Customer service understanding:gender differences of frontline

employeesChristine Mathies and Marion Burford

School of Marketing, Australian School of Business,University of New South Wales, Sydney, Australia

Abstract

Purpose – Despite widespread acknowledgement of the importance of employees to the success ofservice firms, research into how well frontline service staff understand service remains scarce. Thisstudy aims to investigate what constitutes good customer service from the viewpoint of frontlineservice employees and to explore gender differences in particular.

Design/methodology/approach – The data were collected from 876 frontline employees across awide range of service industries. An automated text analysis using Leximancer explored general andgender-specific patterns in employees’ customer service understanding.

Findings – Irrespective of gender, frontline service staff share the perception that the pillars of goodcustomer service are listening skills, making the customer happy, and offering service. Males have amore functional, outcome-oriented interpretation of customer service; females focus more on the actualservice interaction and emotional outcomes.

Practical implications – By acknowledging gender-based dissimilarities in the customer serviceunderstanding of frontline service employees, the efficiency of recruitment and training processes willbe enhanced.

Originality/value – This study contributes to limited work on service models of frontline staff andshows that gender can explain some differences. This study also adds another dimension to theunderstanding of gender effects in services, beyond its influence on customers’ quality perceptions andbehaviours. The results are important for services marketing research and for managers in charge ofrecruiting and training frontline service staff.

Keywords Frontline service employees, Customer service, Customer orientation, Gender,Employee attitudes, Service industries

Paper type Research paper

1. IntroductionSome service industries have been dominated by either male or female frontline servicestaff. For example, flight attendants remain predominantly female, a legacy from the1930s when nurses replaced young boys in that position. Women were consideredbetter able to care for customers and promote a female presence that increased theperceived safety of flying (AFA-CWA, 2010). Frontline service positions overall tend tobe filled by women, often based on their stereotypical roles as emotionally expressivenurturers (Hochschild, 1983; Mattila et al., 2003). Men instead typically gain recognitionfor their technical competence and practical task orientation (Deaux, 1984).

Three basic arguments suggest why gender stereotypes in service roles still prevail;these arguments also imply that male and female service staff may have differentunderstandings of good customer service. First, gender differences mark customers’perceptions of various aspects of customer service and service quality (e.g. Iacobucci and

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Managing Service QualityVol. 21 No. 6, 2011pp. 636-648q Emerald Group Publishing Limited0960-4529DOI 10.1108/09604521111185628

Ostrom, 1993; Mattila et al., 2003; Snipes et al., 2006). These perceptions partly reflectgender stereotypes applied to both staff members and customers during serviceconsumption (Fischer et al., 1997), as well as customers’ reactions to service failure andrecovery (McColl-Kennedy et al., 2003) and loyalty toward employees (Melnyk et al., 2009).

Second, customers may expect, and respond better to, frontline service staff of the“appropriate” gender. Existing research thus has investigated the influence of thegender of the server and the gender dyad between customer and server on perceivedservice quality and customer satisfaction (Bove and Smith, 2006; Mohr and Henson,1996; Snipes et al., 2006).

Third, the firm’s service climate in general influences customer-oriented behaviour(Pimpakorn and Patterson, 2010), but male and female frontline service employees alsoreact differently to work environments and job characteristics. For example, womentend to experience higher levels of role ambiguity and conflict, as well as more mentalstress and emotional labour, than men (Babin and Boles, 1998). They are also expectedto manage their emotional displays better than men. Despite this greater challenge,women are generally more satisfied with their work, perhaps due to theirgender-specific work expectations and understanding of their work (Clark, 1997).

In light of this existing research, we propose that male and female frontline serviceemployees differ in their beliefs about what determines good customer service.A gender-based interpretation of work could explain why men or women appear moresuitable for certain frontline service roles. Extant literature on customer serviceperceptions in general, and potential gender differences in particular, mostly adopts thecustomers’ perspective, such that we know little about the employee’s perception ofgood customer service. One notable exception is Di Mascio (2010), who finds that retailstaff express different interpretations of customer service that guide their workbehaviours. Her typology of cognitive interpretations or schemas of their workenvironment, which she terms customer service models, offers important insights, butmore research is needed to investigate the underlying determinants driving theseservice models. Noting the significant impact of gender on customers’ serviceperceptions, we are particularly interested in the effect of the server’s gender on his orher interpretation of the meaning of customer staff?

