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Business Strategy SeriesEmerald Article: Satisfaction and trust on customer loyalty: a PLS approach

Bee Wah Yap, T. Ramayah, Wan Nushazelin Wan Shahidan

Article information:

To cite this document: Bee Wah Yap, T. Ramayah, Wan Nushazelin Wan Shahidan, "Satisfaction and trust on customer loyalty: a PLS

pproach", Business Strategy Series, Vol. 13 Iss: 4 pp. 154 - 167

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Satisfaction and trust on customer loyalty:

a PLS approach

Bee Wah Yap, T. Ramayah and Wan Nushazelin Wan Shahidan

1. Introduction

The concept of customer satisfaction has received much research attention in recent years.

Satisfying customers is a business challenge in todays competitive marketplace. Today,

firms have realized how important it is to understand, meet and predict customers needs.

Customers have also become increasingly conscious of their value to their banks. Due to the

highly competitive nature in the banking sector, customers will be the key factor indetermining the success of the enterprise. In short, under such intense competition, the

bank that has the largest customer base and the highest customer retention rate will be a

market leader in the industry. Hence, knowing customers needs how they feel about the

company and their expectations have become critically important for maximizing customer

retention.

Studies have shown that the long-term success of a firm is closely related to its ability to

adapt to customer needs and changing preferences (Takala et al., 2006). However, there are

instances when satisfying customers is just not enough. Recent evidence shows that

customers may switch some or all of their businesses to other suppliers even when they are

fully satisfied (Buttle et al., 2002). There are many reasons why customers are likely to

change to other firms. Process improvements, the advent of new technology in banking,

change in customers priorities, customer personalization and improved quality of service

provided by competitors are just a few examples.

Research has shown that there is a positive relationship between customer satisfaction and

financial performance (Fornellet al., 1996). Another important issue is that customer loyalty

is increasingly being recognized by American businesses as a path to long-term business

profitability (Mittal and Lassar, 1998). Some business analysts have suggested that the cost

of recruiting a new customer is fivetimes more than the cost of retaining an existing customer

(Reichheld and Sasser, 1990; Lam and Burton, 2006). Customer loyalty is also deemed as

critical to the conduct of business in todays competitive marketplace and banks are no

exception (Ehigie, 2006). Studies have shown that there is a positive relationship between

customer satisfaction and loyalty in the banking sectors (Hallowell, 1996; Lam and Burton,

2006; Ball et al., 2006). These studies have shown that customer satisfaction is a leading

factor in determining loyalty. In other words, the degree to which customers are satisfied with

their banking experience plays a central role in their loyalty to the bank. However, there arealso studies that suggest trust is more important than satisfaction in ensuring loyalty

(Ranaweera and Prabhu, 2003; Caceras and Paparoidamis, 2007).

Most banks outsource projects on customer satisfaction to survey companies while some

carry out their own small scale customer satisfaction surveys to improve their services.

However, most banks do not place emphasis on studying the level of trust and loyalty of their

customers. According to Reichheld (1993), satisfied customers are more likely to

concentrate their business with one bank. Studies by Kish (2000) and, Duncan and Elliot

PAGE 154 jBUSINESS STRATEGY SERIES j VOL. 13 NO. 4 2012, pp. 154-167, Q Emerald Group Publishing Limited, ISSN 1751-5637 DOI 10.1108/17515631211246221

Bee Wah Yap is a Lecturer

in the Faculty of Computer

& Mathematical Sciences,

Universiti Teknologi MARA,

Selangor, Malaysia.

T. Ramayah is a Professor in

the School of Management,Universiti Sains Malaysia,

Minden, Malaysia.

Wan Nushazelin Wan

Shahidan is a Lecturer in

the Faculty of Computer

& Mathematical Sciences,

Universiti Teknologi MARA,

Perlis, Malaysia.


