I Expertise Recognition: is there more to it than real competence?
Student name: Tullio Cavallero Student number: S2945959
Student e-mail: t.cavallero@student.rug.nl Thesis Supervisor: dr. Hille Bruns
Monday, 24th June 2019
Master Thesis Narrative Literature Review
MSc Business Administration – Change Management Faculty of Economics and Business
University of Groningen
II ABSTRACT
This thesis aimed at reviewing the extant literature available on the topic of expertise recognition.
The relevance of this study is heightened when considering that this the first literature review on the topic and due to the construct’s numerous antecedents and consequences. A narrative literature review was the methodological approach employed. By means of this seminal synopsis, it was possible to outline future opportunities for research as well as possible explanations behind the existing conflicts in results.
III INTRODUCTION
“An expert is someone who knows some of the worst mistakes that can be made in his subject, and how to avoid them.”
-Werner Heisenberg
How do we develop a perception that somebody is an expert? What factors affect this process of expertise recognition? The answer to these questions is far from evident. To begin with, a general definition of expertise recognition does not exist. On one hand, many studies refer to expertise recognition as developing an awareness of someone’s expertise (Littlepage & Mueller, 1997;
Littlepage, Robison & Reddington, 1997; Littlepage, Schmidt, Whisler & Frost, 1995; Littlepage &
Silbiger, 1992). On the other, an important research stream has focused on expertise recognition purely through the lenses of transactive memory theory (Wegner, 1987). Here it was defined as the condition necessary for the development of a transactive memory system (Gupta & Hollingshead, 2010), i.e. “a group information-processing system” (Wegner, 1987, p. 191).
In this literature review, I intend expertise recognition as an individual’s awareness of someone else’s expertise because this is the most comprehensive of the conceptualizations. This conceptualization has the benefit of allowing the inclusion of the results obtained through studies that employed the transactive memory approach, which cannot be said reversely. In fact, the transactive memory interpretation is limiting by assuming that the judgement takes place in a group of other experts. Because someone that is not an expert can also develop an awareness that an individual is an expert, it is not possible to extend the results of the first stream to the transactive memory one.
Understanding how individuals evaluate someone as an expert is crucial. In fact, recognition of expertise ties to better group performance (Littlepage, Robison & Reddington, 1997; Littlepage &
Silbiger, 1992) and recognized experts obtain more influence (Littlepage & Mueller, 1997; Littlepage, Schmidt, Whisler & Frost, 1995). This is related to the notion that the level of expertise of a decision- maker heavily influences the quality of decisions (Malhotra, Lee & Khurana, 2007). Research also found that the recognition of a leader’s competence increases group compliance (Price & Garland, 1981) and the leader’s influence (Knight & Weiss, 1980). The importance of understanding expertise recognition is highlighted when considering that this evaluation is affected by numerous biases, such as, for example, culture (Bazarova & Yuan, 2013; Yuan, Bazarova, Fulk & Zhang, 2013).
IV This only begins to hint at the density of factors that affect the process by which people become aware of someone else’s expertise. Research in this field has investigated and focused on the effect of a number of influences on the recognition of expertise, such as gender (Joshi, 2014;
Thomas-Hunt & Phillips, 2004), cultural backgrounds of those involved (Bazarova & Yuan, 2013;
Yuan, Bazarova, Fulk & Zhang, 2013), medium of communication (Bazarova & Yuan, 2013), group factors (Baumann & Bonner, 2004; Littlepage & Silbiger, 1992) and expertise expectations (Baumann
& Bonner, 2004), among others. As can be noted from this brief introduction, a plethora of variables were found to have an effect on the recognition of expertise.
Additionally, we still lack a full understanding on the topic of expertise recognition, since unresolved conflicts are present within the complexity of factors that affect this process. For instance, research noted that talkativeness, confidence and dominance in group settings were related to perceived expertise, whereas actual expertise was unrelated to the recognition of expertise (Littlepage, Schmidt, Whisler & Frost, 1995). In contrast, other results suggested that talkativeness, confidence and dominance were not related to a perception of expertise by group members, whereas actual expertise was (Yuan, Bazarova, Fulk & Zhang, 2013). Thus, it is necessary to identify these discrepancies as well as opportunities for future research that may shed light on the matter.
For these reasons, I seek to synthesize the hitherto developed literature in order to identify an answer to the following research question:
“What does the literature on expertise recognition look like?”
Having a seminal summary of the literature available on the process of expertise recognition would be useful for academic purposes. Firstly, this is because, to the best of my knowledge, no one has reviewed this research stream. This means that future researchers who want to approach this field of inquiry do not have access to a synthesized foundation of research to build upon. An overview of the extant literature enables to identify divergences and conflicts in this academic stream, which leads to recommendations for future research. In addition, having a comprehensive view of the literature allows to find possible blind spots that have not been examined thus far. In reviewing the literature, I only include peer-reviewed articles from journals of multiple disciplines. These were obtained through the online databases of Web of Science and Google Scholar.