Accordingly, we add to the scarce research that addresses how frontline serviceemployees understand customer service and whether differences in their models ofservice understanding might result from gender differences. Our two main researchquestions thus ask:

(1) What are the key facets of the customer service models (schemas) of frontlineservice employees that guide their efforts to provide good customer service?

(2) And are there any differences in the customer service understandings (schemas)of men and women?

2. Literature review2.1 The service understanding of frontline service employeesOur first research question concerns the building blocks of the customer serviceunderstandings of frontline service employees. Conceptual and empirical work onfrontline service employees’ interpretation of customer service is sparse. Di Mascio(2010, p. 63) identifies three generic interpretations, or schemas, of customer service byretail service employees, namely, as “(1) the act of giving customers what they ask for,

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efficiently and courteously, (2) a means to accomplishing immediate objectives, such assales quota, and (3) the formation of mutually beneficial relationships with customersthrough problem-solving”. However, these three interpretations – referred to as servicemodels – may not be exhaustive, because according to Di Mascio (2010) bothcontextual effects and individual characteristics are likely to affect perceptions of goodservice and its delivery. Our research expands on her work by extending theexploration of service models to a broad range of services industries, and byinvestigating gender as one individual characteristic that shapes the service models offrontline service employees.

Existing research on customer service from the employee’s perspective focusesmainly on customer orientation, and the dimensions of service quality as perceived bytheir customers. Employees’ customer service orientation is defined as theirwillingness and ability to deliver excellent customer service and adjust their servicedelivery to meet the customer’s needs and preferences (Brady and Cronin, 2001; Lytleet al., 1998). Thus, an individual employee’s customer orientation (which is distinctfrom the firm’s service orientation) constitutes his or her service-related attitudes andbehaviours, which directly shape the type of customer service provided (Hogan et al.,1984). This customer orientation can then influence customer satisfaction andperceptions of service quality and employee performance (Brady and Cronin, 2001;Hennig-Thurau, 2004). Intuitively though, the customer orientation of a frontlineemployee should be closely linked to his or her interpretation of good customer service.Vella et al. (2009) offer some indirect support for this notion with their finding thatcustomer service orientation influences an employee’s perception of the service qualityprovided for their customers. However, customer orientation cannot capture theemployee’s underlying beliefs about what constitutes good customer service.

Another area of service research that we can draw on is the understanding of goodservice from the customers’ perspective. Where research adopts the customer’s point ofview, it usually measures the quality of the service received using five dimensions ofservice quality established by Parasuraman et al. (1988): tangible evidence of theservice; the reliability of the service outcome; and the responsiveness; assurance; andempathy of the service delivery. These features all relate closely to the attitudes andbehaviours of the service staff. That is, the way in which service staff carry out theirtasks and interact with customers likely mirrors their own interpretation of goodcustomer service.

In summary, frontline service employees’ beliefs about good customer service formthe guidelines for their service interpretation and service behaviours. Servicesresearchers and managers alike will benefit from a greater understanding of the facetsof frontline service employees’ service models.

2.2 Gender effects in service researchGender research has a long history in social psychology, organisational research,consumer behaviour, and marketing. We briefly outline what is currently known aboutgender effects in services research, shedding some light on possible differences in theservice models embraced by male versus female frontline service employees as positedin our second research question.

Babin and Boles (1998) research gender differences in service employee behavioursand cite some important underlying factors from organisational literature that might

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explain gender effects. For women, service work is more emotionally exhausting, theirwork roles are more ambiguous, and the separation of work and non-work tasks ismore difficult, because they take on greater responsibilities. An employee’s work rolesoften dominate gender roles, but frontline service jobs offers an exception; gender rolesand associated stereotypes continue to reign in this context. Despite these addedcomplexities, women express persistently higher levels of job satisfaction than men.Differences also emerge in the quitting intentions of men and women in services andsales roles, depending on their job satisfaction and job performance. For example, menare more likely to leave an unsatisfactory job (Babin and Boles, 1998), buthigh-performing women are more loyal to their employers than are high-performingmen (Ladika et al., 2002).