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(2002) showed links between customer loyalty and organizational profitability, thus implying

that any organization with loyal customers has considerable competitive advantage. Hence,

in studies on customer satisfaction, trust and loyalty are essential and useful for banks in

developing their strategies for better customer retention. In order to gain competitive

advantage and overcome the problem of customer switching or defecting, it is imperative

that banks measure their customer satisfaction, trust and loyalty level. There are several

variations of the CSI model. The objective of this paper is to test a proposed CSI model and

re-examine the interrelationships between service quality, satisfaction, complaint handling,

trust and loyalty. The proposed conceptual model is given in section 2. A description of the

research methodology is presented in section 3 while the findings are discussed in section

4. The conclusion in section 5 highlights the aims achieved, limitations of the paper and

further possible research.

2. Conceptual foundation

2.1 Review of CSI models

All customer satisfaction indices are usually calculated based on a structural model that

consists of antecedents and consequences of customer satisfaction. This section presents

several variations of CSI models. In the middle of the 1990s, CSI was gradually recognized

by governments and companies worldwide as a good instrument for measuring a nations or

companys output quality. The American Customer Satisfaction Index (ACSI) model

(Anderson and Fornell, 2000) introduced in 1994 is a structural model that links the latentvariables of customer expectations, perceived quality and perceived value to customer

satisfaction. Satisfaction is then linked to customer complaints and loyalty. The successful

experience of the Swedish and American customer satisfaction indexes inspired the

creation of the European Customer Satisfaction index (ECSI), founded by the European

Organization for Quality (EOQ), the European Foundation for Quality Management (EFQM),

and supported by the European Commission (DG III) (Martensen et al., 2000). The ECSI has

a similar model to the ACSI. Although the core model is standard, there are some variations

between them. The split between product quality (hardware) and service quality

(software) has been generalized. Quality is related to the consumers quality experience with

a service, and refers both to product quality or hardware and service quality or software. In

the ECSI model, the variable customer complaints was not taken into account. The

variable corporate image was included with effects on customer expectations, satisfaction

and loyalty. Graphically the ECSI model is displayed in Figure 1.

The CSI models have evolved year by year and additional factors have been included for the

main purpose to explain loyalty better. For example, a study by Ball et al.(2004) introduced

trust and communication in the ECSI model and their latest study in 2006 introduced

personalization as an antecedent of customer satisfaction, trust and also customer loyalty as

shown in Figure 2. From the model reported by Ball et al. (2006) the customer satisfaction

index (CSI) model consists of antecedents of customer satisfaction and the consequents of

customer satisfaction. Customer satisfaction is explained by a firms image, the customers

expectation, perceived value, perceived quality, and communication between firm and

customer and personalization. The two consequents of customer satisfaction are customer

loyalty and customer complaints. The antecedents of loyalty are customer satisfaction,

complaint handling, trust and personalization.

2.2 The proposed CSI model

Figure 3 presents the proposed research model of the study which was adapted from the

revised European Customer Satisfaction Index (ECSI) model by Ball et al. (2006). The

proposed model focuses on service quality as the key antecedent of customer satisfaction

and three antecedents of customer loyalty (trust, satisfaction and complaint handling). The

main difference between this model and the ECSI model is that satisfaction is proposed as

an antecedent of trust. This model also hypothesizes that complaint handling has an effect

on satisfaction, trust and loyalty.

VOL. 13 NO. 4 2012 jBUSINESS STRATEGY SERIESjPAGE 155


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Customer expectation is not included in the proposed model because some studies have

found that customer expectation has no or very little impact on customer satisfaction and

loyalty (Martensen et al., 2000; Johnson et al., 2001). Moreover, Martensen et al. (2000)

recommended that the expectation variables be excluded in future ECSI models. The study

by Turkyilmaz and Ozkan (2007) also showed customer expectations have the lowest effect

on satisfaction. Although the study by Martensen et al. (2000) found that image has the

largest impact on satisfaction and loyalty, the study by Aydin and Ozer (2005) reported that

corporate image does not have a statistically significant effect on loyalty. The proposed CSI

model therefore concentrates only on five latent variables which are trust, perceived service

quality, satisfaction, complaint handling and loyalty.

Figure 1 The European Customer Satisfaction Index (ECSI) model

Figure 2 The updated European Customer Satisfaction Index (ECSI) model revised by

Ballet al.(2006)

PAGE 156jBUSINESS STRATEGY SERIESjVOL. 13 NO. 4 2012


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A detailed explanation of the variables (or factors) of the proposed CSI model is given as

follows.

