The relationship between service quality and ...

Journal of Service Management The relationship between service quality and retention within the automated and traditional contexts of retail banking Mohammad Al-Hawari Tony Ward Leonce Newby

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Article information: To cite this document: Mohammad Al-Hawari Tony Ward Leonce Newby, (2009),"The relationship between service quality and retention within the automated and traditional contexts of retail banking", Journal of Service Management, Vol. 20 Iss 4 pp. 455 - 472 Permanent link to this document: http://dx.doi.org/10.1108/09564230910978539 Downloaded on: 10 December 2014, At: 00:39 (PT) References: this document contains references to 67 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 3913 times since 2009*

Users who downloaded this article also downloaded: Karin A. Venetis, Pervez N. Ghauri, (2004),"Service quality and customer retention: building long#term relationships", European Journal of Marketing, Vol. 38 Iss 11/12 pp. 1577-1598 http:// dx.doi.org/10.1108/03090560410560254 Mohammed Al#Hawari, Tony Ward, (2006),"The effect of automated service quality on Australian banks' financial performance and the mediating role of customer satisfaction", Marketing Intelligence & Planning, Vol. 24 Iss 2 pp. 127-147 http://dx.doi.org/10.1108/02634500610653991 Rizal Ahmad, Francis Buttle, (2002),"Customer retention management: a reflection of theory and practice", Marketing Intelligence & Planning, Vol. 20 Iss 3 pp. 149-161 http:// dx.doi.org/10.1108/02634500210428003

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The relationship between service quality and retention within the automated and traditional contexts of retail banking Downloaded by UNIVERSITY OF SHARJAH At 00:39 10 December 2014 (PT)

Mohammad Al-Hawari Management, Marketing, and Public Administration Department, Business Administration Faculty, Sharjah University, Sharjah, United Arab Emirates, and

Service quality and retention

455 Received 13 November 2008 Revised 26 February 2009 Accepted 16 April 2009

Tony Ward and Leonce Newby Central Queensland University, North Rockhampton, Australia Abstract Purpose – The main purpose of this paper is to highlight the significance of service quality factors on customer retention within the Australian traditional and automated banking contexts. Design/methodology/approach – The relative importance of traditional and automated service quality factors on customer retention was examined with the intention of determining which indicator factors are likely to have a significant impact on customer retention. The paper then proposes a conceptual model of the relationship between service quality factors within the two contexts and customer retention. AMOS 5 was used to test for the hypothesized relationships. Findings – All of the traditional service quality factors have positively influenced customer retention. Conversely, this paper finds that automated service quality in general has no positive significant influence on customer retention. Research limitations/implications – This research was applied to the financial institutions in Queensland, Australia. Further testing of the proposed conceptual model across different industries and countries is needed to determine the generalisability and consistency of this study’s findings. Practical implications – The proposed model of retention prediction has the potential to help Australian bank managers to strengthen the customer-bank relationship and, ultimately, to enhance customer retention ratios. Originality/value – The key contribution of this paper is a conceptualisation of customer retention predictors that takes into account both traditional and automated service customer interactions with banks. Keywords Australia, Customer retention, Automation, Services, Retailing, Banking Paper type Research paper

Introduction During the last two decades, the Australian financial system has developed rapidly in terms of size, industry structure and variety of products and services (Edey and Gray, 1996). The Australian financial system has been transformed from a relatively closed system in the 1950s and 1960s based on traditional banking activities to a more open, effective and competitive system which is able to offer an extensive range of products and services (Edey and Gray, 1996). Service quality has become a critical component in running a successful business in today’s economy (Blose et al., 2005). Provision of high

Journal of Service Management Vol. 20 No. 4, 2009 pp. 455-472 q Emerald Group Publishing Limited 1757-5818 DOI 10.1108/09564230910978539