V METHODOLOGY
This literature review adopts a narrative style. While some authors argue that the researcher should provide criticism of the articles that he or she includes in a narrative review (Depoy & Gitlin, 1993;
Gastel & Day, 2016), others claim that this is not a necessary condition for narrative overviews of literature (Helewa & Walker, 2000). In this review, I provide criticism whenever I could clearly identify weak areas in the literature that I review. In addition, a comprehensive guide on what should be included and excluded in a narrative literature review and other similar guidelines do not exist thus far (Ferrari, 2015; Slavin, 1995), which allows for a certain degree of freedom in this endeavor. Whilst this is the biggest benefit of performing this type of research, it also subjects the whole process to an inevitable evaluative bias and, consequently, a narrative literature review does not offer the same degree of replicability as a systematic review.
I performed the research tasks on two academic databases - Web of Science and Google Scholar. The choice of utilizing two databases leverages the variation in results that one faces when search terms are inserted. First of all, Web of Science allows for the refinement of the queries through filters such as number of times articles were cited, date of publication and relevance vis-à- vis the search terms. In addition, it also allows users to select a discipline (e.g. Management, Psychology, Business, etc.) and the institution of origin. On the other hand, Google Scholar is comprehensive as it spans a number of sources, such as articles, theses and books. It does not offer as many filtering criteria as Web of Science and the reliability of the publishers needs to be double- checked. However, it allows the user to choose the year of publication and indicates how many times a publication was cited as well as cross-references.
I performed this narrative literature review through different rounds of queries. I found the relevant articles through the utilization of the following key search terms: expertise, expert,
perception, recognition, assessment, evaluation, skill, competence, perceived expertise, group expertise, team expertise. These key terms were utilized in isolation as well as in combination. As I performed numerous searches and iteratively added articles to the review, I looked for these terms within the titles of the publications as well as in their key terms. I originally focused on business and organization journals before extending the research to the subjects of psychology and
communication. After having identified an initial set of articles, I used a snowballing approach to find more of them. Therefore, as I progressed through additional articles, I iteratively updated the searching process with new key terms.
VI The articles were only included in the research if they fit certain inclusion criteria. First of all, the literature needed to come from peer-reviewed journals. Secondly, only articles written in English were included. Third, I only integrated articles that were published in the last forty years. I thought this was necessary in order not to miss out on any important publications, especially because a literature review on expertise recognition, to the best of my knowledge, had not yet been performed. Moreover, I employed an interdisciplinary source of journals because the topic of expertise recognition has been analyzed in a diversity of settings.
On the basis of my findings, I crystallized the key topics that emerged. In essence, my process followed the method proffered by Wolfswinkel, Furtmueller and Wilderom (2013), except that I did not specifically classify the codes as open, axial or selective and I rather let them evolve naturally as I found more comprehensive and progressively higher-level themes. Examples of these are culture, gender, personality traits, influence, group performance. The first round or step in the analysis of the literature was that of identifying and gathering a bulk of articles to sort through.
Then, I tentatively sorted these articles according to overarching concepts that I inductively
discovered. In the second phase, I scouted for new key terms and research going through the articles that were referenced in the publications that I initially selected. Once a new key item was identified, I performed additional literature search, updated the overarching concepts that I identified in the first phase and sorted the articles in newly crystallized themes.
This iterative process continued until I reached a level of saturation and no new key terms or articles emerged. At this point, the third phase started: I finalized the overarching concepts identified in the first two stages. Then, I conclusively assigned the articles and publications that I have found to these categories. The last phase of literature analysis included assessing the articles and their findings, as well as providing an overview of the pbulications and their most critical insights. As a final note, a couple of limitations are present in this research. I was not able to gather every article on the topic of expertise recognition as a consequence of access limitations, i.e. paid journals that the University of Groningen I had no subscription to. Further, I did not include recent statistical and IT-based approaches to expertise recognition but instead decided to focus on the human aspect not to dilute the narrative that arose and given my lack of knowledge required to assess the methodologies of these types of studies. The next section of this thesis will treat the actual review of the literature, which is organized in two categories - antecedents and consequences of expertise recognition.
VII LITERATURE REVIEW
One of the first things a reader may notice as they start reviewing the academic literature on the recognition of expertise, is that the concept has been described in numerous ways. Some streams of research refer to “recognition of expertise” (Baumann & Bonner, 2004; Littlepage & Mueller, 1997;
Littlepage, Robison & Reddington, 1997; Littlepage, Schmidt, Whisler & Frost, 1995; Joshi, 2014), others speak of “attribution of task-expertise” (Bunderson, 2003), “expertise perceptions” (Thomas- Hunt & Phillips, 2004), or “expertise judgement” (Liao, Bazarova & Yuan, 2018; Yuan, Liao &
Bazarova, 2019), just to name a few. Regardless, all these terms point to the same idea, i.e. the process by which people’s expertise is recognized by others. The multiplicity of terminological choices underlines the fervor that has been present in this conceptual area as well as the need to consolidate what has been so far achieved.
