International Journal of Bank Marketing
Customer satisfaction, loyalty and financial performance: A holistic approach of the
Greek banking sector
Elissavet Keisidou Lazaros Sarigiannidis Dimitrios I. Maditinos Eleftherios I. Thalassinos
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Customer satisfaction, loyalty and
financial performance
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A holistic approach of the Greek
banking sector
The Greek
banking sector
259
Elissavet Keisidou, Lazaros Sarigiannidis and
Dimitrios I. Maditinos
Department of Business Administration,
Technological Educational Institute of Kavala, Kavala, Greece, and
Eleftherios I. Thalassinos
Department of Maritime Studies, University of Piraeus, Piraeus, Greece
Abstract
Purpose – The present paper is an attempt to provide a holistic approach of the Greek banking sector
and how it operates.
Design/methodology/approach – A survey was carried out in the banking sector of Greece in order
to gather information regarding customer satisfaction and loyalty, while the financial data of the
banks were attained from their annual financial statements. Structural equation modelling was used to
test the hypotheses.
Findings – It has been found that neither customer satisfaction nor loyalty has a significant impact
on the financial performance of banks, while the remaining factors have indicated unprecedented
results.
Research limitations/implications – The main limitation of the study is the economic
environment of Greece and the general crisis of the banking sector.
Practical implications – The study provides an insight into the Greek banking sector and the
interrelationships among the investigated factors, and how customer satisfaction and loyalty could be
enhanced through the remaining factors.
Originality/value – A new factor, the economics factor, was created and included in the study.
Moreover, the tangibles factor was tested as an individual and not as part of service quality.
Additionally, the present study is among the few that have incorporated customer satisfaction, loyalty
and the financial performance of banks. To take it one step further, some more factors were included to
present a more holistic approach of how customer satisfaction and loyalty are enhanced.
Keywords Customer satisfaction, Customer loyalty, Financial performance, Service quality, Image,
Value, Brand credibility, Economics, Convenience, Tangibles, Banking, Greece
Paper type Research paper
1. Introduction
The financial sector relies on the maintenance of a long-term relationship with its
customers, due to the nature of the products and services it provides, and the loss of a
client is viewed with concern (Sweeney and Swait, 2008). The importance of customer
satisfaction in financial services has been studied extensively in the existing literature
(Arbore and Busacca, 2009) and the marketing activity of many companies has focused
on achieving customer loyalty (Vesel and Zabkar, 2009). The studies that recognise
the significance of customer loss regarding the profitability of an industry are
abundant (Sweeney and Swait, 2008; Chi and Gursoy, 2009; Fathollahzadeh et al., 2011;
Akhter et al., 2011).
International Journal of Bank
Marketing
Vol. 31 No. 4, 2013
pp. 259-288
r Emerald Group Publishing Limited
0265-2323
DOI 10.1108/IJBM-11-2012-0114
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260
It has been stated that the antecedents of customer satisfaction and loyalty are
intricate, developing over time and dynamic ( Johnson et al., 2006) and the full extent of
the interrelations among the factors that affect them have not been completely
understood (Taylor et al., 2006). The main objective of the present study is to determine
the factors that affect customer satisfaction, as well as the factors that influence
customer loyalty. And then both of these constructs are tested in order to underline
their importance towards the profitability of banks. This study is in a position to
provide managers with a more complete view of which factors determine customer’s
satisfaction and loyalty and furthermore, the extent to which they affect the financial
performance of banks.
2. Literature review
2.1. The Greek banking sector
The banking sector in Greece consists of 18 commercial banks, 16 co-operative banks
and one credit institution (the foreign credit institutions have not been included)
(Bank of Greece, 2011). The six largest banks of Greece (National Bank of Greece, EFG
Eurobank, Alpha Bank, Pireaus Bank, Agricultural Bank of Greece and Commercial
Bank of Greece) hold a market share of more than 60 per cent in terms of total assets
(Organisation for Economic Co-Operation and Development (OECD), 2010).
During the first stages of the international financial crisis, Greek banks faced minor
difficulties due to two main reasons: their substantial capital adequacy and their
decision not to invest in toxic securities (Hellenic Bank Association, 2010). The
government implemented a liquidity support programme, which in general involved
the provision of bonds and guarantees to the banks, aiming that the economy
would absorb the liquidity generated by this programme through loans (Hellenic Bank
Association, 2011).
However, due to the vast financial debt and lack of trust in the local economy,
Greek banks faced the degradation of the government bonds, which they used in
order to borrow money from other European financial institutions, causing them to
suffer great losses. Additionally, soon the global media started spreading various
speculations stating that the Greek government was about to declare bankruptcy. The
main source of money in the Greek banking sector was and still is the deposits
of the people (Hellenic Bank Association, 2011). Those rumours and fear of losing their
money led people to withdraw their money or transfer their deposits abroad which
sharpened the hostile environment even more.
The Greek government has guaranteed to safeguard deposits up to 100,000.00h, five
times higher than the “pre-crisis” amount (Hellenic Bank Association, 2011).
Everything else is left to be done by the banks. Their survival depends on how they
will plan their strategy to increase their profitability. In this adverse banking
environment, the retention of customers appears to be more crucial than ever. It seems
as if the banking sector is compelled to emphasise on customer satisfaction and loyalty
(Hossain and Leo, 2009) in order to enhance its financial performance.
2.2. Previous studies
The literature which studies the relationships among customer satisfaction, customer
loyalty and the financial performance has been divided into two groups. The first,
involves the service management literature, where customer satisfaction affects
customer loyalty which in turn influences profitability (Hallowell, 1996). Chi and
Gursoy (2009) have stated that a satisfied customer turns into a loyal one and a loyal
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customer, in time, will lead to higher sales and therefore higher financial returns for the
company. Zeithaml et al. (1990), Reicheld and Sasser (1990), Anderson and Fornell
(1994), Heskett et al. (1994), Storbacka et al. (1994), Rust et al. (1995) and Schneider
and Bowen (1995) are all supporters of this theory. According to Hallowell (1996) the
study of the way the above factors interact was initiated by Nelson et al. (1992),
who tested the relationship of customer satisfaction to customer profitability in the
context of hospitals.
The service management literature argues that customer satisfaction results from
the perceptions of customers about the value they receive when making a transaction
or when being part of a relationship, compared to the value provided by the
competition. In this context, value is defined as the perceived service quality relative to
price and customer acquisition costs (Hallowell, 1996). It is believed that customers
recognise and value remarkable services when offered to them and over time they will
exhibit loyalty behaviours (Chi and Gursoy, 2009).
The second group, the marketing literature, studies the impact of customer
satisfaction on customer loyalty and suggests that customer loyalty can be defined in
two different ways, as attitude and as behaviour ( Jacoby and Kyner, 1973). According
to the attitudinal definition, different feelings create an individual’s attachment to an
organisation, product or service. These feelings state the individual’s degree of
loyalty (Hallowell, 1996). Examples of the behavioural definition include the
continuing purchase of services from the same supplier, which increases the level of
relationship (Yi, 1990).
Nowadays, a considerable amount of banks direct their strategies towards
customer satisfaction (Arbore and Busacca, 2009). Researchers such as Winstanley
(1997), Ehigie (2006) and Ndubisi (2006), have proven that customer satisfaction is a
link between critical customer behaviours and the tendency of an individual to
consider his/her bank as one that he/she has a relationship with. Liang et al. (2009)
stated that loyalty is the most important factor in predicting customers’ repetitive
purchasing intentions.
Over time, researchers have identified many other factors that influence customer
satisfaction and loyalty. For example, service quality has been viewed as a factor
that has a strong link to satisfaction (Taylor and Baker, 1994; Levesque and
McDougall, 1996; Johnston, 1997; Lassar et al., 2000; Oppewal and Vriens, 2000; Jamal
and Naser, 2002; Ndubisi, 2006; Arbore and Busacca, 2009; Culiberg and Rojšek, 2010).