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quality services enhances customer retention rates, helps attract new customers through word-of-mouth advertising, increases productivity, leads to higher market share, lowers staff turnover and operating costs, and improves employees’ morale, and financial performance (Duncan and Elliot, 2004; Ranaweera and Neely, 2003; Jamal and Naser, 2003). The literature review revealed that there has been an intensive investigation into service quality outcomes in the traditional banking context where face-to-face interaction between customer and employee was the primary focus. More recently, banks face a situation where employees and traditional delivery functions are no longer their first interest. Instead banks are increasingly depending on technology with their attendant quality issues. Technology development has changed retail banking most significantly by facilitating the creation of a new range of products and improving delivery channels (Thompson, 1996; Edey and Gray, 1996). New service delivery channel options, such as automated teller machine (ATM), phone banking, mobile banking, and recently, internet banking, have resulted in new and additional ways for banks to provide delivery of their services to their customers. The literature asserted that relationships between banks and their customers may change through the introduction of new technologies (Barnes, 1997). The investigations of the relationship between retention and service quality is well established in the literature. Many studies have investigated this relationship within the traditional contexts where face to face is the only interaction method between banks and their customers. Other few studies have investigated this relationship within the banking automated contexts. In the banking sector, customers choose different service delivery channels in a complementary way; consequently developing a relationship with the customer can be achieved through any combinations of these media (Al-Hawari and Ward, 2006). No studies have been revealed into the literature taking into the consideration the influence of the automated and traditional service quality factors on customer retention as in one model. Furthermore, those models currently available to measure automated service quality are limited in their focus, encompassing only one electronic channel – the internet – thereby ignoring attributes of the other automated service channels, such as ATMs and telephone banking services. Accordingly, this research develops a comprehensive model of automated and traditional banking service quality taking into account the unique attributes of each delivery channel and other dimensions that have the potential to influence customer retention. Traditional service quality Traditional service quality is defined as customers’ beliefs or attitudes about the degree of service excellence offered in the bank’s physical location (Castleberry and Resurreccion, 1989). There were many examples of models which were developed to measure customer perceptions of service quality where face-to-face interaction between the customer and employee was the only focus. As the literature showed that there were no absolute perfect measurement models of service quality, this research has restructured the well service quality models to reflect the unique nature of Australian banking context. As a result, three factors were identified: the human element; the consistency of service delivery, and, tangibles of service. These factors were drawn mainly from Sureshchandar et al. (2002) who adapted their items from Parasuraman et al. (1988).


The human element of service quality referred to all aspects of staff/customer interaction in service delivery. Human elements play vital role in shaping the overall customer perception of service quality (Mouawad and Kleiner, 1996; Yavas et al., 1997). Employees have an important effect on customer service as they are the key element that customers interact with during the service encounter stage (Mouawad and Kleiner, 1996). Well trained employees are able to achieve high level of customer cognition as well as affection toward the organisation they are dealing with (Schneider and Bowen, 1995). Consequently, frontline employees’ factor is added as a main factor shaping customers overall perception of traditional service quality. Consistency of service delivery referred to the processes, procedures, and systems that would make service delivery a seamless experience (Sureshchandar et al., 2002). In the literature, there were a few marketing scholars who have tried to focus on the importance of the structural content of service delivery in service quality evaluation (Sureshchandar et al., 2002; Danaher and Mattsson, 1998; Gro¨nroos, 1990). Time considers a vital element in shaping customer perception of service quality; thus, designing a simple and seamless service delivery process help banks to shorten the necessary time of delivering the service products. Accordingly, this factor has included as it has an important role in shaping customers overall perception of the traditional banking service context. Tangibles of service were one of the few dimensions that have been consistently used by different researchers (Bahia and Nantel, 2000). However, tangibles refer to physical facets of the service facility; equipment, machinery, signage, communication materials, etc. (Bahia and Nantel, 2000; Parasuraman et al., 1988). It includes the physical evidence of the service, except the personal appearance of staff which was included in the human element dimension Automated service quality After reviewing the literature intensively, it was observed that there existed no generally accepted model of automated service quality. There have been many studies identifying the key service quality factors in the traditional banking environment, where interaction between employees and customers is the main communication channel (Jun and Cai, 2001). However, there have been few studies that have investigated automated service quality attributes in banking (Joseph and Stone, 2003). The automated service quality model presented in this research is designed to comprehensively include all the possible factors that may shape customer perceptions of automated service quality. The factors of the automated service quality model were drawn mainly from Al-Hawari and Ward (2006). Automated service quality is defined as the customer’s overall evaluation of the excellence of services provided through electronic networks such as the internet, ATM, and telephone banking (developed from Santos, 2003). Customer evaluation of automated service options and their intention to use a particular option are directly affected by their perception of the attributes associated with that option (Dabholkar, 1996). That is, every service delivery channels own its unique features which make it dissimilar to others, so it is essential to measure each channel quality separately rather than aggregating the channels’ attributes (Al-hawari, 2006). The overall customer perception of automated service quality can be established through the quality of every automated delivery channel (Al-Hawari et al., 2005). A number of marketing scholars


