In an era where the globe instantly connects at the click of a mouse, rapid technological advances have led to the adoption of global virtual teams (GVTs) that work beyond time, space, and culture (Kargina 2025; Zakaria & Muton 2022). Dynamism in the business environment and world crises such as the coronavirus disease 2019 (COVID-19) pandemic underscore the criticality of GVTs (Tavoletti et al. 2022, 2023; Zakaria & Muton 2022) as an alternative workplace collaborative setup.

Global virtual teams offer ample benefits for organisations for enhanced decision-making because of borderless knowledge transfer, innovation and increased access to a global pool of human resources that is responsive to rapid market pressures (Froese et al. 2025; Killingsworth, Xue & Liu 2016). Despite these benefits, GVTs experience performance challenges. Substantial challenges have been associated with the cultural diversity of team members (Kargina 2025). Thus, the interface between national cultural diversity of GVT members and team performance is an interesting debate in international human resource management literature (Adamovic 2018; Butler et al. 2018; Hoch & Dulebohn 2017) and the general international business field (Lippert & Dulewicz 2018). There is a continued need for further understanding of the effects of national culture on GVTs’ performance (Han & Beyerlein 2016; Lippert & Dulewicz 2018).

Understanding cultural diversity provides better opportunities in developing superior responses to international business challenges (Minkov & Hofstede 2012). International labour mobility for strategic and operational needs comes at high financial costs and complex immigration laws for firms. To mitigate the challenges, firms resort to blended approaches that include GVTs. Recognising the effects of cultural diversity in the GVTs therefore has practical implications for international firms. Multiple studies have shown that cultural diversity has a strong influence on organisational collaboration, such as leadership (Chutnik & Grzesik 2009; Hoch & Dulebohn 2017), team structure (Hoch & Dulebohn 2017; Zakaria, Amelinckx & Wilemon 2004), communication (Krawczyk-Bryłka 2016; Zakaria & Muton 2022), and processes (Lurey & Raisinghani 2001; Mockaitis, Rose & Zettinig 2012), ultimately affecting team outputs (Gilson et al. 2015).

Given that GVTs are contextually bound, norms, values and beliefs are inculcated in team members through societal institutions (Fong Boh, Nguyen & Xu 2013; Hilali & Benyahia 2026). How a nation’s values and practices affect performance in these inherently multinational, collaborative structures is an area worthy of investigation (Crowne 2020; Taras et al. 2019). This understanding can shed light on how best to manage work teams with cultural differences. However, GVT studies have relied on Hofstede’s cultural framework, leaving other approaches such as Global Leadership and Organisational Behaviour Effectiveness (GLOBE) dimensions underutilised. This study rises to the challenge and extends the GLOBE framework to GVTs to provide nuanced insights beyond commonly studied contexts (Nadeem & Sully de Luque 2020). The impetus for adopting the GLOBE framework stems from its distinctive conceptualisation of culture as values and practices (House et al. 2004) offering more robust theorising.

The objective of the article is to examine the effect of the GLOBE value dimensions on team performance using broad categories based on team processes.

Specifically, we explore the effect of:

The study contributes to diversity literature by applying the GLOBE-inspired theorising of cultural diversity. It extends literature by applying the GLOBE framework to GVT performance literature and providing nuanced insights into the mechanisms through which cultural diversity affects team performance. Practically, the study offers a framework for understanding dynamics of cultural variability in teams to improve collaborations and task execution.

To test the explanatory power of the variables in the study, hierarchical multiple regression analysis (MRA) was employed. Prior to interpreting the results of the MRA, several assumptions were evaluated. Stem-and-leaf plots and box plots indicated the presence of some outliers. The outliers were winsorised (Gignac 2016). This is a process of changing the outlier value to the nearest value that is not an outlier, resulting in no univariate outliers in the data.

The inspection of the normal probability plot of standardised residuals, as well as the scatterplot of standardised residuals against standardised predicted values, indicated that the assumptions of normality, linearity and homoscedasticity of residuals were met. However, the relatively low tolerances for some predictors implied that multicollinearity would interfere with the interpretation of the results. To address the potential problem of multicollinearity, the societal practice and societal value scores of the affected variables ([1] uncertainty avoidance, [2] institutional collectivism, [3] in-group collectivism, [4] power distance, [5] assertiveness, and [6] performance orientation) were combined for an outcome of single composite variables (Allen & Bennett 2012). To illustrate, the uncertainty avoidance societal practices score was combined with the uncertainty avoidance societal values score to yield a composite uncertainty avoidance score. The resulting score measures the specific cultural dimension. A cultural dimension is defined by the values and practices (Javidan et al. 2006), which the composite score accounts for. This resulted in improved tolerance levels, suggesting that the multicollinearity assumption has been met.