Amongst these streams, Transactive Memory Theory (Wegner, 1987) has guided ample research on this topic. It identifies expertise recognition as one of the foundational elements at the individual level of analysis through which transactive memory systems are created. This theory encompasses organization- and team-level knowledge systems (Anand, Manz & Glick, 1998; Brandon
& Hollingshead, 2004) and, therefore, acknowledges expertise recognition as a concept with multi- level outcomes and roots. In addition, the research which was not performed through transactive memory theory also corroborate this notion by having identified both individual and collective factors that correlate with expertise recognition. Examples of this notion are studies that tie
expertise recognition both with personal influence, an individual level consequence, (Bottger, 1984;
Bunderson, 2003) and group performance (Littlepage, Robison & Reddington, 1997). Because of the acknowledgement of the multi-level nature of the construct, I also choose to categorize my findings along the dimensions of:
- antecedent vs consequences;
- individual vs collective level of analysis.
ANTECEDENTS TO EXPERTISE RECOGNITION Individual level of analysis
As already highlighted by the Transactive Memory Theory (Wegner, 1987), one of the most important aspects inherent in the process of expertise recognition is that of communication.
Consequently, a lot of research has focused on this aspect. The overall insight from this line of research is that individuals influence the recognition of their expertise by means of how much they
VIII communicate and by engaging into specific types of communication, although an interaction of other factors is also present.
First of all, recognition of expertise was found to be positively correlated with talkativeness of the individuals involved, at least among a sample of Americans (Bottger, 1984; Littlepage,
Schmidt, Whisler & Frost, 1995; Littlepage & Mueller, 1997). This means that the more an individual speaks up, the likelier it is that their expertise will be recognized. Similar research claims that dominance and confidence of the individuals are positively related with the recognition of their expertise (Littlepage, Schmidt, Whisler & Frost, 1995), which intuitively makes sense in association with the results found with talkativeness. This entails that individuals that are dominant and confident in their communication are more likely to be recognized as experts.
However, there exist conflicting findings in regards to these characteristics. A study claims that talkativeness, confidence and dominance are unrelated to expertise recognition (Yuan,
Bazarova, Fulk & Zhang, 2013), asserting therefore that these communicative cues will not increase the odds that an individual will have their expertise recognized. Although this study differs by also including individuals with a Chinese cultural background, which at first glance could explain the conflicting results, this does not seem to be the reason for the discrepancy. In fact, the extent to which individuals speak up was positively correlated with expertise recognition in other studies that also used American and Chinese participants (Bazarova & Yuan, 2013; Li, Yuan, Bazarova & Bell, 2017).
A very recent study (Yuan, Liao & Bazarova, 2019) concluded that certain communication cues function cross-culturally. With again an intercultural sample of Americans and Chinese,
researchers found that confidence, tenseness, conversational control and relation- and task-oriented communication are universal communicative cues employed in the recognition of expertise.
Tangibly, an individual is more likely to be recognized for their expertise if they engage in respectful communication as well as if they intellectually contribute to the task. On the other hand, being nervous reduces the likelihood of expertise recognition. Interestingly, although conversational control was described similarly to dominance and talkativeness, Chinese participants also relied on it to recognize expertise. The conflict in results with those of Yuan, Bazarova, Fulk and Zhang (2013) might be due to the fact that these studies used different items to measure this construct.
IX Although a certain degree of overlap is clearly present in the way people from different cultures recognize expertise, differences also exist. Considering that recognition of expertise is a subjective process, it makes intuitive sense that cultural stereotypes and biases have an effect.
For instance, Chinese individuals rely more on relation-oriented communication to recognize
expertise, compared to Westerners (Yuan, Liao & Bazarova, 2019). Notably, it seems that people use different cues to judge individuals from other cultures compared to in-groups: western individuals hinge relatively more on tenseness and conversation control to judge Chinese peers, whereas Chinese participants used task-oriented communication for people of both cultural backgrounds (Yuan, Liao & Bazarova, 2019).
Another communicative cue for expertise recognition is the usage of influence tactics, which positively correlates with the recognition of the expertise held by the individual who is using them (Littlepage & Mueller, 1997). Although the study that concluded this only employed a sample of American college students, this suggests that individuals that employ tactics such as manipulation, bullying, coalitions and using reason are more likely to be recognized as experts. Moreover, in the same fashion as previous research, task-oriented communication was multiple times found to be positively correlated with expertise recognition (Treem & Leonardi, 2017; Yuan, Bazarova, Fulk &
Zhang, 2013). In particular, Treem and Leonardi’s study (2017) provided a unique example of this relationship since they actively manipulated the extent to which the participants engaged in task- oriented communication. In this case this took place in the form of advice-seeking, aimed at
ensuring that their self-perceived expertise be recognized. In addition, they also discovered that the degree to which an individual engages in communal communication, i.e. communication that
happens in shared repositories or social networking sites, also correlates with expertise recognition.
