Trust and knowledge sharing in diverse global virtual teams

TL;DR: Results showed that in GVTs, deep level diversity has a more significant relationship with team processes of mutual trust and knowledge sharing than visible functional level diversity, and this relationship is moderated by the collaborative capabilities of available technology and levels of interdependence of the task.

About: This article is published in Information & Management.The article was published on 2013-06-01 and is currently open access. It has received 259 citations till now. The article focuses on the topics: Knowledge sharing & Team effectiveness.

Summary

1. Introduction

• Global virtual teams (GVTs) are groups that (a) are identified by their organizations and group members as being a team; (b) are responsible for making and implementing decisions important to the organization's strategy [8]; (c) use technology-supported communication more than faceto-face communication; and (d) work and live in different countries.
• Technology has therefore become absolutely critical for GVTs in carrying out their basic team functions: communicating, decision-making, learning, collaborating, and managing knowledge.
• Challenges are caused by distance and time zone changes, by language and cultural differences, by adoption and implementation of technology, by member interaction, and by a lack of trust and shared understanding among the team members.
• Project failures have been reported and calls for better understanding of GVT problems have been made.
• Recent literature in GVT highlights the importance of relationship building, cohesion, and trust as processes that foster team effectiveness.

2.1. GVT diversity

• Considerable research has been conducted to understand the differences in the performance of diverse teams compared to their homogenous counterparts [5].
• Thus a growing body of research addresses the issues of improving collaboration between members of a GVT[20].
• Diversity poses both opportunities and threats and empirical findings about team outcomes and performance are mixed [11].
• Diversity due to demographic differences such as age, sex, or race, is termed surface level diversity, whereas diversity due to personal characteristics, such as idiosyncratic attitudes, values, and preferences are termed deep-level diversity [27].
• The authors know of no empirical research that exists to validate such relationships.

2.2. Mutual trust

• Trust, the positive and confident expectation of the behavior of another party, is a vital quality for effective virtual teams and online exchanges [19].
• Trust in a team context has been defined as the degree of confidence of team members in one another.
• For GVT, the risk of potential misunderstanding and mistrust is heightened [30].
• GVTs develop a “swift” form of trust but it is very fragile and temporal; however, trust amongst group members may be improved through social communication that complements rather than substitutes task communication.
• Trust and team performance are apparently positively correlated with effective communication among members.

2.3. Shared knowledge

• The intellectual power of a virtual team is in its diffused expertise and ability to blend different experiences to create shared knowledge.
• When individuals work within a GVT, they can utilize others’ knowledge as well as develop their own [9].
• The more effective their knowledge sharing, the better it they can perform their tasks [13].
• Shared knowledge in team settings occurs through joint training and by experience gained through problem-solving among members.
• When shared knowledge is incomplete, individuals’ interrelate less.

2.4. Collaborative technology

• The technology used by GVT is important, as media richness has been found to impact team effectiveness, efficiency, level of communication, relationships among team members, and team commitment [29].
• Effective ICT increases the positive impact of diversity and mitigates the negative effects of cultural diversity.
• Prior research has found that technology can improve inter personal processes like socialization [1] and reduce conflict.
• Recently Sarker et al. [25] developed a model of technology adoption by groups based on a valence perspective.
• Based on this, they proposed that group supportability may be assessed by determining how technology can increase parallelism, transparency, and sociality within the group.

2.5. Task interdependence

• This can be defined as the degree to which completing a task requires the interaction of team members.
• Several researchers have argued that the degree of task interdependence has a substantial effect on team processes and outcomes; it moderates the relationship between team diversity and team performance by influencing team member interaction and coordination.
• Recently, the focus has been on treating diversity as a single construct without understanding the various facets of diversity, and without looking at the effects of functional level and deep-level diversity.
• Much of the research has also ignored the effect of building relationships on trust and knowledge sharing among team members.
• Overall, research on GVT is fragmented and much of the focus has been on comparisons of traditional teams with GVTs.

