Abstract
Demographic, technological, and global trends have brought the language used at the workplace to the forefront. A growing body of research reveals that language could result in misunderstanding at work, and influence employees’ performance and attitudinal outcomes. Language at work encompasses standard language (e.g., English) as well as several hybrid forms of language (non-native accents, code-switching, and jargon). We delineate how these forms of language could result in misunderstanding. We then identify relational, affective, and informational mechanisms that underlie the relationship between language-related misunderstanding and employees’ performance and attitudinal outcomes, and highlight key boundary conditions. In doing so, we uncover research gaps and identify areas for future research. We conclude with implications for theory as well as for practitioners to navigate language-related misunderstanding at work.
Keywords
Words can educate. Words can enthrall. Words, however, can also exasperate and exclude. This is the essence of language—the ability to forge connection or spark disconnection. In everyday life, we use language to communicate with one another, to transmit critical information, to create bonds with others, and also to antagonize and abuse others. The same dynamics unfold in organizations where demographic, technological, and global trends are compelling employees to navigate a complex linguascape (linguascape is a play on the words “language” and “landscape”). The term linguascape highlights the existence of multiple forms of language within an organizational setting (Steyaert, Ostendorp, & Gaibrois, 2011). These forms include both standard language (e.g., English, French, Spanish) and hybrid language (e.g., business and professional jargon).
For instance, although English remains the predominant language in global business (Cambridge English, 2016), the increase in multinational companies from non-Western countries (e.g., the number of Fortune 500 organizations headquartered in China increased from 10 to 124 from 2000 to 2020) has given an impetus to other languages—Mandarin, Arabic, and Hindi, to name a few—across global workplaces (Pizzola, Carroll, & Mackie, 2020). In addition to the increase in linguistic diversity of standard languages in organizations, there is also an increase in hybrid languages (i.e., informal, or non-standard language practices, such as jargon). For instance, approximately 25% of U.S. employees currently require an occupational license, which is a five-fold increase in professional licensing requirements in the United States since the 1950s (Furman & Giuliano, 2016; Timmons, 2018). In addition to setting quality standards for each profession, occupational licensing has important implications for language use: occupational licensing provides a common parlance (i.e., jargon) for licensed members (Timmons, 2018). The increase in occupational licensing in the workforce thus has also resulted in an increase in jargon in organizations.
At the workplace, this increase in the linguistic diversity of standard and hybrid languages could inadvertently create a fertile ground for misunderstanding. For example, if global team members converse with each other in a different standard language (e.g., German) instead of the corporate-mandated language (e.g., English), it could unwittingly result in a misunderstanding for their colleagues who do not speak German (Neeley, Hinds, & Cramton, 2012). This is because the non-German speaking colleagues could speculate that their German-speaking team members did not value their contributions (and perceive exclusion), even if German-speaking colleagues were conversing on non-work-related topics (e.g., sports, weather). Similarly, hybrid languages could also result in misunderstanding. For example, using jargon eases communication flows between licensed members within the same occupation; however, communication between licensed members of different occupations (e.g., pilots and air traffic controllers) using different jargon could result in unintentional misunderstanding (Howard, 2008). In a tragic instance, misinterpretation of verbal communication about the word “takeoff” (between the captain and the air traffic controller) was instrumental in a collision between two aircraft in Tenerife, Spain, that resulted in the deaths of 583 people (Cookson, 2009; Weick, 1990).
Furthermore, with increasing linguistic diversity, scholars now conceptualize organizations as “multilingual meeting ground(s)” (Brannen, Piekkari, & Tietze, 2014: 496–497), where standard and non-standard languages intersect. This increases the possibility for language-related misunderstanding to occur, and it creates the impetus for documenting how it could impact employees’ performance and attitudinal outcomes. For instance, language-related misunderstanding could result in performance decrements (Volk, Köhler, & Pudelko, 2014), work withdrawal (Nurmi & Koroma, 2020), trigger the formation of in-groups and out-groups (Kulkarni, 2015), and pose inclusion challenges (e.g., Deal, Altman, & Rogelberg, 2010). As these findings suggest, undercurrents of language swirl through many organizational phenomena: status, exclusion, and performance to name a few. Unsurprisingly, cross-disciplinary research on language in organizations has grown rapidly in the last 2 decades (e.g., Tenzer, Terjesen, & Harzing, 2017). This research originates in multiple fields (e.g., management, psychology, and communications). Specifically, scholarship on standard language primarily originates in management research, whereas scholarship on hybrid language primarily originates in sociolinguistics, medical, and psychology research. We bring together research across these fields to zoom in on the phenomenon of language-related misunderstanding.
By drawing on research across domains, our related goal is to spur new research avenues that will provide useful insights to manage this phenomenon in organizations (Cronin & George, 2023; Cronin, Stouten, & van Knippenberg, 2021). In doing so, our review builds on other reviews in organizational theory that consider alternate, distinct aspects of language, such as mechanisms that connect words to action (Lockwood, Giorgi, & Glynn, 2019), vocabularies (i.e., rhetoric, Loewenstein, Ocasio, & Jones, 2012), and sensemaking processes (e.g., Whittle, Vaara, & Maitlis, 2023). In addition, our review also expands on reviews in international business research that focus on the relationship between standard language diversity and the management of multinational organizations (e.g., Karhunen, Kankaanranta, Louhiala-Salminen, & Piekkari, 2018; Tenzer et al., 2017).
We organize our review along the following lines. First, we define the phenomenon of language-related misunderstanding, and describe how it manifests in organizations. Second, we delineate the different forms of language—standard and hybrid—and outline how they could result in language-related misunderstanding. Third, we review empirical findings for how language-related misunderstanding is associated with employees’ performance and attitudinal outcomes. In doing so, we identify theoretical mechanisms and boundary conditions that underlie the relationship between language-related misunderstanding and focal employee outcomes. Through this exercise, we outline a model of language-related misunderstanding at the workplace. Fourth, we delineate the theoretical implications of the model and identify options for managers on how to traverse an increasingly treacherous organizational linguascape. Finally, we point out several broad areas to advance research on language-related misunderstanding.
Language-Related Misunderstanding at Work
Communication involves a sender who transmits information to one or more receivers (Berlo, 1960; Lin, Geng, & Whinston, 2005). This could be a supervisor (sender) providing instructions to a subordinate (individual receiver), or a team member (sender) requesting help from their work colleagues (multiple receivers). In transmitting this information, however, there can be two types of communication errors: errors of commission and omission (Levine et al., 2018; Spranca, Minsk, & Baron, 1991; Yeomans, Minson, Collins, Chen, & Gino, 2020). Errors of commission are intentional—the sender intentionally conveys wrong or unclear information to the receiver (e.g., lying during a negotiation, Gaspar, Methasani, & Schweitzer, 2019). A vast body of research examines such purposeful acts of deception in communication where receivers could misinterpret senders’ communication because senders intentionally lie, deceive, or obfuscate information (e.g., Leavitt & Sluss, 2015; Shulman, 2011).
Conversely, errors of omission are unintentional, and occur because of two broad reasons: situational factors and information processing factors (Keysar, 2007; Volk et al., 2014). An example of situational factors is when the supervisor communicates information to a subordinate in a noisy factory environment; the subordinate is distracted by the noise and may not hear the instructions clearly (e.g., Van Lange, Ouwerkerk, & Tazelaar, 2002). In the communications literature, this is considered to be miscommunication: errors in communication that arise on account of situational factors such as background noise, disability (e.g., hearing loss), or illness (e.g., the receiver has a cold and is unable to hear clearly; Keysar, 2007). Miscommunication is a bidirectional phenomenon: Both senders and receivers of communication can perceive miscommunication on account of situational factors.