This last finding suggests that talkativeness is important not only in a face-to-face setting, but also in digital interactions. This only begins to hint at the complexity of factors that affect
expertise recognition by means of communication. For example, research found that communicative accommodation, which is the practice of changing one’s linguistic style to fit someone else’s, is negatively correlated with recognition of expertise (Liao, Bazarova & Yuan, 2018). What this means, is that people who copy someone else’s terminologies and words are less likely to be recognized as an expert. This effect is stronger for computer-mediated communication, whereas in face-to-face settings this relationship is mediated by perceived task-oriented communication and perceived influence. Communicative accommodation is particularly strong in computer-mediated
communication likely due to the fact that it might be more noticeable textually compared to orally.
X This is not the only way in which word choice affects expertise recognition. In a written and digital context, researchers found that the utilization of long words as well as the length of the messages have a positive effect on expertise recognition. In addition, the linguistic choice of psychological distancing, i.e. writing in third person, is also used as a cue to recognize expertise (Toma & D’angelo, 2015). On the other hand, negations seem to be negatively correlated with expertise recognition. Because this finding was obtained in a written context, it is to be seen whether these cues also apply in face-to-face dynamics, or whether the salience of written text is the reason behind this attribution.
Furthermore, speaking up was found to act as a mediator for the relationship between language proficiency on expertise recognition (Li, Yuan, Bazarova & Bell, 2017). This means that someone who is more proficient in a language will speak up more and, by virtue of their
talkativeness, they are then more likely to be recognized as experts. If we take into account that speaking up is more likely for participants with low language proficiency in a computer-mediated interaction (Bazarova & Yuan, 2013), then it is even clearer that the context in which communication takes place is another important factor that affects the recognition of expertise. The last result in regards to communication relates to the usage of communication channels. In fact, individuals that employ a novel communication channel are more likely to have their expertise recognized. On the other hand, making mistakes with common communication methods has a negative effect on expertise recognition (Treem, 2013).
Moving past the question as to how and what types of communication lead to expertise recognition, an important issue is whether or not an individual’s actual expertise correlates with his or her recognition. In this case, too, there are conflicting findings. On one hand, some studies point to the fact that actual expertise of an individual is not correlated with its recognition (Hutzinger, 2014; Littlepage, Schmidt, Whisler & Frost, 1995; Yuan, Liao & Bazarova, 2019). Bonner (2003) claims that having knowledge and actual expertise are not enough by themselves to obtain expertise recognition. On the other, similar research with more optimistic results claims the opposite, i.e. that actual expertise positively correlates with its recognition (Bonner, 2004; Yuan, Bazarova, Fulk &
Zhang, 2013).
All of these studies had the same methodology, i.e. measuring students’ task-related expertise prior to assigning them to groups where they would have to complete the same task again and where their expertise would then be judged by the other participants. Intercultural effects are
XI also to be excluded as a cause for this divergence, since both sides to this question have intercultural samples backing their findings. It could be that the distribution of the sex among the samples was the culprit for these divergent results, but only two studies actually provide the data on this distribution (Hutzinger, 2014; Yuan, Bazarova, Fulk & Zhang, 2013). Because the study by Yuan and colleagues (2013) also split the groups in only women or only men, this is more likely to be the case, although it is not possible to draw conclusions. Nonetheless, Hutzinger (2014) found that gender of the evaluatee is correlated with expertise recognition, with women being assessed worse than men.
What this suggests is that women, purely by virtue of their sex, are less prone to be recognized as experts.
Other research corroborated this notion (Joshi, 2014; Thomas-Hunt & Phillips, 2004), adding nuance to the effects of gender: paradoxically, women with actual experience are even less likely to be recognized as experts than non-expert women, whereas men with actual expertise benefit from their expertise in the sense of being recognized for it (Thomas-Hunt & Phillips, 2004). Moreover, Joshi (2014) noted that individuals’ expertise recognition hinges more on the gender and gender identification of the evaluators than the characteristics of the evaluatee. Highly educated women and men were more likely to have their expertise recognized by women than by men. This means that women use educational status relatively more as a proxy for expertise. Moreover, gender identification moderated these effects, so that men who strongly identified with their gender rated expert women even less favorably. All in all, the question of whether actual expertise correlates with perceived expertise seems to be, by itself, overly simplistic if it does not take into account the interaction dynamics that are present between evaluatee and evaluator.