3. Research model and hypotheses

• Given the inherently complex nature of GVT environment, the authors argue that GVT effectiveness, as a dependent variable, will increase with the development of mutual trust and knowledge sharing among the team members, which will be affected by diversity and moderated by task and collaborative features of the technology used.
• The authors examined two levels of diversity at the input level: functional diversity and deep-level diversity.
• At the process level, the relationship between mutual trust and knowledge sharing was considered.
• Task holds conventional teams together, while communication and collaborative technologies serve as additional bonds linking the members of a GVT [24].
• Specifically, diversity increases relationship and process conflicts.

H1b.

• Functional level diversity is negatively associated with knowledge sharing in GVTs.
• Deep level diversity is negatively associated with mutual trust in GVTs.

H1d.

• Deep level diversity is negatively associated with knowledge sharing in GVTs.
• Prior research suggests that task interdependence moderates the relationships between team inputs and processes.
• When task interdependence is high, team members depend on each other for expertise, information, and resources to complete a task.
• High levels of task interdependence force team members to work together closely, exchange information and resources, and further develop shared norms for effective team functioning.
• In a low task interdependence situation, however, team members tend to operate as individuals with less intense interaction and coordination, thereby reducing affective outcomes and increasing a potential for lack of trust and shared knowledge arising from member heterogeneity.

H2d.

• Task interdependence will moderate the relationship between GVT deep-level diversity and knowledge sharing in global virtual teams in that the relationship is weaker for teams with high levels of task interdependence, than teams with low level of task interdependence.
• An increase in electronic interaction between team members gradually affects the team's feelings and attitudes, leading to an increased sense of trust and belonging.
• Also, collaborative technologies encourage greater participation in two ways: first, they allow free exchange of communication without having to wait (parallel processing) and second, visual anonymity reduces inhibitions of minorities.
• Collaborative technology will moderate the relationship between GVT functional diversity and mutual trust in global virtual teams in that the relationship is weaker for teams with high levels of collaborative technology, than teams with low level of collaborative technology.

H3d.

• Collaborative technology will moderate the relationship between GVT deep-level diversity and knowledge sharing in global virtual teams in that the relationship is weaker for teams with high levels of collaborative technology, than teams with low level of collaborative technology.
• Trust plays a key role in effective information sharing, leading to mutual understanding in the team.
• Trust is an effective way to manage people who cannot meet face-to-face, and interact: members are then willing to open themselves to each other and cooperate to solve a problem.
• Trust is thus pivotal in GVTs in order to bridge the psychological distance between people who are culturally and geographically apart.

H4.

• Mutual trust is positively associated with knowledge sharing in GVTs.
• When team members have high levels of mutual trust, common goals, unified rewards, and knowledge sharing, they tend to agree on norms regarding work, and this promotes harmony and decreases interpersonal tensions [7].
• In the group working environment, trust is an important premise of successful group decision-making in terms of decision quality, satisfaction and utility.
• Like trust, knowledge sharing has a positively affect team performance.
• High levels of mutual trust will lead to an increase in GVT performance in diverse GVTs (mediating effects).

4.1. Data collection

• Hypotheses were tested using a field survey [18] because the authors found that it was necessary to obtain real world knowledge about GVTs.
• The inter-rater reliability can be assessed and, if convergence is demonstrated, a balanced perspective can be obtained by averaging informants’ perceptions.
• Thus, all items in their instrument/questionnaire were framed as applicable to informants rather than respondents and team-members evaluated their team rather than their own behavior or attitudes.
• Normal good practice was used in developing an instrument with desirable properties; IS research was surveyed to help in developing the questionnaire.
• Items that captured the domain and had high reliability were selected.

4.2. Pre-test

• The instrument was pre-tested in order to refine the items in terms of wording and conveying the overall meaning.
• Four graduate students, four faculty members, and two industry executives tested the instrument and, based on their recommendations, the instrument was refined.
• An important modification was the use of 7-point rather than a 5-point Likert scale to assess the responses.
• All the recommendations were considered and necessary changes were made.