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have identified ATM, internet and telephone banking as the principal automated delivery channels for retail banking (Joseph and Stone, 2003). Accordingly, each delivery channel has been considered as a factor in the proposed automated service quality model. Customer retention In order to lower costs and increase their market share in an era of high levels of competition, many firms acknowledge the need to increase their efforts to retain customers to increase their profitability (Reichheld and Sasser, 1990). However, on turning to the retention literature for guidance in developing retention strategies, practitioners find that there are variations in the conceptualisation of customer retention that confound the research findings. In general, there were three distinctive approaches to measuring retention; behavioural measures, attitudinal measurement, and composite measurement (Bowen and Chen, 2001). In a service context, retention was frequently defined as observed behaviour (Liljander and Strandvik, 1994). However, the behavioural models that used repeat purchase as the only measurement of customer retention have been criticised for their lack of conceptual basis; this measurement may not have indicated an attachment to a particular brand (Day, 1996). The problem associated with treating retention exclusively as a repeat purchase was that this did not differentiate loyal customers (Dick and Basu, 1994). Moreover, a behavioural approach with the only focus on repeat purchase may not yield a comprehensive insight into the underlying reason for retention (Bloemer and Kasper, 1995). Consequently, customer retention has also been approached as an attitudinal construct (Hallowell, 1996) to reflect the emotional and psychological attachment inherent in retention (Bowen and Chen, 2001). This was demonstrated, for example, by the willingness of the customer to recommend a service provider to other consumers (Ziethaml et al., 1996). However, using the attitudinal measure only has also been criticised in the literature (Dick and Basu, 1994). The third approach has combined the behavioural, attitudinal, and cognitive aspect of customer retention (Bloemer et al., 1998). The involvement of a psychological/ attitudinal construct with repeat purchases has been shown to be important in achieving absolute retention (Oliver, 1999). In this regard, customer retention has frequently been operationalised as the first thing that came to mind when making a purchase decision; that is, a customer’s first choice among alternatives, and also, price tolerance (Price and Arnould, 1999; Bloemer et al., 1998; Ziethaml et al., 1996; Dick and Basu, 1994). Thus, retention was defined in this research as the degree to which a customer exhibits repeat purchasing and price tolerance behaviour to a service provider, and, possesses a positive attitudinal and cognitive disposition. To match the above definition, Ziethaml et al.’s (1996) battery has been adopted in this research to operationalise the customer retention construct. They developed a group of antecedents that reflected a wider range of behavioural intention and attitudinal and cognitive attachments to a service provider. This battery included four dimensions; word-of-mouth communications, purchase intention, price sensitivity, and complaining behaviour. Developing the study hypothesises Organisations are operating in an intense competitive environment, thus, many firms are trying to increase their efforts to retain customers (Al-Hawari, 2006). The concept of


relationship marketing has received much attention in recent years as more organisations focus their attention on how to maintain and enhance a relationship with existing customers rather than on how to attract new ones (Caruana, 2002). The focus on customer retention is particularly true in financial sectors where deregulation has given customers more flexibility to select their financial services (Levesque and McDougall, 1996). Moreover, shareholder pressure to increase profitability has forced banks to move away from a transaction and quick sales approach to maintaining a good long-term relationship with their customers (Kandampully and Duddy, 1999). In general, a two percent enhancement of customer retention can lead to a ten percent reduction of overhead costs, which in turn improves the profitability (Jamieson, 1994). Service quality has been found to be an important component in establishing and retaining customers (Ranaweera and Neely, 2003). The relationship between service quality and retention has been investigated both theoretically and empirically over the past few years in the traditional service context where the interaction between the customer and the employee is face-to-face. In this context, the literature has sustained different views on the way that service quality could influence customer retention. Some authors have indicated that service quality influenced customer retention only through satisfaction (Caruana, 2002; Cronin and Taylor, 1992), while others argued for a direct effect (Ranaweera and Neely, 2003; Alexander et al., 2002). Therefore, it is expected that: P1.

Traditional service quality factors are positively related to customer retention.