An interesting note is that an individual’s actual expertise correlates with perceived expertise in late stages of group work, whereas in the initial phase social status affects it (Hong, Zhang, Gang & Choi, 2017). What this seems to suggest is that as teams work together for a longer time, the cues that individuals use to recognize expertise evolve. This would corroborate
Bunderson’s (2003) claims, which I discuss in the upcoming section on collective-level antecedents.
Collective level of analysis
Clearly, factors at a collective level of analysis also affect the process by which expertise is
recognized in individuals. For instance, experience in working together enables a group to recognize expertise in the participants (Littlepage, Robison & Reddington, 1997). Ample research has focused on structural issues. Conflicting findings have been found in regards to group size, with a study
XII claiming it has a positive effect on expertise recognition (Littlepage & Silbiger, 1992) and another one claiming it does not help in predicting expertise recognition (Yuan, Bazarova, Fulk & Zhang, 2013). The difference in these results could be due to the different methodologies employed. For example, the latter study used an intercultural sample and made groups of three to four individuals, composed of either only men or only women. On the other hand, the study by Littlepage and Silbiger (1992) had group sizes of two or ten individuals. This suggests that higher variation in group size might be needed for the effect to be significant.
Node centrality, i.e. the degree to which an individual occupies a central position in a network, is another collective-level structural feature that has an impact on expertise recognition.
This means that someone that is centrally located in a network with other individuals is more likely to be recognized as an expert (Su, 2012), which makes sense intuitively. Because being centrally located in the network implies that an individual has relatively more connections to other
individuals, these will be able to recognize his or her expertise. The same study was able to conclude that an individual who performs work remotely is less likely to be perceived as an expert.
Nonetheless, the negative relationship between remote working and expertise recognition is moderated by the utilization of digital knowledge repositories (Su, 2012). This result suggests that one can make up for their physical absence by being more active on digital settings of interaction with other individuals.
It is interesting to note that another study (Treem & Leonardi, 2017) did not find a significant positive effect of working physically near to others. This was likely due to individuals being
positioned in the proximity of too little people for there to be any significant effect. Nevertheless, giving further backing to a network view of expertise recognition, another factor that aids this recognition is the presence of a third actor. Adding a third individual can, essentially, fill structural holes between two other individuals in the network by connecting them (Lee, Bachrach & Lewis, 2014). This result entails that a third actor improves expertise recognition by encouraging and improving information exchange.
Tying back to the previous discussion about communication as a critical factor affecting recognition of expertise, it was found that it also plays a role at the collective-level of analysis.
Results conclude that the more language proficiency is dispersed in a group, the less accurate the expertise of recognition will be (Li, Yuan, Bazarova & Bell, 2017). Similarly, other research found that expertise recognition is hindered when there is a lack of a shared syntax, so that the recognition will
XIII not be as accurate and there will be discrepant opinions across team members regarding who knows what (Kotlarsky, van den Hooff & Houtman, 2015). In general, it seems that large differentials in language skills or usage only confound the process of recognition.
Reversely, whereas language proficiency dispersion was found to negatively impact
expertise recognition, another study found that large dispersion in group members’ expertise levels led to a better recognition of expertise (Baumann & Bonner, 2004). This might be the case because large differentials in expertise formulate context-related cues that clearly allow to identify who is an expert by means of direct comparisons. In tangible terms, it is naturally easier to identify experts when contraposing them with very inexperienced individuals. The same research also concluded that expertise recognition was improved when the expectations of expertise distribution are consistent with its actual dispersion. Nonetheless, it is interesting to note that Treem and Leonardi (2017) did not find a relationship between the uniqueness or sharedness of expertise and its
consequent recognition. This is especially the case considering that previous research suggested that both the uniqueness of expertise (Austin, 2003) and the sharedness of it (Wittenbaum, Hubbell &
Zuckerman, 1999) are positively related to the recognition of an individual’s expertise.
The lack of results from the study by Treem and Leonardi (2017) might be due to the fact that the variance in expertise distribution within the sample was not big enough to find significant results. Moreover, the effect of other, practically more manipulatable group-level antecedents have also been investigated. These have particular relevance for practitioners since employers and companies have the possibility to directly influence them. For instance, research found that pay transparency in a group that is paid in accordance to performance positively affects expertise recognition (Belogolovsky, Bamberger, Alterman & Wagner, 2016). What this means is that individuals within groups will be better able to recognize the experts by using the data on pay as a proxy for expertise, so that individuals which are paid more are also more likely to be recognized as experts. Similarly, providing performance feedback to a group as well as shared training increase also increases the groups’ ability to recognize expertise (Liang, Moreland & Argote, 1995; Moreland
& Myaskovsky, 2000; Tajeddin, Safayeni, Connelly & Tasa, 2012).