4.3. Pilot study

• A pilot study was conducted using an online version of the instrument with software development teams in South Asia.
• A total of 11 teams representing 22 team members completed the online instrument.
• The average team size was 7 members and average team tenure was 5.3 months.
• Qualitative open-ended questions were collected from team members.
• Their wording, meaning, and understandability were discussed; some managers rewrote questions while others contacted the researchers for clarification.

4.4. Instrument

• The final instrument consisted of 38 items with responses measured on 7-point Likert scale; it was administered to various GVTs in several multi-national organizations.
• Table 1 presents the items, their definitions, some literature references, and the number of items.
• If the participating organization asked for it, they were to be provided with an executive report giving their results and how their teams compared to the sample.
• 13%, with R&D and management being 10%, also known as Others were in Engineering.
• The authors sample had members from 15 countries and some teams spanned 4 countries.

5. Results

• The survey scales were assessed for reliability, construct, convergent, and discriminant validity to ensure that they could be used to test their hypotheses.
• The ability to aggregate the individual level responses to provide a group level response was assessed using James Rwg(J) index, with ICC(1) and ICC(2).
• Once these were confirmed, hypotheses testing for moderator and mediator effects were conducted using Hierarchical Multiple Regression Analysis (HMRA).

5.1. Scale validity

• To assess the validity of the scales, a four-step approach was undertaken.
• Next, item-to-corrected total correlations were examined to assess its construct validity.
• Task interdependence was represented by three items with a single factor structure and factor loading ranging from 0.83 to 0.89.
• GVT effectiveness was represented by two constructs: GVT performance and GVT member satisfaction, but ultimately represented a single factor structure with loadings ranging from 0.56 to 0.86.
• Then the authors examined the convergent and discriminant validity using a multitrait–multimethod matrix approach.

5.2. Data aggregation

• The most common indicator of the validity of aggregated group-level constructs is within-group agreement; i.e., the degree to which raters provide essentially the same rating.
• Also reliability of the group means, as measured by ICC(2) was computed.
• Main effects for deep level diversity and task interdependence were entered.
• The final step was to show that the strength of the relationship between the predictor and outcome was significantly reduced when the mediator was added to the model (path c′).
• Table 7 presents the results from the mediated regression analysis for mutual trust (H5).

6. Discussion

• The authors study extended their understanding of team member diversity to the new organizational form of global virtual teams.
• The authors showed that a relationship exists between mutual trust and knowledge sharing in these teams, and examined the mediating role of mutual trust and knowledge sharing on GVT effectiveness.
• On the other hand, deep level diversity was found to be negatively associated with both mutual trust and knowledge sharing.
• As expected, task interdependence and collaborative technology had a moderating effect on the relationship between deep level diversity and mutual trust and knowledge sharing.
• With high task interdependence, team members overcome their individual diversity differences and collaborate effectively.

6.1. Implications for practice

• Teamwork in the global workplace is challenging.
• The findings from this study are an important step in this direction.
• Managers and stakeholders who are involved in the functioning of global teams need to understand diversity and its various forms.
• Managers should understand the potential presence of deep level attributes in team members and as such, training should be provided to help in the process of relationship building among team members.
• Managers should select a technology that promotes parallelism, transparency, and sociality.

6.2. Contribution to research

• Research findings on diversity within teams have been divided into optimistic (focusing on diverse teams’ access to resources providing increased creativity, innovation, and performance) and pessimistic (focusing on affective problems, as predicted by the similarity attraction paradigm and social categorization theories) [14].
• The findings from their study support the optimistic camp and the claims that greater diversity entails relationship building among team members and leads to increased team effectiveness.
• By broadening their view to include types of diversity, and by focusing more carefully on mediating and moderating mechanisms, the authors provided results that examine the effect of diversity at functional and deep levels.
• Moderator effects of task interdependence and collaborative technology were analyzed and the mediating role of mutual trust and knowledge sharing was established.
• The authors results extend the diversity research to organizational forms which face an increased challenge in diversity management.