Errors of omission could also occur on account of informational processing factors (Volk et al., 2014). An example of information processing factors is when the supervisor communicates a work procedure to the subordinate; the subordinate considers this information to be technically complex and does not understand it. In the communications literature, this is considered as misunderstanding: errors in communication where the receiver erroneously interprets information from the speaker in a way that was not originally intended (Bosco, Bucciarelli, & Bara, 2006; Mauranen, 2006). Misunderstanding is unidirectional phenomenon: Only receivers of the communication perceive misunderstanding.
In our review, we focus on this phenomenon of misunderstanding: unintentional errors in verbal communication perceived by one or more receivers. Specifically, we focus on the misunderstanding that arises when receiver(s) fail to properly interpret the sender's message due to the form of language used to convey the information (Mauranen, 2006). For example, a subordinate may not understand a supervisor's non-native accent (one form of language that we discuss later) and thus complete a work task incorrectly. In this scenario, the supervisor did not intend to confuse the subordinate. Furthermore, the subordinate misunderstood the communication because of the supervisor's non-native accent, and not because the content of the message itself was unclear. That is, language-related misunderstanding does not pertain to the content of the communication but instead pertains to the form of language used to communicate the content. Put simply, language-related misunderstanding is unintentional error in comprehension by receivers because of the form of language used by senders to verbally communicate the message.
Language-related misunderstanding is currently not studied as an independent construct (although, as we discuss subsequently, it is possible to do so). Instead, language-sensitive organizational research discusses language-related misunderstanding as a phenomenon that manifests across a range of organizational settings. Scholars infer that language-related misunderstanding has occurred based on how the language used in organizations impacts employees’ outcomes (e.g., Hinds, Neeley, & Cramton, 2014; Tenzer, Pudelko, & Zellmer-Bruhn, 2021). That is, adverse employee outcomes on account of workplace language are indicative of language-related misunderstanding.
Scope of the Review
We took several steps to identify relevant papers on language-related misunderstanding following best practices in sample selection (e.g., Hiebl, 2023) when conducting literature reviews (Simsek, Fox, & Heavey, 2023). First, we only included studies that focused on language-related misunderstanding. Thus, we did not consider studies that explored overt and purposeful attempts to obscure information flows or deceive and manipulate others using language (Aronsson, 1991; Oesch, 2016; Scott-Phillips, 2006). As such, we excluded articles on lying (DePaulo, Kashy, Kirkendol, Wyer, & Epstein, 1996), linguistic framing (Fausey & Boroditsky, 2010), cheap talk (Farrell & Rabin, 1996; Washburn & Bromiley, 2014; Whittington, Yakis-Douglas, & Ahn, 2016), deception (Larcker & Zakolyukina, 2012; Oesch, 2016), doublespeak (e.g., Walker et al., 2021), obfuscation (Li, 2008), argot (e.g., Halliday, 1976), and workplace ostracism (Robinson, O’Reilly, & Wang, 2013). Second, we only included studies that explored the effects of standard or hybrid language on verbal misunderstanding at work. This is because written communication can result in language-related misunderstanding for reasons that do not pertain to the forms of language (e.g., typographical, legibility of the text, etc.). In addition, some forms of language that result in verbal misunderstanding do not pertain to written communication (e.g., non-native accent). Thus, we excluded articles that focused on written communication (e.g., Brown, Anicich, & Galinsky, 2020). Third, we excluded studies that examined individual differences in the use of the forms of language but did not consider their relationship to employees’ work outcomes. For example, Rodriguez-Fornells, Kramer, Lorenzo-Seva, Festman, and Münte (2012) examined individual differences in code-switching; however, this work does not inform how code-switching might result in language-related misunderstanding and subsequently influence employees’ work outcomes. Fourth, in addition to including articles from management (e.g., human resource management, organizational behavior, international business, safety management), we included articles from applied psychology and communication, where related language research is conducted.
We prepared a list of 48 keywords related to the different forms of language (i.e., standard language, code-switching, jargon, non-native accent, slang, company speak, etc.) that appeared in research on language-related misunderstanding. Based on the criteria we outlined above, we searched for articles using these keywords in the following databases: ABI/INFORM, PsychINFO, and Scopus. This process yielded a total of 2,824 articles across the different databases. Using our inclusion criteria, the first and third authors then reviewed each article for relevance. We removed the vast majority of the articles because they were not empirical (e.g., book reviews, commentaries, editorials) or because they did not focus on language-related misunderstanding at work. For instance, many articles discussed the prevalence of written jargon (and not the verbal use of jargon) or jargon among professional groups (e.g., scientists) without elaborating on its effects. We also considered additional hybrid forms of language (e.g., slang, company speak). However, there were fewer than 10 articles for each of these other forms of language and few included empirical findings. As such, we did not consider these forms in the review. We do, however, include these forms of language in the discussion.
Based on these inclusion criteria, we identified 116 articles across four forms of language: standard language, and three hybrid forms of language, non-native accent, code-switching, and jargon. As an additional check, we inspected the references of all identified articles and examined the Google Scholar pages of 10 noted scholars in the field to ensure that their recent work was included in our list. Through this process, we identified an additional six articles. For each of the forms of language, there were at least 15 articles that we could include in the review. Our review is thus based on 122 articles that span four forms of language: standard language (48), non-native accents (44), code-switching (15), and jargon (15). Please see the Online Supplement S1 for details about these studies.
Forms of Language
As French philosopher Étienne Bonnot de Condillac observed, “every science requires a special language because every science has its own ideas” (as cited in Braudel, 1982, p. 234). An unfortunate consequence of this specialness is that the definitions for the different forms of language are overly complex. To redress this, we endeavored to formulate straightforward definitions that captured the conceptual essence of each form of language. For reference, we have also included the formal definitions of each form of language in the Online Supplement S2. Additionally, to clarify how each form of language has been operationalized in prior work, Online Supplement S2 includes examples of its use as a survey measure and as an experimental manipulation.
Standard Language
Standard language is language that has undergone substantial codification in terms of its grammar, pronunciation, and vocabulary, and is sanctioned by relevant institutions such as regulatory agencies, linguistic and academic institutions (e.g., Académie Française), and other conventional disseminators of information such as news media organizations (e.g., the British Broadcasting Corporation [BBC], Michalski & Śliwa, 2021). That is, standard language has formal language codes and stable norms. Although standard language periodically evolves, these changes are more incremental in nature and are widely disseminated. For instance, once the Associated Press highlighted that the term “the homeless” be replaced with “people without housing” this change was widely disseminated across news organizations and has spurred similar changes across political groups and regulatory agencies (e.g., Associated Press, 2020; Slayton, 2021).
Standard language relies on strong power bases or, consistent with the frequently used linguistic adage, “a [standard] language is a dialect with an army and a navy” (Bright, 1997: 469). That is, standard language draws its legitimacy from formal institutions with the intent to ease its adoption (e.g., Lippi-Green, 2012). Corporate language mandates—when organizations decree that all employees communicate through a single common language or lingua franca—are an illustration of the use of a standard language at the workplace (Neeley, 2017).
