
Another group of two item factor relate to Perceived Ease of Use, being:
 ATM has simple instructions to follow for its use.
 ATM is convenient to use
Finally, the last group of items relate to Perceived Benefits of ATM to customers, being:
 ATM helps customers to cash and access money quickly

 ATM gives customer privacy for information on their accounts when checking accounts
balance
 ATM helps customer to reduce the time needed for banking transactions.
Thus, these seven factors are considered critical factors that are particularly relevant to the GBI, and
are to be given prime importance in banking strategy.
Theoretically, the paper adds to the general marketingand e-banking literature on the usefulness and
challenges banking customers face in use of ATMs [11]-[17], [29].
The study did not find support for eleven items that were originally proposed to be critically
important in GBI. Thus, it highlights the fact that items constituting critical ATM factors may differ
from one context to the other, and that marketing phenomenon may not always be generalizable across
all contexts. Thus, the extent to which perceived benefit, perceived barrier and perceived ease of use
will be critical to customers in ATM adoption will depend a number of factors ranging from
technology readiness [30], individual user adoption level, level of ICT technical know-how, to the
level of development of national e-banking platforms to enhance industry-wide delivery of quality
electronic banking services and products, among others.
This does not mean that these eleven items with low factor loadings are not important and therefore
do not require management attention. Rather, the findings suggest that in the context of GBI, the
eleven items may not be crucial and therefore may not occupy top priority in managerial strategy for
developing customer-driven ATMs.
B. Managerial Implications
This paper offers several implications and recommendations to management of electronic banks in
general, and ATMs in particular. The seven confirmed items found in this study have important
implications for management strategy.
In order to ensure that ATMs are meeting customer requirements and needs, it is recommended that:
1. Management should re-engineer the process of replacing lost ATM card
The study found that customer ATM adoption is affected significantly by the longevity of the period
for replace of lost ATM cards. This is consistent with previous qualitative studies [12]-[16] It is
recommended that management should re-engineer the process of lost card replacement to ensure that
the process is shorter, faster, and more effective to keep customers loyal.
2. Management should ensure immediate repair of faulty ATM
The study found that ATM adoption is affected bythe functionality of ATMs. Where customers
consistently find ATM to be non-functioning or dysfunctional it could affect their attitude and
intentions of using the ATMs, and therefore deny customers from making maximum use of it
[31].Non-functioning of ATM has been cited as one of the reasons for not adopting ATM by non-
users [17]. It is recommended that firms should think of providing adequate number of ATM [9],
[31] and ensure that those that break down are repaired immediately, especially during week-ends.
Further integrated software should be installed to signal ATM service personnel whenever ATM
develops fault.
3. Management should enhance the ease of use of ATMs.
It was found that customer perceived ease of use is critical to the adoption of ATMs. This is
consistent with existing marketing and information systems literature [11]-[17], [24], [31].
Specifically it found that the convenience and simplicity of instruction for the use of ATM are
crucial factors that affect consumer adoption of the self-service technology. It recommended that
management should keep enhancing the ease of use of ATMs by making its use more convenient,
simple to follow instruction, incorporating different local and other foreign languages, apart from
English into the instructions in using the ATMs.
4. Management should enhance perceived benefits of ATM
It was found that customer perceived benefits is critical to the adoption of ATMs. This is consistent

with many of the existing marketing and information systems literature [11]-[17], [24], [31].
Specifically, it found that the four of the proposed benefits are crucial to the adoption of ATM in the
research context. These results show that customers derive benefits from using ATMs that forms part
of customer value for a particular bank’s services [9], [32]. Thus management should continue to use
ATM to help customers to cash and access money quickly, give customers privacy for information on
their accounts when checking accounts balance, and help customers to reduce the time needed for
banking transactions.
It is also recommended that management should keep improving the quality of ATM services to give
customer more benefits. This could be an effective strategy towards influencing customer loyalty
behaviour towards banks.
CONCLUSION AND LIMITATIONS
In conclusion, the main purpose of this paper was to determine the most important factors that
influence the adoption of ATM services among customers in the Ghanaian banking industry (GBI)
through CFA approach. The paper concludes that within Ghanaian banking industry, critical perceived
barriers to ATM adoption includethe longevity in replacement of lost card and the breakdown of
ATMs making it unavailable always as it is expected by customers. Critical perceived ease of use
factors are simplicity of instructions to follow for ATM use and convenience in the process of using
ATMs. Finally, most important factors of perceived benefits that affect customer adoption of ATM are
ability to cash and access money quickly, providing customer privacy for information on their
accounts when checking accounts balance, and reducing the time needed for customers to do banking
transactions.
One limitation of the paper is that the model validated is context specific, in the GBI. Therefore,
the external validity of the model limited and that it is cautioned that the generalizability of the
findings should be interpreted in the context of GBI. It is recommended that future research should use
rigorous statistical data analysis such as CFA and SEM to study ATM adoption factors in other Sub-
Sahara Africa contexts to further our understanding of the critical ATM adoption factor for managerial
and theoretical implications.
REFERENCES
[1] Z. Liao and M.T. Cheung, “Measuring consumer satisfaction in internet banking: a core
framework”, Association for Computing Machinery.Communications of the ACM, Vol. 51 No. 4,
pp. 47-51, 2008.
[2] C. Garau, “Online banking in transition economies: The implementation and development of
online banking systems in Romania”, International Journal of Bank Marketing, 20 (6), 285-296,
2002.
[3] V.A. Zeithaml, A. Parasuraman, and A. Malhotra, “A conceptual framework for understanding e-
service quality: implications for future research and managerial practice”, Working Paper 00-115,
Marketing Science Institute, Cambridge, MA, 2001.
[4] Ghana Banking Survey, 2012. Downloaded at www.pwc.com/gh/en/pdf/ghana-banking-survey-
2012.pdf
[5] J. Abor, “Technological innovations and banking in Ghana: An evaluation of customers’
perceptions”, American Academy of Financial Management, 1, 1-16, 2004. [Online] Available:
http://www.financialcertified.com/armstrong.html on June 6, 2011.
[6] R. Boateng, “Developing E-banking Capabilities in a Ghanaian Bank: Preliminary Lessons”,
Journal of Internet Banking and Commerce, August 2006, vol. 11, no.2, 2006.
(http://www.arraydev.com/commerce/jibc/)
[7] A. Woldie, R. Hinson, H. Iddrisu, and R. Boateng, “Internet banking: an initial look at Ghanaian
bank consumer perceptions”, Banks and Bank Systems, Volume 3, Issue 3, 35-46, 2008.
[8] C. Grönroos, “Service model and its marketing implications”. Eur. J. Market., 18(4): 36-44,1984.
[9] C. Lovelock and J. Wirtz (2007) Services Marketing: People, Technology, Strategy (6th Ed.),
Pearson Prentice Hall, New Jersey
[10]V. Zeithaml, “Service Quality, Profitability and Economic worth of customers: what we know and