6.3. Limitations

• One limitation of the study is its sample size and sample characteristics.
• The statistical power of the analysis is limited.
• The t-test statistic was not significant, confirming their assumption that the means between stakeholder response and member response were not different.
• A final limitation relates to the treatment of non-response bias.
• Thus prior to aggregating individual responses to the group, within-group agreement was analyzed to assure that perceptions of the team construct were sufficiently similar.

7. Conclusion

• The purpose of their research was to understand the different facets of diversity present in global virtual teams and to show how differences among individual members can be harnessed by developing a trusting and sharing environment, leading to greater GVT effectiveness.
• Furthermore, in understanding the relationship between mutual trust, knowledge sharing, and diversity, their research demonstrated the moderating effects of collaborative technology and task interdependence.
• The authors explored the mediating effects of trust and knowledge sharing in mitigating the negative effects of diversity in the team and found that it is essential in such an environment to motivate mutual trust and knowledge sharing.
• The authors also established that task interdependence and collaborative capabilities of technology have significant impact on the functioning of team processes.

Figures

Table 5 presents the moderator analysis for task interdependence. Task interdependence showed significant evidence for moderation for both dependent variables (F = 16.4, p < 0.001 for mutual trust and F = 39.0, p < 0.001 for shared knowledge).

Frequently asked questions

Q1. What are the contributions in this paper?

In this paper, a normative framework was designed to assist organizations in understanding the relationship between diversity, mutual trust, and knowledge sharing among GVTs, with additional focus on understanding the moderating impact of collaborative technology and task characteristics. 

Q2. What were the main criteria for the scales?

The survey scales were assessed for reliability, construct, convergent, and discriminant validity to ensure that they could be used to test their hypotheses. 

Q3. What has been the main focus of the research on virtual teams?

To date, the majority of virtual team research has focused on conflict, interpersonal trust, group and individual identity, and group cohesiveness [16]. 

Q4. What is the role of interdependence on team processes and outcomes?

Several researchers have argued that the degree of task interdependence has a substantial effect on team processes and outcomes; it moderates the relationship between team diversity and team performance by influencing team member interaction and coordination. 

Q5. What is the intellectual power of a virtual team?

The intellectual power of a virtual team is in its diffused expertise and ability to blend different experiences to create shared knowledge. 

Q6. What is the effect of deep level diversity on mutual trust and knowledge sharing?

At low levels, members tend to operate as individuals, thereby strengthening the negative relationship between deep level diversity and mutual trust and knowledge sharing. 

Q7. What is the effect of collaborative technology on the relationship between deep level diversity and mutual trust and knowledge?

The authors found that high levels of collaborative technology weaken the negative relationships between deep level diversity and mutual trust and knowledge sharing. 

Q8. What is the effect of mutual trust on team effectiveness?

It was evident from the analysis and comparison of regression coefficients that team effectiveness can be increased by increasing mutual trust among the members and enhancing shared knowledge among its members. 

Q9. What is the role of task design and its impact on team performance?

The role of task design and its impact on team performance has been investigated resulting in a belief that task differences moderate the relationships between team inputs, processes, and outputs. 

Q10. What is the effect of task interdependence and collaborative technology on the relationship between deep level diversity?

As expected, task interdependence and collaborative technology had a moderating effect on the relationship between deep level diversity and mutual trust and knowledge sharing. 

Q11. What was the method used to test the hypotheses?

Once these were confirmed, hypotheses testing for moderator and mediator effects were conducted using Hierarchical Multiple Regression Analysis (HMRA). 

Q12. What was the significance of path c′?

the significance of path c′ was established by looking at the overall F of the model, which was 4.63 and significant at p < .001. 

Q13. How does Sarker et al. assess group supportability?

Based on this, they proposed that group supportability may be assessed by determining how technology can increase parallelism, transparency, and sociality within the group.