Organizational research on standard language, which is often more descriptive and qualitative (e.g., Neeley, 2013; Vaara, Tienari, Piekkari, & Säntti, 2005), addresses two broad lines of work. The first line of work explores employees’ responses to the organizational mandates of a corporate common language (e.g., Neeley, 2013, 2017). The second line of work explores how home-country employees and expatriates in multi-national organizations communicate given different levels of language fluency (e.g., Peltokorpi, 2015; Peltokorpi & Pudelko, 2021). Thus, both lines of work focus on language barriers—the difficulties employees face when communicating with others at work because they speak different standard languages, or because they speak the same standard language with varying levels of fluency (Harzing & Feely, 2008). Language-related misunderstanding arises on account of such standard language barriers.
Hybrid Language
Hybrid language is any informal language that differs substantively from codified standard language norms, and that lacks the institutional support of standard language (Dragojevic, Fasoli, Cramer, & Rakić, 2021). It arises when speakers modify standard language to fit their needs, and so it often differs substantially from standard language in terms of grammar, pronunciation, or vocabulary rules. Put simply, hybrid language is considered as what it is not (i.e., it is not standard language). Hybrid language has informal language codes and evolving norms. In this review we consider three hybrid forms of language: non-native accents, code-switching, and jargon.
Non-native accents
Accents are a distinctive manner of language pronunciation that is characteristic of a particular geographical or social group (e.g., Gluszek & Dovidio, 2010). By definition, “accent” is a highly imprecise construct because everyone speaks with some form of accent (Lippi-Green, 1994, 2012). Organizational research, however, primarily focuses on non-native accents. One way that listeners assess the “non-nativeness” of an accent is based on how distinct the accent is from the majority group (Hansen, 2020). Native accents are those used by the majority group in a focal region or social class; in contrast, non-native accents are those used by minority group members from different regions or social classes (e.g., Dragojevic et al., 2021). This distinction underlies why native accents are readily embraced—but non-native accents are not (Fuertes, Gottdiener, Martin, Gilbert, & Giles, 2012).
Language-related misunderstanding arises because receivers need to exert additional cognitive effort to understand accented speech, and this strains their ability to process information communicated by speakers (e.g., Dragojevic & Giles, 2016; Russo, Islam, & Koyuncu, 2017). Although this phenomenon could be bidirectional (i.e., it is likely also difficult for those with non-native accents to understand native accents), as noted above, organizational research has primarily focused on the misunderstanding that arises when speakers with non-native accents converse with receivers with native accents (Hideg, Shen, & Hancock, 2022).
Code-switching
Code-switching is the practice of alternating between two or more standard or hybrid languages during a conversation (e.g., Genesee, 1982; Wei, 2013). People code-switch to express themselves so that they are better understood (e.g., Blom & Gumperz, 1972; McCluney, Durkee, Smith, Robotham, & Lee, 2021). Code-switching can occur when speakers switch between standard languages (e.g., switch between English and Spanish), between hybrid languages (e.g., switch between using different accents), and also between standard and hybrid languages. For example, an employee who speaks Spanish could integrate Spanish and English in the same conversation when speaking with other bilingual project team members. Language-related misunderstanding arises when, in switching between standard languages or hybrid languages, speakers inadvertently obfuscate communication for receivers who may not comprehend one or more of the standard or hybrid languages being spoken (Hinds et al., 2014).
Jargon
Jargon includes the distinctive terms, words, or expressions that people of a given profession use in the course of their work. For example, “close the loop,” “circle back,” and so forth are jargon used in business (Cray, 2020). Jargon is generally acronym-laden (e.g., CHRO refers to Chief Human Resources Officer) and facilitates communication within a profession (e.g., law, engineering, medicine) by using unemotional, explicit, and precise terms (Hudson, 1978). The origins of jargon can often be traced to discrete events in professional life. These include expressions or portmanteaus to describe a novel situation (e.g., workaholic combines “work” with “alcoholic”), old language that is repurposed for a different use (e.g., wheelhouse, which originally referred to part of a boat used to shelter the person steering the ship to its current usage as reflecting a person's area of expertise), or expressions borrowed from another language (e.g., entrepreneur from French; Andersson & Trudgill, 1990). Language-related misunderstanding arises when jargon that is unfamiliar to people outside the focal professional group is used during work conversations (Grupp & Heider, 1975; Rakedzon, Segev, Chapnik, Yosef, & Baram-Tsabari, 2017).
Implications of Forms of Language for Language-Related Misunderstanding
There are three broad implications related to these forms of language, and their potential to spark language-related misunderstanding. First, the prevalence of hybrid language points to an important implication: rather than placing different forms of language into discrete categories, they could instead be considered to lie on a hybridity continuum (see Figure 1). For example, the symbol “#” was primarily used by information technology professionals to refer to specific pieces of information. It was then adopted to organize topics on social media (e.g., Twitter; LaFrance, 2014). Its contemporary use in several social movements has imbued it with a new meaning and has resulted in its inclusion in the Oxford English Dictionary—that is, it is formalized as standard language. This fluidity of language on a standard/hybrid continuum is also exemplified by the number of new words and terms that have emerged on account of COVID-19 (e.g., vaccine passport; Merriam Webster, 2021).
The Continuum of Forms of Language at Work
Standard language has undergone substantial codification, is sanctioned by relevant institutions, and is at one end of the continuum. Jargon is at the other end. Although jargon could be sanctioned by a professional body or an organization, it generally does not receive support beyond the specific professional body/organization in which it originates. Non-native accents and code-switching lie between the two ends of the continuum. Non-native accents utilize standard language and are thus closer to that end of the continuum. However, non-native accents are not sanctioned by relevant institutions; instead, relevant institutions emphasize how specific words should be pronounced in standard language (Dragojevic, 2018). In non-native accents, words could be pronounced differently than what is codified in standard language. Code-switching could involve switching between two standard and/or hybrid languages depending on the context. Because it provides speakers with the latitude to incorporate multiple forms of language, it is thus closer to the hybrid language end of the continuum.
Second, a common theme emerges across the forms of language: language-related misunderstanding is unintentional error in comprehension. That is, primarily, cognitive mechanisms underlie why language-related misunderstanding could occur. A key cognitive mechanism is processing fluency. Processing fluency is the ease or difficulty through which information is refined and interpreted by receiver(s) (Dragojevic & Giles, 2016). Processing an unfamiliar standard or hybrid language places a significant cognitive load on receivers because they must process both linguistic and task-relevant information, which strains working memory (Tenzer & Pudelko, 2016; Volk et al., 2014).
For standard language, receivers’ inability to comprehend the language being spoken by senders greatly increases their difficulty to process information (e.g., Harzing & Pudelko, 2014). Similarly, hybrid forms of language (non-native accents, code-switching, jargon) represent novel stimuli for receivers, and can hinder their processing fluency (Dragojevic & Giles, 2016). For instance, a study of Canadian participants revealed that it was more difficult to understand Mandarin-accented English speakers relative to both Canadian-accented and Australian-accented English speakers (Yu, Schertz, & Johnson, 2021). Relatedly, an Event-Related Potential study that measured the cerebral activity of native Spanish speakers who were exposed to native and non-native accented speech revealed that non-native accents interfered with the processing of positive emotion-related words such that participants’ reactions to positive words were slower at the electrophysiological level (Hatzidaki, Baus, & Costa, 2015). These findings illustrate how processing fluency of both standard and hybrid language can strain cognitive resources and give rise to language-related misunderstanding.