Here again though, gender effects have been studied far more widely in servicesresearch from the customer perspective. Research focuses on three main topics: qualityand satisfaction judgments, and loyalty; preference for servers of certain genders; andperceived differences in dealing with service failure and recovery.

First, male and female customers offer different quality and satisfaction judgments.Men put more emphasis on the provision of the core service, whereas women value therelationship with the service staff more (Iacobucci and Ostrom, 1993). Men generallyrate service quality higher than women, and the relative importance attributed todifferent dimensions of service quality depends on the customer’s gender(Charalambos et al., 2004). Mattila et al. (2003) investigate gender effects in serviceencounters and discover that the effect of the server’s emotional display on customersatisfaction varies with the customers’ gender. In particular, men are more outcomefocussed, and negative affective displays do not influence their satisfaction with asuccessful service encounter. However, the satisfaction of female customers drops inresponse to negative emotional displays, even if the service encounter succeeds. Femalecustomers thus seem more focussed on the service process, whereas men place moreemphasis on the service outcome.

Second, research on service perceptions confirms the prevalence of genderstereotypes; Fischer et al. (1997), Snipes et al. (2006), and Mohr and Henson (1996) allshow that the gender of the server influences customer satisfaction ratings. Inparticular, the (dis)confirmation of expected gender stereotypes by the server has a(negative) positive influence on customers’ service perception. Customers expect a manto work in a hardware store or automotive repair shop, and they picture an aerobicsinstructor or a nurse as a woman; they react more negatively to service failures if thesegender expectations have not been met (Fischer et al., 1997; Mohr and Henson, 1996). Inaddition, female customers tend to form stronger relationships with same-sex servers(Mohr and Henson, 1996), though Bove and Smith (2006) cannot confirm this claim. Wepostulate that the different perceptions of women and men in service roles might reflectthe employees’ underlying service models.

Third, gender differences manifest themselves in service failure perceptions andthus in reactions to service recovery attempts. The effectiveness of service recoveryvaries with customers’ gender, the service employee’s gender, and thecustomer-employee gender dyad (McColl-Kennedy et al., 2003). For example, concernshown by a male employee weighs more than female concern, possibly becausecustomers are less likely to expect a male server to be concerned. Female serversprompt more critical assessments of the level of compensation they offer during service

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recovery. With regard to the customer’s gender, women appear to place more emphasison obtaining voice during the recovery process. Butcher and Kayani (2008) also findthat women react more favourably to waiting time in a service interaction if they haveinformation about the duration of the wait, but this effect is absent for men.

In summary, we presume that similar gender stereotypes and effects prevail infrontline service staff’s own interpretations of what entails good customer service. Inparticular, we expect to find that female employees, in responding to an open-endedquestion about good customer service, place higher importance on emotional displaysand expression of genuine concern. Furthermore, the focus on service outcomes versusservice processes likely differs between male and female service employees, an issuethat can be explored in our survey of frontline service employees.

3. MethodologyThe sample for our exploratory study consisted of 876 usable responses from frontlineservice employees, mostly in non-sales-oriented roles; working across the full range ofANZSIC classified service industries in Australia (ANZSIC, 2006). Respondents wererecruited through an online panel over a one-week period in February 2009 andscreened, such that the final participants spent at least 40 per cent of their workingtime interacting with customers. Of the surveyed service staff, 52.1 per cent indicatedthat they spent more than 80 per cent of their working time in face-to-face interactionswith customers, and the average duration per interaction was 21.2 minutes. In areflection of the overrepresentation of women in frontline service roles, 55.4 per cent ofthe respondents were women and 44.6 per cent were men. We also measured theservice orientation of frontline service staff using Brown et al.’s (2002) 12 item scale,and noted that the service orientation of females (4.01) was higher than that of males(4.18, p , 0.001). The participants responded to the following open-ended question:“what do you think is good customer service?” These response statements, typicallycomprising between one and three sentences, with an average length of 10.2 words,were then analysed.