So far it is clear that numerous contingencies are at play in regards to the utilization of cues and antecedents to expertise recognition. Bunderson (2003) classifies these cues into diffuse and specific status cues. Diffuse status cues rely on social characteristics such as gender and ethnic stereotypes, whereas specific cues are task-related. Clearly, the utilization of specific status cues
XIV predicts better the recognition of expertise. What the researcher found, was that in high-tenure groups and groups with low centralization, specific status cues are used more often, whereas in new teams and those with high levels of centralization, diffuse cues are more likely to be employed. This ties back to the previously mentioned research, where actual expertise was used as a cue in later stages of group work and social status in earlier ones (Hong, Zhang, Gang & Choi, 2017). In practice, individuals seem to become better with time at recognizing their groupmates’ expertise.
Just like communication provides collective-level antecedents, gender and cultural stereotypes also affect perception of expertise in a relational and group manner. In fact, when paired with someone of the opposite sex to perform a specific task, participants assumed their partner would be more expert in the subjects which fit their respective gender stereotype (Hollingshead & Fraidin, 2003). Similar effects were found in terms of cultural stereotypes.
Participants assumed that their partner would be more expert in the subjects that fit their cultural stereotype, while also rating themselves as more expert in those subjects that fit their own cultural stereotype (Yoon & Hollingshead, 2010). These results, when coupled with the previously mentioned results on expertise expectations (Baumann & Bonner, 2004), point to the idea that someone’s expertise is more likely to be recognized if the evaluator’s expectations, be it due to stereotypes or biases, are correct. Lastly, results concluded that male and female participants’ expertise recognition depended on the team’s gender composition so that teams dominated by a specific gender were more likely to recognize the expertise of participants of the predominant gender (Joshi, 2014). It is to be noted that expectations might have played a role here, since the study was performed in an industry historically dominated by men.
CONSEQUENCES OF EXPERTISE RECOGNITION Individual level of analysis
Research on expertise recognition, in terms of consequences relative to this attribution, has often noted that an individual that is recognized as an expert also obtains personal influence (Bottger, 1984; Bunderson, 2003; Hong, Zhang, Gang & Choi, 2017; Littlepage & Mueller, 1997; Littlepage, Schmidt, Whisler & Frost, 1995; Tajeddin, Safayeni, Connelly & Tasa, 2012). One of the main findings was that expertise recognition mediates the relationship between speaking up and personal
influence (Littlepage & Mueller, 1997; Littlepage, Schmidt, Whisler & Frost, 1995). Therefore, individuals that are more talkative are more likely to be recognized as experts, which then gives them more influence.
XV Nonetheless, there seem to exist related contingencies: on one hand, task conflict between group members positively influences the effect of expertise recognition on influence, whereas relationship conflict negatively affects this relationship (Hong, Zhang, Gang & Choi, 2017). This means that in situations in which there are intellectual disagreements about tasks that need to be performed, experts will obtain even more influence. On the other hand, emotional conflict between group members will relatively weaken the influence of an expert. The expert’s influence is also stronger in situations in which a great discrepancy between their proficiency and that of their group members is present (Tajeddin, Safayeni, Connelly & Tasa, 2012).
Personal influence is only one of the consequences that arise for an individual that is recognized as an expert. One of these is the fact that they will receive more information-seeking queries from those that judged them as an expert (Su & Contractor, 2011). Similarly, Baumann and Bonner (2004) note that expertise recognition leads to more deferral to the expert and that, by virtue of being recognized, their expertise is then also utilizable in practice. This result is corroborated by other research, which concluded that recognition of expertise is necessary to exercise said expertise as well as to maintain it and to obtain roles and functions that are usually not undertaken by non-experts (Bonner, 2003). Lastly, individuals that are recognized as experts also experience increased work performance through the mediation of job resourcefulness, i.e.
individuals’ ability to gather resources to overcome problems in work issues (Ho & Wong, 2009). This implies that by being recognized as experts, individuals can obtain more means to perform better, which then leads to improved performance. Thus, the importance of ensuring that individuals’
expertise is recognized becomes evident.
Collective level of analysis
When it comes to the collective level analysis, academics have mostly focused on the group
performance benefits that arise as a consequence to expertise recognition. Most streams agree that expertise recognition leads to improved group performance (Austin, 2003; Liang, Moreland &
Argote, 1995; Libby, Trotman & Zimmer, 1987; Littlepage, Robison & Reddington, 1997; Littlepage &
Silbiger, 1992; Li, Yuan, Bazarova & Bell, 2017; Moreland & Myaskovsky, 2000; Thomas-Hunt, Ogden
& Neale, 2003). Results by Thomas-Hunt and Phillips (2004) corroborate this notion by noting that because women are less likely to be recognized as experts, groups that have a woman expert perform worse than those with a man expert. Notably, results claim that groups with a higher proportion of women are better at recognizing and therefore utilizing the expertise of highly educated women and that, vice versa, groups with more men are better at leveraging men’s
XVI expertise (Joshi, 2014). Although these results were actually obtained through longitudinal data and not through short-tenured lab groups like most expertise recognition research, the future of inter- gender collaboration does not necessarily look grim. This is because, as mentioned previously, the sample employed might reduce the generalizability of the results, as it was derived from the engineering and scientific fields, which are historically male-dominated.