Third, different forms of language need not always result in misunderstanding. For instance, the global proliferation of professional jargon (e.g., the widely used term “synergize”) could enhance the flow of communication because employees in global teams could likely use the same jargon (Gaibrois, 2018). Similarly, code-switching may help employees with limited language abilities communicate with their work colleagues (Vigier & Spencer-Oatey, 2017). Even standard language barriers could offer advantages. Rakuten (a large Japanese e-commerce organization) is a famous example of when standard language barriers—through the enactment of a corporate English-language mandate—enabled the firm to draw on expertise across different geographical regions, improve the transmission of its organizational culture to subsidiaries, and facilitate entering new consumer markets (Neeley, 2017). We recognize these positive aspects associated with the different forms of language and, more broadly, with linguistic diversity. Our focus, however, is different: we identify how different forms of language could inadvertently become sources of misunderstanding, which then have potent effects on employee outcomes. 1
Review of Empirical Findings Related to Language-Related Misunderstanding
In a work interaction, a person may communicate with another person (e.g., a subordinate speaking with the boss) or a person may communicate with multiple people at the same time (e.g., a leader addressing work group members). The communications literature thus identifies two categories of receivers of information—single receivers and multiple receivers—who could misinterpret the information transmitted by the sender (Goffman, 1981). By single receivers, we refer to a solitary employee who fails to properly interpret a sender's verbally transmitted message due to the form of language being used to convey the information. By multiple receivers, we refer to two or more employees who fail to properly interpret a sender's verbally transmitted message due to the form of language being used. In accordance, in the section below, we organize findings for standard and hybrid language in these two categories.
Standard Language and Language-Related Misunderstanding: Effects on Single Receivers
Language-related misunderstanding arising from standard language can directly impact individual employees’ performance and job attitudes. For instance, in a study of global research and development teams operating in South Korea and Europe, employees’ productivity was severely hindered by their inability to engage in high quality communication due to existing language barriers between research collaborators (Hwang, 2013). Relatedly, in a qualitative study of foreign business school faculty from universities in Finland, Japan, Spain, and the United States, Pudelko and Tenzer (2019) found that standard language barriers resulted in misunderstanding; they observed that this was a cause for lower performance in research and teaching, which then impacted academic career success. In a longitudinal, quantitative study of an organization that switched its corporate language from Spanish to English, Reiche and Neeley (2019) found that employees who had a high self-efficacy trajectory (an increasing confidence in their ability to learn English) were more likely (relative to employees with a low self-efficacy trajectory) to intend to quit over a period of 2 years. Employees with a higher trajectory were apprehensive of being saddled with a higher workload (i.e., the greater requirements for English that they were capable of fulfilling), and thus preferred to quit (Reiche & Neeley, 2019).
Standard Language and Language-Related Misunderstanding: Effects on Multiple Receivers
Standard language barriers encourage employees with limited language proficiency to cluster and share information with similar others (i.e., colleagues who also speak a language that is different from the corporate language; Lauring & Klitmøller, 2015). Harzing and Pudelko (2014) found that the lack of shared standard language resulted in lower levels of verbal communication. It also increased the prevalence of parallel information networks where managers preferred to contact colleagues who shared the same standard language as opposed to the appropriate person in the organizational hierarchy. In general, standard language barriers could create asymmetrical information structures—distinct from the formal organizational hierarchy—that impede knowledge sharing, increase the time necessary to translate documents and prepare for meetings, and adversely influence performance (Neeley & Dumas, 2016; Neeley et al., 2012; Presbitero, 2020).
Standard language can also impact job attitudes at the group level. For instance, in a qualitative study of United Kingdom and Indian employees of a financial services company, standard language barriers resulted in intergroup tensions (Cohen & El-Sawad, 2007). Fisher and Hutchings (2013) observed similar group processes in a study of Australian military advisers who trained soldiers during the Vietnam War: standard language barriers between military advisers and Vietnamese soldiers were related to lower levels of trustworthiness. Along similar lines, in a study of employees from two Austrian multinational companies that introduced English as the official corporate language, Aichhorn and Puck (2017a) report that standard language barriers resulted in increased mistrust between team members of different linguistic backgrounds. Finally, in a study of Spanish and English speakers across four service-sector organizations, Offermann, Matos, and DeGraaf (2014) found that standard language barriers resulted in feelings of exclusion and suspicion.
Hybrid Language and Language-Related Misunderstanding: Effects on Single Receivers
Hybrid language places a cognitive strain on receivers who are unfamiliar with the jargon, or the accent used to communicate (e.g., Carlson & McHenry, 2006). In an experiment, Lev-Ari, Ho, and Keysar (2018) examined the effects of non-native accented speech on memory. They found that compared to being interviewed by a native accented speaker, participants who were interviewed by a non-native accented speaker performed worse on a recall test of their own interview responses. Lev-Ari and Keysar (2010) found that participants experienced significant processing difficulty when listening to non-native accented speech, and they tended to view these speakers as less credible because their speech was more difficult to understand. Similarly, Dragojevic and Giles (2016) found that participants experienced difficulty processing non-native accented speech (compared to native accented speech); they then had higher negative affective reactions toward the speaker and perceived the speaker as lower in status. The downgrading of speakers with non-native accents appears to result from perceptions that these speakers are less fluent and more difficult to understand (Dragojevic & Giles, 2016). Related to the greater difficulty in understanding accented speech, patients with non-native accents were more likely to receive inaccurate diagnoses by medical professionals (Adams et al., 2016).
Similar effects operate for jargon. Findings from both medicine (Watermeyer, Thwala, & Beukes, 2021) and dentistry (Bowles, Sehgal, Santelmann, Pham, & Kohli, 2020) suggest that if interactions between medical professionals and patients involve a high level of jargon, they could result in misunderstanding and poorer patient outcomes. This is because jargon makes it difficult for patients to understand medical information (Schillinger, Bindman, Wang, Stewart, & Piette, 2004; Watermeyer et al., 2021). Patients may also feign familiarity with the terminology being used in order to appear more competent under the belief that doing so could reduce power differentials and knowledge asymmetries that are inherent in medical professional–patient interactions (Watermeyer et al., 2021). Conversely, medical professionals may underestimate the extent of their use of jargon with patients, and thus overestimate the effectiveness of their communication with patients (Howard, Jacobson, & Kripalani, 2013). Overall, the use of jargon in medical professional–patient interactions is associated with lower perceptions of medical care quality, lack of informed consent, and increased medical errors (e.g., Adams et al., 2016).
Hybrid Language and Language-Related Misunderstanding: Effects on Multiple Receivers
Hybrid language serves as an indicator of a person's social status and could spark in-group and out-group formation. Weber and Camerer (2003) asked pairs of students to create their own jargon to solve a complex task. The pair then merged with a different pair of students who had also created their own jargon. The performance of the merged team was then lower compared to the performance of the two premerged teams. This occurred primarily because differing jargon across the two teams created inefficiency in communication, and increased potential for misunderstanding. In a similar vein, when team members are code-switching, focal team members were only able to interpret a limited amount of information being transmitted (e.g., Aichhorn & Puck, 2017b), which resulted in less knowledge sharing behavior (Albana & Yeşiltaş, 2022; Hinds et al., 2014). Kulkarni (2015) observed that code-switching resulted in poor information exchange and an overall loss of understanding within the workgroup, and adversely affected knowledge sharing.
One possibility for these adverse effects is that code-switching influences trust formation (Vigier & Spencer-Oatey, 2017). In a study of multilingual teams operating across three multinational organizations, Tenzer, Pudelko, and Harzing (2014) observed that code-switching was generally perceived as undesirable and was characterized by receivers as a breach of trust. Employees characterized code-switching as both impolite and unfair because code-switchers were perceived to be using their ability to converse in multiple languages to their advantage.