2.2.1 Service quality. Gronroos (1984) proposed the concept of service quality whereby

service quality consists of two dimensions: technical quality which is the quality of what is

delivered; e.g. the quality and effectiveness of loan procedures of the bank, and functional

quality, which is the quality of how the service is delivered the care and manners of the

delivery personnel. Meanwhile, Fornell et al. (1996) defined two types of perceived quality,

which are product quality and service quality. Perceived product quality is the evaluation of

recent consumption experience of products while perceived service quality is the evaluation

of recent consumption experience of associated service like customer service, conditions ofproduct display, and the range of services and products. This study focuses on perceived

service quality because the industry selected in this paradigm, i.e. banking industry, is a

service industry (Levesque and McDougall, 1996).

Parasuraman et al. (1998) proposed five dimensions of the service experience in their

well-known SERVQUAL model. SERVQUAL measures service quality as five dimensions:

reliability, responsiveness, assurance, empathy and tangibles.

Delivery of high service quality to customers offers businesses an opportunity to

differentiate themselves in competitive markets (Yavas and Benkenstein, 2007). Service

quality seems to lead to positive word-of mouth, lessening of complaint tendencies and

continuity in bank-customer relationship (Caruana, 2002). Levesque and McDougall (1996)

stated that high service quality results in customer satisfaction and loyalty, greater

willingness to recommend to someone else, reduction in complaints and improved

customer retention rates. In this study, perceived service quality is defined as the

evaluation of relational service (or customer service) and enabling service features (such

as convenient branch locations, operating hours and range of services). The items for

service quality were adapted from the work of Beerli et al. (2004). Thus the following

hypothesis is proposed:

H1. Service quality has a positive effect on satisfaction.

Figure 3 Proposed model and hypothesis



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2.2.2 Customer satisfaction. As reported by Fornell et al. (1996) customer satisfaction

improves a companys performance. Customer satisfaction has been conceptualized in two

different ways: transaction-specific satisfaction and overall satisfaction. Most studies focus

on overall satisfaction which refers to the customers overall (dis)satisfaction with the banks

based on all encounters and experiences with the particular bank. When dissatisfaction

occurs, customers become less likely to utilize additional services in the future, and more

likely to engage in switching behavior and vice-versa. According to Hansemark and

Albinsson (2004), satisfaction is an overall customer attitude towards a service provider or

an emotional reaction to the difference between what customers anticipate and what they

receive, regarding the fulfillment of some need, goal or desire. Customer satisfaction is

found to be positively correlated with customer loyalty (Hallowell, 1996; Bendall-Lyon and

Powers, 2003; Lam and Burton, 2006; Ball et al., 2006).

In this study, satisfaction is defined as an overall customer attitude towards a service

provider. The customer satisfaction measures were adapted from the work by Levesque and

McDougall(1996), and Dimitriades (2006) and the following hypothesis is proposed:

H2. Satisfaction has a positive effect on trust.

H3. Satisfaction has a positive effect on loyalty.

2.2.3 Trust. The study by Doney and Cannon (1997) showed that perceived service quality

was positive and significantly affects trust, and trust has positive and significant effects on

loyalty. Ranaweera and Prabhu (2003) argued that trust is a stronger emotion thansatisfaction and that it may therefore better predict loyalty. Their study confirmed that trust

has positive effect on retention or loyalty. Trust was also found by Hsu (2007) to have a

positive effect on loyalty and it helps to attract new customers and later can retain existing

ones besides influencing overall satisfaction.

According to Aydin and Ozer (2005), in order to gain trust; one party must believe that

another party will perform actions that will result in positive outcomes for it and the customer

should perceive quality as positive. Therefore, in building trust, the customer should not only

perceive positive outcomes but also believe these positive outcomes will continue in the

future. Their results showed that perceived service quality positively affected trust and trust

has positive effect on loyalty. According to Ganesan (1994), trust has two components:

performance or credibility trust and benevolence trust. Hence this study defined trust as

belief that the service provider will deliver as promised (credibility trust). and belief that the

service provider is acting in the best interests of the customers and will not take advantage of

the relationship (benevolence trust). The trust measure consists of four items adapted from

Ballet al. (2004) and Ballet al.(2006). Thus, the following hypothesis was proposed:

H4. Trust has a positive effect on loyalty.