Parasuraman et al. (1985) claimed that service quality consists of five dimensions:
reliability, tangibles, responsiveness, assurance and empathy, which are widely known
as the SERVQUAL model.
Culiberg and Rojšek (2010) employed six factors (the five of the traditional
SERVQUAL instrument and access) to measure service quality and its effect on
customer satisfaction but after the factor analysis they were reduced to four.
Assurance and empathy were considered one factor and so did reliability and
responsiveness. All four factors were found to have a positive effect on customer
satisfaction with the assurance-empathy factor being the strongest (Culiberg and
Rojšek, 2010).
Others stated that there are two dimensions that affect customer satisfaction: the
quality of the core service which is provided by the bank and the quality of the
relationship with the bank. The first dimension consists of reliability, security,
functionality, accuracy and speed, while the second includes responsiveness,
competences, assurance, trust, friendliness, courtesy availability, commitment,
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flexibility and communication (Levesque and McDougall, 1996; Johnston, 1997;
Winstanley, 1997; Jamal and Naser, 2002).
Arasli et al. (2005) found that service quality has a positive effect on customer
satisfaction in the Greek-Cypriot banking sector. Ehigie (2006) carried out a research in
Nigeria and found that service quality and satisfaction were strongly related to
customer loyalty. Bloemer et al. (1998) found that service quality had both a direct and
an indirect effect, through customer satisfaction, on customer loyalty.
Akhtar et al. (2011) tested the effect of service quality of Islamic banking on
customer satisfaction in terms of assurance, compliance, empathy and
representativeness and concluded that their relationship is positive. Ladhari et al.
(2011) compared the differences in perceptions of service quality in the banking sector,
using the SERVQUAL instrument, between Tunisians and Canadians and found that
tangibles had no significant effect in both countries. Empathy was found to be the
most important factor that affected both satisfaction and loyalty in Canada while in
Tunisia reliability and responsiveness were found to be the most influential factors
(Ladhari et al., 2011). Baumann et al. (2007) found that empathy, overall satisfaction and
affective attitude can help predict customer loyalty.
Furthermore, Hossain and Leo’s (2009) findings in Qatar, Sohail and Shaikh’s (2008)
findings in Saudi Arabia and Jamal and Ananstasiadou’s (2009) findings in Greece,
suggest that the tangibles factor is a significant predictor of customer
satisfaction. On the other hand, Kheng et al. (2010) tested the SERVQUAL model on
customer satisfaction and loyalty and found that tangibles affected neither
satisfaction, nor loyalty. Also, responsiveness was found to be insignificant
regarding loyalty, while reliability was found not to contribute in the creation of
customer satisfaction.
Korda and Snoj (2010) examined the relations among service quality, value and
satisfaction and found that both service quality and value strongly affect satisfaction.
Arun Kumar et al. (2010) examined the effect of overall service quality on loyalty in the
context of private banking and found positive results. Lai et al. (2009) examined
the various interrelationships among service quality, value, satisfaction, image and
loyalty in the context of telecommunications. Their results showed customer
satisfaction and perceived value have a direct positive effect on loyalty.
Regarding loyalty, apart from customer satisfaction and service quality that were
mentioned earlier, image is another factor that is thought to have a direct effect
on it (Mazursky and Jacoby, 1986; Bloemer et al., 1998). In a research carried out by
Akhter et al. (2011), it was found that customer loyalty is directly and positively
affected by customer satisfaction, product image, trustworthiness and customer
relationship. Fathollahzadeh et al. (2011) studied the effects of customer value on
customer loyalty in terms of satisfaction, co-operation, trust, commitment, service
quality, complaint handling, image and communication in the banking sector and
found that all eight variables were significant. Ogba and Tan (2009) found that
brand image has a positive effect on customer loyalty, commitment, perceived
quality and satisfaction, regarding the telecommunication sector. In addition Sweeney
and Swait (2008) studied the role of brand credibility as a construct that influences both
loyalty and satisfaction.
Varki and Colgate (2001) studied another factor, the cost and especially the
price-quality ratio and the price fairness. Matos et al. (2009) found that switching costs
have a direct effect on loyalty and act as mediators in the satisfaction-loyalty
relationship. Oppewal and Vriens introduced the location factor, both in terms of
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accessibility and convenience. Wu (2011a) found that locational convenience has
neither a direct effect nor an indirect effect through satisfaction, on loyalty.
Moreover, some researchers pointed out the positive impact of problem-solving
skills on customer satisfaction (Levesque and McDougall, 1996; Ndubisi, 2006). Vesel
and Zabkar (2009) found that personal interaction quality affects customer satisfaction
and customer satisfaction influences customer loyalty. No relation was found
between personal interaction quality and loyalty. Thuy and Hau (2010) examined the
effect of service personal values towards customer satisfaction and loyalty and their
hypotheses were verified.
Al-Wugayan and Pleshko (2010) examined customer loyalty and satisfaction and
the effect they have on the market share of banks that offer mutual funds investment
services. They found that only loyalty has a strong linkage to the market share of the
bank. Chi and Gursoy (2009) in their study examined and verified that employee
satisfaction and customer satisfaction lead to better financial performance in the
hospitality industry.
As it can be seen, in recent years many studies have focused on satisfaction and
loyalty, the factors that affect them and how they result in positive financial benefits.
Service quality is among the most widely studied factor in the existing literature.
Those studies usually neglect the effects of others factors on both satisfaction and
loyalty. Wanting to fill this gap and after examining all the aforementioned studies,
in the following section a more complete research model and the hypotheses that were
formed, are stated.
3. Research model and hypotheses
After the wide, extensive and in-depth study of the existing literature, a new model
that has not been tested before is being proposed in this study. The most important
characteristic of this new holistic model is the fact that it is the first time that customer
satisfaction and loyalty are being tested to such an advanced degree by employing
so many factors. The factors that have been selected to be studied in this paper are:
economics, convenience, tangibles, functional and relational quality, image, value,
brand credibility, customer satisfaction, customer loyalty and the financial
performance of banks.
The majority of the factors (functional and relational quality, image, value, brand
credibility) were selected due to the fact that they have been widely tested in literature.
However, they have never been combined in one model before, to see how they
interact with one another and the cumulative effect they have on both satisfaction and
loyalty. The factors that are not as widely tested in literature (economics, convenience,
tangibles) were selected for different reasons. The “economics” factor was constructed
to provide a more general variable than the ones previously used in literature, while
the “convenience” factor was incorporated due to lack of substantial empirical results.
The “tangibles” factor, although it is widely known as part of the SERVQUAL model,
not enough evidence exist where it is tested as an individual factor and since in this
study service quality is measured by functional and relational quality, it was
considered wise to include it.
There are other models that have attempted to provide an understanding of how
customer satisfaction and loyalty interact, like the one of Lee and Overby (2004) who
have divided value in two dimensions (utilitarian and experiential) and tested
how these two dimensions affect satisfaction and how satisfaction affects loyalty in an
online retailers environment. While it provides an in-depth insight of value, it is far
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more simplistic than the one proposed in the present study. Another model is the
American customer satisfaction index (ACSI) proposed by Fornell et al. (1996) which
incorporates antecedents (expectations, perceived quality and value) and consequences
(voice and loyalty) of overall customer satisfaction. Although there are similar factors
in both the ACSI and the proposed model, the ACSI is rather limited to predicting
customer satisfaction while the proposed one is attempting to predict customer loyalty
as well, and how both satisfaction and loyalty can predict the financial performance
of companies. The proposed model is more complete and presents a holistic approach
of customer satisfaction and loyalty and their effects on the financial performance
in the banking sector. A schematic illustration of the proposed research model is
presented in Figure 1.
3.1. Economics
The economics factor, in its present form, has not been mentioned in the existing
literature. Lee and Cunningham (2001) in their study have employed the economic costs
factor, which they distinguish in monetary and non-monetary costs. Monetary
costs include service costs (price) and non-monetary costs involve service time (the
amount of time necessary for a service to be provided). Trassoras et al. (2009)
considered price as part of the approach for measuring value. Levesque and
McDougall (1996) considered competitive interest rates as part of the service features
that affect customer satisfaction.