A second possibility is that when work colleagues switch from the corporate language (e.g., English) to a language that focal employees are not fluent in (e.g., Danish), focal employees could perceive exclusion (Dotan-Eliaz, Sommer, & Rubin, 2009; Kulkarni, 2015). Focal employees could perceive such code-switching as linguistic ostracism; linguistic ostracism is associated with reduced commitment to the group (Hitlan, Kelly, Schepman, Schneider, & Zárate, 2006), higher suspicion and frustration with work colleagues (Kulkarni, 2015), and lower interpersonal citizenship behaviors and higher interpersonal counterproductive behaviors (Fiset & Bhave, 2021).
Theoretical Mechanisms
In the studies we reviewed we identified three primary pathways—relational, affective, and informational—through which language-related misunderstanding impacts employee outcomes.
Relational pathway
In organizations, employees are embedded in a network (Mehra, Dixon, Brass, & Robertson, 2006; Nahapiet, 2011). Networks are based on different types of ties (e.g., friendship, advice, etc.) that form the building blocks of workplace relationships (Methot, Rosado-Solomon, & Allen, 2018; Scott, 2007). Although unintentional, language-related misunderstanding could increase negative feelings toward work colleagues and decrease interpersonal liking, which could degrade existing ties (Labianca, 2014). This is because, in line with social identity theory (Tajfel, 1978), language is an important social category used to define ourselves and others (Bordia & Bordia, 2015; Giles & Johnson, 1981). The use of unfamiliar language can trigger social categorization processes (Giles & Johnson, 1981), which can trigger social identity-based faultlines and create language-based subgroups (e.g., Offermann et al., 2014). Social identity is thus integral to the relational pathway.
Language-based subgroup dynamics prevail for both standard and hybrid language (Ahmad & Barner-Rasmussen, 2019; Dwertmann & Kunze, 2021; Kulkarni, 2015). Specifically, standard language barriers can create in-groups and out-groups, and spark faultlines where people tend to coalesce around their own standard language subgroups (e.g., Danish and English, Tange & Lauring, 2009). For hybrid language, in a project team comprising members from different professions (e.g., accountants, lawyers, engineers), each group is likely to employ jargon specific to their profession even when referring to the same organizational problem, which could then result in misunderstanding (e.g., Peltokorpi & Pudelko, 2021). These “us” versus “them” dynamics based on language can result in language-related misunderstanding by creating relational discord within the group. Such intergroup disunity is associated with adverse employee outcomes, such as higher tension and conflict within the group (Hinds et al., 2014).
Affective pathway
Even though language-related misunderstanding is unintentional, it can be an unsettling experience and spark intense negative emotions such as anxiety (Aichhorn & Puck, 2017b), frustration (Dragojevic & Giles, 2016; Wang, Clegg, Gajewska-De Mattos, & Buckley, 2020), embarrassment (Kim, Roberson, Russo, & Briganti, 2019), and distress (Tenzer & Pudelko, 2015). Neeley and colleagues (2012) found that language-related misunderstanding resulting from standard language barriers can intensify existing tensions and result in emotional conflict. In addition, research on non-native accents demonstrates that non-native accents (compared to native accents) are more likely to spark negative emotions for receivers, which, in turn, adversely impacts receivers’ job attitudes (Dragojevic & Giles, 2016; Dragojevic, Giles, Beck, & Tatum, 2017; Roessel, Schoel, Zimmermann, & Stahlberg, 2019).
The salience of negative emotions could be heightened in situations when organizations institute a corporate standard language mandate that may advantage certain employees over others based on existing language capabilities (e.g., Neeley, 2013; Neeley & Dumas, 2016). For instance, a 2-year longitudinal study in a Chilean organization that instituted a standard language mandate revealed that employees’ negative affective reactions (e.g., distress, hostility, and nervousness) in response to the mandate increased over time (Reiche & Neeley, 2019). These findings illustrate that radical changes involving language could elicit strong negative emotions that could persist over time and highlights the potential long-term implications of language-related misunderstanding on employees’ job attitudes.
Informational pathway
An occurrence of language-related misunderstanding is indicative of poor information exchange between the sender and the receiver—this information loss could then affect receivers’ outcomes. That is, forms of language could affect the communication efficiency for workgroups and can give rise to information loss (Aichhorn & Puck, 2017b; Hinds et al., 2014). For instance, a study of Indian employees revealed that code-switching resulted in information loss, which adversely impacted group productivity and triggered negative emotions (e.g., suspicion and frustration, Kulkarni, 2015).
The salience of information loss could be heightened in situations where power and status imbalances exist between senders and receivers (e.g., Neeley, 2013; Vaara et al., 2005; Wang et al., 2020). When receivers experience language-related misunderstanding, they attempt to reassert their power by strategically sharing information with others who speak the same language (Ahmad, 2018). Because less information is transferred across language boundaries, this results in poor information exchange and increases information asymmetry (e.g., Tange & Lauring, 2009). These findings illustrate that language-related misunderstanding could result in information loss, and thereby strain receivers’ outcomes.
Boundary Conditions
We identify two broad categories of moderators—dispositional and demographic—that influence the relationship between language-related misunderstanding and employee outcomes. Dispositional moderators can be placed in two categories: efficacy-related dispositions (beliefs about successfully navigating language at work) and openness-related dispositions (acceptance and broad-mindedness as it pertains to language at work). 2 For efficacy-related dispositions, we observed that social self-efficacy (a person's perceived ability to successfully navigate new and existing relationships) buffers the relationship between perceptions of linguistic ostracism and creative performance such that the relationship is weaker when social-self efficacy is low than when social-self efficacy is high (Dotan-Eliaz et al., 2009). In addition, foreign language anxiety, or an apprehension to engage or speak in a foreign language, moderated the indirect effect of English language proficiency on willingness to accept an international assignment via openness to corporate globalization (Li, Zhao, & Han, 2020). Employees with foreign language anxiety were less likely to demonstrate a willingness to support their company's globalization plans, which subsequently reduced their willingness to accept future international assignments.
In terms of openness-related dispositions, cultural intelligence buffers the negative relationship between perceptions of linguistic ostracism and knowledge-hiding, such that that the relationship is weaker when cultural intelligence is high than when cultural intelligence is low (e.g., Albana & Yeşiltaş, 2022). Finally, uncertainty avoidance moderated the curvilinear relationship between perceptions of expatriate language proficiency and outgroup categorization such that the relationship was stronger when host country national uncertainty avoidance was high compared to when uncertainty avoidance was low (Peltokorpi & Pudelko, 2021).
In terms of demographic moderators, ethnicity, age, and language difficulty have been considered in prior work. Carlson and McHenry (2006: 71) asked human resource (HR) specialists to assess speakers who spoke in “African American Vernacular English (AAVE), Spanish-influenced English, and Asian-influenced English.” They found that if the speaker’s accent was minimally perceived (i.e., a barely perceptible non-native accent), their ethnicity did not affect HR specialists’ ratings of employability. However, if the accent was maximally perceived, employability ratings were lower regardless of the speakers’ ethnicity. Furthermore, there were statistically significant differences in employability ratings based on non-native accent type (Carlson & McHenry, 2006). Specifically, HR specialists rated Spanish-influenced English speakers higher on employability ratings compared to Asian-influenced English speakers, or AAVE speakers. Employees’ age is another moderator. Older employees, compared to their younger counterparts, are more likely to react negatively to instances where managers code-switch at work. Specifically, older employees were found to be more sensitive when managers used English inconsistently at work compared to their younger counterparts (Lauring & Selmer, 2013). This suggests that older employees are warier of situations in which they could experience language-related misunderstanding. Finally, Selmer and Lauring (2015) identified language difficulty as a moderator of the relationship between expatriate language abilities and sociocultural adjustment such that the relationship was stronger when the host country language complexity was high compared to when host country language complexity was low (The Foreign Service Institute of the U.S. Department of State provides an assessment of the degree of language difficulty). Thus, expatriates who developed strong language abilities in a standard language that is relatively difficulty to learn (e.g., Finnish) were more likely to report higher sociocultural adjustment compared to those who developed strong language abilities in a standard language that is relatively easier to learn (e.g., Norwegian).