2.2.4 Loyalty. Loyalty of a firms customer has been recognized as the dominant factor in a

business organizations success. In the study by Lam and Burton (2006) they found that loyal

customers are more likely to participate in repeat purchases from a supplier or increase their

share of purchases from a particular supplier. They may also provide a recommendation of

business to their bank provider or engage in word of mouth promotion. Customer loyalty can

also lower costs and increase profitability, as the cost of recruiting a new customer is said to

be five times more than the cost of retaining an existing customer. It is also claimed that the

costs of customer retention are substantially less than the relative costs of customeracquisition, and loyal customers, if served correctly, are said to generate increasingly more

profits each year when they stay with a company (Reichheld and Sasser, 1990; Lam and

Burton, 2006).

There are two dimensions to customer loyalty: behavioral and attitudinal. Behavior

dimension refers to a customers behavior on repeat purchases and indicates a preference

for brand or service. Attitudinal dimension refers to a customers intention to repurchase and

recommend, which are good indicators of loyal customers (Dick and Basu, 1994).



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According to Ehigie (2006) loyalty can be defined as a feeling of commitment on the part of

the customer to a product, brand, marketer or services: staying with same provider, likely to

take out new products with the bank and recommend the banks services. He also stated that

loyal customers visit banks more frequently than newly acquired customers do, and they can

be served at a reduced operating cost because there will be fewer complaints to deal with.

Loyalty includes a customers intention to return to a service provider as well as their intention

to recommend the provider to others (Bendall-Lyon and Powers, 2003) and a customers

desire to continue the relationship (even if competitors lower prices), willingness to

recommend to a friend, and intentions to continue patronizing (Ball et al., 2006).

Studies have shown that customer satisfaction is correlated with loyalty, and satisfaction has

been claimed to be a leading factor in determining loyalty (Ehigie, 2006). When customers

are not satisfied with the bank they are less likely to purchase additional services and then

this will lead to switching to other providers, as well as leading to negative word-of-mouth

(Bendall-Lyon and Powers, 2003). This study defined loyalty as the intention of customers to

continue to stay with the bank, intention to repurchase or return for future purchases and

willingness to recommend the bank and service to others. The loyalty measures consist of

two items adapted from Beerli et al.(2004) and one item from Ehigie (2006).

2.2.5 Complaint handling. Levesque and McDougall (1996) found that when customers face

a problem, they may respond by exiting (switching to new supplier), voicing (attempting to

remedy the problem by complaining) or stay loyal (staying with the supplier anticipating that

things will get better). They stated that when the service provider accepts responsibility

and resolves the problem, the customer becomes bonded to the organization. When the

customers complain, they give the firm a chance to rectify the problem and interestingly, if

the firm recovers successfully to increase loyalty and profits. A good recovery (complaint

handling) can turn angry, frustrated customers into loyal ones. Service recovery can help

reduce dissatisfaction, defection and increase loyalty (Spreng et al., 1995).

Johnston (2001) claimed that complaint handling not only results in customer satisfaction but

also leads to operational improvement and improved financial performance. Indeed

research on satisfaction with complaint processes specifically has also shown a clear

relationship of complaint handling with loyalty and repurchases intentions (Halstead and

Page, 1992).

Hansemark and Albinsson (2004) found that encouraging consumers to complain increased

their satisfaction, and this was especially the case for the most dissatisfied customers. Their

study found that dissatisfied customers can become satisfied when complaints are

welcomed and the problem is solved. This will show the customer that you care and are

trying enough. They believe there is more to win than to lose in handling a complaint,

referring both to chance of winning the customer back and to possible positive word of

mouth. The study by Levesque and McDougall (1996) found that customer complaint

handling can have an influence on customer satisfaction and retention. Complaint handling

in this study is defined as the extent to which their complaints will be handled by the bank.

The complaint handling measures were adapted from the work of Chatelin and Esposito

Vinzi (2002). This leads to the following three hypotheses:

H5. Complaint handling has a positive effect on satisfaction.