We applied automated text analysis using Leximancer version 2.25 (Smith andHumphreys, 2006) to examine underlying concepts (common text elements identified inthis paper by their “concept name”) and themes (representing groupings of the foundconcepts) in the descriptions of the customer service understanding of frontline serviceemployees, as well as to explore any gender differences in these common text elements.Leximancer has been used effectively for both conceptual and relational analyses oftextual data (Angus-Leppan et al., 2010; Dann, 2010). Leximancer concept identificationhas been found to have close agreement with expert judgement (face validity) and anability to handle “short and ungrammatical comments” (Campbell et al., 2011, p. 92).Leximancer is particularly well suited to exploratory research of these comprehensivemental models, because it facilitates reliable and reproducible extraction of conceptsand thematic clusters, based on Bayesian probability, without inducing the expectationbiases common to manually coded text analyses (Baldauf and Kaplan, 2010; Dann,2010; Smith and Humphreys, 2006).

The analysis process comprised three steps. An initial exploratory analysisexamined the data for word clusters, called entities or concepts. The concepts werethen further explored by tagging the text with the respondents’ gender, which revealedconcepts that occurred to a greater or lesser extent in each gender group’s responses,

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and also highlighted those that occurred in only one gender group (Grace et al., 2010).The final step consisted of an analysis of the pattern of grouping of concepts intothemes, to reveal in greater detail the thematic clusters underlying employees’customer service understanding (Baldauf and Kaplan, 2010). Leximancer generatesthemes by aggregating concepts, with the aggregation levels being varied to gaingreater insight into how concepts inter-connect. We report the results as thefrequencies of occurrence of common word clusters and show, using a map, how theseentities relate to the respondents’ gender and other identified concepts (see Figure 1:concepts shown as dots and themes as circles).

As with all exploratory studies, this Leximancer analysis of open-ended responsesto frontline employees understanding of customer service has some limitations. Asnoted above, there was a range both in the nature and length of responses.Furthermore, whilst there is richness in the various Leximancer outputs, there is still

Figure 1.Leximancer map –

conceptual/thematicrelational analysis with

gender tags

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researcher interpretation of the data required. However, overall this methodologicalapproach has proven to be robust and insightful.

4. Results and discussionTo address our two research questions, we firstly report the outcomes of conceptualanalysis, in which we identified the key concepts (i.e. word groupings) for the overallsample. We then highlight the prevalence of certain concepts over others when thegender of the frontline service employee is taken into account, as we summarise inTable I. However, we omitted co-occurrences with a very low frequency from this table,to highlight the key differences. Later, relational analysis will explore the thematicconvergence of concepts into themes (Campbell et al., 2011).

As might be expected, the two most common concepts were customer andcustomers, which might be variations on the same theme. However, we did not mergethem into one concept during our analysis, because their degrees of connectivity withother concepts, as well as the lexical words associated with each focal word, show thatthey actually represent different underlying sentiments. For example, the conceptssatisfied, making, smile, product, manner, feel, and time all are unique to the term“customer”, whereas meeting, happy, help, and ability are associated exclusively withthe term “customers”. Furthermore, the text word “needs” links more closely to theconcept of customers, such as in the phrase “customers’ needs”. In other sections of textthough, both these concept labels are likely to co-occur. Thus frontline serviceemployees use different terminology to distinguish a general approach toward

Concepts OverallFemale Male

Rank Absolute count Percent Absolute countPercent(rank) Absolute count

Percent(rank)

(1) Customer 359 81.7 210 47.8 (1) 149 45.1 (1)(2) Customers 181 41.2 105 23.9 (2) 76 23.0 (2)(3) Listening 87 19.8 58 13.2 (3) 29 8.7 (4)(4) Happy 81 18.4 51 11.6 (4) 30 9.0 (3)(5) Service 66 15.0 47 10.7 (5) 19 5.7 (5)(6) Friendly 58 13.2 47 10.7 (6)(7) Smile 50 11.3 35 7.9 (7) 15 4.5 (9)(8) Polite 38 8.6 28 6.3 (8)(9) Product 37 8.4 22 5.0 (11) 15 4.5 (10)