In particular: H1. Employess service quality are positively related to customer retention. H2. Process service quality are positively related to customer retention. H3. Tangibles of service delivery are positively related to customer retention. Relationship marketing is a complicated phenomenon and needs to be addressed within a specific context (Parasuraman and Grewal, 2000). However, with the rapid diffusion and adoption of information technology around the globe, the literature asserts that relationships may change through technology (Barnes, 1997). Customer friendly technologies including ATMs, telephone and internet banking have become important strategies to increase customer retention and market share in recent years (Ribbink et al., 2004). In general, theoretical and some empirical support has been found in the literature for the notion that automated service quality could enhance rather than diminish relationships. Lang and Colgate (2003) determined that there were three possible ways for automated service quality to enhance relationships: improving customer service with the assistance of database management, providing selective and relevant information, and, building stronger relationships. The literature showed that if firms fail to provide channels which their customers seek and value, firms will find it more difficult to have a strong relationship with their customers. Owing to the nature of automated media, such as telephone and internet banking, relationships between some parties have become closer than ever before (Lang and Colgate, 2003). Automated delivery channel quality has the potential to make customers enthusiastic about their bank and inclined to tell other potential customers about its advantages. Thus, automated channel users would be more likely to comment positively about their bank to other people, recommending the bank and encouraging others to do business with it


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(Mols, 1998). The quality and the use of automated channels as a means of delivering banking services have become an important way of maintaining customer loyalty and increasing market share (Joseph and Stone, 2003). However, the literature has also warned that technology could isolate customers, provide a sense of incompetence, and enhance disconnectivity and passivity (Grabner-Krauter and Kalusha, 2003; Mick and Fournier, 1998). In general, both theoretical support and some empirical support have been found in the literature for the notion that automated services represent a positive experience for the users and provide increased value-for-money to entice customers to have the intention of continuing to do business with their bank (Zhu et al., 2002; Meuter et al., 2000). Despite the theoretical background underpinning the importance of automated service quality in retention, researchers have found little empirical investigation that examines this relationship in the automated services context. Therefore, it is expected that: P2.

Automated service quality factors have a positive influence on customer retention.

H4. Internet service quality are positively related to customer retention. H5. Telephone service quality are positively related to customer retention. H6. ATM service quality are positively related to customer retention. Figure 1 shows the theoretical model that is tested in this paper.

Methodology A quantitative study, involving the administration of a survey, was conducted in order to empirically measure and then test the relationship between variables. The survey instrument consisted of 50 items (as shown at Table I) which were identified through a comprehensive literature review of automated; traditional service quality and customer retention. Measuring automated service quality – Three factors (dimensions) of automated service quality were identified: ATM service quality, telephone banking service quality, and internet banking service quality (Al-Hawari, 2006; Al-Hawari and Ward, 2006). Items were identified in relation to: (1) ATM service quality was extracted from various studies such as, Joseph and Stone (2003) and Jabnoun and Al-Tamimi (2003). Five dominant items were selected from these studies. (2) Internet banking service quality items were drawn from many models which measure customer perceptions (Long and McMellon, 2004; Yang and Jun, 2002; Zeithaml, 2002). This factor was represented by seven items originally developed by Jun and Cai (2001) and subsequently used by Yang and Jun (2002), Zeithaml (2002) and Long and McMellon (2004). (3) Telephone banking service quality was generated predominately from a study conducted by Joseph and Stone (2003) which focused upon evaluating the impact of technology on service delivery. Six distinct items were identified from this study.


Automated service quality ATM TEL

461 P2

INT


Retention Traditional service quality EMP P1 PRS

TAN

Independent variables

Dependent variable

Key: ATM → Automated teller machine, INT → INTernet banking service quality, TEL → TELephone banking service quality, EMP → EMPloyees service quality, PRS → Service delivery PRocesS, TAN → TANgibles quality Source: Developed for this research

Measuring traditional service quality – Conceptualising traditional service quality was discussed. These three factors were: human element, tangibles, and consistency of service delivery. (1) Human element of service quality – It was noted from the literature review that the human element has frequently been included in measurements of different dimensions of service quality (such as reliability, empathy, assurance, and responsiveness). For this research, it was important to measure as many as possible of the different aspects of the human element which might impact on the perception of service quality. As a result, all the items that related to tellers were extracted from the different named-dimensions of the previous service quality models (Jabnoun and Al-Tamimi, 2003; Sureshchandar et al., 2002). This led to the extraction of nine items in the first instance. (2) Tangibles – It was found in the literature that tangibles have been consistently used by many marketing scholars to measure customer perceptions of service quality. Items from different scales were extracted to form the pool for this variable. These items were mainly extracted from those models which have usually been used to measure customer perceptions of service quality in banks (Jabnoun and Al-Tamimi, 2003; Sureshchanda et al., 2002; Bahia and Nantel, 2000).

