Journal of Retailing 83 (1, 2007) 65–78
The impact of code switching on service encounters Hope Jensen Schau a,∗ , Stephanie Dellande b , Mary C. Gilly c b
a Eller College of Management, The University of Arizona, 1130 E. Helen Street, Tucson, AZ 85721-0108, United States The George L. Argyros School of Business & Economics, Chapman University, One University Drive, Orange, CA 92866, United States c The Paul Merage School of Business, University of CA, Irvine, Irvine, CA 92697, United States
Abstract Many service retailers, particularly those competing on speed of service with standardized encounters of short duration, rely on scripts to keep both employees and customers on-task and service operations running smoothly. While the benefits of such scripts are well known, what happens when customers do not stay on script? The authors analyze more than 2,000 service encounters and find evidence of two types of code switching suggested by sociolinguists: language and dialect. In addition, the concept of brand codes, the idiosyncratic terminology used in a service provider’s script, is introduced. While on-script encounters are preferred, language code switching can also have positive outcomes at little cost to organizational efficiency. In contrast, dialect and brand code switching subvert the service script with negative consequences. Brand code switching is found to be particularly problematic for small market players attempting to compete against market leaders. © 2006 New York University. Published by Elsevier Inc. All rights reserved. Keywords: Service; Code switching; Scripts; QSR
“Customers who do not behave as expected have the same effect on service organizations that ill-fitting parts or unusual specifications have on assembly lines” (Leidner 1993, p. 31). It has been suggested that services be compared to theater, as both service providers and customers have roles to play in the service performance (Grove and Fisk 1983, 1992). Many service organizations, particularly those that must process many customers quickly and efficiently, provide employees with scripts and expect customers to adhere to a general script as well (Kelley et al. 1992; Schau and Gilly 1998). Such services would be classified by Lovelock (1983) as low in customization and low in customer contact personnel judgment. Routinization through scripting works to ensure uniform service outcomes (Leidner 1993) that provide the retailer a competitive advantage. Scripts can be weak, without sequence information, or strong, with a structure that helps to define appropriate sequences of role behaviors. For example, restaurant scripts are strong scripts (including subscripts for various types of restaurants) with common understanding as ∗
Corresponding author. E-mail addresses:
[email protected] (H.J. Schau),
[email protected] (S. Dellande),
[email protected] (M.C. Gilly).
to customer behaviors (Schank and Abelson 1977). Complex scripts, those that include subscripts for handling anomalies, may facilitate mutual understanding between provider and customer (Mohr and Bitner 1991). Yet much of the research on scripting in services focuses only on the sequence of behaviors or events, the stage direction if you will, rather than the dialogue. For example, Schank and Abelson (1977, p. 41) define a script as “a predetermined, stereotyped sequence of actions that defines a well-known situation”. Yet, as dramatists know, “characters in plays talk a lot. Talking is drama’s most common activity” (Ball 1983, p. 27). If services are like theater with strong, complex scripts, scholars must study the dialogue between service actors as well as behaviors or actions. This research addresses this gap and offers a first look at the verbal interaction of service script participants. In particular, we examine what happens when scripts are followed and when they are not, what we call script subversion. In this study, we consider a specific type of script subversion known as code switching. Codes have been defined in the sociolinguistics literature as community-level communication systems (Gumperz and Gumperz 1982) and code switching as the shifting between codes (Eastman 1992) during an interaction. In a scripted service interaction, code
0022-4359/$ – see front matter © 2006 New York University. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.jretai.2006.10.008
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switching may be considered a form of “ad libbing”. For example, a consumer may ask an employee if they can clarify ingredients in a coffee drink in Spanish, influencing the employee to ad lib from the tightly scripted encounter. We examine the impact of this type of improvisation on service performance and consumer satisfaction. Specifically, we examine the service disruptions, or what ethnomethodologists call “breaches” (Garfinkel 1967), that code switching causes. Unexpected, and therefore unplanned, script subversion via code switching is a prevalent phenomenon that is currently under-theorized and under-represented in the retailing literature. Multiple types of code switching behaviors in service encounters are possible, echoing those identified in sociolinguistics. Code switching may result from shifting and blending broad language codes (e.g., English to Spanish), or through microcultural, or dialect codes (ebonics, regional vernacular, technology jargon). We propose a third type of code relevant to service providers: idiosyncratic, organizational jargon, or what we call brand codes (e.g., Starbucks “Frappuccino” and McDonald’s “Chicken McNuggets”). Regardless of the level of code (language, dialect, or brand), all code switching subverts the organization’s script, may disrupt the service encounter, and ultimately impacts business practices, competitiveness and profitability. The following research questions guide our study: 1. Does code switching occur in scripted service encounters? 2. Is language and dialect code switching found in commercial settings? 3. Can a brand script with its accompanying firm-specific jargon be a legitimate code analogous to a dialect or idiosyncratic vernacular? 4. Regarding brand codes, is code switching more common in smaller service firms than in market leaders who are more likely to establish the industry script, including the dominant code for a given type of service encounter? 5. Does code switching result in script subversion with its attendant negative outcomes, or does code switching result in better outcomes as the script is improvised, or customized for the consumer? Are all types of code switching the same with respect to the valence (positive or negative) of the service outcomes? Role theory and service operations Role theory has been used to understand employee– customer interactions. Role theory states that many social exchanges follow certain patterns due to the participants’ adoption of a role. Once adopted, the behaviors associated with that role will be enacted (Parker and Ward 2000; Solomon et al. 1985). Hubbert et al. (1996) point out that roles are complementary; that is, they are defined in relation to another role, such as doctor/patient or waiter/diner. For a successful encounter to occur, each role enactor must be able to predict the behavior of the other, i.e., have a common script. The source of many employee–customer interface
problems is the participants’ failure to read from this common script. Solomon et al. (1985) indicate that deviations from scripted behavior can lead to both negative and positive consequences. Script subversion can sometimes yield positive consequences like improved understanding when a participant recognizes a misunderstanding in the communication and clarifies it through unscripted dialogue. As well, customers may resent a worker who is perceived as reciting their lines without recognizing the customer as an individual (Leidner 1993). Alternatively, script subversion may result in a negative consequence, where the service provider and customer are not following the same script. Ordering off script can cause translation errors that are not recognized until the service outcome. Learning the script Scripts direct and guide the behavior of both members of the service dyad and ensure efficient protocol is consistently followed. Scripts are important tools in standardizing service experiences and in managing the expectations of consumers and employees alike (Leidner 1993). How can customers learn the common script? Formal orientation programs, organizational literature such as brochures and newsletters, environmental cues including orientation aids (e.g., signage), facility design, observation of other customers, and rules governing customer behavior, e.g., for safety (airlines), dress (restaurants, theaters), noise level (hotels, libraries, theaters), all contribute to customers learning the script (Claycomb et al. 2001). Having repeat customers and low employee turnover will increase the likelihood the script will be understood and followed. The existence of a customer script depends, in part, on the brand’s market standing, i.e., whether a brand is dominant (topdog) or nondominant (underdog) relative to the array of brands targeted to a particular market (Hoch and Deighton 1989). The term dominant is defined as the extent of market power that a firm enjoys. Dominant firms have greater investments in their current markets, greater market share, and greater resources than do other firms (Chandy et al. 2003). Hoch and Deighton (1989) indicate that dominant brands have more resources to exert control over the marketplace than underdogs. Top performing brands communicate to customers via advertising to educate consumers and influence the consumption experience. For example, topdogs like McDonald’s enjoy customer familiarity that is close to universal; approximately 95 percent of consumers in the U.S. patronize a McDonald’s store at least once a year (Koepp 1987; Leidner 1993). Many nondominant firms imitate market leaders only to reinforce the leader’s position (Zimmerman and Cohen 2002). Code switching A code is a neutral term denoting a linguistic variety (language, dialect, vernacular) (Crystal 1987). It is the com-
Changing from the organization’s brand terminology to another organization’s brand terminology in the course of a single communicative episode Brand
Employee: What can I get you? Customer: Can you make a Grande Caf´e Americano? Employee: Um we don’t have that but, I can put hot water in espresso. Customer: Right. I think that’s the same.