H6. Complaint handling has a positive effect on trust.

H7. Complaint handling has a positive effect on trust.

3. Research method

3.1 Research setting and subjects

In light of globalization and financial liberalization leading to intense competition, financial

institutions should place emphasis on retaining their customers. The target population for

this study involves bank customers. Several banks were contacted via telephone but only



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one local bank agreed to allow the survey to be carried out. The two main reasons for

rejecting the proposed survey is that they have outsourced their customer satisfaction study,

and they are worried that customers will complain if were asked to answer questionnaires

while they are at the bank. The manager of the local bank requested that the survey be a

simple one so that it will not take up too much of the customers time. Since the sampling

frame was not available, the sample of this study consists of randomly selected customers

who came to the bank at the time the survey was conducted.

3.2 Sample size

Since the measures are continuous data, based on calculations suggested by Bartlett et al.

(2001), the minimum required sample size obtained using the Cochrans sample size

formula was 118. Sample size determination should take into consideration the statistical

techniques that will be deployed in the study. According to Hair et al. (2010) the ratio of

observations to independent variable should not fall below five (5:1) although the preferred

ratio recommended should be ten respondents for each independent variable (minimum

ratio of observation to variables is 10:1). Hence, considering the 23 variables to be used in

exploratory factor analysis and structural equation modeling, this study required a minimum

sample size of 230 respondents.

3.3 Data collection method

Data was collected via a developed structured questionnaire. Since no sampling frame was

available, samples could not be obtained via probability sampling method. Thequestionnaire was distributed to the bank customers with the assistance of a support

letter from the bank requesting them to participate in this study. Participants were assured of

confidentiality and anonymity of their returned questionnaires. Self-administered

questionnaires with assistance from the researcher were used to ensure a better

response rate. Customers at the bank were given the questionnaires while they were

waiting for their turn to be served. An attempt was made to randomize data collection at

different times of the day and week. At the end of the data collection period, a total of 247

questionnaires were collected. However, only 239 fully completed questionnaires were used

for data analysis.

3.4 Measurement of variables

The questionnaire was developed by adapting measurements from various studies.

Measures for perceived service quality are adapted from Beerli et al. (2004). They reportedtwenty items to measure perceived service quality but in this study the service quality

construct consists of only eight items. The trust construct consists of four items adapted from

the work of Ball et al. (2004) and Ball et al. (2006). The measures for customer satisfaction

construct consist of three items adopted from Levesque and McDougall (1996) and

Dimitriades (2006). The measures for complaint handling construct consists of three items

adapted from Chatelin and Esposito Vinzi (2002). The loyalty construct consists of five items

adapted from the work of Beerli et al.(2004) and Ehigie (2006). The items for each construct

and their scale of measurements are listed in Table I.

3.5 Data analysis

To test the hypotheses generated we used the partial Least squares (PLS) approach using

the Smart PLS M2 Version 2.0 (Ringle et al., 2005) to analyze the data. We used the

bootstrapping method (200 resamples) to determine the significance levels for loadings,

weights, and path coefficients (Chin, 1998; Gil-Garcia, 2008).

4. Results

4.1 Demographic profile of respondents

Of the 239 respondents, a total of 121 (51 percent) were female while 118 (49 percent) were

male. The age group of 31-40 (36 percent) and 21-30 (32 percent) account for the biggest



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portion of the sample followed by age 40-51 years (19 percent). For education attainment,

about 25 percent possessed diploma degree, 23 percent (Bachelor) and 18 percent

(Master). Only 7 percent had a PhD degree. Most of the respondents were professionals

(34.4 percent). Majority 66.5 percent of the respondents have been with the bank for more

than three years.

4.2 Measurement model

We used the two-step approach as suggested by Anderson and Gerbing (1988). We firstassessed convergent validity and reliability as shown in Table I and then the discriminant

validity in Table II. Convergent validity can be ascertained if the loadings are greater than 0.5

(Bagozzi and Yi, 1991), composite reliability greater than 0.7 (Gefen et al., 2000) and the

average variance extracted is greater than 0.5 (Fornell and Lacker, 1981).