The Mahalanobis distance exceeded the χ² for degrees of freedom (df) = 16 (at α = 0.001) of 39.252 for any case in the data file, indicating that multivariate outliers were of concern. The multivariate outliers were identified and ignored because their measure of influence (Cook’s distance) was found to be extremely low (> 0.01). This indicates that the data points do not have undue influence on the regression model’s coefficients. There were no influential observations that skew the results.

After some variables were combined to form composite variables, 13 variables were left for further analysis. These include the dependent variable (team performance) and 12 independent variables. Table 2 presents the descriptive statistics for these variables (N = 254). The means for team diversity in the independent variables ranged from 0.12 (SD = 0.06) for human orientation societal values to 0.45 (SD = 0.08) for in-group collectivism. This indicates that the teams had low diversity in human orientation societal values while moderate diversity in the in-group collectivism dimension. The mean for team performance was 4.96 (SD = 0.94). This implies that team performance was above average with low team-performance dispersion.

Pearson’s correlation matrix was calculated to check for potential multicollinearity problems (see Table 3). The correlations were below the cut-off point of 0.7. This signifies that the scales have acceptable internal consistency and convergent validity. Specifically, the predictor variables are distinct from one another and provide unique information and shall not cause issues with inflated standard errors.

To test the hypothesis that cultural diversity can account for a significant proportion of the variance in GVT performance beyond that accounted for by team member age diversity and team size, a hierarchical MRA was employed.

In Step 1 of the hierarchical MRA, team size, average age of team members, average English score, and team age diversity accounted for a significant 5.5% of the variance in team performance, R² = 0.055, F (4, 249) = 3.64, p < 0.05. This implies that the control variables collectively explain 5.5% of the differences observed in GVT performance. The remaining 94.5% is explained by other factors not included in this step. The probability of these results happening by chance is less than 5%. Therefore, the control variables are authentic significant predictors of GVT performance. Model 1 shows that structural (team size and team age diversity) and demographic traits (age and English language skills) matter for GVT performance.

In Step 2, 12 cultural diversity variables were added to the regression equation and accounted for an additional 8.9% in GVT performance, ∆R² = 0.089, ∆F (12, 237) = 2.056, p < 0.05. This indicates that adding cultural diversity variables explained an additional 8.9% of the variance in GVT performance. Specifically, the 12 cultural diversity variables are responsible for about 9% of why some GVTs perform better than others. This is a statistically significant result. Overall, the results show that cultural diversity matters for GVT performance. After controlling for structural and demographic variables in Model 1, cultural diversity variables still have a measurable and meaningful effect on how well GVTs perform.

In combination, the 16 predictor variables explained 14.4% of the variance in GVT performance, R² = 0.144, adjusted R² = 0.087, F (16, 237) = 2.98, p < 0.05. By Cohen’s (2013) conventions, a combined effect of this magnitude can be considered ‘medium’ (f² = 0.168). The 16 variables successfully predict a statistically significant measure of GVT performance. However, the effect is weaker once adjusted for the larger number of independent variables. Overall, the regression model is statistically significant, implying that the model predicts GVT performance better than chance alone. The independent variables collectively account for 14.4% of the variance of GVT performance. This suggests that 85.6% of the variance is explained by other factors outside the model.

Unstandardised (B) and standardised (β) regression coefficients and squared semipartial (or ‘part’) correlations (sr²) for each predictor on each step of the hierarchical MRA are reported in Table 4. As seen in Table 4, the only significant cultural diversity predictor variables of GVT performance were uncertainty avoidance (sr² = 0.018) and in-group collectivism (sr² = 0.018). The results show a positive significant association between uncertainty avoidance diversity and GVT performance. This indicates that the more diverse the team make-up is in the uncertainty avoidance dimension, the better the GVTs’ performance. On the other hand, the results show a negative significant relationship between in-group collectivism diversity and GVT performance. This implies that the more diverse the team is on the in-group collectivism dimension, the poorer the GVTs’ performance would be. In other words, in-group collectivism diversity can hinder GVT performance.