Changing from standard English to a shared dialect in the course of a single communicative episode Dialect
Employee: Can I get a drink started for you? Customer: Hella cold outside. Grande White Mocha. Employee: True that. With whip?
More positive comments/gestures than on-script encounters
Somewhat longer duration than on-script encounters; somewhat more negative comments/gestures than on-script encounters; more post-fulfillment inquiries than on-script encounters Much longer duration than on-script encounters; somewhat more negative comments/gestures than on-script encounters; more post-fulfillment inquiries than on-script encounters; more returns than on-script encounters Much longer duration than on-script encounters; more negative comments/gestures than on-script encounters; more post-fulfillment inquiries than on-script encounters; more returns than on-script encounters More positive comments/gestures than on-script encounters; similar percentage of returns as on-script encounters More positive comments/gestures than on-script encounters Changing from one language to another in the course of a single communicative episode Language
Employee: Here you go. Customer: Gracias. Employee: De nada. Tenga un buen dia.
Positive outcomes Definition
Script example
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Code switching types
Table 1 Code switching types, definitions, examples, and outcomes
munications system used within a given community and reflects social norms (Gumperz and Herasimchuk 1975; Heller 1995; Smitherman 1977). Code switching is a sociolinguistic communication strategy where a communicator toggles from one code to another (Eastman 1992; Heller 1988) during discourse. Communicators may switch codes in part, as in mixing or blending codes within a single speech exchange (Gumperz 1982); or in total, as in an entire shift from one code to another (Poplack 1988). Code switching is distinct from pidgin and Creole languages, where two codes are consistently mixed throughout a given discourse (Schwegler 2002). Code switching occurs when the organization’s script is written in a language or style that is not ideal from the customer’s viewpoint. This lack of a common preferred script may be due to language proficiency, preferred dialect style, or to greater familiarity with another organization’s brand terminology (see Table 1 for code switching definitions and examples). Given cues from the employee, customers may code switch to increase their comfort level with the interaction. For example, language code switching may occur if the customer for whom English is a second language perceives that the employee may also speak that language. An employee name tag with a Latino surname may prompt a Spanish speaking customer to code switch and place the order in Spanish rather than English. Similarly, a customer immersed in the skater culture may perceive that the employee shares this interest from their hairstyle and attempt to use that dialect in the transaction rather than the standard scripted English. Thus, customers may attempt to rewrite the organizational script to conform to their preferred communication style and code switch to another language or dialect. With brand code switching, the customer uses the brand terminology with which they are most familiar, whether due to frequent use of another organization’s services or to exposure to its advertising. For example, when a frequent McDonald’s user happens to go into Burger King for a meal, s/he may, out of habit order a “Big Mac” rather than Burger King’s preferred script, “The Whopper”. By code switching to a different organization’s brand terminology, the employee must disrupt the service script to clarify what the customer means, since Burger King does not offer anything called a “Big Mac”. Code switching is a commonly employed communication strategy that has been previously theorized to increase communication richness and efficacy (Rickford 1998). As such, we would expect code switching to increase satisfaction via enhanced comfort within service encounters (“you speak my language”). When the consumer and employee share what we identify here as a brand code, this indicates a high level of familiarity with the idiosyncratic script due to brand loyalty or sometimes merely market dominance. Berens et al. (2005) indicate that corporate brand dominance influences consumer involvement with the product and may lead to behaviors that closely mimic brand loyalty including a shared brand code.
Negative outcomes
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Table 2 Encounter data Data source McDonald’s Checkers Total QSR
Encounters 768 261
Small chain
768 261
1,029
Starbucks Independent Bookstore University
518 462 160 302
Total coffee
980
Total large chain Total small chain Total QSR and coffee
Large chain
notion that brand-specific scripts and brand-specific jargon are viable codes among which consumers and employees may code switch, we chose large global and local or regional service providers within the quick service restaurant (QSR) and coffee industries. For the source of the data, see Table 2 and for a summary of the data collection methods used in this study, please see Table 3.
518 160 302
1,286 723 2,009
If there is a shared code (language, dialect, or brand) that is highly salient to participants’ identity, prior research (cf. Heller 1988, 1995) strongly suggests the accuracy of the communication should increase because there is a common frame of reference. For service encounters this implies that language and dialect code switching leads to more accurate and more satisfying encounters. Alternatively, code switching, as a form of script departure, is noted in the services literature to disrupt the service encounter causing negative outcomes like order inaccuracy, consumer confusion and frustration, elongated encounters, and decreased consumer satisfaction (Bowen 1986; Lovelock and Young 1979). Because the research on code switching suggests that encounters that go off script can have positive outcomes, but the services marketing literature documents a number of negatives associated with not following the script, it is necessary that the service encounter be examined holistically and across contexts. The research method used to address our research questions is described below.
