X-Culture was originally envisioned purely as an experiential learning project. Accordingly, we first collected only the data on student performance needed for grading/marking.

However, to better understand processes and outcomes in global virtual teams and develop more effective pre-project training programs for our students, we gradually began collecting data that is not directly used for student evaluation.

Additionally, we began experimenting with different learning conditions, team composition, assignments, and evaluation systems to determine which teaching approach yields the best learning outcomes and student satisfaction.

Our database contains over 4,300 individual-level, 500 team-level, 200 instructor-level, and 100 country-level variables.

X-Culture data are multi-source, multi-level, multi-method, and longitudinal:

 icon-group  Multi-Source:

• Individual and team-consensus responses (various self-report surveys)
• Instructor evaluations
• Peer evaluations
• Deadline and other objective performance records
• Administrative records on participant background (e.g., country of studies, gender, etc.), team composition, and the like
• Data from external sources (e.g., time zone information, characteristics of the economic, cultural, and institutional environment of each country, etc).[/servicebox]

Multi-Level:

• Individual
• Team
• Class
• University
• National

Multi-Method:

• Quantitative
• Qualitative
• Administrative
• Experimental

  Longitudinal:

• 10 waves of survey:
  • Pre-project
  • Weekly during the project
  • Post-project

Normally, we measure: 

• Pre-project training and test performance.
• Team member background (demographics, international background, international experience, etc.).
• Knowledge and skills (cultural intelligence, skills with international virtual collaboration tools, etc.).
• Attitudes (values, various attitudes, beliefs, preferences, perceptions and biases, most measured before and then again after the project).
• Team composition and characteristics, including size, national, demographic, and skill composition, various inter-member distances, including time-zone, cultural, economic, perceptual and the like.
• Expectations about project challenges, communication mode, group interactions, dynamics and performance, measured before project start, and after the project end.
• Observations of project challenges, communication mode, group interaction, dynamics and performance, measured after project finish.
• Conflicts.
• Status and leadership.
• Open-ended question comments, feedback, suggestions, and other qualitative data.
• Various measures of team dynamics, including satisfaction, commitment, conflict, self-efficacy, etc.
• Various measures of team processes, including communication frequency and mode, workload distribution, coordination, leadership and more.
• Various measures of individual and team performance and outcomes, including multi-dimensional multi-rater assessment of the team report quality, ability to meet deadlines, satisfaction, peer evaluations, and the like.
• Original team reports and other records suitable for qualitative and content analysis.
• Characteristics of the experimental conditions, including the specific task the teams have to complete, allocated time, deadlines, etc.
• Information about the participating instructors, their courses and universities, as well as the information on the course delivery mode (online/face-to-face), level of studies (UG, MBA, EMBA), etc. 
• Information about various experimental conditions.

Most variables are deliberately manipulated (e.g., team size, cultural diversity, time allocated to each task) to create sufficient variation along each variable needed for a meaningful analysis. Many factors vary naturally (different teams choose different communication modes, leadership structures, etc.).

We are constantly searching for better ways to evaluate the effects and effectiveness of project, as well as to further explore what shapes cross-cultural interactions and group dynamics. If interesting research ideas are put forth, we would also be happy to consider incorporating new measures and experimental conditions into our project for studies that may not be directly related to global virtual teams.

 icon-book  Download X-Culture Data Code Books

 icon-bar-chart-o  How to Request Data 

Please first read our Collaboration Principles.

To request existing data or a collection of new data, please email us your research proposal.

There are no submission deadlines and no fixed research proposal formatting requirements, but the proposal must contain the following information:

• Research question(s) of the proposed study, no problem if specific hypotheses have not been developed yet, just a general research question or purpose of the study is sufficient at this stage. If available, it would also be helpful to briefly describe the study’s theoretical foundation.
• Constructs: A bullet list of constructs/variables that you would need from our existing database or additional measures that we need to add to our research design to collect new data. Please see the X-Culture Data webpage for what’s already measured.
  If requesting new data to be collected, please attach a complete list of items, details on the timing (when measurements need to be taken), and other information on how the data should be collected.
• Expected research outcomes: A brief review of the goals and results of the study, expected publications, etc.
• Expected timing: Expected research project schedule and other timing information that can give us information as to how long it is likely to take to complete the project – very general information would be sufficient at this stage.
• Preferred Collaboration Mode: A summary of the researcher’s preferences as to collaboration with the X-Culture team, what resources are at the researcher’s disposal, what tasks or functions the researcher prefers to complete on their own and what tasks or functions the researcher prefers to be completed by collaborators from the X-Culture team, any other preferences with respect to communication, workload distribution, timing, co-author team composition, etc.
• CV of the researcher(s) submitting the proposal.
• Other: Any other information you feel would be relevant.

Do NOT spend too much on this initial proposal. It only has to provide a general summary of the idea so we can determine whether we already published it or are working on it, or if it is a new idea. As long as it is a new idea, we will be happy to share our data. If it is an “old/existing” idea, we will work with you to find a way to refine the angle of your study to make it significantly distinct from the idea already published or in development.

Once we establish that the study is new and we (should) have suitable data, we’ll have a longer meeting (or several) to figure out together which exact variables from our database would best capture/represent the constructs in your model. It often takes several meetings to prepare the dataset for analysis, address questions about how each variable was measured and any other questions the researcher may have about the data, and work out authorship, copyright, and data-use issues.

Data Collection Requests: IMPORTANT Constraints and Selection Criteria

We receive a large number of requests for data collection (usually 10+ per semester).
At the same time, our surveys are already extensive, and adding further items increases the risk of respondent fatigue and, consequently, random or low-quality responses.

For this reason, we must be highly selective in approving requests for new measures or experimental conditions.

Priority will be given to studies that meet the following criteria:

1. Research Ethics and Compliance
   The proposed study has already received IRB/ethics approval, or approval can be obtained without difficulty prior to data collection.
2. Fit with the X-Culture Mission
   Clearly aligned with X-Culture’s core research domains (e.g., global virtual teams, cross-cultural management, active/experiential learning)
3. Scholarly Contribution and Publication Potential
   High likelihood of publication in a leading academic journal. Particular weight is given to the lead researcher’s demonstrated track record of publishing in top-tier outlets.

Co-Authorship and Collaboration Expectations

Please review our Research Collaboration Principles carefully before submitting a proposal.

We do not require co-authorship simply for granting access to existing data, and we are often happy to collect data for external researchers when feasible.
However, designing survey instruments, administering multi-wave data collection, preparing datasets, and managing complex longitudinal and multilevel data are substantial, time-intensive undertakings.

Understandably, priority will be given to projects that offer opportunities for collaboration and meaningful intellectual contribution by the representatives of the X-Culture research team, at a level that reasonably warrants co-authorship.

In short, while we are happy to support researchers by collecting high-quality data, our goal is a mutually beneficial collaboration that leads to strong, publishable, co-authored scholarship.