Interestingly, Yoon and Hollingshead (2010) found that, when dyad members are not able to communicate with each other, culture-based assumptions on expertise recognition actually lead to improved performance in intercultural dyads compared to dyads with members of the same culture.
Essentially this means that an unspoken usage of stereotypes to gauge each other’s expertise, when reciprocal, can mitigate the disadvantage that derives from not being able to know each other’s expertise. The absence of reliable cues seems to make individuals resort to simpler heuristics, similarly to Bunderson’s findings (2003). Some of the last results in terms group consequences are that expertise recognition leads to both the exchange of expertise among group members as well as its effective retrieval (Yuan, Carboni & Ehrlich, 2010; Yuan, Fulk, Monge & Contractor, 2010). This ties in with another finding that expertise recognition leads to more efficacious help-seeking from group members (Belogolovsky, Bamberger, Alterman & Wagner, 2016).
Finally, the following model captures the main variables that emerged from the review:
XVII To sum up, many different factors act as antecedents to expertise recognition and other consequences stem from this awareness. I noted that a lot of research has focused on individuals’
communication and on different communicative styles and channels as antecedents to expertise recognition, both on an individual as well as on a higher level of analysis. Furthermore, whereas gender directly impacts the recognition of expertise, culture seems to do so both directly and indirectly by means of moderating the relationship between communication and expertise recognition. Another important segment of research has focused on team-level structural antecedents, such as group size and experience, skill differentials and expectations.
When it comes to the consequences relative to the recognition of an individuals’ expertise, numerous studies focused on the increased amount of personal influence that an individual obtains as they are recognized for their expertise. On the other hand, on a collective level of analysis, ample research has determined that expertise recognition is critical in order to achieve higher levels of group performance. In fact, not being able to recognize and, therefore, utilize expertise due to gender-based biases was found to generally lead to lower performance. Clearly, visual constraints and the ideal of parsimony stand in the way of having a complete model that takes into account all the moderating and mediating variables. Nonetheless, this model captures the key factors and relationships from the literature review. All in all, it shows that research has been able to identify more factors that lead to expertise recognition compared to related consequences.
DISCUSSION AND FUTURE RESEARCH
In this section, I will, first of all, bring to light some complexities and interesting results that emerged as a consequence of the literature review. I highlight issues such as conflicting results and possible solutions and reasons behind these discrepancies. After having discussed these points, I then go on to provide recommendations and implications for further research.
In regards to contradicting findings, talkativeness was not always correlated with expertise recognition (Yuan, Bazarova, Fulk & Zhang, 2013). In this particular study the results might have been confounded by the utilization of an intercultural setting with both East Asian and Western participants: the former group tends not to relate talkativeness with competence and may even present a negative relationship. Other results, however, found that Chinese participants indeed associated conversational control with expertise (Yuan, Liao & Bazarova, 2019). Even though this construct is similar to talkativeness, the items used to measure it differed from those of the previous study, which could imply that the way it was conceptualized was better aligned with Chinese
expectations of competence.
XVIII In addition, studies disagree on the question as to whether actual expertise and real
expertise are correlated (Bonner, 2003; Bonner, 2004; Hong, Zhang, Gang & Choi, 2017; Hutzinger, 2014; Littlepage, Schmidt, Whisler & Frost, 1995; Yuan, Bazarova, Fulk & Zhang, 2013; Yuan, Liao &
Bazarova, 2019). The same problem is to be found with the issue of group size (Littlepage & Silbiger, 1992; Yuan, Bazarova, Fulk & Zhang, 2013), although the reason for this discrepancy likely lies in the variance of the group sizes used. Another interesting finding is that of Yoon and Hollingshead (2010).
They note that when dyads were not able to communicate with each other, culture-based
stereotypes helped increase performance through stereotyped expertise attributions. However, it is arguable whether this result has any concrete relevance in the world of business and organizations as communication is usually possible.
These contradictions give way for one of the defining findings of this literature review, i.e.
that expertise recognition seems to be a relational and contingent process that lacks, for the most, absolute predicting factors. For instance, gender, gender identification and culture of both the evaluated and the evaluator are involved in this process (Bazarova & Yuan, 2013; Hollingshead &
Fraidin, 2003; Hutzinger, 2014; Joshi, 2014; Thomas-Hunt & Phillips, 2004; Yoon & Hollingshead, 2010; Yuan, Liao & Bazarova, 2019). Additionally, other contingencies are also present, such as pay transparency (Belogolovsky, Bamberger, Alterman & Wagner, 2016), performance feedback
(Tajeddin, Safayeni, Connelly & Tasa, 2012) and group tenure (Bunderson, 2003; Hong, Zhang, Gang
& Choi, 2017; Littlepage, Robison & Reddington, 1997).