Research method To study the phenomenon of code switching at three basic levels: language, dialect, and brand codes, we collected data in two service environments. Because we are introducing the
Data QSR drive-thru encounters The authors obtained videotapes of drive-thru service encounters for McDonald’s, planned and executed by the fast food chain and an outside consultancy firm. Approximately 40 hr of video taped drive-thru encounters within the continental United States were captured and include peak meal times. The encounters at a number of different sites caught on tape are in situ or naturally occurring and the video cameras filming the encounters are conspicuous to both employee and customer, thereby ensuring that participants are not deceived. Discussions with McDonald’s executives identified attributes of the ideal encounter. Observations of walk-up service encounters Naturalistic observation (Lincoln and Guba 1985) of walkup service encounters was conducted in Checkers, a regional QSR chain (21 hr), Starbucks (22 hr), a coffee bar within a bookstore (12 hr), and one freestanding local coffee kiosk located on a large urban East Coast university campus (13 hr). In the bookstore data, there was only one employee observed, a monolingual European American woman; therefore, these data were only used to investigate brand code switching. Like the drive-thru tapes for McDonald’s, the researcher did not participate in the encounters, but rather observed them in situ as they occurred during peak times. The researcher was able to observe the counter interactions in detail from a nearby seating area. The encounters were recorded via field notes and audio taping. Audio-recorders were placed at the researcher station rather than the counter; background noise is present throughout the encounters and at times obstructs the focal encounter. In these cases, researcher field notes are the sole record of the encounter.
Table 3 Description of data Data source
Data collection method
Source of script knowledge
Number of coders (undergraduates and researchers)
Rate of coder agreement across categories (duration, breach, utterance) (percent)
McDonald’s Checkers
Videotape Audio, observation, field notes
3 3
99 94
Starbucks
Audio, observation, field notes
3
98
Bookstore Coffee Bar University Coffee Kiosk
Audio, observation, field notes
Books, executive interviews Employee interviews, customer interviews, signage, menu boards Employee interviews, customer interviews, signage, menu boards Employee interviews, customer interviews, signage, menu boards Employee interviews, customer interviews, signage, menu boards
3
93
3
92
Audio, observation, field notes
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As in the drive-thru tapes, the researcher coded the encounters for adherence to script and breaches. The researcher used the posted menu board and other servicescape signage to assist in identifying the ideal encounters from the corporate perspective and to establish the ordering script. Interviews McDonald’s has been the subject of numerous empirical inquiries including three prominent books focusing on the use of scripting, corporate culture and its impact upon popular culture (Leidner 1993; Love 1995; Schlosser 2002). For this reason, we felt confident that we knew the firmspecific protocol. Using a semi-structured interview protocol, we interviewed three employees and nine consumers of the Checkers chain. The employees were interviewed to ascertain what the ideal encounter was from the firm perspective, and to identify strategies employees of the chain used when confronted with consumer code switching and employee code switching temptation. Nine consumers were interviewed to help ascertain the ideal encounter from their perspective: six of whom had been involved in seemingly ideal encounters and three of whom were involved in encounters that appeared to contain a breach, specifically code switching. The interviews ranged in duration from 18 to 50 min and were audio recorded; researcher commentary was detailed in field notes. Four coffee bar employee interviews were conducted to derive the corporate ideal encounter, the corporate emphasis on scripting, the employee’s discomfort with script departures and other service encounter breaches. Similarly, interviews were conducted with twelve customers experiencing observable breaches and five customers engaged in seemingly ideal encounters. Interviews lasted between 25 and 45 min and were audio recorded. Analysis Ethnography and ethnomethodology The tapes, interviews, and naturalistic (nonparticipant) observation data were analyzed using ethnographic techniques and ethnomethodology. The most common of these research methods is ethnography where observational and interview data are analyzed and taken holistically to uncover the lived reality of participants (Spradley 1979). In ethnomethodology, mundane tasks, like ordering at a QSR or coffee bar, are examined looking for behavioral expectations (known routines) and departures from the expectations (breaches). Ethnomethodology is an interpretive method similar to phenomenology that examines everyday life and social practice as a complex cooperative act (Heritage 1984): “ethnomethodology is the empirical investigation (“-ology”) of the methods (“method-”) people (“ethno-”) use to make sense of and at the same time accomplish communication, decision making, reasonableness and action in everyday life” (Rogers 1983).
