Cultural diversity does not automatically improve teamwork. The crucial question is where the team’s information elaboration happens: across cultural boundaries, or mainly among people who already share a culture. Work teams are increasingly characterized by diverse cultural backgrounds, and cultural diversity holds the potential to enhance team performance through information elaboration: the exchange, discussion, and integration of task-relevant information.

The differentiated elaboration perspective distinguishes cross-culture information elaboration between culturally dissimilar members from same-culture information elaboration between culturally similar members. Using a multi-source, multi-wave study of 104 culturally diverse teams comprising 587 members, cross-culture elaboration was more strongly related to team performance than same-culture elaboration.

Team learning orientation predicted both forms of elaboration, and its indirect association with team performance was stronger through cross-culture elaboration. Team cultural diversity—member differences in their cultural backgrounds—has been argued to be a double-edged sword for team functioning.

On the one hand, it increases the available pool of information. Team diversity research has treated information elaboration as an undifferentiated team-level process, leaving unspecified whether elaboration occurs across or within cultural boundaries. To draw on team cultural diversity as an informational resource, teams need what is called cross-culture elaboration.

Cross-culture elaboration involves members with different cultural backgrounds, whereas same-culture elaboration is elaboration among members with the same cultural background. Prior research has focused on information elaboration of the team as a whole, implicitly assuming that more team-level information elaboration means more elaboration between members with different cultural backgrounds.

Comparable levels of team information elaboration may reflect substantially different patterns of interaction: elaboration may primarily connect members from different cultural backgrounds, occur mainly among culturally similar members, or reflect comparable levels of both.

An undifferentiated perspective on information elaboration ignores such variance among teams. Differentiating cross-culture and same-culture elaboration adds theoretical precision and predictive power to research on culturally diverse teams.

The Categorization-Elaboration Model holds that diversity benefits team performance to the extent that members exchange, discuss, and integrate the task-relevant information and perspectives that their differences provide. The primary mechanism through which team performance may benefit from cultural diversity is cross-culture elaboration, because information and perspectives associated with cultural differences need to be shared across cultural boundaries.

Same-culture elaboration is not said to be worthless, but it is not the primary process through which cultural diversity contributes to team performance. This recognition motivates the differentiated elaboration perspective. Team mean learning orientation—the tendency to focus on developing knowledge and competence in achievement settings—is proposed as highly relevant for stimulating cross-culture elaboration.

Learning orientation is associated with a stronger motivation to engage in information elaboration and with a lower inclination to rely on stereotypes that may invite intergroup bias. Higher mean learning orientation should promote both cross-culture and same-culture elaboration, but its emphasis on open-minded information processing makes it especially important for cross-culture elaboration.

Figure 1 presents the research model. The study focuses on both cross-culture and same-culture elaboration at the team level, as well as the associated team performance benefits. Elaboration is most valuable when members elaborate more on nonredundant perspectives, and culturally grounded differences are most likely to reside across cultural boundaries.

This diversity of perspectives and knowledge enables teams to consider problems from multiple angles and identify novel solutions, benefits that are less pronounced among culturally similar members. If elaboration occurs primarily within the same culture, culturally diverse knowledge remains compartmentalized rather than becoming a shared team resource.

Cross-culture elaboration, more than same-culture elaboration, is therefore key to translating team cultural diversity into team performance benefits. Cross-culture information elaboration and same-culture information elaboration are predicted to be positively related to team performance in culturally diverse teams.

Cross-culture information elaboration is predicted to have a stronger relationship with team performance than same-culture information elaboration. Cross-culture elaboration is more contingent than same-culture elaboration on the motivation to engage in effortful information processing and the tendency to look beyond cultural stereotypes.

Learning orientation concerns a focus on gaining knowledge and developing skills, and involves an open-mindedness in understanding diverse perspectives. This dual relevance to effortful processing and reduced stereotyping makes learning orientation particularly relevant in stimulating information elaboration, especially cross-culture elaboration.

Team learning orientation is examined as a compositional variable, an index of the team’s aggregated learning orientation. The team mean most adequately captures the extent to which the members of the team will behave in line with learning orientation. Cross-culture elaboration is predicted to be more strongly linked to team performance and more strongly influenced by learning orientation than same-culture elaboration.

The proposed mediation paths run from learning orientation to team performance via cross-culture elaboration and same-culture elaboration. Participants were second-year students enrolled in a Human Resource Management course at a large Dutch university, and students formed teams of five to six individuals.

The team assignment accounted for 40% of the final grade and required members to jointly address Human Resource challenges using problem analysis and evidence-based solutions. Over six weeks, teams engaged in frequent online and in-person meetings where all members actively participated in deliberating on task-related matters.

After this intensive collaborative process, all teams produced and submitted a team assignment evaluated by the course instructor, who was not one of the authors. Data were collected at two time points: immediately after teams were formed, and two weeks later.

The first survey included gender, age, cultural background, and learning orientation, while the second survey measured information elaboration using a round-robin design. Each team member rated their elaboration with any other team member. Two weeks after the second survey, all teams submitted assignments that were evaluated by the course instructor based on standard evaluation metrics.