A Model of Language-Related Misunderstanding at Work
In Figure 2, we depict a model that emerges from the preceding set of findings, which illustrates the phenomenon of language-related misunderstanding. A brief description of the model follows: senders communicate a message to receivers. Receivers, however, fail to interpret senders on account of the form of language (standard or hybrid) used by senders. This creates relational discord, sparks negative affect, or triggers information loss for receivers. These relational, affective, and informational factors then influence receivers’ performance and job attitudes. Dispositional (e.g., efficacy- and openness-related), demographic (e.g., age), and situational (e.g., noise) factors moderate these pathways. Although situational factors have been less examined in this body of work, we included them in the model because they represent an opportunity for future research (which we subsequently discuss).
A Model of Language-Related Misunderstanding at Work
Discussion
In this review, we delineate how standard and hybrid forms of language could result in unintentional error in comprehension. We clarify how such language-related misunderstanding could occur, and identify the multiple pathways through which it influences employees’ job attitudes and performance. We also identify important boundary conditions that influence these relationships. In doing so, our review points out the challenges that workplace language poses in an increasingly linguistically diverse workforce.
Theoretical Implications
The model of language-related misunderstanding at work that we identify stems from research from diverse fields: from medicine to management and from information sciences to international business (see Online Supplement S1). We draw connections between disparate bodies of research—endeavoring to achieve “synthesized coherence” (Locke & Golden-Biddle, 1997)—to spotlight the phenomenon of language-related misunderstanding. This is an essential conceptual advancement because language-related misunderstanding is currently inferred based on how language influences employees’ outcomes; that is, language-related misunderstanding is generally not investigated as an independent construct (an aspect that we discussed previously). We provide construct clarity by defining language-related misunderstanding, delineating its relationships with other constructs, and identifying relevant boundary conditions (Suddaby, 2010). In doing so, the model offers the building blocks for future empirical and conceptual work to refine the nomological network for language-related misunderstanding (Cronbach & Meehl, 1955).
We now turn to the broader theoretical implications offered by the model; the implications also point out associated limitations of the model that provide guidance for future research. To begin with, as the model indicates, language-related misunderstanding arises during a communication episode involving a sender and receiver(s). For language-related misunderstanding to occur, it thus requires the presence of at least two people. In our effort for parsimony, however, we did not incorporate the role of size (i.e., the number of senders involved) in the model. For instance, two bilingual speakers of English and Danish could be switching between the two languages, and this could result in language-related misunderstanding for other member(s) of their team who only speak English (e.g., Tenzer et al., 2021). If the number of senders increases from two to three (or an even higher number), then other factors (beyond language-related misunderstanding) may also come to the fore. This is because larger groups encounter greater communication difficulties (e.g., Staats, Milkman, & Fox, 2012). Thus, for instance, receivers who experience language-related misunderstanding could construe that senders are intentionally excluding them from the conversation (i.e., experience it as a form of workplace ostracism; Robinson et al., 2013). This brings up another potential wrinkle: although language-related misunderstanding constitutes unintentional errors in transmission, larger group size (i.e., more senders) could change receiver(s)’ attributions of its intentionality. Future refinements of the model could thus incorporate attributions of intentionality in concert with contingencies like group size.
We identify that primarily cognitive factors—specifically, processing fluency—underlie language-related misunderstanding. For instance, because jargon represents novel stimuli for receivers, it increases receivers’ cognitive burden and hinders their processing fluency, which then results in misunderstanding. It is conceivable that affective factors could also be at play here. That is, use of jargon that is unfamiliar to the receiver could elicit emotions such as anxiety, irritation, or even anger (Burt & Reagans, 2022). Thus, language-related misunderstanding could also have affective roots. As we reason, however, when receivers hear jargon, they utilize their cognitive capacities to first classify whether it is familiar or not; affective reactions based on (un)familiarity would then be secondary processes. For this reason, we suggest that cognitive processes are the key mechanism that underlie language-related misunderstanding. Nevertheless, we acknowledge that it is challenging to distinguish between cognition and affect, even at the neurobiological level (Adolphs & Damasio, 2001). Empirical work, specifically at the within-person level, that can dissect the role of cognition and affect, could facilitate in refining the model (Dalal, Bhave, & Fiset, 2014).
It is possible to categorize a communication episode as an instance of language-related misunderstanding only after its occurrence; receivers may not be aware that they are experiencing language-related misunderstanding (e.g., Tenzer et al., 2014). In other words, the phenomenon of language-related misunderstanding is inferred based on its outcomes; adverse outcomes for receivers are indicative of language-related misunderstanding (e.g., Hinds et al., 2014; Tenzer et al., 2021). Scholars and practitioners may also wish, however, to predict the occurrence of language-related misunderstanding. To move from inference to prediction of language-related misunderstanding, would require clearer insights into its antecedents (Shmueli, 2010). In this regard, the model primarily points to how each form of language could result in misunderstanding. Future refinements to the model could therefore focus on whether some forms of language have a greater propensity to result in misunderstanding than others. Along similar lines, elucidating the interplay of multiple forms of language and their joint propensity to result in misunderstanding could also enhance our capabilities to predict this phenomenon.
Relatedly, we have not depicted the interconnections between the forms of language. This is in line with the papers we reviewed, which primarily focused on a single form of language. This is understandable as scholars have elected to isolate the effects of one form of language on specific employee outcomes. This approach, however, fails to consider organizations as “multilingual realities” (Brannen et al., 2014: 496) where standard and hybrid languages coexist. There are, however, notable exceptions where scholars have investigated the concurrence of multiple forms of language. For example, the British Broadcasting Corporation's (BBC) Arabic Service endeavored to create a unified professional jargon for its journalists that simultaneously met the needs of Standard Arabic (i.e., standard language) and Arabic dialect (i.e., hybrid language) speakers around the world (Michalski, & Śliwa, 2021). In doing so, however, the BBC sparked tensions among Arabic journalists from different countries by imposing Standard Arabic as the corporate language without prior consultation. Conversely, Gaibrois (2018) highlights how the use of multiple hybrid forms of language instead of a single standard language could result in language-related misunderstanding because receivers could feel excluded. These findings suggest that the interplay between two or more forms of language influences the occurrence of language-related misunderstanding.
Furthermore, we have not identified specific moderators, mechanisms, or outcomes pertaining to each form. For instance, each of the pathways (i.e., relational, affective, informational) could operate in isolation (or simultaneously) and shape how language-related misunderstanding influences employees’ performance and attitudinal outcomes. A study by Hinds and colleagues (2014) illustrates this aspect: relational (i.e., language subgroup identification) and affective (i.e., negative affective states) pathways operated together and resulted in heightened tensions and power contests between language subgroups. The dominance of one pathway over others may change based on the form of language. For example, if a receiver does not know specific jargon, information exchange will be poor and indicate the saliency of the information pathway. If a receiver struggles to follow a non-native accent, however, the receiver could experience negative emotions (e.g., frustration) with the sender, and indicate the saliency of the affective pathway. In addition to the relative strengths of the pathways, for a specific pathway one target could be more relevant than another. For instance, in the aforementioned examples, it is possible that receivers are also frustrated when they hear jargon; this frustration, however, could be self-directed (because receivers are irked by their personal unawareness of jargon). However, as discussed above, receivers’ frustration on hearing non-native accents is likely to be directed to senders (i.e., other-directed). For the different forms of language, additional empirical studies are essential to refine the relative strengths of these mechanisms and the directionality in terms of target.