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It “is the study of the common, mundane methods that are used by people to produce and manage the common, everyday, activities like shaking hands, taking turns-at-talk in conversation, reaching a verdict, standing-in-line,” picking up coffee from a coffee bar, or grabbing food from a QSR drive-thru (p. 10, Livingston 1987). Of particular interest in this inquiry is how consumers negotiate the process of ordering food from a QSR or coffee at a coffee counter and how the script expectations are formed, produced, and reproduced by members of the production cohort, in this case consumers and employees within the servicescape. Differences between practice and corporate ideal were noted as breaches and investigated. Breaches Ethnomethodologists are known for their breaching experiments, which have the researcher purposefully subvert the social expectations in order to cause the members of the local production cohort to quickly shed their underlying assumptions and perhaps reveal the usually obscured aspects of their social interaction and order (Garfinkel 1967). In our data, we distinguish between a breaching experiment which is an artificially imposed subversion of social practice from a naturally occurring breach which is an in situ disruption from the normal social expectations of the particular servicescape. These naturally occurring breaches were caught on the taped encounters and recorded as nonideal in our coding sheets, or noted in the field notes and coding sheets in the nonvideotaped encounters. Coding A total of seven undergraduate coders were employed to analyze the data: three coded the McDonald’s encounters (two coded all and a tie breaking coder was used when they did not agree), two coded the Checkers encounters (with a researcher as a tie breaker when coders did not agree) and three coders were used across the Starbucks and independent coffee encounters (each encounter was coded by at least two coders with a third used to break any ties). All seven coders were selected based on their familiarity with either QSR or coffee bar consumption. This allowed them to collaborate on the interpretation of the social practices we examined (Ahuvia 2000). In a manner consistent with traditional content analysis (Kassarjian 1977), coders were trained by researchers to recognize encounters within ideal corporately defined parameters and breaches in the taped encounters and in the researcher field notes. Coders were also trained to recognize script subversions, specifically code switching behavior. Coders were given examples of code switching across broad language, dialects, and brands. In order to evaluate the encounters, coders were trained to record: (1) the duration (in minutes) of the encounter from the onset of the order through fulfillment, (2) comments (statements and nonverbal cues such as grunts) and body language (smile, nod, hand wave) of both dyad parties immediately after encounter fulfillment, (3) whether com-
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ments/gestures were positive or negative expressions, and (4) consumer inquiries (i.e., “is this a diet drink?” or “where’s the ketchup?”) and returns made to the counter following the encounter fulfillment. Consistent with a more interpretive content analysis (Ahuvia 2000), coding sheets were developed collaboratively with researchers encouraging coders to identify common events used to identify the social practice of the QSR and coffee encounters. The tapes and field notes were reviewed to pull out recurring examples of each coding classification. Encounters were transcribed and examined in detail. Social conventions were identified. Coding commonalities emerged, where certain coded classifications would appear linked together with regularity. These co-occurrences were further analyzed and compared to one another until the social practice from approach to departure was defined. Then, each encounter was timed and the number of utterances and number of words within utterances were counted and compared to look for patterns across ideal encounters and breaches. Lastly, the initiator of code switching was noted as was duration of code switching behavior. Analysis triangulation Hirschman (1986) suggests that humanistic inquiry should be evaluated on the criteria of credibility, transferability, dependability, and confirmability. Credibility can be demonstrated by submitting the interpretation “to those individuals upon whom it is based, and seek their responses as to its authenticity” (Hirschman 1986, p. 244). In the interviews described above, employees and consumers were asked about the observed data and our interpretation. Interviewees confirmed that our interpretation had credibility. Transferability is analogous to external validity or generalizability. We found similar scripting in the QSR and coffee shop contexts and identified the details that differentiate the settings. Code switching breaches were found in both contexts, and the frequency of breaches was similar in the venues, although the types of code switching differed. Dependability was assessed via inter-coder agreement for identifying the presence of breaches, which ranged from 95 to 98 percent. This means that in less than 5 percent of the encounters, the coders were not able to agree on the classification of the encounter as a breach. In those rare cases, a third coder was used to break the tie and resolve the discrepant coding. In terms of the exact utterance that began a breach or pinpointing a code switching instance, the intercoder agreement was not quite as high, but was above 87 percent for all encounters. In all cases, discrepancies were resolved with a third coder (another trained coder or a primary researcher). This means that the impetus for code switching was not identified with perfect agreement as coders were not always able to ascertain which encounter participant was responsible for the code switch (e.g., an accent or phenotype recognition that may have triggered the code switch was not obvious). There were no discrepancies in the coders’ recording of the encounter time that exceeded 2 seconds. This means that coders were in extremely high agreement as to when the
order taking began, which we later determined was the onset of the encounter. In addition to the extensive training they received, we believe the high degree of agreement among our coders was in part due to the coders’ familiarity with the consumption venues of the service encounters and their lived experience as QSR and coffee consumers. Finally, confirmability was assessed by the coders who were not involved in actual data collection. Coders were selected who were familiar with the QSR and coffee shop contexts. Coders examined taped encounters (video and audioonly) as well as field notes and were debriefed as to the field notes’ appropriateness relative to their experience. There was nearly perfect coder agreement between the data and the coder experience of the contexts which confirmed that we had indeed captured the focal phenomenon.
Findings Findings are reported across and within the service environments as the compelling trends and themes warranted. As in the ethnomethodological tradition, we have made breaches our focus for understanding the normative behaviors and lived experience within the servicescapes. By focusing on the breaches, we are able to better understand the elements of the ideal encounter and the manner in which behavioral expectations are communicated. It should also be noted that we focused on a specific form of breach, code switching. The social practice and ideal encounters Before we address the research questions it is necessary that we define the encounter itself. Researchers and coders worked together (Ahuvia 2000) to determine the elements of the ideal encounter from both the firm and consumer perspective. We concluded that there are three basic stages in every the encounter: (1) the order, (2) the fulfillment, and (3) the consumer evaluation of the outcome. The following represents an ideal encounter at Starbucks: The order: Employee: “What can I get started for you?” Customer: “I’ll have a Decaf Grande White Chocolate Mocha with no whip”. Employee: “That’ll be $3.95. Can I have a name with that?” Customer: “Diane” [payment card used]. The fulfillment: Employee: “I have a Grande Decaf White Chocolate Mocha with no whip for Diane”. The outcome: Customer: [takes drink in cup sleeve and sips.] “Great! Thanks”. If one were to choose the single most important stage in the encounter, both employees and consumers express the
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perception that it is the order stage. It is at the point of order where the real contact between the firm and the consumer takes place. It is also the only stage where the consumer has any influence over the process and outcome. Script adherence is important to the ordering process as it helps shape behavioral expectations and reinforces the efficient protocol. In essence, the script is the most important tool within the most important stage in the QSR and coffee encounters. Research question #1: code switching in scripted service encounters To address our first research question, we identified encounters in which employees and customers changed to another language (language code switching), used a shared dialect rather than standard English (dialect code switching), or used the brand terminology of a competitor (brand code switching). Our data strongly demonstrate that code switching does occur in scripted service encounters. Code switching was not expected to account for a large segment of the script subversions but as detailed below and in Table 4, it does. Interestingly, code switching was almost always initiated by the customer. No language code switching was initiated by employees, but there were a few instances of employees making the first move in dialect code switching. Employees never initiated brand code switching, although there were a few instances where they responded to a customer brand code switch by adopting the competing brand code (e.g., a Checkers employee would adopt McDonald’s brand terms or a University Coffee Kiosk employee would use Starbucks brand code). Across both the QSR and coffee bar data, we see a significant amount of script subversion as general code switching behavior. Fully one-third of all encounters in our data set contain some kind of code switching script subversion. Even in tightly scripted service environments, there is considerable improvisation and specifically a tendency for participants to blend or shift from one shared code to another leaving the original script behind. There is some difference between the service environments with 30 percent of the QSR encounters exhibiting code switching compared to 36 percent of the coffee encounters.
