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: [email protected]

Nana Kwame Gyamfi

Department of Computer Science, Kumasi Polytechnic, Kumasi – Ghana,

West Africa.

E-mail:[email protected]

Critical ATM Adoption Factors in Ghanaian Banking Industry: CFA approach

mailto:[email protected]

mailto:[email protected]


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,

2006

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Critical ATM adoption