In this form, it is a more general construct of the economic-related items which
previously have been used as individual constructs by the aforementioned researchers
(Levesque and McDougall, 1996; Lee and Cunningham, 2001; Trassoras et al., 2009).
It deals with the cost of transactions and interest rates that are established by a bank.
It involves structures like price fairness and price-quality ratio (Levesque and
ECONOMICS
H
1
(+
)
CONVENIENCE
TANGIBLES
H2
(+)
H3 (+
)
FUNCTIONAL
QUALITY
H4
(
,2
a1
+)
H4
c
d1 1, 2
,2
(+ (+)
)
SERVICE QUALITY
H8
+)
a(
CUSTOMER
SATISFACTION
)
,2
)
Figure 1.
Research model
+)
H6
b(
+)
BRAND
CREDIBILITY
)
H6
a(
H
VALUE
)
(+
(+
)
a
H5
)
(+
5b
IMAGE
H7
a
(+
FINANCIAL
PERFORMANCE
(+
)
H4
H5d
(+)
,2
(+
b1
RELATIONAL
QUALITY
H6d (+)
c1
c
H8b (+)
H4
H5c1, 2 (+)
H6
H8
b
H7
)
(+
CUSTOMER
LOYALTY
H9
(+
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McDougall, 1996; Lee and Cunningham, 2001; Varki and Colgate, 2001; Nagar and
Rajan, 2005; Matzler et al., 2006; Manrai and Manrai, 2007). Levesque and McDougall
(1996) stated that the economic-related factors are usually considered as part of the
overall satisfaction.
Since in this form it has never been tested before, no evidence exists in literature
regarding its effect. Overcoming this gap in literature and based on other
studies that have employed other economic structures, this newly developed factor
is thought to positively affect the satisfaction the customers receive from their
selected banks:
H1. Lower economics have a positive effect on customer satisfaction.
3.2. Convenience
Convenience is scarcely mentioned in the existing literature, yet it has been found to
have a positive effect on customer satisfaction (Arbore and Busacca, 2009; Wu, 2011a).
It involves issues such as the location of a bank, the opening hours, the distance that a
customer has to travel to reach a bank, the parking places around the bank and the
ATM availability (Levesque and McDougall, 1996; Oppewal and Vriens, 2000; Jones,
2004; Manrai and Manrai, 2007).
In the study carried out by Wu (2011a) locational convenience, which involves the
necessary time and effort for a customer to reach one’s service provider (Seiders et al.,
2000), was tested in order to examine the moderating effect it had on customer
satisfaction with regard to different types of service providers. Another type of
convenience is inertia (Wu, 2011b). Inertia is defined by the customer’s unwillingness to
search for new products and services due to habitual attachments to the existing status
quo (Lee and Cunningham, 2001; Gounaris and Stathakopoulos, 2004; White and
Yanamandram, 2004; Ye, 2005). In a struggling economy, as is the Greek economy, all
forces of habit tend to disappear and thus inertia is not incorporated in the convenience
factor. In this study the operational and locational characteristics of bank convenience
are tested on the effect they have on customer satisfaction:
H2. Convenience has a positive effect on customer satisfaction.
3.3. Tangibles
This factor includes constructs like the physical layout and furniture of a bank, the
physical facilities, the equipment, the cleanliness, the personnel appearance and the
atmosphere and environment inside the bank (Arbore and Busacca, 2009; Hossain and
Leo, 2009). It refers to the physical appearance and atmosphere every bank has created
by utilising their resources.
Some researchers support that tangibles have no impact on customer satisfaction
(Wakefield and Blodgett, 1999; Oppewal and Vriens, 2000; Jones, 2004; Kheng et al.,
2010; Ladhari et al., 2011) where others support the exact opposite (Levesque and
McDougall, 1996; Jamal and Naser, 2002; Sohail and Shaikh, 2008; Hossain and Leo,
2009). Jamal and Ananstasiadou (2009) found that tangibles are one of the most
important predictors of customer satisfaction in the Greek banking sector. Although
the tangibles factor is considered to be part of the SERVQUAL instrument in the
present study it is used as a separate variable:
H3. Tangibles have a positive effect on customer satisfaction.
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3.4. Functional and relational quality
Service quality is considered to be a key factor for a successful business, especially
banks (Angur et al., 1999; Akhtar et al., 2011), and is considered to contribute in
achieving strategic benefits and increasing the competitive advantage (Akhtar et al.,
2011). Service quality, as a term, originated from the product quality and customer
satisfaction literature (Korda and Snoj, 2010). It involves the customer’s evaluation
about the overall excellence of the product or service offered and it is based on the
difference between the customer’s pre-consumption performance expectations and
the post-consumption performance of the product or service (Parasuraman et al., 1988;
Culiberg and Rojšek, 2010; Korda and Snoj, 2010).
Service quality in the banking sector is viewed to increase customer satisfaction and
to contribute to profitability (Ladhari et al., 2011). Moreover, it decreases customer
defection, it increases customer loyalty and enhances corporate image (Arasli et al.,
2005; Baumann et al., 2007). Additionally, exceptional service quality is considered
to enable the development and maintenance of long-term customer relations
(Camarero, 2007).
In order for researchers to measure service quality in the banking sector they most
commonly employ the SERVQUAL instrument (Parasuraman et al., 1988; Ladhari et al.,
2011) which consists of five dimensions (tangibles, reliability, responsiveness,
assurance and empathy) and it has been widely tested in the context of different types
of service providers which include banks, restaurants, hotels and insurance companies,
and regarding different countries (Parasuraman et al., 1985; Hossain and Leo, 2009;
Ladhari et al., 2011).
Many researchers have questioned the use of the SERVQUAL instrument to
measure service quality due to the fact that it measures the gap between expectations
and performance. The same researchers suggest that service quality should only be
based on performance measures (Cronin and Taylor, 1992; Brown et al., 1993; Teas,
1993; Levesque and McDougall, 1996; Ladhari et al., 2011). More specifically, Brown
et al. (1993) stated that there is no distinction between perception and expectation
scores and Cronin and Taylor (1992) added that service quality is measured more
precisely by using the performance scores. Furthermore, Culiberg and Rojšek (2010)
questioned the universal character of the instrument regarding its dimensions and the
scale it is measured on.
Moreover, the five dimensions of the SERVQUAL instrument have raised
substantial doubts regarding the use of all five variables (Brown et al., 1993; Cronin
and Taylor, 1992; Teas, 1993; Ladhari, 2009). It has been stated that there are two
prevailing dimensions of service quality, the functional or core and the relational
one (Morgan and Piercy, 1992; Levesque and McDougall, 1996). Functional quality
measures items like reliability, speed, accuracy, security and functionality of a service
provided, while relational quality measures items like the responsiveness,
assurance, friendliness, courtesy, commitment and communication (Levesque and
McDougall, 1996; Johnston, 1997; Winstanley, 1997; Jamal and Naser, 2002; Arbore and
Busacca, 2009).
Several researchers have found that both functional and relational quality have a
strong connection to customer satisfaction (Taylor and Baker, 1994; Levesque and
McDougall, 1996; Johnston, 1997; Lassar et al., 2000; Oppewal and Vriens, 2000;
Jamal and Naser, 2002; Arasli et al., 2005; Ndubisi, 2006; Arbore and Busacca, 2009;
Culiberg and Rojšek, 2010; Ladhari et al., 2011) and loyalty (Bloemer et al., 1998;
Ladhari et al., 2011). Moreover, it has been stated that service quality has a positive
direct effect on customer value and that it is the factor best predicting it (Petrick, 2004;
Lai et al., 2009; Korda and Snoj, 2010). Additionally Lai et al. (2009) validated in their
study that service quality contributes to corporate image.
Considering all the above, it was decided not to employ the traditional SERVQUAL
model, instead functional and relational quality will be employed:
H4a1. Functional quality has a positive effect on customer satisfaction.