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Research question #2: language and dialect code switching in commercial settings To address our second question, we examined the language and dialect code switching sociolinguists have examined in noncommercial settings. Language code switching occurs when an employee or a consumer blends, toggles between or outright switches from the script based in standard American English to another broad language code like Spanish or Farsi. For example, here is one encounter at Starbucks: Employee: Can I help you? Consumer: Yes. Um. What is that? [points to menu board] Employee: Caf´e Mocha? Consumer: Huh? Employee: It’s a shot of espresso, chocolate, steamed milk and whip cream. Consumer: ¿Habla espa˜nol? Employee: Un poco. Consumer: Columbian? Employee: My parents are. Padres. Consumer: Ahhh. Mocha esta dulce? Employee: S´ı. Mocha esta dulce. Hay cacao y Cool Whip. Consumer: S´ı. Grande Caf´e Mocha. In the above encounter, we see that the consumer initiates a broad language code switch. Based on phenotypes, she guesses that the employee might speak Spanish and might be Columbian. The employee answers that his parents are Columbian, but he only speaks a little Spanish. The order segment of the encounter is elongated as the consumer and employee struggle to communicate the product offerings, but ultimately understanding is reached by code switching to Spanish. In our dataset we see that language level code switches occur in both QSR and coffee encounters and in both large firm and small firm servicescapes. The percentages for the QSRs and the coffee encounters at Starbucks and the university kiosk are very similar (See Table 4). Dialect code switching occurs when a participant in a scripted service encounter blends, toggles or outright switches from the script which is based on standard American English to a recognizable dialect (ebonics, Southern drawl,
Table 4 Incidence of code switching (CS) Data source
On-script (percent)
Language CS; percent of encounters
Language CS; percent of CS
Dialect CS; percent of encounters
Dialect CS; percent of CS
Brand CS; percent of encounters
Brand CS; percent of CS
McDonald’s Checkers Total QSR Starbucks Bookstore Coffee Shop University Coffee Kiosk Independent total Total coffee Total QSR and coffee
77 49 70 72 47 58 55 64 67
3 5 3 4 N/A 4 N/A 3 3
12 9 11 13 N/A 9 N/A 9 10
19 15 18 8 N/A 13 N/A 8 13
84 29 60 29 N/A 31 N/A 23 40
1 32 9 16 w/o size 3 53 25 75 25 17
4 62 29 58 w/o size 11 N/A 61 N/A 68 50
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contemporary urban youth). An encounter exhibiting a dialect codeswitch follows: Employee: Welcome to McDonald’s. Can I take your order please? Consumer: How ya doin’? Employee: Stuck in here. [laughs] Order when ready. Consumer: Chill a sec. Lemme see. Employee: Like ice. Consumer: Damn, so many choices. OK, I’ll have a Big Mac meal deal with a Coke and . . . a chocolate shake. Employee: Nothin’ shakin’ today. Done broke. Consumer: [laughs] A’ight, make it a sundae wit chocolate. In the above drive-thru encounter, we see a consumer initiate a code switch to a shared dialect. The employee and consumer depart from the formal script opting to communicate in a less formal shared code. Dialect code switching occurred across all our data. Here, we find that encounters at Checkers, Starbucks, and the university are all similar in their percentages of dialect code switching, while McDonald’s has an extremely high level relative to other types of code switching (see Table 4). McDonald’s relatively low levels of brand code switching (see below) may account for dialect code switching representing a large proportion of code switching encounters for them. Research question #3: brand code as an idiosyncratic vernacular While previous research on code switching has examined broad language codes and common microcultural dialect codes, in answer to our third research question, we find compelling reasons in our data to believe that corporate scripts and brand-oriented jargon can be included as legitimate code structures. Just as languages and microcultural vernacular are codes used within social groups, or speech communities, where specific words and symbols have meanings, are relatively stable over time, and are taught to new entrants to the group (Franceshini 1998), corporate lingo also constitutes a code. In an examination of McDonald’s and Starbucks encounters, we find that each sets the standard in their industry for nomenclature related to their respective service environment and offerings within the environments. For example, consumers know the standard condiments for the Big Mac without an explicit description on the menu board, in part due to the advertisement jingle, “Two all beef patties, special sauce, lettuce, cheese, pickles, onions on a sesame seed bun”. Perhaps more interestingly, the consumers know the taste, color and consistency of the “special sauce”. In a drive-thru encounter, the following illustrates this understanding: Employee: “Sure, so you’d like a Big Mac with no sauce with fries. Would you like the meal deal?
Consumer: “Yes, but make sure the Big Mac doesn’t have the chunky sauce”. Employee: “Sure. Can I super size that for you?” Consumer: “Yeah”. In the above exchange, we can see that the consumer and the employee know the code, which is unique to the firm. They share an understanding of the characteristics of the burger (special sauce) and the portions (super size). These are idiosyncratic terms, but they are shared within the brand community and indeed the QSR community. No one needs to recite the exact portion size of a Super Sized item; it is understood. Similarly, Starbucks has introduced a set of products with firm-specific names which are often imitated. Coffee consumers demonstrate knowledge of Starbucks’ offerings: Employee: “Welcome. What’ll it be today?” Consumer: “I’ll have a grande Coffee Frappuccino and a grande Caf´e Mocha, no whip with double cup”. Employee: “Great. Can I have your name please? Consumer: “Debbie”. Employee: “Thanks, Debbie. That’ll be right up at the end of the counter. [gestures to section of counter marked ‘pickup’. repeating to coffee chefs] Grande Coffee Frap, and a grande Mocha no whip in 2 for Debbie”. In the two examples above, both dyads demonstrate role clarity for the dominant brand code, McDonald’s and Starbucks, respectively. They understand where to queue, when to order and to whom, and where to pick up the order, which is the same across the servicescapes within each industry. Both examples demonstrate how adherence to the brand code facilitates efficient encounters. Brand code switching occurs when employees and consumers subvert the brand-specific script blending, toggling or outright switching to another common brand code. The following is an excerpt from an encounter with a brand codeswitch: Employee: “Welcome to Checkers”. Consumer: “Can I get a cheeseburger kid’s meal, and a Chicken McNugget meal?” Employee: “Sure, a cheeseburger kid’s meal and how about a number 12? Consumer: “Is that like the McNuggets?” Employee: “It’s more like chicken strips”. Consumer: “Oh, OK, that’s cool”. In the above, we find a consumer who orders from Checkers using a McDonald’s brand code. The employee is familiar with the McDonald’s code and translates the order for the consumer asserting the Checkers menu items. The code switch results in a longer encounter, but the outcome appears to have met the consumer’s expectations. Similar brand switching is seen in the independent coffee stores where employees must contend with customers who want to speak “Starbucks”:
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Consumer: “I’ll have a low cal mocha decaf Frappuccino with no whip cream”. Employee: “I’m sorry we don’t serve Frappuccinos. Would you like to try our blended frozen coffee with chocolate?” Consumer: “I guess that is what I meant. Can I get it low cal and decaf?” Employee: “Decaf. No problem. Low cal? Do you mean skim milk and less sugar? How much less?” Consumer: “Uh, I dunno. Like the low cal Fraps. Sweet but maybe a third less calories”. Employee: “OK, I can try. I’ll put the sugar in and use half sugar free syrup”. Consumer: “That sounds right. Can I get that in grande? Employee: “You mean medium? This size? [holds up the cup]” Consumer: “Yep. That’s it, but no whip cream”. Employee: “Ok, no whip”. The consumer orders using Starbucks code and the employee struggles to assert the competing firm’s code, translating the consumer’s order. The encounter takes much longer than an order using the appropriate brand code. The researcher’s field notes indicate that the employee displays frustration with the number of corrections they engage in, but due to his familiarity with the Starbucks code he is able to create the coffee drink the consumer ordered. Research question #4: brand code switching is more common in small firms Brand code switching occurs throughout our dataset. In answer to our fourth research question, we find that brand code switching occurs far less often within McDonald’s and Starbucks servicescapes compared to nonmarket leaders. Less than 1 percent of all McDonald’s encounters contained brand code switching (4 percent of code switching). McDonald’s as a large global QSR with decades of dominance in the QSR marketplace, has developed very clear scripts with which consumers are extremely familiar, especially those consumers who frequent QSRs. In fact, it is safe to say that McDonald’s has set the industry standard for QSR routinization and protocol. While we would expect Starbucks with a coffee bar on every corner to also exhibit strong script adherence, we initially found a great deal more brand code switching at Starbucks than McDonald’s. A closer examination of the brand code switching led us to suspect that the sizing nomenclature at Starbucks was not well assimilated into the vernacular of coffee consumers. When we removed the sizing (tall, grande, venti) code switching, we find that Starbucks has a brand code switching rate of 3 percent of encounters (11 percent of code switching), closer to the McDonald’s findings. This finding as modified by removing the sizing code switching for Starbucks indicates that McDonald’s and Starbucks, as market leaders, reap a benefit of script adherence and set the industry standard for encounter protocol. It seems as if McDonald’s over its decades of market dominance sets
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a more rigid standard than Starbucks. However, given that Starbucks began revolutionizing coffee consumption behavior in earnest in the 1990s, its brand code dominance is quite impressive. Brand code switching was much more prevalent at the regional firms. For Checkers, 32 percent of encounters contained brand code switching (62 percent of code switching). The bookstore coffee shop experienced brand code switching in 53 percent of its encounters and the University Coffee Kiosk had 25 percent of encounters with brand code switching (61 percent of code switching). It should be further noted that code switching at Checkers was exclusively to the McDonald’s brand code and similarly, that the brand code switching at the bookstore and the university was overwhelmingly toward the Starbucks brand code. So, while scripting has received considerable attention in scholarly studies, we firmly believe that scrutinizing the patterns of script subversion, specifically code switching, is warranted to understand the social practice and to improve efficiency and accuracy of outcomes within the servicescape. Research question #5: code switching and service outcomes Our fifth research question was addressed using outcome data. Outcomes examined include encounter duration, the presence of positive and negative comments and gestures, and post-fulfillment inquiries and returns (see Table 1 for a summary of outcomes for each code switching type). Our data demonstrate the impact of code switching generally and across the types of code switching (language, dialect and brand) on scripted service encounters. Table 5 indicates that on-script encounters, across the board, result in fewer negative outcomes than code switching encounters. The on-script encounters were shorter and resulted in fewer post-fulfillment returns. This finding holds for market leaders and smaller players in both industries. Interestingly, on-script encounters result in positive gestures/comments less frequently than most encounters with code switching. Language code switching has outcomes that are quite similar to the on-script encounters. These code switches are of short duration, with fewer returns and negative comments/gestures than either dialect or brand code switching. Interestingly, language code switching results in the highest incidence of positive comments/gestures, often higher than even on-script encounters. Dialect code switching resulted in encounters having the longest duration. This type frequently involved going offtask, conversing about movies, celebrities, the weather, etc. A relatively high rate of returns resulted for the dialect code switching encounters. While brand code switching encounters stayed on-task, they tended to be of similarly long duration as the dialect encounters. Overall, there were fewer instances of positive comments/gestures than either language or dialect code switching (although more than on-script encounters) while
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Table 5 Outcomes of code switching (CS) Data source
Average duration
Positive comments gestures (percent)
Negative comments gestures (percent)
Post-fulfillment inquiries (percent)
Post-fulfillment returns (percent)
McDonald’s On-script Total CS Language CS Dialect CS Brand CS
2 min 18 s 3 min 47 s 3 min 17 s 3 min 53 s 3 min 41 s
18 34 27 37 23
3 9 13 9 4
6 22 24 14 11
1 8 6 9 2
Checkers On-script Total CS Language CS Dialect CS Brand CS
4 min 19 s 5 min 24 s 4 min 26 s 5 min 48 s 5 min 21 s
14 38 46 35 37
7 12 18 13 8
9 28 29 19 15
3 9 6 11 7
Total QSR On-script Total CS Language CS Dialect CS Brand CS
2 min 49 s 4 min 12 s 3 min 35 s 4 min 22 s 4 min 6 s
17 35 32 36 27
4 10 14 10 5
7 24 25 15 12
2 8 6 10 3
Starbucks On-script Total CS Language CS Dialect CS Brand CS
3 min 28 s 5 min 7 s 4 min 2 s 5 min 18 s 4 min 52 s
16 36 47 38 34
11 21 7 19 24
24 36 41 32 43
4 9 2 8 11
Bookstore Coffee Shop On-script Total CS Language CS Dialect CS Brand CS
4 min 31 s 5 min 16 s 4 min 41 s 5 min 23 s 5 min 14 s
12 N/A N/A N/A 18
11 N/A N/A N/A 29
29 N/A N/A N/A 34
6 N/A N/A N/A 8
University Coffee Kiosk On-script Total CS Language CS Dialect CS Brand CS
3 min 55 s 5 min 31 s 4 min 32 s 5 min 53 s 5 min 36 s
32 39 56 39 42
14 22 6 14 27
19 31 28 33 32
2 4 1 6 4
Independent total On-script Total CS Language CS Dialect CS Brand CS
4 min 8 s 5 min 26 s 4 min 35 s 5 min 42 s 5 min 28 s
25 39 56 39 34
13 22 6 14 28
23 31 28 33 33
3 4 1 6 5
Total coffee On-script Total CS Language CS Dialect CS Brand CS
3 min 47 s 5 min 16 s 4 min 18 s 5 min 30 s 5 min 9 s
20 37 50 38 34
12 21 7 17 26
23 34 36 32 38
4 7 2 7 8
Total QSR and coffee On-script Total CS Language CS Dialect CS Brand CS
3 min 17 s 4 min 43 s 3 min 56 s 4 min 55 s 4 min 37 s
19 36 40 37 30
8 15 11 13 15
15 28 30 23 25
3 8 4 9 6