We also tested for the discriminant validity (see Table II) using the Fornell and Lacker (1981)

criterion whereby the average variance shared between each construct and its measures

should be greater than the variance shared between the construct and other constructs. As

shown in Table II, the correlations for each construct is less than the square root of the

Table I Results of measurement model

Model construct Measurement item Loading CR a AVEb

Complaint handling COMPLAIN1 0.872 0.849 0.738COMPLAIN2 0.846

Loyalty LOYAL1 0.901 0.930 0.768LOYAL2 0.864LOYAL3 0.909LOYAL4 0.828

Satisfaction SAT1 0.914 0.921 0.796SAT2 0.857SAT3 0.904

Service quality SQ1 0.704 0.912 0.567SQ2 0.743SQ3 0.821SQ4 0.843SQ5 0.784SQ6 0.798SQ7 0.654SQ8 0.652

Trust TRUST1 0.702 0.854 0.596TRUST2 0.777TRUST3 0.808TRUST4 0.796

Note:COMPLAIN3 and LOYAL5 were deleted due to low loadings of ,0.50; aComposite Reliability

(CR)(square of the summation of the factor loadings)/{(square of the summation of the factor

loadings) + (square of the summation of the error variances)}; bAverage Variance Extracted

(AVE)(summation of the square of the factor loadings)/{(summation of the square of the factor

loadings) + (summation of the error variances)}

Table II Discriminant validity of constructs

Constructs 1 2 3 4 5

1. Complaint handling 0.8592. Loyalty 0.463 0.8763. Satisfaction 0.486 0.832 0.8924. Service quality 0.608 0.592 0.581 0.7535. Trust 0.444 0.595 0.684 0.566 0.772

Note:Diagonals represent the square root of the average variance extracted while the other entries

represent the correlations



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average variance extracted by the indicators measuring that construct indicating adequate

discriminant validity.

4.3 Structural model

The structural model was tested next. The results are presented in Table III and Figure 4. The

R2 values ranged from 0.365 to 0.695 which suggest that the modeled variables can explain

36.5 to 69.5 percent of the variance of the respective dependent variables. As shown in

Table III, all hypotheses were fully supported.

5. Discussion

This study proposed a CSI model which is adapted from the ESCI model. This model

re-examines the relationship between satisfaction, trust and loyalty by proposing satisfaction

as an antecedent of trust. The results of this study support the findings in the literature that

service quality has a positive effect on customer satisfaction (Caruana, 2002; Levesque and

McDougall, 1996). This study also provided empirical evidence that satisfaction has a

positive effect on trust and this trust will eventually has a positive influence on loyalty to the

bank (Hallowell, 1996; Bendall-Lyon and Powers, 2003; Lam and Burton, 2006; Ballet al.,

2006). Complaint handling is found to have a significant effect on satisfaction, trust and

loyalty (Johnston, 2001; Hansemark and Albinsson, 2004; Levesque and McDougall, 1996).Therefore, banks should not take complaint handling lightly as poorly handled complaints

may be viewed by consumers as banks incompetence and lack of care towards their

customers.

Table III Path coefficients and hypothesis testing

Hypothesis Relationship Coefficient t-value Supported

H1 Service quality! satisfaction 0.453 5.866** YesH2 Satisfaction! trust 0.613 14.216** YesH3 Satisfaction! trust 0.795 9.047** YesH4 Trust! loyalty 0.485 8.944** YesH5 Complaint handling! satisfaction 0.211 2.382** Yes

H6 Complaint handling! trust 0.146 2.305* YesH7 Complaint handling! loyalty 0.248 3.323** Yes

Note:*p, 0.05; **p, 0.01

Figure 4 Results of the structural model analysis



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5.1 Implications

Banks should focus on building credibility trust (belief that the provider will deliver as

promised) and benevolence trust (belief that the service provider is acting in the best

interests of the customers) with their customers. Commercial service is of utmost importance

and hence banks should develop strategies and train officers on delivering efficient

communication and administrative service as these will elevate customer satisfaction. In

conclusion, this study can be replicated and results could be further validated by collecting

more data from various banks. This would lead to a better generalization for the banking

sector. The CSI model can also be revised to include other antecedents of customersatisfaction and loyalty and investigation of mediating and moderating effects of trust and

satisfaction on loyalty. Future research could also focus on standardizing the various

measurements of service quality, satisfaction, trust, complaint handling and loyalty.