Figure 1. Theoretical model

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Critical dimensions

Related items

ATM

Sufficient number of ATMs Secure locations ATM has a user-friendly system Conveniently located ATM functions Pleasant musical backgroundb Reasonable number of voice prompts Short waiting time Clear instructions Reliability Telephone banking options Availability of information Easy to use Secure Error free transactions Attractive web site Website interface accuracy Up to date information Friendly Inquiry responses Feel safe and secure Served promptly Investments availableb Best interest at heart Right service Queues Enough tellersb Hassles Minimum time Simple Fool-proof Pleasant environment Physical design Clean facilities Well decorated Easily accessible Advertising materialsb Saying positive things Recommending your bank Encouraging friends Consider your bank first choice Switch to competitors if you face problemsa Complaining to other consumersb Complaining to the bankb Complaining to external agenciesb Remove some business in the case of more attractive priceb Remaining with the same bank if fees increase Pay higher fees than competitors charge for the benefits you receive from your banka Do less business with your banka

Telephone banking

Internet banking

Employee service quality

Process service quality

Tangible service quality

Customer retention

Table I. The measurement items

Notes: Items deleted in the afirst; bsecond stages


This process led to the identification of six items which reflected closely the definition and aspects of service tangibles in this research. (3) Service delivery consistency – From the literature review, consistency of service delivery was identified as a single dimension. It was represented by the items concerned with standardisation, simplification, structure, procedures and facilities. All of the items were extracted from Sureshchandar et al. (2002). Measuring customer retention – The main approaches to conceptualising customer retention were introduced, and thus in the operationalisation of this concept the degree to which a customer exhibits repeat purchasing and price tolerance behaviour for a service provider were considered. Recognition of a positive attitudinal and cognitive disposition in the customer underpinned the operationalisation of the concept. Consequently, the items that were developed by Zeithaml et al. (1996) in their study were adopted in this study as they adequately represented the definition and have been used widely in the literature. This battery included four dimensions; word-of-mouth communications, repeat purchase, price sensitivity, and complaining behaviour. Research design This study was conducted in two stages. Stage 1 involved a pilot study which was conducted to refine the test instrument. Totally 35 respondents were interviewed in the pilot testing phase. The results showed Cronbach a above 0.7 for all variables, indicating an acceptable level of reliability (Nunnally and Bernstein, 1994). However, “switching to another competitor” and “paying higher fees for the benefit” items in the customer retention battery were deleted as they had an item-to-total correlation value of less than 0.3 (Henryson, 1971). Stage 2 involved a sample of people from the general public. A mall intercept method was used to administer the survey with 442 useable surveys being collected using the face-to-face interview method. A response rate of 74 percent was obtained in gaining the 442 completed responses. Measurement model Structured equation modelling was used to analyse the data and test the hypotheses. To assess the measurement model, four analyses were conducted (Al-Hawari, 2006; Al-Hawari and Ward, 2006). Unidimensionality was assessed first, prior to examining reliability and validity (Hair et al., 1995). In order to test for unidimensionality, confirmatory factor analysis (CFA) was conducted on measurement models for each of the constructs. In this study, the Comparative Fit Index (CFI) indices for all of the seven constructs were above the 0.9 level which indicated evidence of unidimensionality. Second, squared multiple correlations (R 2) for each measurement item, composite reliability, and variance extracted for each factor were used in this study to test the construct reliability (Hair et al., 1995). The first run of the measurement model indicated that the R 2 for the majority of measurement items was greater than 0.5, which indicated a good reliability level (Holmes-Smith, 2001). Eight items, however, were deleted as the R 2 values ranged from 0.20 to 0.32 which was less than 0.5 (shown with one asterisk at Table I). In the second run of testing the measurement model R 2 values for all measurement items were greater than 0.5 or very close (Table II).