(10) Satisfied 36 8.2 20 4.5 (14) 16 4.8 (7)(11) Time 36 8.2 19 4.3 (16) 17 5.1 (6)(12) Help 35 7.9 27 6.1 (9)(13) Manner 32 7.2 20 4.5 (13) 12 3.6 (12)(14) Helpful 32 7.2 26 5.9 (10)(15) Ability 31 7.0 21 4.7 (12)(16) Making 29 6.6 17 3.8 (17) 12 3.6 (11)(17) Expectations 29 6.6 16 4.8 (8)(18) Meeting 29 6.6 20 4.5 (15)(19) Giving 24 5.4(20) Providing 23 5.2 16 3.6 (18)

Notes: Absolute count refers to the number of text segments in which the concept was identified,according to Leximancer; Blank cells have a frequency of ,3.6 per cent

Table I.Overall andgender-specific keyconcepts (%) and rankorder

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customers and their needs from attending to an individual customer (e.g. “I believe thecustomer is always right. I am always attentive to all our customers” (respondent 658,female)).

The next most frequent concepts related to good customer service are listening,happy, and service – regardless of the frontline service employees’ gender. To clarifythe basic service models emerging from these data, we also investigated theconnectivity scores of the ten most connected concepts (see Table II). This score offersan additional indicator of the prevalence of a concept and its association with otherconcepts extracted by the Leximancer analysis. It reveals how often two concepts arementioned together. The results reconfirm the basic definition of service as a subjectiveexperience of value by the customer (Shostack, 1977). Listening provides thefoundation for understanding and meeting customers’ needs, which is a prerequisitefor value creation. Frontline service employees also meet customer needs by providing

Concepta Connectivity relevance (%)Associated concepts (co-occurrence in %, most toleast common)b

Listening23.2

Customer (48.2), customers (26.4), meeting (9.1),giving (6.8), manner (5.7), service (5.7)

Happy

21.9

Customer (67), customers (14.6), satisfied (12.1),service (12.1), making (8.5), time (7.3), feel (7.3),friendly (6.0), smile (6.0)

Service

20.0

Customer (54.6), customers (28.0), product (18.6),happy (13.3), friendly (9.3), smile (9.3), feel (9.3),providing (9.3), making (6.6), expectations (6.6)listening (6.6), satisfied (5.3), polite (5.3)

Friendly

16.0

Customer (40.0), customers (26.6), manner (20.0),helpful (18.3), polite (15.0), service (11.6), help (10.0),happy (8.3), product (8.3), listening (6.6), smile (6.6),expectations (5.0), providing (5.0)

Smile

13.3

Customer (48.0), polite (20.0), service (14.0), help(12.0), customers (12.0), happy (10.0), friendly (8.0),helpful (8.0), ability (6.0), providing (6.0)

Product

11.4

Customer (53.4), service (32.5), customers (18.6),making (13.9), friendly (11.6), helpful (9.3), happy(6.9), time (6.9)

Polite

10.4

Customer (28.2), smile (25.6), friendly (23.0),customers (20.5), helpful (17.9), service (10.2), help(10.2), time (5.1), manner (5.1), listening (5.1)

Time

10.1

Customer (50.0), customers (18.4), happy (15.7),manner (7.8), product (7.8), satisfied (5.2), outcome(5.2), listening (5.2), friendly (5.2), helpful (5.2), polite(5.2), service (5.2)

Satisfied

9.8

Customer (89.1), happy (27.0), making (24.3), feel(10.8), service (10.8), customers (10.8), smile (5.4), time(5.4). outcome (5.4)

Help

9.3

Customer (34.2), customers (28.5), friendly (17.1),smile (17.1), ability (14.2), polite (11.4), listening(11.4), service (8.5), feel (5.7), product (5.7), happy (5.7)

Notes: aConcepts customer and customers not included; bConcepts included if .5 per cent

Table II.Degree of concept

connectivity in overallsample

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a particular value-creating service, which has a product or tangible service outcome atits core; the service delivery interaction is an auxiliary value creator. The end result isto make customers happy by satisfying their needs in a friendly and timely manner.This basic interpretation of good customer service is also a common denominatorunderlying Di Mascio’s (2010) efficiency and win-win service models, though it seemsunrelated to her sales-oriented means service model, possibly because most of ourrespondents did not represent an industry with a sales focus.