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Chichester.



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Appendix

About the authors

Bee Wah Yap received her MSc (Statistics) from the University of California, Riverside, USAand her PhD (Statistics) from the University of Malaya, Malaysia. Currently she is anAssociate Professor in the Department of Statistics, Faculty of Computer and MathematicalSciences. She teaches courses in multivariate analysis, statistical modeling and datamining. She is an avid researcher, especially in the areas of applied and computationalstatistics. Her publications have appeared in Expert Systems with Applications, AppliedStochastic Models in Business and Industry, International Journal of Business and Social

Table AI Measurement items for each construct

Label Construct Source

Service quality

SQ1 When you have a problem, bank shows a sincere

interest in solving it

Adapted from Beerli et al.(2004). Scale 1 (very

dissatisfied) to 7 (very satisfied)

SQ2 Employee of bank solves your problems when

they promise to do so

SQ3 Employees of bank give you prompt service

SQ4 Employees of bank are willing to help you

SQ5 Employees of bank are never too busy to

respond to your request

SQ6 Banks give you individual and personal attention

SQ7 Bank has operating hours convenient to all its

customers

SQ8 Bank has convenient branch locations

Complaint handling

COMPLAIN1 How well was your most recent complaint

handled?

Adapted from Chatelin and Esposito Vinzi (2002).

Scale: (1) extremely poor to (10) extremely well

COMPLAIN2 Imagine you have to complain to this bankbecause of bad quality of service/product

COMPLAIN3 How well do you think your complaint will be

handled?

Trust

TRUST1 I feel that I can rely on this bank to serve well Adapted from Ballet al. (2004) and Ball et al.

TRUST2 The bank treats me in an honest way in every

transaction

(2006). (1) strongly disagree to (7) strongly

agree

TRUST3 I believe that I can trust this bank will not try to

cheat me

TRUST4 This bank is reliable because it is mainly

concerned with the customers interests

Satisfaction

SAT1 Overall, I am satisfied with this bank Adapted from Levesque and McDougall (1996)

SAT2 My bank meets my expectations and Dimitriades (2006). (1) strongly disagree

SAT3 The overall quality of the service provided by this

bank is excellent

to (7) strongly agree

Loyalty

LOYAL1 I prefer this bank above others Adapted from Beerliet al.(2004) and

LOYAL2 I intend to continue using this bank Ehigie (2006) Scale: (1) strongly disagree

LOYAL3 I would recommend this bank to others to (7) strongly agree

LOYAL4 I am a customer loyal to my bank

LOYAL5 I a m t hinking o f c losing m y a ccount w ith t his b ank



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Science, Journal of Statistical Computation and Simulationand Journal of Applied Sciences.She is constantly invited to review papers for international journals and proceedings. BeeWah Yap is the corresponding author and can be contacted at: [email protected]

T. Ramayah has a MBA from the Universiti Sains Malaysia (USM). Currently he is anAssociate Professor at the School of Management at USM. He teaches mainly courses inresearch methodology and business statistics. Apart from teaching, he is an avidresearcher, especially in the areas of technology management and adoption in business andeducation. His publications have appeared in Computers in Human Behavior, ResourcesConservation and Recycling, Direct Marketing: An International Journal, Information

Development,Journal of Project Management

,Management Research News

,InternationalJournal of Information Management, International Journal of Services and Operations

Management, Engineering, Construction and Architectural Management, and NorthAmerican Journal of Psychology. He is constantly invited to serve on the editorial boardsand program committees of many international journals and conferences of repute. Hisprofile can be accessed at www.ramayah.com

Wan Nushazelin Wan Shahidan received her MSc (Statistics) from the Universiti TeknologiMARA. Currently she is a Lecturer in the Faculty of Computer and Mathematical Sciences,Universiti Teknologi MARA. She teaches courses in mathematics and statistics. She is anavid researcher, especially in the areas of applied statistics.


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