A total of 1259 team members in 225 teams participated in the survey, with 1141 responses at Time 1 and 1043 responses at Time 2. Only teams with the structural possibility for both cross-culture elaboration and same-culture elaboration were included, and only teams with 100% response rates across two survey measures were included in the final sample.

Of the 225 participating teams, 86 were excluded for incomplete survey participation and 35 for not meeting the cultural diversity criterion, yielding a final analytic sample of 104 teams and 587 members. The average team size was 5.64, with 36% of teams having five members and 64% consisting of six members.

Information elaboration was measured with a social network measure based on the exchange, discussion, and integration of task-relevant information and perspectives. Members indicated how frequently they interacted with each team member when finding solutions or making decisions about the task in the past two weeks.

The interactions involved exchanging information about the task, discussing the implications of the information, and combining each other’s knowledge. Each other member was rated on a seven-point Likert scale ranging from almost never to almost always.

Team performance was measured using the team grade of the Human Resource Management assignment. The evaluation used standardized rubrics with problem identification weighted at 25% and feasible, specific solutions weighted at 75%. Each part was scored on a ten-point scale, and the final score was obtained by multiplying the scores by their respective weights.

The evaluation was conducted by an independent rater who was blind to the hypotheses, team demographic composition, and individual survey responses. The analysis used the PROCESS macro 4.3 in SPSS, with model 4, to test the hypotheses.

PROCESS estimated a parallel mediation model with team cross-culture and same-culture information elaboration as mediators. The parallel mediation model allowed statistical comparison of the indirect effects through the different mediators. Cross-culture elaboration was positively related to team performance, with a coefficient of point three four and a p-value of point zero zero one.

Same-culture elaboration was not related to team performance, with a coefficient of point zero five and a p-value of point five three. The difference between the effects was point two nine, with a 95% confidence interval from point zero four to point five four, and the difference was positive and significant.

Cross-culture elaboration therefore had a stronger positive effect on team performance than same-culture elaboration, in line with Hypothesis 1b. Learning orientation was positively related to cross-culture elaboration, with a coefficient of point nine six and a p-value of point zero zero two.

Learning orientation was also related to same-culture information elaboration, with a coefficient of point eight one and a p-value of point zero four five. These results supported the prediction that team learning orientation was positively related to both cross-culture and same-culture forms of elaboration.

The comparison of their strength was not significant, with a difference of point one five and a 95% confidence interval from negative point eight five to one point one five. The prediction that learning orientation would have a stronger effect on cross-culture elaboration was not supported.

In the team-performance columns, the cross-culture elaboration row shows a coefficient of point three four with two significance stars, while same-culture elaboration shows point zero five without stars. Adding these elaboration variables raises the reported R-squared from point zero five in Step One to point two one with three stars in Step Two.

The indirect effect through cross-culture elaboration was point three three, with a 95% confidence interval from point one zero to point six three, whereas the indirect effect through same-culture elaboration was point zero four, with a 95% confidence interval from negative point zero nine to point two three.

The difference between the indirect effects was point two nine, with a 95% confidence interval from point zero one to point six zero, and the difference was positive and significant. The hypothesis that the indirect effect through cross-culture elaboration was stronger than the indirect effect through same-culture elaboration was supported.

The study differentiates cross-culture information elaboration and same-culture information elaboration in research on culturally diverse teams. In diverse teams, cross-culture information elaboration was more strongly associated with team performance than same-culture information elaboration, while team mean learning orientation predicted both types of elaboration.

Member learning orientation had a stronger indirect effect on team performance via cross-culture information elaboration than via same-culture elaboration. Table Five contrasts general, or undifferentiated, elaboration practices with differentiated practices designed specifically for cross-cultural exchange.

The authors show how this changes team training, discussion structure, team composition, and assessment: instead of only encouraging knowledge sharing, teams deliberately seek perspectives across cultural subgroups and assess whether elaboration crosses cultural boundaries.

This matters because the differentiated elaboration perspective treats cultural diversity as requiring structures that make cross-cultural collaboration feasible. The first limitation is the adoption of student teams, chosen to ensure a high response rate across multiple waves of data collection.

Findings from student samples may not generalize to professional work teams, although a meta-analysis found no indication that findings diverge for student and non-student samples in team diversity research. In field settings, cultural differences may be more strongly associated with task-relevant differences in experiences, information, and perspectives than in the course-assignment context.

The informational resources associated with cultural diversity may therefore be greater in an organizational setting, which may mean that the study attenuated effect sizes and contributed to partial support for the hypotheses. The student teams were temporary, project-based groups rather than ongoing organizational teams with long histories, established routines, or hierarchical power dynamics.

The findings may generalize more accurately to short-term, agile teams and task forces rather than permanent departments, and future research should draw on field samples. In these diverse student teams, cross-culture elaboration was more strongly connected to performance than same-culture elaboration, and learning orientation helped through that cross-cultural pathway.

The implication is to assess not only how much teams discuss, but who is included.