what we need to learn”. Academy of Marketing Journal,Winter, 2000.
[11]Mobarek, A. (2007). “E-Banking Practices and Customer Satisfaction - A Case Study in
Botswana”. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=10111 12
(Accessed on 16/02/2012)
[12]S.C. Chimeke and A.E Ewiekpafe and F.O. Chete “The Adoption of Internet Banking in Nigeria:
An empirical investigation”, Journal of Internet Banking and Commerce, Vol.11, No., 2006.
[13]W. M. Olatokun and L. J. Igbinedion, “The Adoption of Automatic Teller Machines in Nigeria:
An Application of the Theory of Diffusion of Innovation”, Issues in Informing Science and
Information Technology Volume 6, 2009
[14]J. O. Adeoti, “Automated Teller Machine (ATM) Frauds in Nigeria: The Way Out”, J SocSci,
27(1): 53-58, 2011.
[15]A. S. Adepoju and M. E. Alhassan Challenges of Automated Teller Machine (ATM) Usage and
Fraud Occurrences in Nigeria – A Case Study of Selected Banks in Minna Metropolis, Journal of
Internet Banking and Commerce, vol. 15, no.2, August 2010
[16]L. Abdulwahab, “Studies on e-transaction using the technology of automatic teller machine by
bank customers in north west geographical Zone of Nigeria”, Bayero Journal of Pure and Applied
Sciences, 3(1): 1 – 5, 2010.
[17]N. Y. Asabere, R. O. Baah, A. A. Odediyah, “Measuring standards and service quality of
automated teller machines (atms) in the banking industry of Ghana”, International Journal of
Information and Communication Technology Research, Volume 2 No. 3, pp. 216-226, March,
2012.
[18]J.F. Jr Hair, W.C. Black, B.J. Babin, R.E. Anderson and R.L. Tatham, Multivariate Data Analysis.
6th Edn., Upper Saddle, Pearson Prentice Hall, NJ., 2006.
[19]Burrows P (2001). The Era of efficiency. Bus. Week 18:94-98.
[20]M. J. Bitner, “Self-service technologies: what do customers expect?” Mark. Manag. 10(1):10-11,
2001.
[21]Corporation Bank FAQs on ATM Usage; Retrieved from:
http://www.corpbank.com/uploadedfiles/custom/ 2_00_350_ 538 5706.pdf (Accessed on
14/02/2011)
[22]Vargo, S.L. and R.F. Lusch,“Service-dominant logic: Continuing the evolution”. J. Market. Sci.,
36(1): 1-10, 2008.
[23]P. Legris, J. Ingham, & P. Collerette, “Why do people use information technology? A critical
review of the technology acceptance model”. Information & Management, 40, 191–204, 2004.
[24]F. D. Davis, R. P. Bagozzi, & P. R Warshaw, “User acceptance of computer technology: A
comparison of two theoretical models”. Management Science, 35(8), 982–1003, 1989.
[25]R.P. Bagozzi, "The legacy of the technology acceptance model and a proposal for a paradigm
shift.”, Journal of the Association for Information Systems, 8(4): 244–254, 2007.
[26]Ajzen, I., &Fishbein, M. Understanding attitudes and predicting social behavior. Englewood
Cliffs, NJ: Prentice-Hall., 1980.
[27]R.P. Bagozzi, and Y. Yi, “On the evaluation of structural equation models”. Acad. Market. Sci.,
16: 74-94, 1988.
[28]D. Straub, M. Boudreau, and D. Gefen, “Validation guidelines for IS positivist research”,
Communications of the Association for Information Systems, 13:380-427, 2004.
[29]H. Li and R. Suomi, “Customer’s adoption of e-service in the airline context: Addressing the
benefits and barriers”, IADIS International Conference e-Society, 2007.
[30]K.M, Elliott J, Meng, and M.C.Hall, “Technology Readiness and the likelihood to use self-service
technology: Chinese vs. American consumers”. Mark. Manag. J. 18(2):20-31, 2008.
[31]Joseph, M., & Stone, G., “An empirical evaluation of US bank customer perceptions of the impact
of technology on service delivery in the banking sector”. International Journal of Retail &
Distribution Management, 31(4), 190- 202, 2003.
[32]P. Kotler and K. Keller, “Marketing Management”, 12th Ed., Pearson Education Inc, New Jersey,
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