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H4a2. Relational quality has a positive effect on customer satisfaction.
H4b1. Functional quality has a positive effect on customer loyalty.
H4b2. Relational quality has a positive effect on customer loyalty.
H4c1. Functional quality has a positive effect on value.
H4c2. Relational quality has a positive effect on value.
H4d1. Functional quality has a positive effect on image.
H4d2. Relational quality has a positive effect on image.
3.5. Image
Although image is considered a valuable asset for companies, a widely accepted
definition does not exist (Pina et al., 2006). Hatch and Schultz (1997) suggested to
opposing viewpoints of image, one related to the organisational literature and the other
to the marketing literature.
The organisational literature suggests that the image of a company is defined
be the way its members would like external stakeholders to perceive it. In other
words, image is the internal notions of the company’s public impression. The
marketing literature suggests that the image of a company is defined by the
perceptions of all the external stakeholders, especially customers, and it represents
their beliefs and attitudes towards it (Pina et al., 2006). Image has been used
extensively to describe how customers perceive a company, regarding the products
and services it offers and its reputation, and it is considered to be able to generate
value (Fathollahzadeh et al., 2011). A favourable image is regarded as an important
factor in maintaining the company’s market position (Korgaonkar et al., 1985).
It reflects a customer’s overall impression about the company (Bloemer et al., 1998)
and is thought to influence the customers’ perceived service quality (Korda and
Snoj, 2010).
The exact relationship between image and loyalty is a matter of debate. According
to Sirgy and Samli (1989) and Akhter et al. (2011), there is a positive relationship
between image and loyalty. Fathollahzadeh et al. (2011) stated that the higher the
customers perceived image of the company, the higher level of loyalty they will exhibit.
Ogba and Tan (2009) verified the positive relationship of image on satisfaction, loyalty
and service quality and Lai et al. (2009) verified that image has a positive direct effect
on value and satisfaction:
H5a. Image has a positive effect on customer satisfaction.
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H5b. Image has a positive effect on customer loyalty.
H5c1. Image has a positive effect on functional quality.
H5c2. Image has a positive effect on relational quality.
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268
H5d. Image has a positive effect on value.
3.6. Value
Porter (1996) stated that the creation of superior customer value is considered to be one
of the most essential factors that can lead to the success of a company. Moreover, it has
been said that perceived value is a significant part of high costumer involvement
industries, as is the banking sector (Angur et al., 1999). Trassoras et al. (2009) stated
that perceived value is a factor that influences loyalty.
A widely accepted definition states that value reflects the customers’ perceptions of
the delivered products or services and not what a company desires to provide
(Fathollahzadeh et al., 2011). Woodruff (1997) mentioned that customer value is linked
to the relationship of what the customer pays to acquire and use a product or service,
and his/her notion of what he has received. In other words, value derives from the
benefits-sacrifices relationship; the higher the relationship is, the higher the level of
perceived value (Korda and Snoj, 2010).
Value is considered to increase the company’s competitive advantage and has, as
well, a significant effect on customer satisfaction and loyalty (McDougall and
Levesque, 2000; Lai et al., 2009; Trassoras et al., 2009). Additionally, Fathollahzadeh
et al. (2011) found that value is strongly connected to image and influences service
quality:
H6a. Value has a positive effect on customer satisfaction.
H6b. Value has a positive effect on customer loyalty.
H6c1. Value has a positive effect on functional quality.
H6c2. Value has a positive effect on relational quality.
H6d. Value has a positive effect on image.
3.7. Brand credibility
Brand credibility is defined as the level to which the product or service position
information is considered to be believable. It entails the consistent delivery of what has
been promised to the customers and it represents the cumulative effect of all marketing
attempts of the past (Erdem et al., 2002).
The brand of any company and especially banks can play an important role in
the marketing actions because the brand functions as a signal. An important
characteristic of this signal is its credibility (Erdem and Swait, 1998). The notion
of credibility is distinguished in two main dimensions: trustworthiness and
expertise. Trustworthiness suggests the brand delivers what has promised
while expertise suggests its capability to deliver it (Erdem et al., 2002).
Every customer feels related not only to the personnel of the institution, but to the
brand name of the bank as well (Licata and Chakraborty, 2009). Managing the brand
name of a bank effectively can lead in the retention of more and more customers
(Trassoras et al., 2009). Brand credibility involves the customers’ beliefs about the
commitment to be provided the quality of service that has been declared by the bank.
Brand credibility is considered to have a positive influence on both customer
satisfaction and loyalty (Sweeney and Swait, 2008):
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H7a. High brand credibility positively affects customer satisfaction.
H7b. High brand credibility positively affects customer loyalty.
3.8. Customer satisfaction
It has been stated that customer satisfaction is the most influential factor on customer
loyalty (Kanning and Bergmann, 2009; Hoq and Amin, 2010). Oliver (1980) defined
customer satisfaction as the difference between an individual’s expectations before
the consumption of a product or service and the actual experience that results the
consumption. The term satisfaction describes the sense of fulfillment (Vesel and
Zabkar, 2009), that a customer feels after having interacted with a company (Wu,
2011a). Additionally, it can be defined as the evaluation that occurs after the
consumption of a product or service and at what degree it has met or exceeded the
customers’ expectations (Yu and Dean, 2001; Akhtar et al., 2011).
Regarding the banking sector, Ladhari et al. (2011) defined customer satisfaction
as the total evaluation of the overall level of services provided. It is thought that
satisfaction is likely to increase customer loyalty (Vesel and Zabkar, 2009; Akhter et al.,
2011) and according to the service-profit chain and other studies, it is suggested
that satisfied customers result in better financial performance (Bernhardt et al., 2000;
Chi and Gursoy, 2009; Fathollahzadeh et al., 2011). Kandampully and Hu (2007) tested
the effect of customer satisfaction on image, regarding hotels and verified that there
is a positive relationship between them. Wanting to be innovative, this relationship is
studied in the context of banks:
H8a. Customer satisfaction has a positive effect on image.
H8b. Customer satisfaction has a positive effect on customer loyalty.
H8c. Customer satisfaction has a positive effect on financial performance.
3.9. Customer loyalty
Loyalty can be measured with both attitudinal and behavioural items ( Jacoby and
Kyner, 1973; Dick and Basu, 1994; Fathollahzadeh et al., 2011; Akhter et al., 2011).
Attitudinal measurements, due to the fact that they reflect the psychological and
emotional attachment to loyalty, are used in order to understand the cognitive elements
that underlie purchasing motives and future actions (Bowen and Chen, 2001;
Fathollahzadeh et al., 2011). They are viewed to add some degree of value to the
product or service (Wu, 2011a). Behavioural measurements, on the other hand, focus on
the customer’s purchasing history (Vesel and Zabkar, 2009; Fathollahzadeh et al., 2011)
and have been measured by the repetitive purchasing behaviour that a customer
shows towards a product or service (Wu, 2011a).
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270
Another distinction of customer loyalty is between active loyalty and passive loyalty.
Active loyalty refers to the word-to-mouth advertising and the customer’s intention
to use a product or service, while passive loyalty involves the customer’s decision
to remain with the company even when he/she is not fully satisfied with the products
or services delivered (Fathollahzadeh et al., 2011; Akhtar et al., 2011). It is said that
true loyalty is demonstrated when individuals choose to remain customers of a
company even when they are not offered the best quality of products and services
(Ahluwalia et al., 2000). The type of loyalty that is characterised by commitment is
called premium quality (Gounaris and Stathakopoulos, 2004). Furthermore, Tucker
(1964) stated that brand loyalty is a biased outcome of a combination of characteristics,
which do not contribute equally to the choice a user makes.
Loyalty regarding the banking sector is defined as the customer’s repeated
patronage of a certain bank over a long period of time (Ladhari et al., 2011). Loyal
customers are characterised by repetitive purchasing of products and services,
recommending the company to others, defending it against bad comments by strongly
supporting their choices (Akhter et al., 2011).