In the review, we primarily delineated findings related to demographic and dispositional moderators. One reason for the dearth of situational moderators is because of consistent findings for focal relationships for some forms of language (e.g., non-native accents; Hideg et al., 2022). However, situational moderators could be relevant, and occur across the dyadic, team, and organizational levels. At the dyadic level, the extent to which senders’ and receivers’ work are connected (i.e., their task interdependence; Morgeson & Humphrey, 2006) could impact the relationship between language-related misunderstanding and receivers’ outcomes. At the team level, if members of multilingual teams feel free to speak up when language-related misunderstanding occurs (i.e., perceive psychological safety; Edmondson, 1999), its effects on receivers’ outcomes could be mitigated (e.g., Nurmi & Koroma, 2020). At the organizational level, diversity climate could be a relevant situational moderator. Previous work on diversity climate suggests that when organizations explicitly value diversity in their policies, practices, and procedures, social categorization processes are dampened; the likelihood of mitigating the effects of language-related misunderstanding on receivers’ performance and attitudinal outcomes is then higher (e.g., Gonzalez & DeNisi, 2009).
Practical Implications
Managing language concerns at work is complex. Organizations benefit from linguistic diversity (e.g., improving customer service: Holmqvist, Van Vaerenbergh, & Grönroos, 2017; facilitating geographical expansion: Neeley, 2017), but also need to be cognizant that language could inadvertently result in misunderstanding. Because findings on language-related misunderstanding have resided across disciplines (e.g., Adams et al., 2016; Dragojevic & Giles, 2016), specific implications for managers to navigate the organizational linguascape are diffuse. We draw on these disparate bodies of work, and cluster our recommendations into four areas: language management interventions, training, leadership, and employee interpersonal competencies. Broadly, these recommendations target the relational, affective, and informational pathways in the model.
Language management interventions
To mitigate language-related misunderstanding, one intervention organizations often utilize is to implement a common corporate language; English is the most popular choice (Feely & Harzing, 2003). Research suggests that if organizations are considering a language mandate, they should develop a language management strategy (Conway, Anicich, & Galinsky, 2021; Neeley, 2017; Neeley & Kaplan, 2014). When organizations have not adopted an inclusive and proactive language management approach, it has resulted in difficulties to transition to a common corporate language (Neeley, 2017; Sanden, 2016, 2020). Key elements of a language management strategy include that organizations determine the existing linguistic competencies of their workforce, and then allocate appropriate resources to address linguistic competency gaps (Marschan-Piekkari, Welch, & Welch, 1999).
Some examples of resources include ensuring that all important messages are communicated both verbally and in writing. This is to help employees who experience issues with verbal communication to process relevant information on their own time and/or access other tools at their disposal (e.g., translation software; e.g., Harzing et al., 2011; Neeley, 2015; Tenzer & Pudelko, 2017). In addition, organizations can offer translation services for employees (Piekkari, Tietze, & Koskinen, 2020; Piekkari, Welch, Welch, Peltonen, & Vesa, 2013) and ensure that corporate jargon, acronyms, and other terminology is defined and readily available for all organizational members (e.g., through the corporate intranet). Provision of such resources decrease the likelihood of poor information exchange. To coordinate these efforts, organizations could empower a specific department (e.g., diversity or corporate communications) for this purpose. Multinational organizations, or organizations that grapple with complex language concerns, could also consider designating a chief language officer (Marschan-Piekkari et al., 1999; Steyaert et al., 2011).
Training
Training is another intervention that is often suggested to mitigate language-related misunderstanding. For instance, to help minimize standard language barriers, organizations could offer training that targets the cognitive mechanisms that underlie language-related misunderstanding (Tenzer et al., 2021). As an illustration, training programs geared toward learning a specific language to improve interactions with host country nationals (Peltokorpi & Pudelko, 2021) could serve to improve overall language processing fluency and reduce the cognitive burden on receivers.
To help reduce language-related misunderstanding, other scholars suggest training to boost empathy and engage in perspective-taking (Edwards, Bybee, Frost, Harvey, & Navarro, 2017; Neeley et al., 2012). Such training programs serve to increase liking toward workgroup members who combine standard and hybrid forms of language (Kim et al., 2019; Xie, Liu, & Jaeger, 2021) and help employees celebrate and appreciate the benefits of workplace language diversity (Hoever, Van Knippenberg, Van Ginkel, & Barkema, 2012). For example, exposure to a specific non-native accent (even for a few minutes) could help comprehension in subsequent interactions with other non-native accented speakers with that accent (Xie et al., 2021).
Leadership
Leaders of linguistically diverse teams have an important part to play in facilitating communication (Boies, Fiset, & Gill, 2015) and reducing language-related misunderstanding. For instance, Tenzer and Pudelko (2015) suggest that leaders encourage redundancy in workgroup communication to address informational deficiencies. Redundancy could be accomplished by adjusting discourse (e.g., double-checking mutual understanding), language (e.g., adopting simplified language), and media (e.g., non-verbal communication: Bonaccio, O’Reilly, O'Sullivan, & Chiocchio, 2016). Along these lines, leaders can encourage workgroup members to engage in continuous comprehension checks and seek clarifications without any fear of reprisal (Aichhorn & Puck, 2017a; Leonardi, Neeley, & Gerber, 2012). In addition to these adjustments to daily communication, to address language-related misunderstanding, leaders could encourage metacommunication (i.e., discussions around communication practices) as a way of aligning workgroup discussions (Kim et al., 2019; Tenzer et al., 2014).
Employee interpersonal competencies
Given the saliency of interpersonal interactions at work (Bhave & Lefter, 2018), employees’ interpersonal competencies, particularly for those working in linguistically diverse teams, are crucial for mitigating the effects of language-related misunderstanding. Displaying empathy, situational awareness, and halting or slowing down conversations to ensure that all group members are on the same page and are comprehending what is taking place could serve to reduce the impact of language-related misunderstanding (Chen, Blount, & Sanchez-Burks, 2004; Neeley, 2013; Neeley & Dumas, 2016). Additionally, employees could minimize the effects of language-related misunderstanding through translanguaging. Translanguaging is a method of communication repair that involves employees drawing upon their entire linguistic repertoire (of both standard and hybrid languages) to facilitate communication (Otheguy, Garcia, & Reid, 2015). In a study of bilingual Chinese engineers, Du and Zhou (2022) found that employees who engaged in translanguaging were better able to convey their ideas to their colleagues, which improved their overall productivity. Enhancing such interpersonal competencies could help minimize language-related misunderstanding and improve overall workplace communication. These interpersonal competencies could also function as dispositional moderators that impact the relationship between language-related misunderstanding and receivers’ outcomes.
Directions for Future Research
We detail three broad realms for future research: (1) the operationalization of language-related misunderstanding; (2) other forms of language within an organizational linguascape; and (3) the interplay between language-related misunderstanding and other markers of identity. Furthermore, in Table 1, we delineate additional questions pertaining to language-related misunderstanding.
Research Questions Related to Language-Related Misunderstanding
aEfficacy-related.
bOpenness-related.
Operationalizing language-related misunderstanding and increasing conceptual clarity
To begin with, developing a scale to assess language-related misunderstanding is opportune. This scale could assess perceptions of unintentional misinterpretation of verbal communication (from the perspective of the receiver) via either standard or hybrid language. A scale could also facilitate identifying base rates of this phenomenon and clarify the patterns in these rates across standard and hybrid languages.