Thematic convergence analysis identified four central thematic concept groupings:service, manner, customer and customers. To aid reporting our findings, wedistinguish such thematic concept cluster from similarly named individual concepts byusing capitalization and italics for themes, e.g. Smile, whereas “smile” indicates aconcept. These overarching thematic groupings, common to all respondents, arecentrally located on the Leximancer map (Figure 1, within frame). They combine toreflect a general service model effectively illustrated by this respondent’s description:

Knowing your customers’ needs and wants, making sure they leave satisfied [. . .], a smilingface and a happy customer who you will see again and again (respondent 672, female).

Beyond this common core, we find notable differences between men and women, ashighlighted in Table I, where some concepts are proportionally more represented, ornon-existent, for one or other gender. In Figure 1, Leximancer places concepts andthematic clusters more closely associated with one particular gender group visuallycloser to that gender tag. For example, concepts below the frame and nearer the gendertag TG_MALE_GS_TG are more likely to be sourced from within the male responses.To explore potential gender differences in employees’ customer service understanding,we relied on gender concept relativities from the entire data set. By investigating theconcepts and associated themes tagged for gender membership, we can reveal thesimilarities and differences between genders; the common central themes remain thesame.

Specifically, the concepts of friendly, polite, smile, help, helpful, and meeting weremore commonly linked to female frontline service personnel. For women, concepts suchas smile and polite epitomise good customer service, which means “Serving with asmile and being polite” (respondent 324, female). For male respondents, interactionalfacets such as smiling and politeness are more means to an end:

Smile, be polite, being able to answer questions effectively and reach the customers goal asthat is my goal (respondent 202, male).

The concepts most closely associated with male responses also included satisfied,making, time, and expectations. These findings are supported by the thematic analysis,where the proximity of a theme (circle) to a gender tag is a direct reflection of theincreased likelihood of association with a particular gender. Themes of smile, friendly,and polite emerge again as mainly female themes (Figure 1, above frame); expectations,provider and job are the themes most clearly linked to male frontline service employees(Figure 1, below frame).

These gender differences reflect our findings regarding the gender differences incustomer service orientation, and seem to correspond with the distinction betweenfunctional and emotional outcomes of customer service, as proposed by Sandstrom et al.(2008). According to their study, services provide a means to reach end states and thus

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fulfil both basic functional qualities and the need for emotional end states. Theemotional and functional components contribute equally to the overall serviceexperience. Gronroos (2000) also distinguishes technical and functional qualities ofservices but uses this terminology differently; he refers to the technical dimension aswhat is being done (outcome), whereas the functional dimension addresses how theservice gets delivered (process).

Our findings thus suggest that male frontline service employees tend to focus on theservice outcome, and particularly the functional outcome, such as “good productknowledge and ability to listen and evaluate correctly” (respondent 36, male). Theirproduct-driven view of customer service emphasises the core product or service, ratherthan auxiliary services. This attitude relates most closely to Di Mascio’s (2010)efficiency service model, which involves giving customers what they ask for, quicklyand efficiently. The focus on the efficient provision of a desired outcome is clearlyreflected in the following quotes from male respondents:

Prompt service, on time for appointments, a happy customer at the end (respondent 97).

Being available quickly to service client needs; ensuring client’s requirements are satisfied(respondent 238).

Making sure your customers expectations are met with the product or service you areproviding, if they are not met then clearly explain the benefits your goods or service willdeliver to them (respondent 386).

In contrast, female frontline service employees reveal a focus on the emotional value ofthe service encounter and the manner of service interaction. This serviceunderstanding is somewhat similar to the relationship aspect of the mutuallybeneficial win-win service model (Di Mascio, 2010), but it does not explicitly highlight aproblem-solving focus. The following quotes from female respondents illustrate howwomen acknowledge the functional service outcome as a prerequisite for satisfactoryservice but focus on the delivery of this outcome:

To help customers to the best of my ability, to answer their needs and to provide enthusiastic,helpful, and friendly advice and/or results (respondent 267).