Hallowell (1996) suggested that loyalty increases the financial performance
of an organisation. It has been reported that a 5 per cent increase in customer
retention can lead from 25 to 85 per cent increase in profits (Ladhari et al., 2011; Akhter
et al., 2011):
H9. Customer loyalty has a positive effect on the financial performance of banks.
3.10. Financial performance of banks
Financial performance as a factor, is not commonly measured in literature, however,
the researchers that have included it in their studies have measured it in a variety of
ways. Anderson et al. (1994, 1997) chose to measure the financial performance in terms
of return on investment. In the research carried out by Chi and Gursoy (2009) in the
hospitality industry, financial performance was measured by asking the managers
of every hotel to rate their hotel’s financial performance in comparison to their
three major competitors in terms of profitability, return on investment and net profit.
Hallowell (1996), on the other hand selected two indicators to measure financial
performance: return on assets and non-interest expense as a percentage of
total revenue.
In the present study a new, more realistic approach was adopted. When anyone
refers to the financial performance of a company he/she refers to its profitability. Thus,
the three most widely known profitability ratios were used to measure the true
financial performance of banks. These are: return on assets or investment, net profit
margin and return on equity.
4. Research methodology
4.1. Sample
The sample of the research is random and consists of 304 bank customers throughout
Greece who have at least one bank product and have transactions with their banks,
which implies that they maintain a close relationship with their financial institution.
Hair et al. (2010) suggested that the observation to independent value ratio should
not be less than five (5:1), although the recommended ratio is ten responses for each
independent variable (10:1). In the present study 42 items where employed thus making
the minimum sample size 210 and the ideal 420 responses. Due to time limitations, the
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sample size that was collected was 304 responses which surpass the minimum 5:1 ratio
stated by Hair et al. (2010). Other studies in the banking sector that have significant
results with a sample that does not abide by the 10:1 ratio include the one of Zafar et al.
(2012) and Chen et al. (2012).
Every respondent was asked to choose one bank from those they might have
transactions with as their main bank, and complete a questionnaire which would refer
to their perceptions of their selected bank.
4.2. Data collection method
The collection of the necessary data was made with the use of a questionnaire. The
construction of the questionnaire was made after thorough and in-depth research
of the existing literature.
The questionnaire consists of three parts: the first part states the purpose of the
research, the second part is about the participants’ personal characteristics (age,
education, income, etc.) and consists of eight questions and the third part contains the
42 questions used to measure the previously mentioned factors. It has been distributed
with personal interviews, telephone interviews, e-mails and through social networking
sites. Moreover, a web site was constructed to further promote the questionnaire online.
Since the research was carried out in Greece, all the questions were translated in
Greek and were checked by professional translators and academics, in order to avoid
any misinterpretations. Then a pilot testing was carried out to further ensure the
minimisation of misinterpretations.
All questions were measured in a one to five-Likert scale and a total of 304 usable
questionnaires were returned. These data were processed with both statistical
programmes SPSS and AMOS in order to test the hypotheses mentioned earlier.
4.3. Measurement development
As mentioned earlier, in order to select the items that were used in the construction of
the questionnaire, the existing literature was studied extensively. Table I provides a
synopsis of the items used to measure the aforementioned factors.
5. Empirical analysis – results
5.1. Respondent’s profile
A detailed view of the respondents’ profile is provided in Table II.
5.2. Description of statistical data
The results indicate that the participants of this study consider themselves customers
of 12 banks. Furthermore, the percentages of the respondents’ preferred banks do not
correspond to the market share of each bank in terms of total assets as stated by the
OECD (2010), yet it can be viewed as the true market share in terms of customer
preference.
Most of the participants of the research (91.1 per cent) have visited their bank
o12 times in the last trimester and 62.5 per cent have visited their bank less than
five times, which clearly validates the sharp economic situation of the banking
sector in Greece. A more detailed view of the aforementioned discussion is provided
in Table III.
5.3. Content validity
The purpose of content validity is to eliminate or correct questions that have not
fulfilled their research objective (Bock and Kim, 2002). Kim et al. (2008) in order to
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272
Factors
References
Economics
Adapted from Levesque and McDougall (1996), Lee and
Cunningham (2001) and Trassoras et al. (2009)
Culiberg and Rojšek (2010)
Ladhari et al. (2011)
Levesque and McDougall (1996)
Convenience
Tangibles
Functional quality
Relational quality
Image
Value
Brand credibility
Customer satisfaction
Customer loyalty
Table I.
Factors’ measurement
development
Financial performance
Data
Gender
Male
Female
Single
Married
Divorced
Widowed
Primary school
Junior high school
Senior high school
University degree
Masters degree
PhD degree
Under 18
18-24
25-34
35-44
45-54
55-64
65-74
Over 75
Less than 5,000h
5,001h-10,000h
10,001h-15,000h
15,001h-20,000h
20,001h-25,000h
25,001h-30,000h
30,001h-40,000h
More than 40,001h
Education level
Age
Income
Table II.
Respondents’ profile
Adapted from Lai et al. (2009) and Bravo et al. (2009)
Adapted from Lai et al. (2009) and Trassoras et al. (2009)
Sweeney and Swait (2008)
Levesque and McDougall (1996), Sweeney and Swait
(2008), Licata and Chakraborty (2009), Thuy and Hau
(2010)
Zeithaml et al. (1996), Jamal and Ananstasiadou (2009),
Liang et al. (2009), Trassoras et al. (2009) and Thuy and
Hau (2010)
ROA/ROI, NPM, ROE
Measure
Marital status
Items
3
3
4
5
5
5
3
6
4
4
3
Frequency
%
128
176
156
124
17
5
9
13
115
104
51
11
1
51
112
76
38
21
5
0
44
59
42
48
37
35
26
9
42.1
57.9
51.7
41.1
5.6
1.7
3.0
4.3
38.0
34.3
16.8
3.6
0.3
16.8
36.8
25.0
12.5
6.9
1.6
0.0
14.7
19.7
14.0
16.0
12.3
11.7
8.7
3.0
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Measure
Data
Respondents’ bank
National Bank of Greece
Eurobank
Alpha Bank
Pireaus Bank
Agricultural Bank of Greece
Commercial Bank
Marfin Egnatia Bank
Hellenic Post Bank
Bank of Cyprus
Millennium Bank
Attica Bank
Geniki Bank
Under 5 years
6-10 years
11-20 years
Over 21 years
Less than 5 times
5-12 times
13-20 times
More than 21 times
Customer of the bank
Bank visits in the last trimester
Frequency
%
97
46
30
46
31
14
9
7
13
2
3
6
106
106
59
17
190
87
15
12
31.9
15.1
9.9
15.1
10.2
4.6
3.0
2.3
4.3
0.7
1.0
2.0
36.8
36.8
20.5
5.9
62.5
28.6
4.9
3.9
ensure the validity of the instrument, proposed a thorough review of the existing
literature, followed by a pilot testing among experts on the subject and then a
confirmatory pilot testing involving another group of respondents.
All items were adopted or formed after studying extensively the existing literature
which fulfils the first criterion. Then a pilot testing among experts and professionals
of the subject was conducted so as to verify that the scales measure what they were
intended to measure (Chu and Murramann, 2006). Last but not least, another pilot
testing was conducted which did not include any of the participants of the previous
pilot testing. This process has allowed the questions of the instrument to be clearly
stated and easily comprehended, and avoid any misinterpretations of their meaning
among the respondents.
5.4. Unidimentionality analysis
This type of analysis provides evidence that a construct that is not visible can be
formed by combining different items (Flynn et al., 1990). The two most common
methods of assessing the level of unidimentionality of a factor are: the exploratory
factor analysis (EFA) and the confirmatory factor analysis.
The main objective of the EFA is to summarise the information of a large
group of variables into a smaller one by allocating them into distinct factors
without significant loss of their containing information (Hair et al., 1995). The
extraction of the factors was performed with the method of principal component
analysis and the orthogonal varimax. Moreover, the measure sampling adequacy of
Kaiser-Mayer-Olkin was used, which measures the degree to which some items belong
to the same factor.
