INTRODUCTION

At a time of increasing deregulation, intensifying competition from other financial institutions and continuously evolving customer demands,^{1, 2} banks realise that delivering quality service to customers is a must for their success and survival. Frontline employees are perhaps the most critical link in the provision of superior service to customers.^{3, 4, 5} This is because a service is often produced through interaction between the customers and the frontline employees during service encounters. The frontline employees' performance during those so-called moments of truth largely determines customers' service quality perceptions.⁶ In effect, customers' notion of service quality hinges on the success of their interactions with frontline employees who represent the organisation in each encounter. Customers' satisfaction with this process is a crucial facet of their service evaluations.⁷ In addition, since nearly two-thirds of customer complaints are initiated with frontline employees,⁸ these boundary-spanning personnel's actions are also critical for service recovery when a service failure occurs.^{9, 10, 11, 12}

Given these, understanding customers' perceptions of service quality, identifying underlying dimensions of such perceptions and tailoring service strategies according to the needs of customers are imperative for survival and success in today's competitive milieu. While the chain of events that lead to customer satisfaction runs through all operations of a bank, it begins with an understanding of how customers assess the quality of service they receive. Arguably, frontline employees, who serve as the interface between the customers and the bank, are in the best position to know about customers' evaluations. Surprisingly though, the evidence on the extent to which frontline employees have accurate assessments of customer perceptions is sparse. Specifically, little is known whether the underlying configurations of customer evaluations of service quality as perceived by frontline employees and as reported by customers match. Against this background, the current study addresses two fundamental questions: Do service quality attributes decompose into comparable configurations for frontline employees and customers? How congruent are these configurations between the two groups?

Surveys of two groups of female bank customers (students and adults) and female bank employees in Turkey serve as the setting of the current study that investigates these issues. The study focuses on female employees because of three reasons. First, the number of women employed in customer-contact positions in Turkey is substantial. In fact, in banking which is one of the largest and fastest growing sectors in Turkey, high rates of women are employed at every level.¹³ Secondly, while the Turkish society is male-dominated and males are the primary breadwinners, changes enacted in the Turkish Civil Law in the 1990s have accelerated the transition in the status of Turkish women from that of traditional housewife to equal partner. These days, Turkish women are economically active. Many are no longer 'stay-at-home' moms waiting for their husbands to return to the nest. Turkish women, especially in urban metropolitan areas (such as Istanbul, the location of this study), join the workforce in increasing numbers.¹³ Not surprisingly, Turkish women, who under Islamic precepts have always inherited property and handled their finances, now open bank accounts in their own names in increasing numbers and represent a growing and potentially lucrative customer segment for banks. Thirdly, the literature to be reviewed in the next section suggests fundamental female–male differences in service marketing contexts. Thus, limiting the scope of the study to females only should allow a better delineation of the issues investigated.

The banking sector permits a viable setting for the study since banking services represent high-risk, high-involvement decisions for most consumers.^{14, 15} Customer-service provider exchanges in banking are not limited to just a single experience but rather represent an ongoing relationship involving several transactions.¹⁶ The next section presents the background literature. This is followed with a description of the study method. The paper concludes with discussions of the results, their implications and suggestions for future research.

BACKGROUND

The growing volume of theoretical and empirical studies on gender differences is prima facie evidence of the central role of gender in marketing management thought and practice.^{17, 18} Studies in sociology, psychology as well as in marketing management pertaining to gender differences point to a number of interesting findings. For instance, studies show that men are more agentic (task- or goal-oriented) whereas women are more communal (relationship-oriented).^{19, 20, 21, 22, 23} This agentic versus communal distinction between the two sexes impacts how each gender (the more emotional females and the more rational males) observes, evaluates and relates to the environment.²⁴ It has been suggested that women have a greater concern for social context and relationships and place more importance on interpersonal relationships relative to men.²⁵ Women are seen as warm and emotionally expressive while men are typically perceived as technically competent and instrumental.²⁶ Overall, women are more expressive and receptive to emotional communication in their personal lives (eg, Sprecher and Sedikides²⁷). In the formation of relationships, emotional considerations are more important to women whereas men tend to stress rational factors.

The importance women place on emotional as opposed to rational factors is reflected in their approach to evaluating an experience. For instance, in research based on the widely studied Myers–Briggs Type Indicator (MBTI), most women are characterised as emotion-dominated 'Feeling' types while most males are designated as logic-dominated 'Thinking' types.²⁸ This stream of research suggests that 'Thinking' type people evaluate experiences on the basis of rational factors whereas 'Feeling' types tend to rely on affective processes.²⁹

There is also some evidence that females and males differ in their approaches to forming relationships with service providers³⁰ and in evaluating service encounters.²¹, ³¹ For instance, because women are socialised to maximise the interpersonal aspects of their relationships, they emphasise the process component of service delivery.³² They are also influenced more by relational information as opposed to efficiency and accuracy cues.²¹ Men, on the other hand, tend to focus more on the successful delivery of the core service. As long as the appropriate outcome is attained, the process or the delivery style is not as important to them. Indeed, according to Hall,³³ gender stereotypes are incorporated into customer expectations regarding good service. Research shows that women are more likely to be frontline service providers who assist the customer.³⁴ Women customers also rate employees more favourably if they are of the same gender,³⁵ and they tend to more likely identify with the frontline employees.³⁶ As noted before, by limiting the scope of the study to same-gender customers and frontline employees, the potentially confounding effect of gender in this study is controlled for.