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Table II. Reliability test outcomes for each factor

Variable name

li

ATM service quality F34 (Sufficient number) 0.678 F35 (Secure places) 0.754 F36 (User friendly) 0.791 F37 (Conveniently located) 0.803 F38 (Number of functions 0.800 Telephone banking service quality F40 (Voice prompts) 0.829 F41 (Waiting time) 0.852 F42 (Clear instruction) 0.912 F43 (Reliable) 0.879 F44 (Services range 0.868 Internet banking service F45 (Information) 0.889 F46 (Easy to use) 0.906 F47 (Safe transaction) 0.891 F48 (Error free online) 0.865 F49 (Attractive web site) 0.778 F50 (Free error interface) 0.814 F51(Up to date information 0.805 Employees service quality B5 (Enquiry responses) 0.843 B8 (Friendly) 0.753 B10 (Feel safe and secure) 0.813 B11 (Served promptly) 0.761 B13 (Best interest at heart) 0.760 B14 (Right service) 0.786 B15 (Queues) 0.660 Tangibles C18 (Pleasant environment) 0.849 C19 (Physical design) 0.846 C20 (Clean facilities) 0.747 C21 (Well decorated) 0.856 C23 (Easily accessible) 0.771 Service delivery process E28 (Hassles) 0.863 E29 (Minimum time) 0.830 E30 (Simple) 0.808 E31 (Fool-proof) 0.767 Customer retention L58 (Positive things) 0.943 L59 (Recommendation) 0.966 L60 (Encouraging) 0.938 L61 (First choice) 0.891 L67 (Remaining if fees up) 0.701

R2

Critical ratios

0.460 0.569 0.625 0.644 0.639

13.949 14.516 14.698 14.653 13.675

0.687 0.726 0.832 0.772 0.754

16.725 18.709 17.598 17.256 17.456

0.791 0.820 0.794 0.748 0.605 0.662 0.648

20.764 19.939 18.683 15.194 16.495 16.179 18.345

0.711 0.567 0.661 0.579 0.578 0.618 0.435

18.473 20.751 18.756 18.733 19.688 15.373 19.234

0.722 0.715 0.559 0.732 0.594

22.173 18.311 22.601 19.176 19.077

0.744 0.688 0.653 0.588

21.725 20.820 19.170 20.679

0.889 0.934 0.881 0.793 0.500

45.781 40.093 33.113 13.713 12.345

Composite reliability

Variance extracted

0.84

0.52

0.86

0.55

0.90

0.56

0.87

0.50

0.84

0.52

0.79

0.50

0.90

0.64

The values of composite reliability, variance extracted (Fornell and Larker, 1981) and Cronbach a greatly exceeded the minimum acceptable values of 0.7, 0.5, 0.7, respectively, (Holmes-Smith, 2001), thereby indicating the reliability of measures and subsequently yielding very consistent results (Table II) (Zikmund, 2003).


Evidence of convergent validity was gained as the measurement items represented their factors significantly; the critical ratio of every item exceeded the 1.96 value (Anderson and Gerbing, 1988) (Table II). To test for discriminant validity the procedure described by Fornell and Larker (1981) was used. The analysis showed that the average variance extracted for each pair of variables was greater than the squared correlation for the same pair, indicating that each construct was distinct (Table III). Finally, CFA was conducted to empirically investigate whether the proposed model reasonably fitted the data. The model x 2 is 1,589 (df ¼ 644, p ¼ 0.000). It should be noted that if the model chi-square significance is , 0.05; this indicates a problem with the model fitness by this criterion. However, the model chi-square criterion could be misleading as it is so conservative and very sensitive to sample size (Kline, 1998). Accordingly, researchers who use SEM believe that if they achieve a reasonable sample size . 200 and appropriate fit indicated by other fit tests such as CFI and RMESA, the significance of Chi-square test can be disregarded and is not a reason by it self to modify the model (Byrne, 2001). In this research the overall fit of the model was acceptable, with a x 2 x 2/df ratio of 2.47, RMSEA of 0.058, and the (CFI) of 0.923 (Byrne, 2001).