The analysis showed that from the 45 items that were used 11 factors are produced.
The results of this analysis (Table IV) justify the use of the EFA since all the criteria are
well exceeded.
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Table III.
Bank usage data
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Conceptual factors
Items
Loadings
KMO
TVE
Bartlett’s
test
significance
Functional quality (FQ)
B.1.1.
B.1.2.
B.1.3.
B.1.4.
B.1.5.
B.2.1.
B.2.2.
B.2.3.
B.2.4.
B.2.5.
B.3.1.
B.3.2.
B.3.3.
B.3.4.
B.3.5.
B.4.1.
B.4.2.
B.4.3.
B.5.1.
B.5.2
B.5.3.
B.5.4.
B.5.5.
B.5.6.
B.6.1.
B.6.2.
B.6.3.
B.6.4.
B.7.1.
B.7.2.
B.7.3.
B.8.1.
B.8.2
B.8.3.
B.9.1.
B.9.2.
B.9.3.
B.9.4.
B.10.1.
B.10.2.
B.10.3.
B.10.4.
C1
C2
C3
0.763
0.886
0.778
0.814
0.793
0.930
0.775
0.774
0.808
0.796
0.839
0.838
0.796
0.769
0.857
0.730
0.698
0.794
0.845
0.843
0.888
0.889
0.925
0.935
0.785
0.770
0.778
0.789
0.599
0.603
0.751
0.705
0.705
0.733
0.804
0.810
0.841
0.920
0.895
0.781
0.761
0.878
0.873
0.738
0.757
0.804
62.121
0.000
0.844
0.808
68.469
0.000
0.883
0.815
68.153
0.000
0.881
0.736
81.291
0.000
0.883
0.881
67.342
0.000
0.901
0.780
68.676
0.000
0.848
0.629
61.088
0.000
0.675
0.714
72.285
0.000
0.808
0.835
76.821
0.000
0.896
0.818
78.108
0.000
0.906
0.785
98.648
0.000
0.773
274
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Relational quality (RQ)
Image (IMG)
Value (VAL)
Brand credibility (BC)
Tangibles (TANG)
Convenience (CONV)
Economics (ECON)
Satisfaction (SAT)
Loyalty (LLT)
Table IV.
Exploratory factor
analysis and reliability
analysis results
Financial performance (FPER)
Cronbach’s
a
Confirmatory factor analysis is not necessary according to Sharma (1996), because the
structure model is based on existing literature that has previously been tested and
therefore, it is implied.
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5.5. Reliability analysis
This type of analysis refers to the internal consistency of the factors (Chu and
Murramann, 2006). In order to analyse the reliability of the 11 factors and measure the
internal consistency of each factor Cronbach’s a coefficient was used (Fornell and
Larcker, 1981). As it can be observed from the results of the present study (Table IV),
the values of Cronbach’s a exceed the minimum 0.6 score (Nunnally, 1978).
5.6. Convergent validity
The degree to which multiple methods of measuring a factor provide the same results
is called convergent validity (Churchill, 1979; Spector, 1992). Wixom and Watson (2001)
stated that the acceptable value of convergent validity is 0.5 for all loadings of the
items and Kim et al. (2008) added that all items should load to only one factor with an
eigenvalue 41.
In this study, all items have loaded to their predestined factor with an eigenvalue
41. As it can be viewed by the results illustrated in Table IV, all items bear loadings
from 0.599 and above which completes the criteria mentioned about convergent
validity.
5.7. Discriminant validity
Burns and Bush (1995) claimed that discriminant validity revolves around the idea that
dissimilar constructs should be different. For that reason a table was constructed
(Table V) containing the correlations coefficients of the factors and in the diagonal of
this table Cronbach’s a values are introduced. Churchill (1979) stated that Chronbach’s
a values of the factors should be higher than the correlation values. This would
indicate that the correlations among the factors are lower than within them (Widener,
2004).
From the results of the present study, it can be said that the above criterion is met,
and thus discriminant validity has been accomplished.
5.8. Structural equation modelling
The examination of the conceptual framework was conducted with the use of the
“structural equation modelling technique”. The certain multivariate technique was
used because of its ability to simultaneously examine a number of depended linear
relations, where one or more constructs (variables) are both dependent and
independent (Hair et al., 1995).
The five common fit measures: (w2/df ), (GFI), (CFI), (RMR) and root mean square
error of approximation were used to appraise the overall model fit. The overall fit
values of the model are summarised in Table VI and all their scores fulfil the acceptable
levels.
Moreover, the causal relationships among the variables were examined by using the
structural equation modelling approach. The structural model, along with path
coefficients is illustrated in Figure 2. It was found that the statistical significance of H2
(convenience-satisfaction), H4a1 (functional quality-satisfaction), H4b1 (functional
quality-loyalty), H4b2 (relational quality-loyalty), H4d1 (functional quality-loyalty),
H4d2 (relational quality-loyalty), H6b (value-loyalty), H7b (value-loyalty) (brand
credibility-loyalty), H8c (satisfaction-financial performance) and H9 (loyalty-financial
performance) justifies their rejection.
From the modification indices analysis additional relationships have emerged and
are presented in Figure 2 in red lines. These are the negative effect of economics on
The Greek
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275
Table V.
Correlations
0.562**
0.000
0.546**
0.000
0.511**
0.000
0.629**
0.000
0.480**
0.000
0.348**
0.000
0.419**
0.000
0.571**
0.000
0.491**
0.000
0.037
0.519
0.844
0.591**
0.000
0.572**
0.000
0.682**
0.000
0.534**
0.000
0.403**
0.000
0.463**
0.000
0.679**
0.000
0.562**
0.000
0.014
0.810
0.562**
0.000
0.883
0.708**
0.000
0.774**
0.000
0.452**
0.000
0.343**
0.000
0.551**
0.000
0.755**
0.000
0.716**
0.000
0.074
0.196
0.546**
0.000
0.591**
0.000
0.881
IMG
Note: **Correlation is significant at the 0.01 level (two-tailed)
FPER
LLT
SAT
ECON
CONV
TANG
BC
VAL
IMG
RQ
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
Pearson correlation
Significance (2-tailed)
RQ
0.772**
0.000
0.446**
0.000
0.300**
0.000
0.549**
0.000
0.733**
0.000
0.655**
0.000
0.038
0.512
0.511**
0.000
0.572**
0.000
0.708**
0.000
0.883
VAL
0.586**
0.000
0.416**
0.000
0.607**
0.000
0.799**
0.000
0.729**
0.000
0.001
0.982
0.629**
0.000
0.682**
0.000
0.774**
0.000
0.772**
0.000
0.901
BC
0.472**
0.000
0.401**
0.000
0.569**
0.000
0.483**
0.000
0.080
0.162
0.480**
0.000
0.534**
0.000
0.452**
0.000
0.446**
0.000
0.586**
0.000
0.848
0.368**
0.000
0.446**
0.000
0.432**
0.000
0.073
0.202
0.348**
0.000
0.403**
0.000
0.343**
0.000
0.300**
0.000
0.416**
0.000
0.472**
0.000
0.675
Correlation
TANG
CONV
0.707**
0.000
0.671**
0.000
0.022
0.707
0.419**
0.000
0.463**
0.000
0.551**
0.000
0.549**
0.000
0.607**
0.000
0.401**
0.000
0.368**
0.000
0.808
ECON
0.819**
0.000
0.024
0.680
0.571**
0.000
0.679**
0.000
0.755**
0.000
0.733**
0.000
0.799**
0.000
0.569**
0.000
0.446**
0.000
0.707**
0.000
0.896
SAT
276
FQ
FQ
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0.004
0.948
0.491**
0.000
0.562**
0.000
0.716**
0.000
0.655**
0.000
0.729**
0.000
0.483**
0.000
0.432**
0.000
0.671**
0.000
0.819**
0.000
0.906
LLT
0.037
0.519
0.014
0.810
0.074
0.196
0.038
0.512
0.001
0.982
0.080
0.162
0.073
0.202
0.022
0.707
0.024
0.680
0.004
0.948
0.773
FPER
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6 Conclusions
6.1 Discussion
The economics factor is an invention and innovation of this paper. It has been
constructed in order to provide a more general understanding of all the economicrelated constructs and has never been examined before in this form. In this study it has
been found to have a positive effect on customer satisfaction, as it was hypothesised.