METHOD

To achieve the purposes of the study, data were collected via self-administered questionnaires from two groups of bank customers (students and adults) and bank employees. To collect the data from the students, about 350 questionnaires were distributed during regular class meetings to students attending Bogazici and Marmara universities in Istanbul. The returned questionnaires were carefully checked, and those with excessive missing data and those which were completed by students who did not have a bank account in their own name were discarded. Of the remaining 292 usable responses, 151 came from female students. To collect the data from the adult population, 200 questionnaires were distributed by a field force of students formed by the researcher to residents living in different neighbourhoods of Istanbul who had a bank account. After three weeks, 156 usable questionnaires were retrieved from the residents for a response rate of 78 per cent. Eighty-three of the usable questionnaires were completed by females. To collect the data from the frontline bank employees, questionnaires were distributed to employees attending training seminars sponsored by their banks and organised by a consulting firm. Employees were requested to complete the questionnaire during their lunch and coffee breaks and return to the seminar instructors. The questionnaires retrieved from the instructors were carefully checked and after discarding those with excessive missing responses, 158 usable questionnaires were obtained. Sixty-eight of the usable questionnaires were completed by female frontline employees.

In the student and adult studies, respondents' service quality perceptions were measured via Parasuraman, Zeithaml and Berry's SERVQUAL instrument.³⁷ In line with a procedure advocated by Brown et al.,³⁸ respondents were asked, on seven-point scales ranging from 'Much worse than I expected' to 'Much better than I expected,' to evaluate the performances of their bank for each item in the instrument. Brown et al.³⁸ found this alternative method to have favourable psychometric properties and to be more efficient than the disconfirmation procedure used in the original SERVQUAL measure.

In the employee study, in line with the procedure recommended by Parasuraman et al.,³⁹ service quality perceptions were operationalised by asking the respondents to fill out the expectations section of the SERVQUAL instrument as if their customers were filling it out. Specifically, the statements were administered to the respondents with the following instructions: 'We would like you to put yourself in place of a bank customer and then respond to all of the following statements by checking the category which best reflects your opinion.' A typical statement read: 'Excellent banks will have operating hours convenient to their customers.' Respondents' answers to the statements were recorded on seven-point scales ranging from 'Strongly disagree' to 'Strongly agree.' Items included in the survey instruments of all three studies are presented in Table 1.

Table 1 - Service quality items.

Full table

ANALYSIS AND RESULTS

Factor analysis (principal factoring with iteration) was applied to each sample independently in order to identify the fundamental dimensions underlying the original service quality items. The resulting factor matrices were rotated using the varimax procedure and factors with eigenvalues greater than 1.0 were retained. These analyses resulted in three factors for both customer segments and five factors for the employee sample. The percent of variance explained by the factors were: 63.6 per cent for students; 72.9 per cent for adults and 70.3 per cent for employees (see Table 2).

Table 2 - Varimax rotate factor matrices.

Full table

By using items with highest loadings on a particular factor, for the student sample, Factor 1 can be identified as a relational service dimension. It incorporates items pertaining to the interpersonal process by which the service is delivered to customers. Factor 2 seems to suggest an accurate and timely service dimension. Such items as performing service right the first time, accuracy of records and providing service at the promised time form this dimension. Factor 3 incorporates such items as appearance of physical facilities, employees and materials (eg, pamphlets). Collectively these items seem to suggest a tangible elements dimension. Based on the variance it explains (47.1 per cent), relational service dimension is the most salient one. It is followed by accurate and timely service dimension. The least important dimension (tangible elements) accounts for about 7 per cent of the variance.

Similar to the student sample, items pertaining to relational aspects of the service are at the root of Factor 1 of the adult sample. Therefore, this factor is named relational service. Factor 2 appears to reflect an accurate and timely service dimension. Again items such as performing service right the first time, accuracy of records, telling customers exactly when services will be provided and providing service at the promised time have their highest loadings on this factor. Factor 3 represents an ambient conditions/tangible elements dimension and incorporates such items as appearance of physical facilities, employees and materials. Based on the variances they explain, the saliences of the factors for the adult customers mirror image those of the students. Emergence of relational service as the most important dimension for both customer segments is not surprising and lends credence to the findings of earlier reviewed literature that women place more emphasis on relational aspects in service marketing contexts.²¹, ³¹

Because a diversity of items in several instances cross-load on multiple factors, interpretation of the five factors emerging from the employee sample is not as straightforward. Nevertheless, by considering only the item(s) that loaded highest on a particular dimension, the following labelling can be offered for the employee sample. Factor 1, which is the most salient one with an explained variance of 40.3 per cent, pertains to employee appearance. The item with highest loading on Factor 2 is understanding customer needs. Factor 3 captures personal attention paid to customers. Two items exhibit highest loadings with Factor 4. They are performing service right the first time and providing service at the promised time. Hence, this factor can be termed service timeliness and accuracy. Factor 5, the least salient dimension accounts for about 5 per cent of the variance and identifies the equipment/facilities dimension.