465

Structural model Assessing the model in the last section reduced the data and resulted in a manageable number of valid and more reliable measurement items which were then used to evaluate the structural model in this section. The overall fit indices for the proposed structural model were x 2 ¼ 1,589 (df ¼ 640, p ¼ 0.000), x 2/df ratio of 2.3, a CFI of 0.914 and the root mean square error of approximation (RMSEA) of 0.058 (Hair et al., 1995; Byrne, 2001). These values indicated that the model fits the data well. Having established the final structural equation model, it was possible to test the hypotheses developed for this study. These hypotheses can be tested by evaluating the path coefficients and the significance levels among the constructs in the model. Analysing the results showed that telephone service quality was the only automated service quality which had a significant relationship with customer retention (as shown at Table IV). Thus, H5 has supported. However, the analysis shows no significant relationship between internet service quality and customer retention as well as no significant relationship between ATM service quality and customer retention. Thus, H4 and H6 were rejected. It can be concluded that the overall automated service quality-customer retention relationship has a weak influence on customer retention disproving proposition two. On the other hand, all of the traditional service quality a

ATM

ATM TEL INTER EMP TAN PRO RET a

0.275 0.264 0.358 0.390 0.399 0.298

TEL

INTER

EMP

TAN

PRO

RET

0.535

0.54 0.56

0.51 0.525 0.53

0.52 0.535 0.54 0.51

0.51 0.53 0.53 0.50 0.51

0.58 0.60 0.60 0.57 0.58 0.57

0.383 0.293 0.302 0.325 0.306

0.213 0.365 0.374 0.230

0.456 0.470 0.549

0.480 0.403

0.518

Note: The upper level represents the average extracted variance while the lower level represents the squared correlations for every pair

Table III. Discriminant validity test outcomes

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Table IV. Results of standardised regression weights (R) for the model

factors had a significant relationship with customer retention, which proved H1, H2 and H3 supporting the first proposition of the study. All of the customer retention predictors have explained 0.61 percent of customer retention indicating the importance of these predictors in predicting customer retention in the Australian banks. Research findings The aim of the study was to highlight the significance of customer retention in the context of the twenty-first century banking environment in Australia. This paper proposed a conceptual model which was empirically validated by perceptual data collected from customers of banks, building societies, and credit unions in Australia. The results of the survey provided strong empirical support for four of the six hypothesised relationships between the constructs. Figure 2 shows the final model and highlights the significant relationships in bold. The relationships between variables

Standardised regression weights

ATM ! retention Tel ! retention Internet ! retention Employee ! retention Process ! retention Tangible ! retention

Not significant 0.137 * Not significant 0.385 * * 0.251 * 0.116 *

Notes: *p , 0.05; * *p , 0.01

Automated service quality ATM TEL

0.137

INT

Traditional service quality EMP PRS

Retention

0.385

0.251 6

0.11

TAN

Figure 2. Final model

Independent variables Source: Developed for this research

Dependent variable


The findings of this paper confirm the literature and showed that all of the traditional service quality factors have positively influenced customer retention; thus H1, H2 and H3 were supported. Conversely, the findings disconfirm the literature in regard to the relationship between automated service quality and customer retention. The results find that automated service quality in general has a weak positive relationship to customer retention. In particular, out of the three automated service quality dimensions, only the telephone banking factor has a positive significant influence on customer retention; consequently, H5 was accepted, while H4 and H6 were rejected. Internet and ATM factors were not significantly related to overall customer retention. These findings confirm the warning in the literature about the possibility of automated services isolating customers from their service provider (Mick and Fournier, 1998). One explanation of these findings is that internet banking might result in offering much information to bank customers about service fees and different financial products, and that it is easier for customers to switch their banks with minimal cost (Jun and Cai, 2001; Evans and Wurster, 1997). Accordingly, high quality internet banking service attributes might offer better chances for customers to browse and obtain the best choice with minimal cost. In relation to ATMs, the wide spread provision of ATMs might also make it easier for consumers to switch banks with minimal costs. Another reason why ATMs have no significant impact on retention is the absent of differentiation as all seem the same. Moreover, ATM of any particular bank can be used by any customer belong to another bank. Telephone banking has a significant relationship with customer retention. The explanation of this result could include the interpersonal element of telephone banking. When customers use telephone banking they still have the option of talking directly to bank personnel who can help with any inquiry. As telephone banking has an influence on customer retention, and as customers have the option to talk to bank staff, banks can utilise telephone banking to sell current customers a new financial service product and thus gain more profit from such cross selling. Managerial implications The continuously growing number of automated retail bank service offerings and the adoption of a policy encouraging customers to use automated banking services rather than direct personal interaction channels could facilitate customer defection to other competitors, thus placing pressure on a bank’s financial performance over time. Despite automated banking services being widely used, it has been suggested that customers might still not be very familiar with these new services, especially internet services (Snellman and Vihtkari, 2003). Therefore, learning difficulties may impact on the use automated services; customers might not be able to manage these difficulties (Moore and Benbasat, 1996). Since customers lack direct contact with the bank through personnel or the physical branch, electronic exchange presents risks to customers (Grabner-Krauter and Kalusha, 2003). Familiarity with traditional service and the absence of personal interaction negatively influence perceptions of automated service quality. Thus, this research makes a contribution to current knowledge about the difference between the impact of service quality on retention in the automated context and the traditional context. This situation raises the issue of whether it would be feasible for banks to build long-term relationships with their customers through automated banking services only.