Moreover, new paths have arisen regarding the economics variable; it has been
found that it has a positive effect on both customer loyalty and brand credibility
and a negative effect on image. Levesque and McDougall (1996) have considered
the economics factor as part of satisfaction, which now has been proven wrong.
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277
Overall fit of the model
Chi-square/degree of freedom (w2/df )
Goodness-of-fit index (GFI)
Comparative fit index (CFI)
Root mean square residual (RMR)
Root mean square error of approximation (RMSEA)
)
ECONOMICS
H1
(+
(+
44
(–)
4
Table VI.
Model fit
)
–0.
H2
(+)
0.7
69
CONVENIENCE
0.1
796
0.
1.942
0.972
0.989
0.033
0.056
(+)
38
)
0.29
8
(+
)
.
(+ 0
)
54
6
BRAND
CREDIBILITY
4a
2(
FINANCIAL
PERFORMANCE
H8b (+)
0.464
H
H5b
(+)
(+
)
H6
b(
H5
+) H6
H
a
a(
(+ 7a (
(+
+)
+)
)
)1
1.3
2.9
.2
95
22
04
IMAGE
H6
H6d(+) 0.874
c
1. 1, 2
11
VALUE
2, (+)
0.
84
6
(+
)
H4b2 (+)
7b
1.200
H5d (+)
0.440, 0.725
H5c1, 2 (+)
c
H8
a
b1
H
d1
H4
RELATIONAL
QUALITY
H8
68
H4
+)
SERVICE QUALITY
H
3.
2
FUNCTIONAL
QUALITY
,2
0.9
6
H4 9, 0.
c1, 665
2(
+)
(+
)
0.
40
CUSTOMER
SATISFACTION
4a1 (+)
CUSTOMER
LOYALTY
H9
(+
H3
(+
9
TANGIBLES
70
0.0
)
(+)
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image, the positive effect of economics on both brand credibility and loyalty, the
positive effect of convenience on loyalty and last, the positive effect of tangibles on
brand credibility. Furthermore, the validity of the hypothesised paths was examined
by examining the statistical significance of each structural parameter estimate.
A summary of the structural parameter estimates is presented in Table VII, as well as
the new relationships that have arisen.
4
0.18
Accepted hypothesis
Rejected hypothesis
New paths
Figure 2.
Hypotheses testing results
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Path
coefficient Remark
Research model hypotheses
H1
Lower economics have a positive effect on customer
satisfaction
H2
Convenience has a positive effect on customer satisfaction
278
H3
Tangibles have a positive effect on customer satisfaction
H4a1
Functional quality has a positive effect on customer
satisfaction
H4a2
Relational quality has a positive effect on customer
satisfaction
H4b1
Functional quality has a positive effect on customer loyalty
H4b2
Relational quality has a positive effect on customer loyalty
H4c1
Functional quality has a positive effect on value
H4c2
Relational quality has a positive effect on value
H4d1
Functional quality has a positive effect on image
H4d2
Relational quality has a positive effect on image
H5a
Image has a positive effect on customer satisfaction
H5b
Image has a positive effect on customer loyalty
H5c1
Image has a positive effect on functional quality
H5c2
Image has a positive effect on relational quality
H5d
Image has a positive effect on value
H6a
Value has a positive effect on customer satisfaction
H6b
Value has a positive effect on customer loyalty
H6c1
Value has a positive effect on functional quality
H6c2
Value has a positive effect on relational quality
H6d
Value has a positive effect on image
H7a
High brand credibility positively affects customer
satisfaction
H7b
High brand credibility positively affects customer loyalty
H8a
Customer satisfaction has a positive effect on image
H8b
Customer satisfaction has a positive effect on customer
loyalty
H8c
Customer satisfaction has a positive effect on financial
performance
H9
Customer loyalty has a positive effect on the financial
performance of banks
New paths
Economics-Image
Economics-Brand credibility
Economics-Loyalty
Table VII.
Convenience-Loyalty
Hypotheses testing results
Tangibles-Brand credibility
0.738
Accepted
0.298
Rejected
Accepted
Rejected
0.546
Accepted
1.112
0.846
0.874
2.922
Rejected
Rejected
Accepted
Accepted
Rejected
Rejected
Accepted
Accepted
Accepted
Accepted
Accepted
Accepted
Rejected
Accepted
Accepted
Accepted
Accepted
3.268
0.464
Rejected
Accepted
Accepted
0.969
0.665
1.204
0.184
0.440
0.725
1.200
1.395
Rejected
Rejected
0.796
0.444
0.169
0.070
0.409
Accepted
Accepted
Accepted
Accepted
Accepted
This is probably due to the global crisis and its consequences on the Greek economy
and the banking sector. Nowadays, people care more than before about the pricefairness and the price-quality ratio, when before the crisis they would be willing to pay
a premium for the products and services they received. Having consistently low prices
compared to the provided quality could lead to more loyal customers over time. The
effect of economics on brand credibility could be explained by the notion that by
providing lower prices than competition people perceive the bank as being truthful,
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reliable and consistent to its promises. Finally, the negative effect of economics on
image could be explained by the fact that it is not an advised marketing strategy
for a bank to be viewed as “inexpensive” regardless of the relatively lower prices that it
may offer. This is due to the notion that usually lower costs and prices represent
products and services of lower quality. Such a strategy could harm the prestige
and good name of the bank with regard to the products and services it provides. Bank
managers should take into consideration the above when deciding the pricing policy of
their institution. They should also focus on the fact that over-pricing or under-pricing a
product or service could have serious repercussions on the bank and they ought to
select their strategy carefully.
Regarding the convenience factor it has been found to have no impact on customer
satisfaction which contradicts the findings of Arbore and Busacca (2009) and Wu
(2011a). The opening hours of all the banks operating in Greece are the same, while the
location of every bank is not very far from the others; most banks are located very
close to or even opposite one another. All the above are an obvious indication that
competition has driven all banks to be, in terms of facilities, the same. The banking
sector in Greece has become indifferent to customers in the context of convenience
because bank managers strive to keep up with their competition. This is possibly
why the convenience factor was ineffective on satisfaction. However, the new path that
has arisen from the study indicates that convenience has a positive effect on loyalty
which is probably the result of repetitive behaviour and being accustomed to visiting
the bank at its certain location. Bank managers should not rely on convenience in
order to achieve loyalty, they should keep reminding their customers of all the
characteristics the bank has to offer them.
The tangibles factor has been proven to positively affect customer satisfaction
which is in line with the studies carried out by several researchers (Levesque and
McDougall, 1996; Jamal and Naser, 2002; Sohail and Shaikh, 2008; Jamal and
Ananstasiadou, 2009; Hossain and Leo, 2009). Wakefield and Blodgett (1999) have
found that tangibles have an impact on the affective responses of customers, which
include the sense of pleasure and relaxation and the feeling of excitement. This is
probably why this factor was found to positively affect customer satisfaction; a nice
environment can help the customer feel more relaxed, less defensive and more satisfied
with one’s bank selection. Moreover, tangibles have been found to have a positive
effect on brand credibility, which suggests that people associate the overall physical
appearance of the bank to the level of reliability the bank offers. The better the
facilities, equipment and stationery are the more credible the bank appears to be.
Managers should allocate part of their annual budget on renewing their tangibles to
keep their customers satisfied and enhance their brand credibility. However, since
this constitutes a cost for the bank, managers should not materialise drastic changes,
they need to find ways of renewing the appearance of their institution by incorporating
intuitive ideas and smart solutions.