While previous research has presented inconclusive effects of cultural diversity on team performance, the results of this study indicate that cultural diversity has a significant effect on GVTs’ performance. This is consistent with the optimistic perspective that advances the value of diversity (Mayo et al. 2017). This study is clear on the positive effect of cultural diversity on team performance, albeit with a medium explanatory power. While this study suggests a positive effect of cultural diversity on GVT performance, other studies have been inconclusive, as the direction of the effect could not be determined (Kankanhalli et al. 2006; Shachaf 2008). The issue of cultural diversity and performance continues to be a ‘black box’, especially because the current results suggest that there are other variables that have a larger influence on GVT performance than cultural diversity. For instance, Taras (2025) found that cultural diversity was less significant in influencing GVT performance as compared to institutional differences, a lack of informal communication, and competing project commitments. Trust has also been found to be a critical mechanism through which communication and collaboration influence performance in teams (Schreiber et al. 2025).

Specifically, GVTs’ performance was found to be positively associated with the heterogeneity in uncertainty avoidance, suggesting that GVTs that consist of individuals from cultures that prefer structure and orderliness and those from cultures that embrace uncertainty and thrive in unstructured situations are likely to perform better. In the setup of a GVT where there is a different understanding of accountability, varying values and practices, and even divergent communication styles (Hoch & Dulebohn 2017; Lippert & Dulewicz 2018), then such heterogeneity is likely to help the team to develop a balanced understanding and common practices that would benefit the team. Consistent with these results, high-performing GVTs have been found to be risk-averse (not leaving anything to chance when making decisions and taking time to consider all possible options, etc.), flexible in behaviour (change behaviour depending on who they interact with), communicate in a direct and precise way, use indirect language to avoid confrontation, etc. (Lippert & Dulewicz 2018). These characteristics are consistent with a heterogeneous team on the uncertainty avoidance dimension. Furthermore, Zakaria and Muton (2022) found that GVT members from high context cultures tend to switch their behaviours to accommodate effective collaboration and knowledge sharing with team members from other cultures. This cements the finding that heterogeneity in uncertainty avoidance is likely to positively influence GVT performance.

Another cultural dimension whose diversity was found to have a significant effect on GVT performance was in-group collectivism, albeit a negative effect. This implies that diversity in the in-group collectivism dimension is likely to reduce GVT performance. This is consistent with Mockaitis et al. (2012) who found that collectivist orientation was favourable for GVT performance as well as Lin, Standing and Liu’s (2008) conclusion that cohesion affected GVTs’ performance. Lippert and Dulewicz, (2018) also found high-performing GVTs to comprise members that are benevolent, put themselves in others’ shoes, and perceive their service as valuable to the team. These are characteristics consistent with in-group collectivism.

The purpose of this article was to understand the effect of cultural diversity on GVT performance. The study used GLOBE dimensions of culture. The results show that two cultural dimensions are likely to influence the performance of a GVT: (1) uncertainty avoidance and (2) in-group collectivism. However, the influence of these dimensions on GVT performance is not uniform.

Precisely, the more heterogeneous the teams were in the uncertainty avoidance dimension, the more likely the team was to perform better in their assigned task. This is not entirely surprising, considering that uncertainty avoidance is the extent to which members of a society seek orderliness, consistency, structure, and formalised procedures (House et al. 2004) and literature suggests that teams that perform well have a balance of these traits (Lippert & Dulewicz 2018). Therefore, in line with this finding, it is important for firms to have hybrid frameworks that offer a balance between highly structured functional standards and safe unstructured areas for innovation. A balanced framework provides stability of planned key performance areas to be achieved while allowing the team the space to determine how to achieve the targets within set limits. Team members who are high on uncertainty avoidance require psychological security to effectively contribute to the team without fear of making mistakes, which is offered by the documented standards, while members who are low on uncertainty avoidance creatively focus on how to achieve the end goal. Typically, members from societies that are low on uncertainty avoidance are given more room to explore; however, they are managed not to ‘over-explore’ through the set limits.

Lastly, in-group collectivism diversity was found to be negatively associated with GVT performance. This is also not surprising because in-group collectivism is the extent to which a society values cohesiveness, loyalty, and pride in the collective. Thus, if there is diversity in this dimension, then there will be little team cohesiveness, and members will not feel proud of being part of the collective. Literature has also suggested that collectivism enhances team performance (Lippert & Dulewicz 2018). Hence, following this finding, it is important to have a unified team. Deliberate management actions are required to align shared goals and individual responsibility to build a basis where team members feel collective responsibility for achieving team results. Specifically, each team member should understand the overarching purpose of the team and how each member’s role is dependent on the others for the team to achieve its purpose. Furthermore, each member should feel psychologically safe to contribute to debates and be vulnerable. Team members should be clear that healthy debates, tension, and diverse perspectives are necessary to enhance team performance.