The phenomenon of language-related misunderstanding focuses on instances when the senders’ use of standard and hybrid language can unintentionally trigger misunderstanding for receiver(s). This, however, does not provide an indication of the intent perceived by receiver(s). That is, receivers could consider that the sender intentionally spoke in a language that they did not understand. Attributions of harmful intent—from the standpoint of receivers of communication—could underlie language-related misunderstanding. One could argue that standard language is less susceptible to attributions of harmful intent because of formal language codes and stable norms that minimize the likelihood of misinterpretation. For example, receivers could consider that senders who consistently speak their mother tongue are doing so because they are more comfortable in that language (i.e., not attribute any ill intent). An alternate view, however, is that employees speaking in their mother tongue—and not the corporate language—are intentionally choosing to flout organizational norms (i.e., attribute ill intent). Understanding such attributions of intentionality is even more complex for hybrid languages. This is because of the relative fluidity of language codes and evolving nature of norms for hybrid languages. Overall, investigating base rates and attributions of intentionality will aid in further refining the conceptual underpinnings of language-related misunderstanding.
Language-related misunderstanding within an organizational linguascape
There are other forms of language prevailing in the linguascape, and their connections with standard language (and the other hybrid forms of language) deserve research attention. One such form is slang. Slang is a form of hybrid language, which is used to build solidarity within a social group that does not necessarily involve professional membership (Agha, 2015). Slang is generally viewed as an informal way to communicate that could serve to build stronger interpersonal connections with work colleagues; its use, however, could also create tensions with those who view it as disrespectful or difficult to understand because it denotes a clear “irreverence or even the rejection of formal conventions” (Roth-Gordon, 2020: 1). That is, slang serves to easily identify ingroup members from outgroup members, and so it could result in language-related misunderstanding, especially for outgroup members. For example, older employees view Gen Z and Millennials as poor communicators because of their fondness for using slang (Deal et al., 2010; Schroth, 2019).
Company speak is another hybrid form of language. A mix of standard language, jargon, and slang could give rise to “company speak”: the language used internally in an organization (de Vecchi, 2014; Logemann & Piekkari, 2015). Because company speak is unique to each organization, it could result in language-related misunderstanding, especially for newcomers. Company speak, however, could also reflect newcomers’ identification with the organization (Aichhorn & Puck, 2017a; Welch, Welch, & Piekkari, 2005). Overall, forms of language are interrelated, yet highly variable, constructs that can emerge, unify, and hybridize over time (Makoni & Pennycook, 2012), and investigating their interplay will be essential to better clarify the phenomenon of language-related misunderstanding.
One area that is likely to have a transformational impact on the organizational linguascape is the Metaverse. The Metaverse is a digitally immersive world where users can interact, play games, and engage in activities in a similar manner as they would in the real world (Needleman, 2021). In the Metaverse, people can assume a digital avatar that acts as a virtual representation of their identity to communicate with one another. Considered by many to be a foundational shift in how humans communicate, organizations are beginning to test the functionality of these digitally immersive online environments (e.g., Needleman & Dill, 2022). For example, organizations including Meta, Roblox, and Microsoft are experimenting with holding meetings, interviews, and industry events on these platforms (Baszucki, 2021; Lanxon, 2021). Recently, Meta has announced plans to create a universal speech translator powered by artificial intelligence to facilitate speech translation in real time between anyone on their platform, regardless of language (Vincent, 2022). In this context, it will be possible that employees will be able to use their own voice, or speak in one common “digital accent,” which could conceivably decrease language-related misunderstanding. Digital accents, however, represent an identity threat because they could deindividualize employees (Scott, 2007). Research examining tradeoffs of language-related misunderstanding versus language-related identity threats will be helpful in guiding transitions to this new frontier in the linguascape.
Language-related misunderstanding and markers of identity
Language is an important social category in determining social identity (Bordia & Bordia, 2015; Giles & Johnson, 1981). For instance, even among young children, language markers appear to play a more important role than racial markers when it comes to selecting friends, such that children are more likely to consider those from other racial backgrounds but who share the same accent as their friends compared to those from the same racial background but who speak using a non-native accent (Kinzler, Shutts, Dejesus, & Spelke, 2009). However, language could also interact with other markers of identity such as race, nationality, and sexual orientation. In addition to the possibility of language-related misunderstanding, the intersection of language with other markers of identity could result in stereotyping, prejudice, and discrimination. Non-native accents can activate negative stereotypes of the speakers (e.g., Hideg et al., 2022; Romero-Rivas, Morgan, & Collier, 2021). Speakers of non-native accented speech that deviates from the majority norm are often viewed as less credible (Lev-Ari & Keysar, 2010), less intelligent (Fuertes et al., 2012), less friendly (Dragojevic, 2020), less hirable (Carlson & McHenry, 2006), and are more likely to experience discrimination (Schinkel, Schouten, Kerpiclik, Van Den Putte, & Van Weert, 2019).
Accented speech could result in stereotypes with real-world implications. Across a series of studies Purnell, Idsardi, and Baugh (1999: 11) contacted landlords over the telephone for housing using “African American Vernacular English (AAVE), Chicano English (ChE), and Standard American English (SAE)” accents. Their results suggest that landlords engaged in housing discrimination against prospective tenants based on their accent. Moreover, landlords were able to identify a particular accent using only the word “hello,” which often was sufficient information to engage in discriminatory behavior. Relatedly, another study examined code-switching based on style of speech (vernacular; another hybrid form of language) and race—a phenomenon labeled as racial code-switching (McCluney et al., 2021). The authors found that both Black and White participants rated colleagues who racially code-switched higher on prestige (i.e., professionalism) compared to those who did not engage in racial code-switching. These findings connect to the dual-route approach to speech perception (Sumner, Kim, King, & McGowan, 2014), a model that delineates how receivers extract both linguistic (lexical meaning) and social (identity markers) information from speech. In that vein, Fasoli, Maass, Karniol, Antonio, and Sulpizio (2020) found that receivers interpreted gay- and straight-sounding speaker messages in a way that was consistent with identity marker stereotypes. Across four studies, receivers’ inferences about speakers’ voices were based on oversimplified and often stereotypical knowledge about the speakers’ identity (i.e., sexual orientation).
Overall, this body of work suggests that language (standard and hybrid) could suffuse with other identity markers, and result in stereotyping and prejudice (Hideg et al., 2022). As workplaces become increasingly diverse, it will be essential to discern when language is a source of unintentional occurrences of language-related misunderstanding, and when language interacts with other identity markers and is a source of intentional acts of discrimination. Insights into these distinctions will help to design appropriate organizational interventions to mitigate language-related misunderstanding.
Conclusion
In closing, Bob Dylan, the great singer-songwriter, once remarked “A mistake is to commit a misunderstanding” (Hentoff, 2004: 99). This trenchant observation applies to the many perils pertaining to language at work. By providing a “common language,” our review endeavors to spur conversations between scholars across disciplines and stimulate future research that could help minimize language-related misunderstanding at work and derive the benefits of linguistic diversity.
Supplemental Material
sj-docx-1-jom-10.1177_01492063231181651 - Supplemental material for The Effects of Language-Related Misunderstanding at Work
Supplemental material, sj-docx-1-jom-10.1177_01492063231181651 for The Effects of Language-Related Misunderstanding at Work by John Fiset, Devasheesh P. Bhave and Nilotpal Jha in Journal of Management
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