Being friendly, helpful and listening to a customer’s needs; asking questions to be sure theyget the correct product or service (respondent 596).

Being greeted with a genuine, connected smile and a polite, friendly hello; someone who isinterested in you as a customer and providing you with whatever you require in a warm butprofessional manner (respondent 663).

These findings correspond with Gronroos’s (2000) process-oriented functional qualitydimension. For female frontline service staff members, it is equally important toachieve an emotional outcome, such as warm service. Women’s focus on processesrather than outcomes has been well documented (see for example Iacobucci andOstrom, 1993; Mattila et al., 2003). In a similar vein, Mohr and Henson (1996) report thatindustrial buyers rate female sales personnel more favourably on process-relatedaspects, such as understanding of other people and friendliness, but male salespersonnel score higher ratings on outcome-oriented aspects, such as productknowledge and technical assistance. Our results indicate that this prevalent

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process-versus-outcome pattern also emerges in the customer service understanding ofwomen versus men.

5. Managerial relevance and conclusionOur exploratory study adds to sparse literate on the interpretation of what constitutesgood customer service, as described by those who deliver it. Regardless of theindividual employee’s service model or gender-specific predispositions, listening to thecustomer to offer service in a way that makes the customer happy constitutes the coreof frontline employees’ service understanding. However, the interpretation of goodcustomer service also is influenced by the gender of the employee. The service modelsof women and men, though similar in their core elements, reveal obvious differences.For female service staff, the quality of the interaction and service processes dominatetheir understanding of good customer service; their male counterparts instead are moreoutcome focussed and consider good customer service mainly as a result of efficientproblem solving.

An appreciation of gender-specific differences in the customer serviceunderstandings of frontline service employees has important implications formanaging service staff, allowing optimal use of resources, adapting to and refiningcustomer service outlooks – “doing more with less”. Certain service roles lendthemselves to either a “male” or “female” service understanding, and service staffrecruiters should consider the best fit between service types and service models. Weimply no judgement about the efficacy of the service models of men and women; bothhave equal merit, though perhaps in different service situations. Our results alsoprovide important insights for the members of service delivery teams, because teamefficacy can benefit from a greater awareness of team members’ different serviceunderstandings, linked to their gender.

Although our findings provide some valuable insights into gender differences ofservice models, we acknowledge the limitations of our research. Our exploratory studyis based on short written statements rather than a face-to-face interview which wouldafford the opportunity to explore in depth their service models. However this ispartially offset by the large and diverse sample. Furthermore, gender is just one –albeit important – of the underlying determinants of frontline service employees’service models. Human beings are complex, thus further research is needed. Suchstudies could determine the effects of other defining employee characteristics and theinfluence of contextual issues, such as the type of service delivered, as well as theirinterplay, on their underlying service models. For example, the employee’s customerorientation, display of emotional labour, age, cultural background, and overall jobsatisfaction are likely to also impact on service models. Some of these factors may evenbe confounded with the server’s gender, and additional research is required todistinguish their effects clearly. Also of great interest would be a longitudinal studytracking how service models develop with increasing work experience in aboundary-spanning service role, or changes in the work environment. Differencesalso might exist among various service industries, and for high versus low contactservices. What we demonstrate clearly with our exploratory study is that gender, initself, is an important factor that influences the formation of service models held byfrontline service employees.

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About the authorsChristine Mathies is a Lecturer in the School of Marketing at the University of New South Wales.Her research focuses on services marketing and consumer decision making. She is particularlyinterested in psychological effects on customer choices, revenue management, customer-centricmarketing, and service staff performance. Marion Burford is the corresponding author and canbe contacted at: m.burford@unsw.edu.au

Marion Burford is a Lecturer in the School of Marketing at the University of New SouthWales. Her research focuses on reflective practice, strategic marketing, research methodologies,and the service aspects of education.

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