In this paper service quality was examined in terms of functional and relational
quality and not as a single factor. The results indicated that these two dimensions
of service quality do not behave in the same way. This is to be expected, due to the fact
that they measure two different aspects of service quality, functional quality measures
how efficiently the bank operates while relational quality measures the level of
intimacy the customer receives from the bank and its employees. It has been found
that functional quality has no effect on customer satisfaction while relational quality
was found to have a positive impact. This occurred due to the customers’ notion that all
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280
banks provide the same level of functional quality, while the personal relation
varies according to the staff the bank has selected to employ. Moreover it has been
found that neither functional nor relational quality have an effect on customer
loyalty. It appears that just service quality is not enough for customers to be loyal to
their bank and they are driven by other factors towards loyalty, especially in this sharp
economic environment. Furthermore, both functional and relational quality were
proven to have a strong relationship to value. This is consistent with the findings
of Lai et al. (2009). The better the service the better value the bank appears to have.
Additionally, the two dimensions of service quality have no impact on the image
of a bank which indicates that the overall performance of a financial institution does
not help create and maintain its image. Since relational quality affects customer
satisfaction managers should educate their employees on new techniques of customer
interaction and handling which can lead to customer retention. Also, these findings
suggest that service quality should not be neglected because it is crucial to the
maintenance of company value.
Image is one of the constructs that has been found to significantly affect all the
factors it has been tested on. It positively affects customer satisfaction, it drives
people to be loyal to their banks and enhances the notion customers have about the
bank’s service quality and value. All these are an outcome of how the banks have dealt
with their public image throughout the years, the services and products offered, their
people skills and customer complaints policy. The image of a bank is built slowly and
with a lot of effort; managers should always try to maintain or enhance it. This is why
it is considered one of the most important factors in the success of any company,
not only banks.
Value has been found to positively affect customer satisfaction. This implies that a
customer thinks the benefits he/she is offered by one’s bank, are far greater than the
sacrifices he/she makes. Yet this is not enough to lead to loyalty, since no positive
connection has been found between value and loyalty. Moreover, value positively
affects both service quality and image, making it one of the factors a bank manager
should focus on. The process of creating value is also slow and continuous; it is the
banks reward for the products and services it consistently has offered over the years.
Brand credibility has been proven to have a significant effect on customer
satisfaction. This is possibly due to the fact that people relate to a brand name and this
leads them to feel satisfied with their banks. As stated by Adcock et al. (1995), Kotler
and Armstrong (1996) and Kotler (2003) the brand is one of the most significant drivers
to the selection of a product, service, company or in this case, bank, and reflects the
overall notion an individual has about them. Customer loyalty has not been found to be
affected by brand credibility which suggests that the reliability and trustworthiness of
a bank is not enough in this harsh environment to create loyal customers.
Customer satisfaction was found to have a strong effect on the image of the bank
and on customer loyalty. If a bank repeatedly satisfies a customer this customer will
continue to realise his/her transactions in this particular bank (Yi, 1990). Additionally,
in this study it has been verified that customer satisfaction has a positive effect on
image regarding the banking sector, as was suggested by Kandampully and Hu (2007)
in the hotel industry. This can be explained by the fact that increased satisfaction is
reflected on the image the customers have about their bank. Managers should always
have as a priority the satisfaction of their customers since it is the strongest predictor
of customer loyalty. This can be accomplished by listening to their requirements and
then by creating products and services that fulfil them.
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Regarding the financial performance of banks it has been found that neither customer
satisfaction nor customer loyalty have an effect on the profitability of the bank contrary
to the findings of many studies (Hallowell, 1996; Bernhardt et al., 2000; Chi and Gursoy,
2009; Fathollahzadeh et al., 2011) supporting the exact opposite. This can be explained
by the current financial condition of the banking sector in Greece, which has been facing
losses for the past two years. These past two years the banking sector and the overall
economy in Greece have been under a lot of distress, as it has been described earlier.
6.2 Limitations
Although this study is more holistic than the ones that have been carried out so far
regarding customer satisfaction and loyalty, it had its limitations.
One of the main limitations is that the banks’ financial data used were taken from
the annual report of each bank. By using objective measures that would minimise to
some extent the effects of the crisis. Furthermore, the respondents were made to choose
one bank which constitutes an additional limitation. Some of the respondents may have
transactions in more than one bank. Last but not least, this study measures the notions
of the respondents at the present time when the economic environment is not ideal due
to the financial crisis Greece and especially, the banking sector faces, which makes the
findings of the study inadequate for generalisation.
6.3 Further research
In the future, it is considered essential to extend this research to multiple bank users in
order to have a clearer view of the notions of the respondents who have financial
products in more than one institution. Another, recommendation would be to test the
model when the economy of Greece becomes more stable. This would provide more
accurate outcomes of the stated hypotheses.
This study introduced an innovative extended model which involved the impact of
customer satisfaction and loyalty on the profitability of banks. Moreover, it has
provided a more holistic understanding of how all the aforementioned factors
interrelate and how the affect both satisfaction and loyalty.
This model is an innovative tool which managers can use in order to design their
marketing strategy and accomplish the best results for their bank. It indicates the
tendencies of the target population, the elements or factors of the marketing mix
customers consider most important, it provides a more holistic view of the target
market and the factors that can cause satisfaction and loyalty, and also, it guides
managers to the implementation of a strategy that will enable them to fulfil their goals.
In order for it to be established as an adequate instrument in predicting satisfaction,
loyalty and financial performance it needs to be tested in different economic
environments, countries and industries.
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About the authors
Elissavet Keisidou is a business executive in Hatzistefanou Educational Group, member of QLS,
Xanthi, Greece. She holds a BA in Business Administration from the Technological Educational
The Greek
banking sector
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Institute of Kavala, Greece and an MSc in Finance and Financial Information Systems from
Greenwich University, UK. Her research interests include consumer behaviour, e-commerce,
human resource management and organisational behaviour. Elissavet Keisidou is the
corresponding author and can be contacted at: [email protected]
Lazaros Sarigiannidis is a tutor in Project Management in the Kavala Institute of Technology,
School of Business and Economics, Greece. He holds a BA in Economics from the University of
Macedonia, Thessaloniki, Greece, an MSc in Finance and Financial Information Systems from
the University of Greenwich, London, UK, and a Doctor of Philosophy (PhD) in Project Risk
Management from Democritus University of Thrace, Xanthi, Greece. His research interests
include project management, risk management, business outsourcing, applied economics and
e-business.
Dimitrios I. Maditinos is Associate Professor of Business Administration and Information
Technology at the Department of Business Administration, School of Business and Economics,
Kavala Institute of Technology, Kavala, Greece. He holds degrees in Business Administration
with specialisation in Information Technology from Lund University, Sweden, and a PhD in
Finance and Financial Modelling from the Business School, Greenwich University, London, UK.
Before becoming a full academic, he was working in a senior position for Greek Productivity
Centre, responsible for professional training in information technology and management. His
research interests are in financial modelling, performance measurement systems, capital
markets, financial information systems and electronic commerce, with more than 35 journal
publications, 60 conference papers and around 120 references.
Eleftherios I. Thalassinos, PhD (UIC), MBA (De-Paul, Chicago), is a Professor of Quantitative
Methods and International Economics and Finance at the Department of Maritime Studies of the
University of Piraeus, Greece. He has been elected Chairman of the Department for three terms
(1998-2000, 2002-2004 and 2004-2006) and Director of Graduate Studies for four terms (20032005, 2005-2008, 2009-2011 and 2011-today). Since 1998 he has been the General Editor and
Founder of the European Research Studies Journal indexed in EconLit, JEL, REPEC, EBSCO,
SSRN, SCOPUS and other databases. He has held a Chain Monnet Chair since 1997. His primary
research interests are in international economics, quantitative financial analysis, banking and
international finance. He has extensive research published in journals and in international
conferences.
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