This last point raises a critical question regarding the methodologies of many of the papers that analyze expertise recognition. Due to practical considerations, clearly, most of the teams and individuals that were analyzed performed in short-tenured research groups. This means that the majority of studies are lab based. However, there are results that claim that higher group tenure leads to a better assessment via the utilization of more valid status cues (Bunderson, 2003; Hong, Zhang, Gang & Choi, 2017; Littlepage, Robison & Reddington, 1997). I doubt that the relationships which were discovered would still be present if the studies had been done in a longitudinal manner, which, although costly and impractical, would provide a better reflection of the way that individuals within organizations actually perform work together. In fact, if groups that have worked together for a longer time use different and more valid status, it remains to be seen if cues such as gender and culture still have a significant effect once individuals learn to work with each other.
XIX For this reason, future research should focus on researching high-tenure groups for different reasons. First of all, as mentioned, most literature has focused on short-lived groups, the dynamics of which seem to be inherently different. Secondly, in the realm of business and management, project groups tend to have longer-lives, so the result of such research would prove substantially more valid. Third, meticulously researching high-tenure groups would bring further evidence for the notion that different mechanisms are at play during different life-stages of group work. Future research should also study group composition in terms of culture of the participants. It seems that these two variables act to confound some of the results that were found thus-far, such as in the case of actual expertise.
Opportunities for research are, thus, to be found in examining the effects that derive from having different combinations of cultural background represented within future samples. So far, intercultural samples have only been composed of Americans and Chinese. It would be interesting to investigate whether using samples that have more than two cultures alter any of the results
obtained. It could be that inter-cultural groups are generally better at recognizing expertise due to an extinguishment of biases. Additionally, this means that new factors that are not present in single- culture groups might also emerge. For instance, research on influence tactics was also only
performed amongst Americans (Littlepage & Mueller, 1997). It would be interesting to further expand our understanding by investigating whether other cultures employ different types of
influence tactics as well as by examining whether these work in intercultural contexts. All in all, then, I consider further extending expertise recognition through the lenses of multicultural research as one of the most important opportunities.
Our understanding of language choices can also be further extended. Since Toma and D’angelo (2015) note that in a digital and written context the usage of long words and psychological distancing help the recognition of expertise, it would be interesting to find whether the usage of this type of jargon also has a significant effect in face-to-face interactions or whether the effect
disappears. Other research on the context in which communication takes place can also investigate the question as to whether creating an inviting atmosphere can mitigate the negative consequences of poor language proficiency (Li, Yuan, Bazarova & Bell, 2017). It might be that when individuals are invited to speak up that they are more likely to be talkative regardless of their proficiency, which would then lead to enhanced expertise recognition.
XX Comparatively speaking, consequences to expertise recognition have not been studied nearly as much as the antecedents. There are many potential areas worth investigating. For example, it would be interesting to see whether the expertise levels over time become shared or even more centralized among individuals as well as whether expertise recognition has any
complexities that relate to the motivation and emotional attitude of those involved. It could be, for example, that a group that fails to recognize its experts is not only less productive, but could also be less motivated as a whole. Another point worth researching is that of communication in the sphere of consequences. As I have noted, communication and its nuances are one of the strongest
antecedents to expertise recognition. Therefore, it would be interesting to see whether expertise recognition also leads to consequences in terms of communication. Perhaps the group would adopt a shared syntax or communication style that resembles that of their experts.
One final recommendation for future research lies in the utilization of a novel methodology of approaching the issue of expertise recognition. In fact, a case study among headhunting
companies would allow to further extend our understanding of expertise recognition by identifying what could be a radically different approach to it. Overall, there are many future avenues of research that stem from this literature review. To sum up, I would recommend academics to:
- focus on high-tenure groups;
- investigate the effect of actual expertise;
- further analyze cultural contingencies;
- provide more nuance to our understanding of language effects;
- expand our knowledge of consequences to expertise recognition.
CONCLUSION
In this thesis, I introduced the topic of expertise recognition as well as reviewed the extant
literature. After having classified it in themes, I, then, identified areas with conflicting results as well as idiosyncratic findings. I summed up my main findings in a conceptual model and defined the areas that have received the most attention from researchers. Then, I provided possible explanations for the conflicting findings that I identified and I finalized the thesis by defining possible future
directions for research.
ACKNOWLEDGMENTS
This thesis would not have been possible without the guidance of dr. Bruns who acted as my supervisor as well as without the support that I received from my peers throughout the process of writing the thesis.
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