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This research showed that service quality in the traditional banking context had a strong positive influence on customer retention. Different from some earlier studies that raised the importance of automated service quality in increasing the rate of customer retention, this paper concludes overall that there is a very weak link between automated service quality and retention. Accordingly, the decision of some bank managers to replace human labour with machines is completely unwise. This study proves that replacement of people with machines is likely not to help banks to build a strong relationship with their customers and maintain a high rate of retention. It therefore seems that only focusing on automated service quality would not build a long-term relationship. This research suggested that the establishment of a personal relationship would reduce risk and uncertainty in the relationship. Thus, the quality issues of automated services interaction with the customer should be seen as complementary to the quality issues of traditional service interactions rather than an alternative to them. Banks should have as their first priority the improvement of the quality of the personal interaction with bank customers to minimise any risk or uncertainty; then they can move forward to the quality issues of automated services. Improving the level of interaction quality in automated banking services is an important aspect which could be used to improve automated services (Merrilees, 2002), which in turn might have a stronger influence on retention, and thus on profitability. In order to enhance the quality of automated channel interactivity, automated channels should be better able to: help customers participate in, learn from, take action, offer a good system for two-way communication, and, facilitate a pleasant and an enjoyable experience (Merrilees and Fry, 2003). When bank managers consider enhancing the level of automated service quality they should engage customers in the design process and respond earlier than their competitors to customers’ needs, in order to eliminate some of the negative aspects of automated banking service quality. Moreover, it might be essential for banks not only to design their automated channel in order to satisfy their customers but to delight them to insure higher level of retention within the context of online banking (Herington and Weaven, 2007). The paper shows that the customer perception of employee services quality plays the most important role in retention level followed by the service delivery process quality, and finally the bank tangibles within the traditional service context. Accordingly, the bank management attention should be centred on Employee service quality in drawing customer retention. Bankers need to develop of the employees’ services skills consistently so banks enjoy a high level of customer retention. The continuous improvement of services delivery process is also very important for the success of the bank. Bankers might have to be alert all the time in making the process of delivering their services easy through regular eliminating of unnecessary steps which doesn’t add any value to the customers. Finally, physical surroundings (tangible aspects) should be well maintained as customers are welling to be in a convenient atmosphere while they are served. The above guidelines should be used to bank managers in analysing the opportunities for building better levels of retention. This study provides the above guidelines to bank managers for use in analysing the opportunities for building better levels of retention with their customers through the provision of automated services. It is not an appropriate marketing strategy for banks to ignore having a high level of face-to-face banking in favour of less expensive automated banking because focus on automated services would be likely to result in a


drop in a bank’s competitive advantage as well as a drop in the bank’s long-term profitability. For that reason, the quality aspects of automated banking services should not be made the only focus for bank managers; recognition of the importance of the quality aspects of the human factor in banking service is fundamental.


Research limitation and further study This research covered financial institutions in Queensland, Australia. The usage patterns of the different banking channels may vary among countries. Consequently, if the findings and the managerial implications of this paper are to be used in other regions with different cultures and governmental financial polices, additional research has to be done to validate the consistency of this research results. The focus of this study was on the service quality issues within traditional and automated contexts on retention. An expansion of this research is suggested to include the influence of more variables such as price, customer satisfaction, customer trust, and relationship strength within the two contexts on customer retention. The results of such a study would contribute to improving the knowledge of bank managers on how to increase the rate of customer retention within traditional and automated banking contexts. Moreover, the proposed conceptual model could be applied to different service industries to test how the results might vary among different industrial contexts.

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