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there were somewhat more negative comments/gestures than any other encounter type. If we examine the valence data for code switching based on industry, we see that code switching has a similar impact on QSR and coffee encounters. On-script encounters are shorter, result in fewer positive or negative overt responses and seem to minimize post-fulfillment inquiries and returns. These similarities are interesting when we consider that QSRs offer discount dining, while coffee consumption is a high-end customized beverage choice. In terms of large versus small market players, both McDonald’s and Starbucks had shorter on-script encounters on average than their competitors. The large international firms have set the standard for efficient service. Code switching outcomes are also similar across firms; however, it must be remembered that smaller firms did experience much lower rates of on-script encounters, largely due to brand code switching. Discussion In this section, we acknowledge limitations of our research, followed by discussion of the theoretical and managerial implications of our results. Limitations The findings of this study are most appropriate in service contexts, e.g., QSRs and coffee bars, where speed and efficiency are important. However, we believe that we can generalize the study’s findings to other types of services. Similar observations are also likely in the service delivery process of emergency medical services and stock trading where speed and efficiency are important and script subversion can lead to costly errors. While our study has relevance for other types of services in which speed and efficiency are critical, there are a few limitations of this examination. Our language and dialect code switching findings are limited to QSRs and coffee shops in diverse urban settings rather than homogenous communities. We would expect the percentages of language and dialect code switching to be considerably different in instances in which QSRs and coffee shops were located in towns with homogeneous populations. In addition, our findings are limited where dialect code switching might be a positive attribute, such as service contexts where quickness and efficiency are less material to the service delivery process. Examples include check cashing, debt management, tax preparation, real estate, and retirement planning services. Because almost all data were observational (the employee and customer interviews were used to define the script), we were only able to infer positive and negative outcomes based on encounter duration, the number and valence of utterances and gestures, and order returns. Future research should include patron intercepts to determine their attitudes toward the encounter.
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We relied on interviews with customers and employees to define the ideal script. More extensive input from corporate executives at each of the firms would help to more precisely define each firm’s intended service script. Theoretical implications The literature has focused on service scripts as a sequence of events, ignoring the content of service interactions. Our research on the service script dialogue reveals a new set of issues scholars should consider to understand provider/customer interactions. An important finding of our research is that code switching is quite common in even tightly scripted service encounters. This finding holds across two industries and for large and small firms. The extensive sociolinguistic literature on code switching is empirically reliant on dyadic and multiperson casual conversations within classrooms and other social settings. Focusing on language and dialect code switching, these researchers reveal that a great deal of social, interactional, discursive, and other information can be signaled through the alteration of speech varieties in their broadest sense (Auer 1998; Heller 1995). They conclude that people make use of code switching to assert political and other agendas (us versus them). Our research investigated the same phenomenon but within a commercial setting. We found that both language and dialect code switching occur in service encounters, but language code switching serves as a means to find common ground to facilitate transactions rather than to make a political statement. The Spanish speaking customer may ask “¿Habla espa˜nol?” or the bilingual service provider may sense the customer’s language difficulties so that communication can transpire in a common language to enhance order accuracy. This type of language code switching is utilitarian rather than political. Regarding dialect code switching, sociolinguists have studied Black English and other dialects and suggest that “language is one cue that seems to provide a basis for interpersonal judgments” (Koch et al. 2001, p. 30). In a service encounter, the time to form an impression is limited and customers or employees may adopt a dialect to make a connection, however brief. For example, we find that some African American customers code switch to Black English (BE) when interacting with African American service employees, hip hop references are used between participants based on manner of dress as opposed to phenotypes, and similarly skater lingo is employed when employee and consumer recognize a shared common community bond. Koch et al. (2001) found that African American university students responded positively to BE speakers when it was used in informal interactions. In commercial settings, consumers and employees have goals different from settings typically studied by sociolinguists. Speed and efficiency are also concerns. In addition to language and dialect code switching, we observed substantial evidence of brand code switching, a phenomenon not previously studied. “Brand language” can be
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considered analogous to a language or dialect in that users communicate to others they assume share a common understanding of the brand code. Brand code switching is different from language and dialect code switching in that employees are legally prevented from using the customer’s preferred brand code if it is trademarked by a competitor. Thus, while employees are free to toggle between language or dialect codes, using another provider’s code is not an option. In fact, we did not find one instance of an employee initiating a brand code switch to a competitor’s brand code. Managerial implications Service scripting was used as efficient protocol for the encounters in both industries. Employees were trained in the manner in which they should engage the consumer in ordering and in recording the order for fulfillment. Typically the market leaders led in the development of the encounter parameters and expectations within the industry. Institutional training at places like Hamburger University in the McDonald’s corporation teaches employees to enact efficient encounters (Schlosser 2002). When code switching took place for language codes, there were positive outcomes to the encounter. In locations where people without English language skills are likely to be frequent customers, service providers should seek to employ people with bilingual abilities whenever possible. In addition, some basic language training targeting the ordering process and product attributes could help even monolingual employees better serve customers. For ESL (English as a Second Language) employees interacting with English speaking customers, employers must take the lead in including brandspecific language training in the overall script orientation. In addition, having a photo menu available at the order point would allow customers unable to language code switch to communicate their order nonverbally by pointing at the pictured items. For dialect code switching, outcomes were less positive and marketers should be aware of actions that may encourage it. Even when considering the percent of all encounters, the McDonald’s dialect code switching is higher than other firms and is not easily explained; perhaps McDonald’s is more tolerant or accepting of dialect code switching than the other establishments in our study. McDonald’s likely has a larger minority customer and employee base than the other firms in this study. In addition, McDonald’s advertising and other promotions specifically target consumers with hip hop music and motifs, implying that it is cool (and acceptable) to use dialect. Firms, particularly industry leaders, may want to be cautious in their approach to influencing the customer’s script. Even industry leaders with well-known scripts may need to model appropriate in-store interactions in their promotional materials. Further, firms should be diligent during employee training to reinforce the importance of adherence to the script, providing evidence of the adverse consequences of dialect code switch.
