Customer satisfaction, loyalty and financial performance

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


A holistic approach of the Greek banking sector

The Greek banking sector

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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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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


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 Rojsˇek, 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 Rojsˇek (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 Rojsˇek, 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


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

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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 Rojsˇek, 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 Rojsˇek (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 Rojsˇek, 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. Downloaded by Eastern Macedonia and Thrace Institute of Technology At 00:42 30 July 2015 (PT)

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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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): Downloaded by Eastern Macedonia and Thrace Institute of Technology At 00:42 30 July 2015 (PT)

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).


269

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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


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


271

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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 Rojsˇek (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


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.


273

Table III. Bank usage data

IJBM 31,4 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 Downloaded by Eastern Macedonia and Thrace Institute of Technology At 00:42 30 July 2015 (PT)

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.


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


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


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

IJBM 31,4

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.


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

)

(+)


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


IJBM 31,4

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,


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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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.


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. References Adcock, D., Bradfield, R., Halborg, A. and Ross, C. (1995), Marketing Principles and Practice, Pitman Publishing, London. Ahluwalia, R., Burnkrant, R.E. and Unnava, H.R. (2000), “Consumer response to negative publicity: the moderating role of commitment”, Journal of Marketing Research, Vol. 37 No. 2, pp. 203-214. Akhtar, M.N., Hunjra, A.I., Akbar, S.W., Rehman, K.U. and Niazi, C.S.K. (2011), “Relationship between customer satisfaction and service quality of Islamic banks”, World Applied Sciences Journal, Vol. 13 No. 3, pp. 453-459.


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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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