To discern whether the factor loading patterns are similar across the study samples and whether the service quality items decompose into comparable configurations for the customers and the employees, coefficient of congruence technique was used. While there are a number of techniques to determine the extent of similarity between factors obtained from different samples with fixed variables, one that is sensitive to both pattern and magnitude differences is the coefficient of congruence.⁴⁰ The coefficient of congruence between factors p and q can be defined as:⁴¹

where a_jp and a_jq represent the factor loadings of the two factors being compared. The value of the coefficient of congruence can range from +1 for perfect agreement to -1 for perfect inverse agreement. A value of zero represents no agreement.¹⁷ Factors with congruency coefficients approaching 1 are considered to be corresponding factors and non-corresponding factors are indicated by small coefficients. According to an empirical rule offered by Harman,⁴⁰ a pair of factors are congruent if the coefficient between them is larger than 0.90.

This measure was calculated for the factor structures reported in Table 2 and the results are presented in Table 3. An inspection of the pairwise congruency coefficients reported in Table 3 shows that coefficients between Factor 1 of student and Factor 1 of adult, Factor 2 of student and Factor 2 of adult, and Factor 3 of student and Factor 3 of adult samples all meet Harman's⁴⁰ empirical rule. With a coefficient of 0.88, however, only Factor 2 of student and Factor 4 of employee samples approach congruence. The rest of the coefficients between customers (both adults and students) and frontline employees are all below the minimum threshold value of 0.90.

Table 3 - Factor congruency results.

Full table

DISCUSSION

This study investigated the extent of congruence between the underlying configurations of customer evaluations of service quality as perceived by frontline employees and as reported by customers. An overall conclusion that readily surfaces from the results is that the underlying configurations for the two customer groups neatly correspond. Indeed, all the coefficients for the corresponding factors exceed congruence under Harman's⁴⁰ empirical rule. None of the coefficients between customers (whether they be students or adults) and employees, however, meet the guidelines.⁴⁰

The general pattern of inconsistencies between self-reported and customer-reported perceptions of service quality is troublesome. This discrepancy reveals a fundamental problem about a lack of touch with the customers. It appears that, for the most part, frontline employees in Turkish banks are unaware of how the customers really see them. On one hand, this may reflect an erroneous, 'we know we are doing a good job, our customers are satisfied,' attitude on their part. On the other hand, the discrepancy may be partially due to what is referred to as perceptual rigidity in classic studies of perception.⁴² In other words, employees apparently see what they expect to see. Whatever the explanation, such anchoring biases result in employees' failure to recognise the true sentiments of their customers.

Given that marketers with the best understanding and the least biased perceptions of customer expectations will be the most to gain, employees should not be lulled into a risky complacency and simply monitor customer sentiments as they (ie, frontline employees) define it. Instead, banks should first assess accurately customers' service quality perceptions and then educate their staff on how customers define service quality. In other words, staff should be trained to look at service quality from the perspective of customers by using customers' definitions. In this regard, it is perhaps best to assign top priority for immediate attention to the timely and accurate service dimension as the customer–employee gap, at least in the case of one customer segment, is not as great as for other factors. Once employees are trained then a regular tracking mechanism should be institutionalised to generate the dyadic data. As more accurate data are collected and a higher degree of congruency between the employees and customers is achieved, customers would go beyond being a group simply voicing their needs, but also serve as 'partners' in strategy design.

Future research directions

On a closing note, it should be noted that while the results and implications of the present study are useful, for broader conclusions, future research in several directions are needed. First, replications among other samples of female customers and employees in Turkey would be illuminating in cross-validating the findings. Secondly, this study's sample consisted of female employees and customers. This permitted not only control of possible gender effects, but also provided some insights into the perceptions of the growing female bank customer segment. Undoubtedly, banks cannot ignore the needs of their traditionally strong customer segment, males. Thus, extension of the research to male customers and employees would enrich not only the theoretical knowledge base, but could also pave the way for more pointed strategies. Thirdly, this study's scope was limited to banking. Future research should investigate the issues addressed in this study in different service settings. Finally, cross-cultural research is needed to understand the role of culture in shaping customer and employee perceptions of service quality and whether culture might attenuate any gender-based similarities and differences.

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