The finding that dialect code switching leads to longer service encounters with greater incidence of problems is countered by the positive expressions of participants. The individual customer who code switches to dialect may enjoy the extended encounter, but interfere with the efficient processing of other customers in the system. Research on service quality has focused on individuals’ assessment of service attributes (e.g., Parasuraman et al. 1988; Zeithaml et al. 1996). Because customers in the service factory impact other customers (Grove and Fisk 1997), managers may want to take a more holistic view of service quality, considering the waiting customers as well as the customer being served. Brand code switching is evidence that the customer is lacking the customer readiness (clarity, ability, motivation, or all) (Meuter et al. 2005; Dellande et al. 2004) needed to comply with the company script. This phenomenon is less of a problem for market leaders such as McDonald’s because their script is the industry standard. In fact, we find that McDonald’s has the lowest percent of brand code switching in our sample, less than 1 percent of encounters. Through years of heavy advertising, clear signage, consistency between locations and well-trained employees, McDonald’s and other market leaders enable their customers to use the brand code (George and Berry 1981). These actions are consistent with research that suggests ways to “train” customers (Bowen 1986; Kelley et al. 1990). Because trademarked brands cannot be used by other companies, market leaders will have the advantage of writing at least part of the service script for the industry as a whole. For smaller players, this means that they will need to train their employees in the brand code of their major competitor as well as their own script. Their employees must know what a “Frappuccino” or a “Big Mac” is in order to direct the customer to the closest alternative on their menu. Employees should be trained to use this opportunity to offer role clarity to their customers by educating them to order on-script in the future. The following verbatim illustrates such an effort: Employee: What will you have today? Consumer: Hmmm, I’ll have a Mocha Frappuccino with no whip cream. Grande please. Employee: Would you like to try our frozen blended chocolate coffee? Consumer: Yeah, I’m sorry. That. Is it like a shake? Employee: I suppose. More like a shake than a coffee. Consumer: Sure. That. Employee: A medium? Consumer: I guess. That’s a grande, right? Employee: [laughs] Here, it’s a medium. Normann and Ramirez (1993) assert that companies create value when they make not only their offerings more intelligent, but their customers more intelligent as well. How can customers be motivated to adhere to the brand code of the provider? Mills et al. (1983) suggest that productivity improvement techniques require that the intended customer behavior be viewed by the customer as satisfying.
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Training employees to let the customers in on the brand code (e.g., “Next time, order the blended coffee instead of the iced shaken and you’ll get just what you want”) will motivate the customer to adopt the correct script in the future. As well, the customer will feel a part of the brand community if they are given the brand code that outsiders do not know. For example, In-N-Out, a regional burger chain, has a “not so secret” menu of items not on the menu board. Their website explains that you can get a burger “Animal Style” which is a “Burger of your choice with hand-leafed lettuce, tomato, a mustard cooked beef patty; add pickle, extra spread, with grilled onions” (http://www.in-n-out.com/secretmenu.asp). Ordering off the menu using the brand code (e.g., “I’ll have a burger, and make it animal style”) communicates to the employee and other customers that this person is a member of the brand community. Building a brand community (Mu˜niz and O’Guinn 2001) will enable even a small chain to avoid brand code switching and keep customers on-script. Efforts to develop a loyal client base will help any service provider reduce the amount of brand code switching in their encounters. Adopting brand codes is risky even for market leaders. The majority of breaches in our Starbucks encounters were due to the failure of customers to stray from the traditional drink sizes and adopt the “tall/grande/venti” nomenclature. While it may be the intention that these terms will add to the European coffee house image of the brand and distinguish Starbucks from mainstream competitors such as Dunkin Donuts (Shultz and Yang 1997), it should be recognized that this image is at the cost of smooth running encounters adhering to the service script. Examination of online chat rooms and blogs suggests some consumers intentionally subvert the Starbucks script by ordering small/medium/large despite their knowledge of the preferred brand code. Trademarked brand names appeared to cause breaches for competitors; therefore, service providers should consider unique brand names trademarked for new product introductions.
Conclusion Applying the theater metaphor to services has been a reasonable approach to understanding the interaction between employee and customer, with roles that are played and scripts that are followed. However, the dialogue component of service scripts has been overlooked. Our research enables firms to compete on service by highlighting one-way scripts can be subverted, by code switching via language, dialect, or brand code. Our research contributes to the code switching literature by confirming the positive effects of language code switching in a context not previously studied (i.e., commercial services), by identifying a context in which dialect code switching may not be appropriate, and by introducing brand code switching and its negative repercussions. Here, we have looked at the impact of language and dialect code switching but within the collaborative context of the service encounter (cf. Luna and
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Peracchio’s (2005) code switching research in an advertising context). We also introduce the notion of the corporate script as a legitimate code system, where consumers and employees can toggle back and forth between codes. We firmly believe these marketplace codes are as valid as other vernacular as they have wide-spread use within the global fast food and coffee cultures. Managers of highly scripted services, those with little customization or judgment from providers (Lovelock 1983) should encourage going “off script” when the provider and customer can communicate better in another language and when there is a need to “educate” the consumer as to the appropriate brand script (for small market players). Script subversion should be discouraged when dialect code switching is at issue. Scripting plays an important role in such services, and managers must understand what type of “ad libbing” is detrimental to the service experience.
Acknowledgements The authors would like to thank McDonald’s for their generous sharing of data with us. We also thank the editors and three reviewers who provided helpful suggestions that so improved our original submission.
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